DOCTORAL THESIS
2023
A NOVEL METHODOLOGY FOR THE ASSESSMENT
OF WAVE ENERGY OPTIONS AT EARLY STAGES
PABLO RUIZ-MINGUELA
SUPERVISORS: PROF JESÚS MARIA BLANCO ILZARBE & DR VINCENZO NAVA
?
A no el me hodology o he holis ic
assessmen o wa e ene gy echnologies a
ea ly design s ages
AUTHOR:
José Pablo Ruiz Minguela
SUPERVISORS:
P o Jesús Ma ía Blanco Ilza be
D Vincenzo Na a
A hesis submi ed in ul ilmen o he equi emen s o he deg ee o
Doc o o Philosophy
Bilbao, May 2023
(cc)2023 JOSE PABLO RUIZ MINGUELA (cc by-sa 4.0)
In lo ing memo y o my dea mo he Lucía (1929-2020)
“Pygmies placed on he shoulde s o gian s see mo e han he gian s hemsel es”
F ia Diego de Es ella (1524 – 1578)
ii
ABSTRACT
Inc easing he sha e o elec ici y gene a ion om enewable sou ces is key o ensu e a
ully deca bonised ene gy sys em and igh agains clima e change. Wa e ene gy is an
abundan and powe ul esou ce bu a he same ime, he leas de eloped o all enewable
ene gy echnologies. I is discou aging ha despi e he conside able e o s he
in e na ional esea ch communi y has made o e he las decades, wa e ene gy
echnologies ha e once and again ailed o achie e he desi ed design con e gence o
suppo hei u u e ma ke g ow h.
T adi ional app oaches mainly ocused on assessing echnology ma u i y ha e p o en
insu icien o ensu e ha wa e ene gy echnologies achie e hei echnical, economic and
social goals. To mee he high sec o expec a ions, his esea ch p oposes a sys ema ic
app oach om he ou se o echnology de elopmen ha ensu es aceabili y o
equi emen s, c ea es ai pe o mance assessmen s and applies sound inno a ion
s a egies o o e come he emaining echnological challenges.
The common e alua ion amewo k is based on sound Sys ems Enginee ing p inciples. I
encompasses he ex e nal con ex , sys em equi emen s and e alua ion c i e ia. This s ep
o he me hodology c ea es a p io i isa ion o he a ious wa e ene gy a ibu es o he
quali a i e assessmen o wa e ene gy echnologies. The analysis o he ex e nal con ex
p o ides an unde s anding o he ac o s in luencing he de elopmen o wa e ene gy
echnologies and he co esponding impac on sys em equi emen s. The iden i ica ion o
he ma ke applica ion, key d i e s and s akeholde s’ g oups p o ides an excellen
ounda ion o he objec i e assessmen o wa e ene gy echnologies agains he sys ems
equi emen s.
This amewo k a oids any inconsis ency wi h he o mula ion o sys em equi emen s
and can be applied o di e en le els o echnology ma u i y. I p o ides lexibili y o
adap ing i o apidly changing ma ke condi ions o s akeholde p io i ies and can be
expanded o ocus he analysis on speci ic wa e ene gy sub-sys ems. Besides, i g asps he
quali a i e aspec s ela ed o he s akeholde expec a ions ha highe -le el me ics such as
LCOE canno p o ide.
On he o he hand, he p oposed no el app oach guides design decisions along he
de elopmen p ocess o he adequa e managemen o isk and unce ain y. To his
pu pose, he holis ic assessmen de eloped h ough his esea ch comp ises he e alua ion
a in e media e de elopmen s ages and he p ojec ion o u u e cos s when he echnology
iii
has been su icien ly eplica ed. This s ep o he me hodology acili a es wa e ene gy
echnology selec ion and benchma king a di e en le els o ma u i y in a con olled
manne .
The ai assessmen o wa e ene gy echnology pe o mance c ea es awa eness o po en ial
echnology gaps h oughou he a ious de elopmen s ages. I acili a es he selec ion o
he mos sui able op ion o a pa icula ma ke applica ion and enables benchma king o
echnologies ac oss di e en ma ke s. Addi ionally, i o e s a ool o explo ing
unce ain ies, d awing a en ion o he cos es ima e accu acy and iden i ying po en ial
lea nings om he beginning o echnology de elopmen .
The inno a ion s a egies p oposed in his esea ch deli e aluable in o ma ion o
ocusing inno a ion e o s on a eas ha ing he highes in luence on echnology
pe o mance. The me hods include he analysis o s uc u al pa e ns in he wa e ene gy
sys em a chi ec u e and he iden i ica ion o echnical ade-o s and co esponding
in en i e p inciples. This inal s ep o he me hodology esul s in he iden i ica ion o
p omising concep s wo h explo ing.
Inco po a ing e ec i e inno a ion s a egies in o wa e ene gy de elopmen helps o
manage sys em complexi y, enhance he unde s anding o causali y wi hin he sys em, and
channel inno a ion owa d use ul imp o emen s. I subs i u es he con en ional ial-and-
e o me hod based on expe judgemen and enginee ing comp omise. Mo eo e , i
p o ides a p edic able echnique o deal wi h p oblems based on pas knowledge and
p o en p inciples, b inging e iciency in o he p ocess.
The p ac ical implemen a ion o his me hodology o a ious illus a i e cases o
hypo he ical wa e ene gy sys ems, public e e ence models and s a e-o - he-a
echnologies has p oduced p omising esul s. While he indings o his esea ch do no
ocus on a speci ic concep ha can deli e he necessa y s ep change, he hesis p o ides
a holis ic and s uc u ed app oach o assessing he po en ial o inno a i e a che ypes.
Fu he mo e, u u e wo k could expand and adap his no el me hodology o he
assessmen o wa e ene gy op ions o o he possible se ings.
RESUMEN
El aumen o de la p opo ción de elec icidad gene ada a pa i de uen es eno ables es
cla e pa a ga an iza un sis ema ene gé ico o almen e desca bonizado y lucha con a el
cambio climá ico. La ene gía de las olas es un ecu so abundan e y po en e, pe o, al mismo
iempo, es la menos desa ollada de odas las ecnologías eno ables. Resul a desalen ado
que, a pesa de los conside ables es ue zos que los in es igado es in e nacionales han
ealizado en las úl imas décadas, las ecnologías de cap ación no hayan conseguido log a
la deseada con e gencia de diseño pa a sus en a su u u o c ecimien o come cial.
Las me odologías con encionales cen adas p incipalmen e en e alua la madu ez de la
ecnología han demos ado se insu icien es pa a ga an iza que las ecnologías
undimo ices alcancen sus obje i os écnicos, económicos y sociales. Pa a cumpli con las
al as expec a i as del sec o , es a in es igación p opone un en oque sis emá ico desde el
inicio del desa ollo de la ecnología que ga an iza la azabilidad de los equisi os, c ea
e aluaciones de desempeño obje i as y aplica es a egias de inno ación sólidas pa a
supe a los e os pendien es.
El ma co de e aluación común se basa en los p incipios sólidos de la Ingenie ía de
Sis emas. Aba ca el con ex o ex e no, los equisi os del sis ema y los c i e ios de
e aluación. Es e paso de la me odología c ea una p io ización de los di e sos a ibu os de
un sis ema de ene gía undimo iz pa a la e aluación cuali a i a de las ecnologías de
ene gía de las olas. El análisis del con ex o ex e no p opo ciona una comp ensión de los
ac o es que in luyen en el desa ollo de dichas ecnologías y el impac o co espondien e
en los equisi os del sis ema. La iden i icación de la aplicación de me cado, los ac o es
cla e y los g upos de in e és p opo ciona una base sólida pa a la e aluación obje i a de las
ecnologías de ene gía de las olas en e a los equisi os de los sis emas.
Es e ma co e i a cualquie inconsis encia en la o mulación de los equisi os del sis ema y
se puede aplica a di e en es ni eles de madu ez ecnológica. P opo ciona lexibilidad pa a
adap a lo a las condiciones del me cado o p io idades de las pa es in e esadas
ápidamen e cambian es además de pode se ex ende pa a cen a el análisis en
subsis emas especí icos de ene gía de las olas. Asimismo, cap a los aspec os cuali a i os
elacionados con las expec a i as de los g upos de in e és que mé icas de al o ni el como
el LCOE no pueden p opo ciona .
Po o o lado, el en oque no edoso p opues o o ien a las decisiones de diseño a lo la go
del p oceso de desa ollo pa a una adecuada ges ión del iesgo y la ince idumb e. Pa a
ello, la e aluación holís ica desa ollada a a és de es a in es igación comp ende la
e aluación en e apas in e medias de desa ollo y la p oyección de cos es u u os as habe
eplicado su icien emen e la ecnología. Es e paso de la me odología acili a la selección y
CONTENTS
x i
5.5
Conclusions ................................................................................................................... 125
CHAPTER 6
ESTIMATING FUTURE TECHNOLOGY COSTS ................................. 127
6.1
O e iew ........................................................................................................................ 127
6.2
Me hods and Tools ...................................................................................................... 128
6.2.1
P opaga ion o E o o Unce ain y ............................................................... 128
6.2.2
Technological Lea ning ...................................................................................... 129
6.3
Fu u e Cos s o Wa e Ene gy .................................................................................... 131
6.3.1
Backg ound .......................................................................................................... 131
6.3.2
Cu en Cos and Pe o mance ........................................................................ 132
6.3.3
Cos Escala ion..................................................................................................... 136
6.3.4
P ojec ion o Fu u e Cos s ................................................................................. 138
6.4
P ac ical Implemen a ion ........................................................................................... 139
6.4.1
Case S udy: Re e ence Model 5 ......................................................................... 139
6.4.2
Cos and Pe o mance o he 50-Uni Fa m ................................................... 141
6.4.3
Cos Escala ion o Accoun o Unce ain ies ................................................ 142
6.4.4
P ojec ing he Fu u e Cos o Ma u e Technology ....................................... 144
6.5
Conclusions ................................................................................................................... 146
CHAPTER 7
OVERCOMING THE CHALLENGES ...................................................... 149
7.1
O e iew ........................................................................................................................ 149
7.2
Me hods and Tools ...................................................................................................... 150
7.2.1
Design S uc u ed Ma ix (DSM) ..................................................................... 150
7.2.2
Theo y o In en i e P oblem Sol ing (TRIZ) ................................................ 151
7.3
Inno a ion S a egies ................................................................................................... 156
7.3.1
Backg ound .......................................................................................................... 156
7.3.2
Design S uc u e o Wa e Ene gy Sys ems ..................................................... 157
7.3.3
Es ablishing P io i ies o TRIZ In en i e P inciples .................................... 160
7.4
P ac ical Implemen a ion ........................................................................................... 163
7.4.1
Lea ning om Failed Technologies ................................................................. 163
7.4.2
P omising Concep s Wo h Explo ing ............................................................ 171
7.5
Conclusions ................................................................................................................... 177
CHAPTER 8
OVERALL CONCLUSIONS ........................................................................ 179
8.1
O e iew ........................................................................................................................ 179
CONTENTS
x ii
8.2
Summa y o Findings .................................................................................................. 179
8.2.1
Common amewo k o wa e ene gy sys em equi emen s and me ics.. 180
8.2.2
A ai assessmen o wa e ene gy echnology pe o mance h oughou he
de elopmen p ocess ........................................................................................................ 183
8.2.3
Inno a ion s a egies o imp o e he cos -e ec i eness o wa e ene gy .. 186
8.3
Recommenda ions o Fu u e Resea ch .................................................................. 187
REFERENCES .............................................................................................................................. 189
APPENDICES .............................................................................................................................. 215
Appendix A: Su ey o Ex e nal Fo ces .............................................................................. 215
Appendix B: P io i isa ion Ma ices ................................................................................... 217
Appendix C: Lis o TRIZ 39 Technical Pa ame e s ........................................................ 222
Appendix D: Con adic ion Ma ix .................................................................................... 225
Appendix E: Lis o TRIZ 40 In en i e P inciples ............................................................ 226
Appendix F: RM5 B eakdowns ............................................................................................ 232
PUBLICATIONS ......................................................................................................................... 239
This page in en ionally le blank
xix
FIGURES AND TABLES
Lis o Figu es
Figu e 1.1: The h ee pe spec i es o success ul inno a ion (adap ed om [7]). ................ 2
Figu e 1.2: Summa y o hesis s uc u e. ..................................................................................... 8
Figu e 2.1: Global dis ibu ion o annual mean wa e powe in kW/m [25]. ...................... 13
Figu e 2.2: Global dis ibu ion o wa e powe seasonal a iabili y [25]. ............................. 13
Figu e 2.3: Miles ones o wa e ene gy de elopmen : Ea ly his o y (1799-1970). .............. 14
Figu e 2.4: Miles ones o wa e ene gy de elopmen : Age o Enligh enmen (1970-1990).
........................................................................................................................................................... 15
Figu e 2.5: Miles ones o wa e ene gy de elopmen : Con empo a y age (1990-2020). ... 15
Figu e 2.6: Classi ica ion acco ding o he de ice loca ion. ................................................... 16
Figu e 2.7: Classi ica ion acco ding o de ice o ien a ion (adap ed om [49])................. 17
Figu e 2.8: Classi ica ion acco ding o de ice wo king p inciple. ........................................ 18
Figu e 2.9: Types o eac ion poin s. .......................................................................................... 20
Figu e 2.10: Al e na i e PTO Con igu a ions. ......................................................................... 20
Figu e 2.11: Domains o he design wo ld (adap ed om[84]). ............................................ 25
Figu e 2.12: Rep esen a ion o dependencies in a mul iple-domain model (adap ed om
[87]). ................................................................................................................................................. 26
Figu e 2.13: Requi emen s and Me ics in he Sys ems Enginee ing V-model. ................. 27
Figu e 2.14: Technology Readiness Le els and IEC S ages. ................................................... 35
Figu e 2.15: E alua ion A eas included in he E alua ion and Guidance F amewo k [142].
........................................................................................................................................................... 37
Figu e 2.16: Va ious sys em bounda ies o a wa e ene gy assessmen . ............................. 38
Figu e 2.17: Example o a hie a chy o wa e ene gy me ics (adap ed om [142]). ......... 39
Figu e 2.18: Design eedom, knowledge and ela ed cos s (adap ed om [64]). ............. 41
Figu e 3.1: An example o a h ee-le el decision hie a chy. .................................................. 48
Figu e 3.2: The House o Quali y. ............................................................................................... 50
Figu e 3.3: The six dimensions o PESTLE analysis. ............................................................... 55
FIGURES AND TABLES
xx
Figu e 3.4: Wa e ene gy s akeholde g oups. ........................................................................... 57
Figu e 3.5: Key D i e s o U ili y-scale Gene a ion ............................................................... 61
Figu e 3.6: Key D i e s o Remo e Communi y Gene a ion ................................................ 62
Figu e 3.7: Poli ical conce ns o he wa e ene gy s akeholde s ........................................... 63
Figu e 3.8: Economic Conce ns o he Wa e Ene gy S akeholde s. ................................... 64
Figu e 3.9: Social Conce ns o he Wa e Ene gy S akeholde s. ........................................... 65
Figu e 3.10: Technological Conce ns o he Wa e Ene gy S akeholde s. .......................... 66
Figu e 3.11: Legal Conce ns o he Wa e Ene gy S akeholde s. .......................................... 67
Figu e 3.12: En i onmen al Conce ns o he Wa e Ene gy S akeholde s. ........................ 68
Figu e 3.13: Rela i e impo ance o SD o he applica ion ma ke . .................................... 69
Figu e 3.14: Rela i e impo ance o SH o he applica ion ma ke . .................................... 72
Figu e 4.1: Wa e Ene gy Sys em, Ex e nal Sys ems and Con ex (adap ed om [62]). ... 76
Figu e 4.2: Oc opus diag am. ....................................................................................................... 77
Figu e 4.3: Func ion hie a chy in a FAST diag am ................................................................. 78
Figu e 4.4: Deg ees o simul anei y/ eplaceabili y o logic ope a o s (adap ed om [159]).
........................................................................................................................................................... 79
Figu e 4.5: App oach o building Wa e Ene gy Sys em Requi emen s. .............................. 81
Figu e 4.6: Agg ega ion o MOE. ................................................................................................ 84
Figu e 4.7: Fundamen al ela ionship be ween he CF and he wa e ene gy le el (adap ed
om [217], Supplemen al In o ma ion). ................................................................................... 85
Figu e 4.8: Li ecycle o he wa e ene gy sys em and en i ies. ................................................ 86
Figu e 4.9: Oc opus diag am o he ope a ion phase (a) and es o phases (b). .............. 87
Figu e 4.10: FAST diag am o he Wa e Ene gy Sys em....................................................... 88
Figu e 4.11: Agg ega ion o MOP. .............................................................................................. 90
Figu e 4.12: Illus a i e ela ionship be ween he LF and e iciency. ................................... 93
Figu e 4.13: S a egies o minimise ailu es (adap ed om [228])........................................ 94
Figu e 4.14: Agg ega ion o TPM. ............................................................................................... 95
Figu e 4.15: Rela i e impo ance o SRs o he applica ion ma ke . ................................... 97
Figu e 4.16: Sensi i i y o Global Me i o MOE U ili y o each ma ke applica ion: (a)
U ili y-scale gene a ion; (b) Powe ing emo e communi ies. ................................................ 98
Figu e 4.17: Rela i e impo ance o FR o he applica ion ma ke . ..................................... 99
Figu e 4.18: MOE Sensi i i y o U ili y-scale Gene a ion: (a) Con e wa e ene gy; (b)
Ope a e when needed; (c) Reduce up on cos s; (d) P e en business isks. .................. 100
FIGURES AND TABLES
xxi
Figu e 4.19: Sensi i i y o Global Me i o MOP U ili y o each ma ke applica ion: (a)
U ili y-scale gene a ion; (b) Powe ing emo e communi ies. ............................................. 101
Figu e 4.20: Rela i e impo ance o DPs o he applica ion ma ke . ................................ 102
Figu e 5.1: Maximisa ion (a) and minimisa ion (b) alue unc ions. ................................ 107
Figu e 5.2: Sa u a ion (a) and cons ain (b) alue unc ions. ............................................. 108
Figu e 5.3: Op imisa ion (a) and a oidance (b) alue unc ions. ........................................ 109
Figu e 5.4: De i ing h eshold me ics om benchma k da a ............................................ 109
Figu e 5.5: Me ic exhibi ing a dec easing pe o mance beha iou (lowe is be e ). .... 113
Figu e 5.6: Me ic exhibi ing an inc easing pe o mance beha iou (highe is be e ). . 113
Figu e 5.7: Comme cial A ac i eness (CA). ......................................................................... 115
Figu e 5.8: Technical Achie abili y (TA). ............................................................................... 116
Figu e 5.9: Cone o unce ain y and DD le els....................................................................... 117
Figu e 5.10: Value unc ions o he six benchma k cases.................................................... 120
Figu e 6.1: P obabili y ep esen a ion o unce ain y and main s a is ical p ope ies. ... 129
Figu e 6.2: Cos educ ion pa hways wi h cumula i e expe ience a h ee di e en
Lea ning Ra es (5%, 10% and 20%) .......................................................................................... 130
Figu e 6.3: The p oposed 3-s ep app oach o es ima ing he u u e cos o an eme ging
wa e ene gy echnology a di e en s ages o echnology de elopmen , wi h an illus a i e
LCOE es ima e and unce ain y a each s age. ....................................................................... 131
Figu e 6.4: S anda d cos and pe o mance b eakdown o an illus a i e comme cial
p ojec (adap ed om [156], [227], [257], [258]). ................................................................. 132
Figu e 6.5: Schema ic o he RM5 loa ing OWSC. ............................................................... 140
Figu e 6.6: 50-uni a m a ay layou (no d awn o scale). ................................................. 140
Figu e 6.7: B eakdown o cos s o he RM5 a m. Le : pe cen age o o al li e ime cos s;
Righ : dis ibu ion o OPEX cos s. ............................................................................................ 142
Figu e 6.8: Unce ain ies o he high-le el componen s in he LCOE equa ion. No e ha
LCOE unce ain y is p opaga ed and no simply added. ..................................................... 144
Figu e 6.9: Lea ning Ra es (LR) o he high-le el componen s in he LCOE equa ion. No e
esul ing LR o he LCOE is p opaga ed and no simply added. ....................................... 145
Figu e 6.10: Eme ging echnology cos ajec o ies wi h h ee dis inc le els o unce ain y
(U) and lea ning capaci y (L). The numbe s ①②③ ela e o me hodological s eps,
depic ed in Figu e 6.3. ................................................................................................................. 147
Figu e 7.1: Example o sys em g aph (le ) and co esponding DSM ( igh ). .................. 150
Figu e 7.2: Types o in e connec ions and co esponding DSM ep esen a ions............ 151
FIGURES AND TABLES
xxii
Figu e 7.3: The TRIZ app oach o p oblem-sol ing. ............................................................. 152
Figu e 7.4: Finding con adic ions in he ma ix. .................................................................. 154
Figu e 7.5: Hie a chical ep esen a ion o he wa e ene gy sys em.................................... 158
Figu e 7.6: Block diag am o he wa e ene gy sys em wi h in e ac ions ........................... 158
Figu e 7.7: Pelamis P2 de ice, pic u ed a he Eu opean Ma ine Ene gy Cen e, 2011. . 163
Figu e 7.8: Block diag am o he 3 MW Pelamis P2 a m. .................................................. 164
Figu e 7.9: Mocean Blue X es ing (le ) and Blue Ho izon a is ic imp ession ( igh ). . 165
Figu e 7.10: Block diag am o he 3 MW Blue Ho izon 250 a m..................................... 165
Figu e 7.11: Wa eBob 1:4 de ice es s (le ) and ull-scaled design ( igh ). ...................... 167
Figu e 7.12: Block diag am o he 3 MW Wa eBob a m. .................................................. 168
Figu e 7.13: Co Powe C4 hull (le ) and schema ic ( igh ). ................................................ 169
Figu e 7.14: Block diag am o he 3 MW Co Powe C4 a m. ........................................... 169
Figu e 7.15: Pneuma ics o hyd aulics and co esponding in en i e ope a o s. ............. 172
Figu e 7.16: Use o pneuma ics o hyd aulics (a) Onsho e OWC de ice [304]; (b)
No iOcean de ice [303].............................................................................................................. 172
Figu e 7.17: Dynamism and co esponding in en i e ope a o s. ....................................... 174
Figu e 7.18: Replace he wo king p inciple and co esponding in en i e ope a o s. ..... 174
Figu e 7.19: Dynamism and eplacing wo king p inciple (a) NREL’s FlexWEC [306] ; (b)
PNNL’s FMC-TENG de ice [309]. ........................................................................................... 175
Figu e 7.20: Change p ope ies and co esponding in en i e ope a o s. .......................... 176
Figu e 7.21: Change p ope ies (a) NREL’s Va iable Geome y OSWC [311]; (b) WEPTOS
[312]; (c) Co Powe C4 [37]. ..................................................................................................... 177
Figu e 7.22: P elimina y ac ion and co esponding in en i e ope a o s. ......................... 177
FIGURES AND TABLES
xxiii
Lis o Tables
Table 2.1: Sys em b eakdown o wa e ene gy echnologies. ................................................ 19
Table 2.2: Design domains acco ding o di e en au ho s. ................................................... 24
Table 2.3: Es ima ion o he assessmen e o . ......................................................................... 42
Table 3.1: G ada ion scale o pai wise compa isons [102]. .................................................. 49
Table 3.2: Random Index, RI [102]............................................................................................. 49
Table 3.3: Applica ion ma ke cha ac e isa ion. ...................................................................... 54
Table 3.4: Wa e ene gy d i e s. .................................................................................................. 55
Table 3.5: Wa e ene gy s akeholde s. ........................................................................................ 58
Table 3.6: Impo ance a ing scale [204]. .................................................................................. 72
Table 4.1: Special cases o weigh ed powe mean m=2 [210] ............................................... 80
Table 4.2: Gene alised conjunc ion-disjunc ion. Values o d [159] ..................................... 80
Table 4.3: S akeholde oles and expec a ions. ......................................................................... 82
Table 4.4: S akeholde Requi emen s and Me ics. ................................................................. 83
Table 4.5: Func ional Requi emen s and Me ics. ................................................................... 89
Table 4.6: Technical Requi emen s and Me ics. ..................................................................... 92
Table 4.7: IEC Technology Classes [226]. ................................................................................. 93
Table 4.8: Mapping o Technical Requi emen s (TRs) o Design Pa ame e s (DPs). ....... 96
Table 4.9: Ranking o S akeholde Requi emen s (SRs). ........................................................ 97
Table 4.10: Ranking o Func ional Requi emen s (FRs). ........................................................ 99
Table 4.11: Ranking o Design Pa ame e s (DPs). ................................................................. 103
Table 5.1: Technical Di icul y (adap ed om [249])............................................................ 116
Table 5.2: Illus a i e benchma k cases. .................................................................................. 118
Table 5.3: S akeholde Requi emen s and U ili y. ................................................................. 119
Table 5.4: Quali a i e assessmen o MOE. ............................................................................. 121
Table 5.5: Global Me i (GM) o wa e ene gy op ion o he applica ion ma ke s. ........ 121
Table 5.6: Wa e ene gy a ac i eness. .................................................................................... 123
Table 5.7: TA o he MOE in he u ili y-scale gene a ion ma ke . .................................... 124
Table 5.8: TA o he MOP in he u ili y-scale gene a ion ma ke . .................................... 124
Table 5.9: Deg ee o di icul y ac o s o FR. ......................................................................... 125
FIGURES AND TABLES
xxi
Table 6.1: Sugges ed con ingencies and logno mal p ope ies o unce ain y anges
no malised by mode (adap ed om [270]). ............................................................................ 137
Table 6.2: Case s udy speci ica ions .......................................................................................... 141
Table 6.3: Unce ain y ca ego ies, associa ed s anda d de ia ion and 80% con idence
in e als. ......................................................................................................................................... 143
Table 6.4: Componen -based LR, unce ain y and s anda d de ia ion ............................. 145
Table 7.1: TRIZ 39 Technical Pa ame e s ............................................................................... 153
Table 7.2: TRIZ Sepa a ion P inciples and In en i e P inciples......................................... 154
Table 7.3: TRIZ 40 In en i e P inciples .................................................................................. 155
Table 7.4: DSM model o he block diag am om Figu e 7.6. ........................................... 159
Table 7.5: Top-10 in en i e p inciples o he u ili y ma ke – imp o ing a posi i e ea u e.
......................................................................................................................................................... 161
Table 7.6: Top-10 in en i e p inciples o he u ili y ma ke – minimising he impac o a
wo sening ea u e. ........................................................................................................................ 162
Table 7.7: Top-10 in en i e p inciples o he u ili y ma ke – bo h objec i es. .............. 162
Table 7.8: DSM model o he 3 MW Pelamis P2 a m ......................................................... 164
Table 7.9: DSM model o he 3 MW Blue Ho izon 250 a m ............................................. 166
Table 7.10: DSM model o he 3 MW Wa eBob a m ......................................................... 168
Table 7.11: DSM model o he 3 MW Co Powe C4 a m .................................................. 170
Table 7.12: Summa y o Complexi y Sco es. .......................................................................... 170
Table 7.13: Impac o he DP con lic s (blue=high; ed=low). ............................................ 171
Table 8.1: Summa y o he No el Me hodology. .................................................................... 180
Table A.1: Sys em D i e s o U ili y-scale Gene a ion. ....................................................... 217
Table A.2: Sys em D i e s o Remo e Communi y Gene a ion. ....................................... 217
Table A.3: Sys em D i e s o S akeholde s (SHs) o U ili y-scale Gene a ion. ............... 218
Table A.4: Sys em D i e s o S akeholde s (SHs) o Remo e Communi y Gene a ion. 218
Table A.5: S akeholde s o S akeholde Requi emen s (SRs) o U ili y-scale Gene a ion.
......................................................................................................................................................... 219
Table A.6: S akeholde s o S akeholde Requi emen s (SRs) o Remo e Communi y
Gene a ion. .................................................................................................................................... 219
Table A.7: S akeholde Requi emen s o Func ional Requi emen s (FRs) o U ili y-scale
Gene a ion. .................................................................................................................................... 220
Table A.8: S akeholde Requi emen s o Func ional Requi emen s (FR) o Remo e
Communi y Gene a ion. ............................................................................................................ 220
FIGURES AND TABLES
xx
Table A.9: Func ional Requi emen s o Design Pa ame e s (DPs) o U ili y-scale
Gene a ion. ................................................................................................................................... 221
Table A.10: Func ional Requi emen s o Design Pa ame e s (DPs) o Remo e
Communi y Gene a ion. ............................................................................................................ 221
Table A.11: Lis o TRIZ 39 Technical Pa ame e s. ............................................................... 222
Table A.12: Con adic ion Ma ix. ........................................................................................... 225
Table A.13: Lis o TRIZ 40 In en i e P inciples. .................................................................. 226
Table A.14: De ailed B eakdown o Cos and Pe o mance (adap ed om [282]) ......... 232
Table A.15: P opaga ion o Unce ain ies and Co esponding Cos s. ............................... 234
Table A.16: Componen -based Lea ning and Fu u e Cos P ojec ions. ............................ 236
NOMENCLATURE
xxxii
n
i
No. o ins alla ion ips pe de ice
n
s
No. o se ice ips pe de ice
O Plan ope a o
p shape ac o o he alue unc ion
P Ra ed powe
Discoun a e
ij
QFD ela ionship ma ix coe icien s
s
i
Sui abili y
S A ea o he hyd odynamic objec
Tole ance o he alue unc ion
c
Cycle ime
l
Logis ic ime
T a el ime
w
Wai ing ime
T Ta ge pe o mance
U Unce ain y le el
(x) Value unc ion
w Impo ance weigh ings
W Ocean wa es
W
k+
Weigh ings o he IPs when he aim is o imp o e a posi i e ea u e
W
k-
Weigh ings o he IPs when he aim is o imp o e a wo sening ea u e
X Cumula i e expe ience
y P ojec li e ime
Y Fu u e cos o he echnology
NOMENCLATURE
xxxiii
G eek Le e s
δ Unce ain y
λ Failu e a e
λ
max
Maximum eigen alue o he judgemen ma ix in AHP
µ Mean
η
d
Deli e y E iciency
η
T ans o ma ion E iciency
ρ
Repai a e
σ S anda d de ia ion
ω Wa e F equency
This page in en ionally le blank
1
CHAPTER 1 INTRODUCTION
1.1 O e iew
This chap e begins wi h an in oduc ion o he social, echnical and comme cial landscape
and he unde lying challenges ha mo i a e his esea ch (sec ion 1.2). The esea ch goal
and objec i es a e desc ibed in sec ion 1.3. Sec ion 1.4 summa ises he main con ibu ions
o he hesis. Finally, he hesis s uc u e is p esen ed in sec ion 1.5.
1.2 Mo i a ion and P oblem S a emen
Na ions all o e he wo ld a e se ing ambi ious deca bonisa ion a ge s as a means o igh
clima e change [1]. Howe e , despi e he need o inc ease he sha e o elec ici y
gene a ion om enewable sou ces, ocean ene gy, and pa icula ly wa e ene gy, emains
a la gely un apped esou ce [2]. Wa e ene gy is abundan , p edic able, widely dis ibu ed
and indigenous o many popula ions li ing in coas al a eas [3]. Toge he wi h idal
s eam, wa e ene gy has he po en ial o sa is y up o 10% o he global elec ici y demand
by 2050 [4].
All in all, he pa h o de eloping e ec i e wa e ene gy echnologies has been poised wi h
many challenges [5]. Designing wa e ene gy echnologies is a long and in ica e p ocess
implying many decisions. In an ea ly s age, mul iple design pa ame e s mus be assigned,
which signi ican ly in luence i s ul ima e cos and pe o mance expec a ions [6]. Failu e
o he wa e ene gy sec o o mee hose expec a ions has mo e han once delayed he
indus ial de elopmen o wa e ene gy [3].
Hence, he enginee ing challenge is o c ea e obus de ices ha ha ness wa e ene gy
e icien ly, eliably and cos -e ec i ely while also su i ing he oughes seas. Fo his
pu pose, he echnology de elopmen p ocess should g adually eplace ini ial assump ions
wi h knowledge since hese unce ain ies ep esen a signi ican isk.
Fu he mo e, any success ul inno a ion mus con ain h ee essen ial ea u es, namely
social desi abili y, echnical easibili y and comme cial iabili y [7]. Al hough hese
“I you canno make knowledge you se an , make i you
iend”
Bal asa G acián (1601 – 1658)
INTRODUCTION
2
c i e ia may no be de eloped simul aneously, all mus be p esen inciden ally o ensu e a
h i ing business.
Social desi abili y explo es whe he he inno a ion will mee eal use needs, in o he
wo ds, i we a e sol ing he igh p oblem. On he o he hand, he echnical easibili y and
comme cial iabili y in es iga e ou capabili y o deli e he inno a ion and i s
p o i abili y in he ma ke espec i ely, ha is, i we a e sol ing he p oblem igh . A he
in e sec ion o he h ee lenses lies he op imum design space o success ul inno a ion.
Figu e 1.1: The h ee pe spec i es o success ul inno a ion (adap ed om [7]).
Righ now, social desi abili y is qui e a ou able o wa e ene gy. The ansi ion o a
sus ainable and esilien ca bon-neu al economy is no longe a poli ical decision bu an
ample social demand. Wi h wo ld ene gy consump ion es ima ed o ise conside ably o e
he nex decades, in e na ional ins abili y (e.g. Uk aine wa ) and high ene gy p ices,
inc easing secu i y o supply and educing ossil uel dependence a e becoming powe ul
d i e s [8].
Wa e ene gy can play a b oad ole in a aining UN Sus ainable De elopmen Goals [9] by
p o iding a o dable and clean ene gy (Goal 7), c ea ing jobs in coas al egions (Goal 8),
p omo ing ene gy secu i y (Goal 9), educing CO
2
(Goal 13) and p o ec ing ecosys ems
(Goal 14). Addi ionally, he need o a igo ous o wa d-looking eco e y om he ha m
in lic ed by Co id-19 may e i e in e es in wa e ene gy de elopmen [10]. Las ly, wi h a
high pene a ion o enewable ene gies in he ene gy sys em, wa e ene gy can p o ide
signi ican alue in balancing he g id due o i s complemen a i y o o he enewable
ene gy sou ces such as wind and sola [4].
Many wa e ene gy concep s ha e been de eloped o e he las 30 yea s. Va ious
echnologies a e in di e en de elopmen s ages, bu none ha e achie ed comme cial
eadiness [11]. The g ea di e si y o a che ypes can explain why he ma u i y o wa e
ene gy echnologies is s ill ela i ely low. Howe e , he limi ed numbe o echnologies
deployed in he wa e has shown ha nessing wa e ene gy is echnically easible [12]. Due
INTRODUCTION
3
o he wide a ie y o wa e ene gy echnologies and he s ong dependence o hei
pe o mance on he sea condi ions in which hey a e es ed, i is ex emely di icul o
objec i ely assess he ela i e me i s o he ma kedly di e en designs.
The ocean is a u hless en i onmen whe ein echnologies mus demons a e long- e m
eliable pe o mance o compe e wi h mo e ma u e al e na i es. A p esen , comme cial
iabili y is he main missing inno a ion ac o o wa e ene gy echnology success. The
business case o wa e ene gy is made upon he cos o p oducing ene gy. To demons a e
an a ac i e business case p oposi ion, wa e ene gy echnology de elope s a e expec ed
o ga he signi ican e idence. This is especially challenging since he de elopmen p ocess
o wa e ene gy echnology is pa icula ly cos ly and leng hy [13].
To achie e sys em cos and pe o mance equi emen s, ea ly echnological de elopmen
is essen ial. Acco ding o se e al expe s, he concep ual design phase de e mines a ound
70–80% o he p oduc li ecycle cos s [14] [15] [16]. The logical conclusion is ha decisions
made du ing he ea ly s ages o p oduc de elopmen a e a mo e impo an han hose
made la e on. Too li le ime spen on concep ual design can esul in a lack o
unde s anding o he p oblem's equi emen s and an insu icien abili y o gene a e no el
concep s. This migh esul in a design being de eloped ha canno pe o m well enough
o be a iable comme cial solu ion, was ing ime and esou ces [17].
I is disappoin ing ha many wa e ene gy companies ha e mo ed h ough he echnology
eadiness le els, eaching he p e-comme cial scale, jus o ealise hey ail o mee hei
a ge s. The e o e, i is highly ad isable o ha e clea guidance on he po en ial o wa e
ene gy echnologies om he ea ly s ages o design.
Common me hodologies mainly ocused on assessing echnology ma u i y ha e p o ed
inadequa e o ensu e wa e ene gy echnologies each hei echnical, economic and social
goals. Hence, a igo ous de elopmen p ocess o wa e ene gy echnologies is needed o
help egain in es o con idence, imp o e he social pe cep ion o he sec o ’s po en ial and
p o ide compelling e idence o d i e echnical decisions.
Many indus ial sec o s (e.g. au omo i e, ae ospace, and oil & gas) ha e success ully
applied Sys ems Enginee ing me hods o de elop inno a i e p oduc s mee ing e y
di e se and demanding cus ome needs. Fo ins ance, Mulle and Falk [18] illus a e he
con ibu ion o Sys ems Enginee ing o oil & gas wi h conc e e case s udies om subsea
p oduc ion. Discou agingly, hei applica ion in wa e ene gy is s ill limi ed and
agmen ed.
INTRODUCTION
4
1.3 Resea ch Objec i es
The ul ima e esea ch goal o his hesis is o de elop a no el me hodology o he holis ic
assessmen o wa e ene gy sys ems om he ea ly s ages o echnology de elopmen based
on he applica ion o sound Sys ems Enginee ing p inciples. This sys ema ic design
app oach aims o:
1. Build a common amewo k ha ensu es aceabili y and consis ency o wa e
ene gy sys em equi emen s and me ics.
2. C ea e ai pe o mance assessmen s o wa e ene gy echnologies o objec i ely
guide design decisions h oughou he de elopmen p ocess.
3. Apply sound inno a ion s a egies o sugges p omising concep s ha can
imp o e he cos -e ec i eness o wa e ene gy echnologies.
The esea ch goal will be achie ed h ough he ollowing speci ic objec i es:
• Re iew he exis ing me hods applicable o he speci ica ion and assessmen o
wa e ene gy echnologies.
• Analyse he ex e nal o ces in luencing decisions ela ed o he concep ion,
de elopmen and ope a ion o wa e ene gy sys ems.
• P opose a s anda d se o s akeholde , unc ional and echnical equi emen s o
wa e ene gy sys ems.
• Gua an ee he aceabili y o sys em equi emen s h oughou he en i e wa e
ene gy design p ocess.
• Es ablish a hie a chy o me ics and co esponding agg ega ion me hods.
• De elop alue unc ions o acili a e he quali a i e assessmen o wa e ene gy.
• Alloca e design a ge s and unce ain y anges o benchma k wa e ene gy
echnology pe o mance along he in e media e de elopmen s ages.
• Imp o e he accu acy, consis ency, and use ulness o p ojec ed cos p edic ions
o eme ging wa e ene gy echnologies.
• Visualise po en ial p oblems in he unc ional alloca ion o wa e ene gy sys em
capabili ies o he physical embodimen .
• Iden i y he mos impac ul ade-o s o wa e ene gy sys ems and
co esponding in en i e p inciples.
• Implemen he no el app oach in a pe o mance assessmen and inno a ion ool
de eloped in Excel.
• Apply his assessmen me hodology o illus a i e cases o hypo he ical wa e
ene gy sys ems, public e e ence models and s a e-o - he-a echnologies.
INTRODUCTION
5
1.4 Con ibu ions
The main con ibu ions o his hesis a e ou lined below.
1.4.1 Analysis o ex e nal o ces in luencing he
de elopmen o wa e ene gy echnologies
Unde s anding wa e ene gy equi emen s is c i ical o he c ea ion o any success ul
echnology. Howe e , wa e ene gy de elopmen canno be sepa a ed om he la ge
con ex in which he echnology is in ended o ope a e, because mul iple ex e nal o ces
in luence i s concep ion, de elopmen , and ope a ion.
The wo undamen al elemen s ha cons i u e his b oad en i onmen a e ex e nal d i e s
and s akeholde g oups. Ex e nal d i e s a e closely ela ed o he in ended ma ke use,
whe eas s akeholde g oups exp ess echnological pe o mance expec a ions. Each
in ended ma ke applica ion may call o a di e en combina ion o ex e nal d i e s. In
u n, anking hose ex e nal d i e s o each s akeholde g oup will ul ima ely dic a e he
impo ance o he wa e ene gy equi emen s.
Ex e nal d i e s a e iden i ied and anked o wo ma ke applica ions based on he
Analy ic Hie a chy P ocess (AHP) me hod. Simila ly, wa e ene gy s akeholde s a e
elici ed and p io i ised ega ding he ex e nal d i e s using a Quali y Func ion
Deploymen (QFD) app oach o he same applica ion ma ke s. This anking can be easily
cus omised o local con ex s and expanded o new wa e ene gy applica ion ma ke s.
1.4.2 Hie a chical o mula ion o wa e ene gy
equi emen s and me ics
The o mula ion o equi emen s aims o c ea e a sys ema ic o e iew o he pu poses
unde pinning he sea ch o solu ions. Requi emen s ha bind a solu ion space a e
hie a chical and in e ela ed.
Ini ially, he wa e ene gy speci ica ion includes all necessa y and p io i ised S akeholde
Requi emen s (SRs) ha a e compa ible wi h he echnical, inancial and isk cons ain s.
Upon comple ion, he nex s ep is o de ine he Func ional Requi emen s (FRs). FRs de ine
wha he sys em mus do o achie e he SRs wi hou add essing how he sys em should
accomplish hem. Las bu no leas , Technical Requi emen s (TRs) speci y he issues
ela ed o he echnology needed o he success ul implemen a ion o he sys em in
physical componen s.
Sys ems enginee ing is d i en by he need o sa is y equi emen s. Thus, o Sys ems
Enginee ing o be success ul, e alua ing and alida ing hose equi emen s is equally
c ucial. Ve i ica ion and alida ion a e p ocesses based on e idence used o e alua e i a
sys em ul ils he speci ica ion o equi emen s. They ely on me ics and da a. A QFD
INTRODUCTION
6
app oach has been used o collec and ank s akeholde , unc ional, and echnical
equi emen s common o wa e ene gy ma ke applica ions. This amewo k gua an ees
he seamless aceabili y o design in o ma ion o each s age o he design p ocess oge he
wi h a h ee-le el hie a chy o me ics.
1.4.3 Assessmen o wa e ene gy echnology
pe o mance
The esul o he pe o mance e alua ion o a wa e ene gy concep o e s an es ima e o
how close o dis an he echnology is om eaching i s echno-economic objec i es. I is
essen ial o unde s and ha mos es ima es o wa e ene gy a e based on p ojec ed da a.
The assessmen me hod in oduces isks due o he eliance upon p ojec ed igu es, which
can be signi ican depending on he s age o echnological p og ess, he amoun o
inno a ion, he quali y o he assump ions, and he e alua ion de ail. The p ojec ed
accu acy o he es ima ions will inc ease as de elopmen p oceeds, esul ing in a dec ease
in he unce ain y ange.
A quali a i e assessmen o he Global Me i o a wa e ene gy echnology is enabled by an
agg ega ion me hod o me ics based on he Logical Sco ing o P e e ence (LSP) heo y.
Besides, wo new concep s a e in oduced o pe o mance benchma king o wa e ene gy
echnologies. Comme cial A ac i eness (CA) enables no only he selec ion o he bes
wa e ene gy al e na i e o a ce ain ma ke applica ion bu also he compa ison o
echnologies ac oss a ious ma ke applica ions. The concep o Technical Achie abili y
(TA) p o ides a me hod o assess he abili y o echnologies unde de elopmen o achie e
he sys em equi emen s, based on he unme pe o mance and he Deg ee o Di icul y
(DD). The DD is de ined by echnology ma u i y and undamen al limi s.
1.4.4 Me hod o p ojec u u e cos s o eme ging wa e
ene gy echnologies
Di ec LCOE compu a ion is highly inapp op ia e o p o o ype echnologies. Assessing
he a o dabili y o eme ging echnologies needs a u u e p ojec ion o cos s wi h a
e e ence o he ma u e echnology and a i s -o -a-kind comme cial deploymen .
S a ing om he cu en b eakdown o wa e ene gy cos s, he sugges ed app oach
alloca es unce ain y bands depending on he es ima ion accu acy used o de e mine he
i s -o -a-kind cos o he comme cial echnology. A e ins alling a ce ain capaci y
h ough se e al comme cial p ojec s, componen -based lea ning a es a e hen used o
es ima e he LCOE o he ma u e echnology. This me hod coun e s he human p opensi y
o o e -op imism in p elimina y es ima es, which p oduces highly un ealis ic LCOE
alues o comme cial echnology. I o e s a ool ha may be used o in es iga e
unce ain ies, concen a e e o s on he accu acy o cos p ojec ions, and iden i y any
lessons ha migh ha e been lea ned du ing he ea ly s ages o echnological de elopmen .
INTRODUCTION
7
S a is ical p opaga ion o unce ain ies is achie ed by combining unce ain ies om
mul iple sou ces in o he inal LCOE me ic. Besides, a disagg ega ed echnique is u ilised
o conside indi idual lea ning e ec s a he componen le el, esul ing in mo e accu a e
cos educ ion es ima es o echnologies unde de elopmen ha lack his o ical da a.
1.4.5 Inno a ion s a egies o o e come echnical
challenges
The de elopmen o cos -e ec i e wa e ene gy sys ems is a di icul endea ou due o he
size o he solu ion space, which calls o inno a i e echnologies o designs. Many
echnical challenges emain un esol ed and inc emen al inno a ion alone canno ill he
gap be ween he cu en echno-economic es ima es and he medium- e m policy a ge s
es ablished o wa e ene gy.
A s anda d ep esen a ion o wa e ene gy subsys ems and hei in e aces is p esen ed
based on he Design S uc u ed Ma ix (DSM) me hod. DSM is a ool o suppo he wa e
ene gy sys em imp o emen , helping isualise po en ial p oblems ha can lead o majo
changes in la e phases, longe in eg a ion ime, and g ea e unce ain ies and isks.
S uc u ed inno a ion me hods a e applied o poin ou po en ial inno a ion s a egies.
The TRIZ p oblem-sol ing app oach has pe mi ed he iden i ica ion o he mos
impac ul ade-o s and co esponding in en i e p inciples ha ing he g ea es impac on
he ini ial S akeholde Requi emen s (SRs). In en i e p inciples sugges ed can be used o
o e come he main echnology shows oppe s and ecu en challenges.
1.5 Thesis S uc u e
The emainde o he hesis is s uc u ed in o se en chap e s o add ess he esea ch goal
and objec i es, as shown in Figu e 1.2.
The ollowing desc ip ions b ie ly ou line he con en o each chap e .
STATE OF THE ART
14
mo e han 3,000 applica ions ha e been iled wo ldwide, and his numbe has no ye
s opped g owing.
The Eu opean Ma ine Ene gy Cen e (EMEC) lis s 256 concep s on i s websi e [29].
Besides, he ELBE p ojec iden i ied 87 companies in 2021, 60% s ill in he ea ly phase o
de elopmen [30]. One eason o he la ge di e si y o concep s is he wa e ene gy
esou ce’s high empo al and geog aphical a iabili y.
The his o y o wa e ene gy has unde gone a cyclic p ocess o op imism, se back and
eassessmen [5]. In he ea ly yea s o wa e ene gy de elopmen , many concep s we e
p oposed. P og ess was slow and inconsis en as in en o s lacked a comple e
unde s anding o he complex hyd odynamic in e ac ions. Figu e 2.3 illus a es he main
miles ones om his ea ly pe iod, which ended wi h he i s comme cial applica ion o
wa e ene gy, a na iga ion buoy om Japanese commande Yoshio Masuda, conside ed
he a he o mode n wa e ene gy echnology [31].
Figu e 2.3: Miles ones o wa e ene gy de elopmen : Ea ly his o y (1799-1970).
The oil c isis o 1973 igge ed a signi ican change in he enewable ene gy scena io,
d awing a en ion o wa e ene gy. A scien i ic pape published in 1974 by S ephen Sal e
[32] became a landma k o he esea ch communi y. This was he ime o he i s
pionee s o he hyd odynamic heo y and maximum powe abso p ion, he i s Na ional
unded concep s and he i s scien i ic con e ences. In his pe iod, many concep s o wa e
ene gy echnologies we e p oposed whose design sough o maximise he annual powe
gene a ion. Figu e 2.4 illus a es he main miles ones om his pe iod.
STATE OF THE ART
15
Figu e 2.4: Miles ones o wa e ene gy de elopmen : Age o Enligh enmen (1970-1990).
Mo e ecen ly, conce ns abou clima e change, he secu i y o ene gy supply and an
inc ease in ene gy p ices enewed he in e es in o he enewable sou ces, and mo e
p ecisely in wa e ene gy. The a ailable R&D unding in his pe iod inc eased s eadily om
he i s p elimina y ac ions s a ed in 1991 o he mos ecen p og ammes. F ui o his
Eu opean and Na ional suppo , a weal h o p o o ypes was de eloped, and a small po ion
was demons a ed a sea. Su i abili y conce ns mainly d o e he design o wa e ene gy
echnologies. In e na ional con e ences, coope a ion and s anda disa ion acili a ed
sha ing o good p ac ices and p omo ed consensus in he sec o . Figu e 2.5 illus a es he
main miles ones om he con empo a y age. Despi e he conside able e o s, he only
g id-connec ed p ojec is he Mu iku Wa e Powe Plan , which has been con inuously
ope a ing since 2011 and deli e ed mo e han 2.7 GWh.
Figu e 2.5: Miles ones o wa e ene gy de elopmen : Con empo a y age (1990-2020).
STATE OF THE ART
16
Despi e he inc eased e o s o e he las decades, ha nessing wa e ene gy con inues o
ox he bes enginee ing minds. Failu e o he wa e ene gy indus y o deli e on he ini ial
expec a ions o in es o s has once and again delayed i s comme cial-scale de elopmen
[3]. Al hough echnologies ha e no eached ull ma u i y, he e is s ill signi ican ac i i y
in wa e ene gy de elopmen a ound he wo ld, including in he Uni ed Kingdom, Eu ope,
he Uni ed S a es, Aus alia, Japan, China, and India. Fu he R&D is needed o explo e
and iden i y he bes solu ions and o achie e con e gence in design.
2.2.3 Technology Classi ica ion
The design o e ec i e wa e ene gy de ices is a complex endea ou ha b ings in o play a
la ge se o decisions. Many design pa ame e s, such as he size and deploymen posi ion
o he ex ac ion p inciple, mus be selec ed a an ea ly s age. E en hough wa e ha nessing
concep s a e so di e se, echnologies can be classi ied acco ding o h ee main c i e ia:
de ice loca ion, o ien a ion and wo king p inciple.
To begin wi h, he classi ica ion based on he de ice loca ion and dis ance o he coas
dis inguishes among h ee gene a ions o de ices (see Figu e 2.6). This classi ica ion was
adop ed by he Eu opean hema ic ne wo k Wa eNe [33].
• Onsho e ( i s gene a ion). De ices which a e ixed o o embedded in sho elines,
om whe e he elec ici y is easily ansmi ed. These a e less ene ge ic loca ions
due o ene gy loss as he wa es each he sho e. Examples include Mu iku [34]
and SSG [35].
• Nea sho e (second gene a ion). Floa ing o bo om-moun ed de ices ins alled in
shallow wa e s (10-40 m). De ices mus be placed beyond he b eake zone o
a oid any su i abili y issues. Pe o mance migh be sensi i e o idal ange.
Examples include Wa eRolle [36] and Co Powe C4 [37].
• O sho e ( hi d gene a ion). Floa ing o subme ged de ices deployed in deep
wa e s. They bene i om he much la ge ene gy esou ce bu also imply highe
cos s o seakeeping and ene gy ansmission o sho e. Examples include Mocean
[38] and SBM S3 [39].
Figu e 2.6: Classi ica ion acco ding o he de ice loca ion.
STATE OF THE ART
17
The second classi ica ion conside s he de ice size and o ien a ion conce ning he
dominan di ec ion o he inciden wa e on (see Figu e 2.7). This classi ica ion
o igina ed in he wo k by Budal and Falnes in 1975 and was la e ex ended by Falnes and
Hals [40].
• Te mina o (T). A de ice wi h has a la ge dimension in he di ec ion ac oss he
p edominan wa e c es s. The main dimension is la ge han one wa eleng h.
Examples include Wa e D agon [41] and CycWEC [42].
• A enua o (A). A de ice wi h a la ge dimension aligned wi h he di ec ion o
he p edominan wa e p opaga ion. Examples include Pelamis [43] and
Anaconda [44].
• Poin Abso be (PA). A de ice wi h small dimensions ela i e o he inciden
wa eleng h and able o abso b ene gy om all di ec ions. Examples include OPT-
PB3 [45] and AWS [46].
• Quasi Poin Abso be (QPA). An axisymme ic de ice wi h ela i ely la ge
dimensions compa ed wi h he wa eleng h. The p ima y dimension is be ween a
PA and a Line Abso be (i.e. he agg upa ion o T & A). Examples include OE
Buoy [47] and Wello [48].
Figu e 2.7: Classi ica ion acco ding o de ice o ien a ion (adap ed om [49]).
The g ea di e si y o concep s has mo i a ed a hi d classi ica ion o de ices. This ime,
de ices a e classi ied acco ding o hei wo king p inciple. The nine g oupings a e based
on ecen classi ica ion e o s o [2], [3], [50] and [51].
• Oscilla ing Wa e Column (see Figu e 2.8-a): Pa ially subme ged s uc u es
open below he sea le el and wi h ai apped abo e he wa e su ace. Incoming
wa es make oscilla e he wa e su ace wi hin he de ice, mo ing he ai like a
pis on. Examples include Mu iku [34] and OE Buoy [47].
• Hinged Con ou (see Figu e 2.8-b): De ices wi h wo o mo e sepa a e bodies
ha mo e ela i e o each o he as a wa e passes hem. Ene gy is ex ac ed om
STATE OF THE ART
18
he eac ion be ween he indi idual componen s. Examples include Pelamis [43]
and Mocean [38].
• Buoyancy (see Figu e 2.8-c): Ene gy is ex ac ed om he mo ion induced as
wa es pass he ela i ely small buoyan bodies. Examples include OPT-PB3 [45]
and Co Powe C4 [37].
• Oscilla ing Wa e Su ge (see Figu e 2.8-d): De ices which ex ac ene gy om
wa e su ges and he mo emen o wa e pa icles wi hin hem. Examples include
Wa eRolle [36] and Wa ePis on [52].
• O e opping (see Figu e 2.8-e): De ices which a e essen ially ese oi s ha
wa es ill wi h wa e . The wa e is hen e u ned o he sea ia a u bine. Examples
include SSG [35] and Wa e D agon [41].
• Subme ged P essu e Di e en ial (see Figu e 2.8- ): Subme ged de ices in which
a p essu e di e en ial is c ea ed as he wa e passes abo e due o he sea le el
luc ua ion. The al e na ing p essu e is used o gene a e ene gy. Examples include
AWS [46] and mWa e [53].
• Bulge Wa e (see Figu e 2.8-g): Subme ged ubula de ices illed wi h p essu ised
seawa e and moo ed o he seabed. The passing wa e causes p essu e a ia ions
c ea ing a bulge ha a els along he leng h o he ube and is used o gene a e
ene gy. Examples include SBM S3 [39] and Anaconda [44].
• Ine ia (see Figu e 2.8-h): De ices ha use he mo ion o he wa es o o a e,
swing o p ecess an ine ial mass. Examples include Wello [48] and ISWEC [54].
• Li Fo ce (see Figu e 2.8-i): The passing wa es p oduce li on a hyd o oil
c ea ing a o que a he main sha o o a ion. Examples include CycWEC [42]
and Li WEC [55].
Figu e 2.8: Classi ica ion acco ding o de ice wo king p inciple.
STATE OF THE ART
19
2.2.4 Main Subsys ems
An o e iew o he key subsys ems ha equi e conside a ion o wa e ene gy sys ems is
p o ided in [56], [57] and [58]. Acco ding o hese sou ces, he WECs can be g ouped in o
i e main subsys ems, Reac ion Sys em, Powe Take-O , Hyd odynamic Sys em, Powe
T ansmission and Con ol, leading o many combina ions. The la ge a ie y o wa e
ene gy concep s makes i challenging o analyse all possible decomposi ions and o
p oduce a gene ic and manageable sys em b eakdown.
Thus, he s anda d app oach adop ed in he sec o is o de ine he high-le el b eakdown
conce ning he a ious unc ions he de ice mus ul il. The axonomy o subsys ems
desc ibed below is mainly de i ed om [56] and [59].
Table 2.1: Sys em b eakdown o wa e ene gy echnologies.
Func ion Subsys ems
Cap u e ene gy Hyd odynamic Sys em (HS)
P o ide eac ion poin Reac ion Body (RB)
Con e ene gy Powe Take-O (PTO)
S o e and condi ion ene gy S o age and Powe Condi ioning (SC)
Deli e ene gy T ansmission Sys em (TS)
Main ain posi ion S a ion Keeping (SK)
Con ol ope a ion Ins umen a ion and Con ol (IC)
Hyd odynamic Sys em (HS). This e m desc ibes he de ice s uc u e and mechanisms
di ec ly in e ac ing wi h he wa es, which can be ei he loa ing o subme ged. I is
he e o e he p ima y wa e abso p ion sys em. The HS is connec ed o he RB and he
PTO o he ac i e ans e o o ces and mo ions.
Reac ion Body (RB). I is he s uc u e ha p o ides a eac ion poin o he PTO and/o
suppo o he HS. Th ee main eac ion ypes can be iden i ied (see Figu e 2.9):
• Fixed e e ence: A s a ic coupling o he Seabed o a dynamic one h ough he
SK. In he la e , he RB has a la ge mass o emula e a ixed e e ence a oiding he
need o adjus o he idal ange.
• Sel - e e ence: In his case, he HS eac s agains ano he HS wi hou needing a
physical RB.
• Ine ial e e ence: The RB is somehow encapsula ed wi hin he HS and eac s
agains i . Examples a e a pendulum, sliding o o a ing mass, apped wa e and
gy oscope. The RB mass is smalle han ha o he HS.
STATE OF THE ART
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Figu e 2.9: Types o eac ion poin s.
Powe Take-O (PTO). This sys em con e s he mechanical ene gy ex ac ed om he
wa es in o a use ul o m, gene ally elec ici y. Se e al al e na i e con igu a ions ha e been
p oposed in ol ing a combina ion o luid, mechanical and elec ical powe lows (see
Figu e 2.10).
Fo each p ima y ene gy con e sion s age, di e en comme cial solu ions exis (see [60],
[61]):
• Ai Tu bine: Wells u bine, Dennis-Auld u bine, Impulse u bine, Bi- adial
u bine.
• Hyd o Tu bine: Pel on u bine, Kascheme u bine, F ancis u bine.
• Hyd aulic Sys em: Hyd aulic am, Hyd aulic pump.
• Mechanical T ansmission: Gea box d i e, Rack and pinion d i e, Ball sc ew
d i e.
• Di ec D i e: Linea gene a o , Ball sc ew gene a o , Elec oac i e polyme s,
T iboelec ic nanogene a o s (TENGs).
Figu e 2.10: Al e na i e PTO Con igu a ions.
STATE OF THE ART
21
S o age and Powe Condi ioning (SC). The ins an aneous wa e powe abso bed by he
PTO luc ua es b oadly be ween indi idual wa es and wa e g oups. When p esen , his
op ional subsys em aims o a oid excessi e peaks, allow a smoo h ou pu and imp o e he
powe quali y. Depending on he WEC con igu a ion, i can be placed a di e en poin s
o he ans o ma ion chain (see Figu e 2.10) and can make use o ei he luid powe
(Accumula o ), mechanical powe (Flywheel), elec ical powe (Ba e y, Capaci o ,
In e e ) o a combina ion o hem.
T ansmission Sys em (TS). This is he me hod by which ene gy is ans e ed o sho e. I
gene ally in ol es agg ega ion, expo and g id connec ion. Al hough opologies a y,
elec ici y ansmission om indi idual de ices o an onsho e subs a ion equi es in e -
a ay cables connec ed o a collec ion poin , which is likely o in ol e s ep-up
ans o ma ion and isola ion swi chgea and an expo cable.
S a ion Keeping (SK). This sys em main ains he de ice in posi ion ela i e o he seabed.
I can be ei he igid ( ounda ion) o complian (moo ing). The o me is mo e likely o
be used nea sho e (i.e. shallow wa e ), whe eas he la e is mo e app op ia e o o sho e
loca ions (i.e. deep wa e ). Moo ing sys ems a e comp ised o one o mo e lines and an
ancho ing sys em. In u n, moo ing lines can be slack, au o combined.
Ins umen a ion and Con ol (IC). Ha dwa e and so wa e sys ems o sa egua d he
de ice and op imise i s pe o mance unde a ange o ope a ing condi ions. They comp ise
senso s, da a acquisi ion, communica ion, and da a ans e equipmen o implemen
con ol ac ions.
2.3 Sys ems Enginee ing
2.3.1 A Sys ema ic P oblem-sol ing App oach
Sys ems Enginee ing (SE) has a ela i ely sho his o y. The i s documen ed use o his
e m da es o Bell Telephone Labo a o ies in he ea ly 1940s [62]. De eloped a Bell Labs
in he ollowing decade, SE was u he e ined du ing he success ul NASA Apollo
p og amme in he 1960s. Since hen, i has e ol ed in o a o mal discipline ha can be
adap ed o a ious ypes o p oduc de elopmen s.
SE uses a sys em hinking app oach o analyse enginee ing p oblems. The indi idual
ou come o such e o s is he enginee ed sys em. A sys em can be de ined as an in e ac ing
combina ion o elemen s o accomplish a de ined objec i e [63].
Fundamen al o SE is he no ion o he sys em li e cycle [64]. The li e cycle o a p oduc
begins wi h he iden i ica ion o a need. I ex ends h ough concep ual and p elimina y
design, de ailed design and de elopmen , manu ac u e and ins alla ion, ope a ion and
main enance, decommissioning and inally disposal o ecycling.
STATE OF THE ART
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The need o SE a ises wi h he inc ease in he complexi y o enginee ed sys ems. SE is a
holis ic, op-down app oach o unde s anding s akeholde needs, explo ing oppo uni ies,
documen ing equi emen s, and syn hesising, e i ying, alida ing and e ol ing solu ions
while conside ing he comple e p oblem [63]. The ambigui y in de ining he equi emen s
and he lack o p ope planning a e he majo ac o s ha d i e he need o a SE app oach
[65].
SE hinges upon se e al undamen al p inciples. Among hem, i e o he mos impo an
ones a e [66]:
• Abs ac ion. SE is based on he idea ha he pu pose o design is no o p oduce
a conc e e solu ion bu o c ea e an abs ac en i y called a sys em. Such a sys em
can hen be ma e ialised h ough se e al di e en solu ions.
• Decomposabili y. A sys em can be b oken down in o sepa a e elemen s
(modula isa ion) ha may co e se e al laye s (hie a chy). These elemen s ha e
an in eg a i e a chi ec u e.
• Plu alism. The sys em can be add essed om complemen a y poin s o iew,
which mus be o ganised in ways ha pe mi he sha ing o complex knowledge.
• Alignmen . SE conce ns bo h he p oduc and he way he design is o ganised.
De eloping a solu ion equi es aligning design p ocesses and p oduc s uc u e.
• Inc emen al imp o emen . Design o ganisa ion is based on “ ou ines” ha can
be codi ied, gene alised, lea ned and e-cycled om one p ojec o eam o
ano he .
SE is abou bo h design and decision-making [66]. The success o any complex enginee ing
p ojec depends upon ou main ac i i ies:
• Iden i ying and e alua ing al e na i es,
• Managing unce ain y and isk,
• Designing quali y in o a sys em, and
• Dealing wi h p ojec managemen issues.
The i s ac i i y is c i ical as i de ines he p obabili y o success, whils he es help he
enginee o a oid any e o s. A Sys ems Enginee needs o unde s and ha decisions mus
be made wi h he bes in o ma ion a ailable a he ime, and he e o e he e a e always
subjec o some deg ee o unce ain y.
SE app oaches and me hods ha e been success ully applied in many indus ial sec o s (e.g.
au omo i e, ae ospace, oil & gas) o de elop inno a i e p oduc s mee ing e y di e se and
demanding s akeholde equi emen s. Se e al s anda ds ha e been de eloped o SE such
as [67], [68], and [69].
Th ough he yea s, he ini ial p ac ice-based SE has been en iched wi h a ple ho a o
heo e ical app oaches, ools and models in di e en SE schools wo ldwide [70]. Among
STATE OF THE ART
23
he many me hodologies used, he SE app oaches can be g ouped in o h ee ca ego ies
acco ding o hei p ima y ocus:
• Gene ic design me hodologies such as Sys ema ic Design [16], [71], and
Axioma ic Design [72];
• P ocess-o ien ed me hodologies such as Concu en Enginee ing [73] and
Design S uc u e Ma ix [74]; and inally
• Design me hodologies o achie e conc e e goals such as D X [75], QFD [76],
FMEA [77] and TRIZ [78].
Abs ac models a e eplacing he adi ional documen -based SE as he p ima y means o
e aining and communica ing in o ma ion. Model-based Sys ems Enginee ing (MBSE)
enhances he abili y o cap u e, analyse, sha e, and manage he da a associa ed wi h he
speci ica ion o a p oduc [63]. MBSE helps o iden i y issues ea ly in he sys em de ini ion,
hus imp o ing sys em quali y and lowe ing bo h he isk and cos o sys em de elopmen .
As in oduced in CHAPTER 1, ini ial ideas o expec a ions abou he enginee ing sys em
a e buil on a ela i ely insecu e in o ma ion basis a an ea ly s age [79]. F equen ly,
nei he he p oblem no he solu ion ield is pa icula ly well-known. The e o e, a
sys ema ic and well-s uc u ed p ocess should unde pin he sea ch o solu ions and
selec ion.
2.3.2 The Concep o Design Domains
The design o a new p oduc is an endea ou ha in ol es a mix o c ea i i y, echnical
skills and decision-making. No ma e whe e an inno a i e concep may come om, i s
ealisa ion should always be he ou come o a ho ough design p ocess. To ha pu pose,
o ganising he design in o ma ion is c i ical.
Design in ol es an in e play be ween wha he enginee wan s o achie e and how his
need is sa is ied. Howe e , he e is no single commonly acknowledged sequence o s eps
in enginee ing sys ems design. The concep o design domains helps sys ema ise his
p ocess by c ea ing bounda y lines be ween di e en design ac i i ies [72].
Design domains p o ide enginee s wi h an imp o ed way o a anging design in o ma ion
o acili a e be e SE [80]. They help o o ganise in o ma ion on equi emen s and o
disc imina e i om he in o ma ion associa ed wi h design solu ions. The sys ema ic
p esen a ion o in o ma ion s imula es he sea ch o solu ions and acili a es iden i ying
and combining essen ial solu ion cha ac e is ics [71]. Ul ima ely, his amewo k a oids
quan um leaps om he ini ial equi emen s o he physical ealisa ion ha a e ad hoc,
ine icien , ine ec i e, and o en lead o cos and schedule o e uns [81].
Design domains s uc u e in o ma ion in pa icula ways o accommoda e hei own
needs. Much a en ion should be paid o he consis ency o in o ma ion wi hin and ac oss
domains. Each design domain has an associa ed model, which ac s as a amewo k o
STATE OF THE ART
30
included by combining u ili y analysis wi h SBD me hods. To apply u ili y-based decisions
in SBD, designe s c ea e a u ili y unc ion ha weigh s each concep ’s a ibu e. Wi hin
each a ibu e, he concep is gi en an in e al sco e. The in e al sco e allows he
designe s o accoun o he span o possible alues gi en he imp ecision o concep ual
design.
Mul i-c i e ia analysis me hods in o m he decision-making p ocess o selec ing
solu ions o complex enginee ing p oblems, mainly when al e na i e solu ions can be
he e ogeneous. Many me hods ha e been de eloped o sol e di e en ypes o decision
p oblems. Howe e , he decision make is aced wi h he a duous ask o selec ing an
app op ia e decision suppo ool [100]. One way o add ess his ask is o look a he
modelling e o (i.e. equi ed inpu da a) and he g anula i y o ou comes (i.e. easible
solu ion, pa ial o comple e anking). Mul i-A ibu e U ili y Theo y (MAUT) [101] is
used a he highes modelling e o when a ep esen a ion o he pe cei ed u ili y o e e y
selec ion c i e ion can be buil . Analy ical Hie a chy P ocess (AHP) me hods [102] use
pai wise compa isons be ween c i e ia and op ions a a medium scale o he modelling
e o . Finally, a he lowes end o he modelling e o , Da a En elopmen Analysis (DEA)
[103] is mos ly used o pe o mance e alua ion o benchma king, whe e no subjec i e
inpu s a e equi ed.
Sol ing a eal p oblem using a linea app oach is seldom achie able. The SE app oach can
be applied i e a i ely o mo e owa ds an accep able solu ion o a p oblem wi hin a la ge
cycle o s akeholde alue [63]. The e alua ion is epea ed a inc easing le els o
echnological ma u i y as he concep p og esses om an ini ial idea o a ho oughly es ed
and p o en sys em. This i e a i e isk-based analysis me hod o p oduc de elopmen is
o malised in SE h ough he spi al model [85] and he S age-Ga e model [104]. O e he
yea s, SE has de eloped many ools and echniques o isk managemen , such as FMEA
[77], FTA [105], Fuzzy Logic [106], Bayesian Analysis [107] and Mon e Ca lo simula ion
[108]. I a SE app oach is es ablished ea ly in he p ojec , he sys em me ics achie ed a
any s age a e compa ed o he design goals and imp o emen s implemen ed, i necessa y,
o achie e hese goals.
2.3.6 Applica ion o SE Me hods o Wa e Ene gy
Wa e ene gy echnology is a clea example o a complex enginee ing p oduc , whose
de elopmen is ine i ably mul idisciplina y. So a , wa e ene gy de elopmen expe ience
shows ha excellence in each discipline is a necessa y bu no su icien condi ion o
achie e a iable p oduc . SE p o ides a amewo k o a holis ic app oach ha migh allow
p og ess owa ds a success ul wa e ene gy echnology [109].
The need o a mo e comp ehensi e sys ems pe spec i e on he de elopmen o wa e
ene gy echnologies was also highligh ed in a ecen wo kshop on iden i ying u u e
eme ging echnologies in he ocean ene gy sec o [60]. The epo poin s ou ha some
p ac ical aspec s neglec ed a an ea ly s age can become a p oblem i aken up a a la e
s age. The e o e, echnology de elope s should mo e om a sequen ial o a sys em design
STATE OF THE ART
31
p ocess. To o e come ailu es p e iously expe ienced in he sec o , an in eg a ed sys ems
app oach is equi ed o de elop wa e ene gy sys ems; subsys ems canno be de eloped in
isola ion.
Simila ly, sec o expe s ha e ecognised SE p inciples as a way o accele a e ma ine ene gy
esea ch [110]. Su ey esul s ecommended ocusing on common componen s o enable
a o dable ways o ha es ma ine ene gy and no on speci ic echnologies. Expe s also
sugges ed p o ing ha a sys em wo ks eliably, checking i s unc ionali y in he ea ly
p ojec s ages and consequen ly ocusing on end-use equi emen s.
As p esen ed in sec ion 2.2, wa e ene gy echnologies span a b oad design space. The
a ie y o concep s makes i ex emely di icul o iden i y common design app oaches.
Mo eo e , he e is li le published wo k on he speci ic design me hods used in de eloping
hese de ices since mos echnology de elope s a e p i a e companies.
E en hough some companies seem awa e o exis ing SE me hods, i is a s ikingly ecen
phenomenon (only documen ed in he las 10-yea ime ame). Also, he applica ion o SE
migh ha e been limi ed and agmen ed, since hese echnology de elope s ha e no been
ee om su e ing expensi e, high- isk, slow, igid and discon inued echnology
de elopmen s.
A small ac ion o e e ences o ac i i ies ca ied ou du ing he en i onmen al analysis
can be ound in he li e a u e:
• Bull e al. [111] p esen ed he con ex diag am used o de ine he ex e nal sys ems
ha di ec ly in luence he success o a g id-connec ed wa e ene gy a m. This lis
iden i ies he ac o s ha a e ou o he con ol o he ex e nal sys ems and he
a m (i.e. poli ical, social, and economic clima e). I is poin ed ou ha he
o e a ching con ex can in luence he ex e nal sys ems and he a m’s success.
Howe e , he SDs a e no explici ly analysed.
• Sandbe g e al. [112] analysed he c i ical ac o s o he comme cial iabili y o
WECs in o -g id luxu y eso s and small u ili ies using PESTLE ools and
Po e ’s i e compe i i e o ces. Fac o s like he a ailable wa e esou ce, dis ance
om sho e, exis ing in as uc u e, powe demand, supply chain logis ics,
al e na i e ene gy sou ces and cu en cos o ene gy we e ound o ha e
signi ican impac s.
• de And es e al. [113] ca ied ou a simila analysis o e eal he isks and
unce ain ies acing la ge-scale g id-connec ed wa e and idal ene gy p ojec s.
This wo k showed ha al hough he poli ical, economic and social aspec s ha e
g ea impo ance, he echnological ba ie s a e key o a ac ing in es o s.
• PNNL and NREL a e conduc ing a h ee-yea p ojec o e iew he g id alue o
ma ine ene gy de elopmen a scale on an in e media e- o long- e m ho izon.
G id alues a e a anged in o h ee ca ego ies: ma ine ene gy's spa ial o
loca ional aspec s, empo al o iming ac o s, and speci ic applica ions o cap u e
he mos si ua ional bene i s [114].
STATE OF THE ART
32
• H2020 DTOceanPlus p ojec p esen ed a summa y o non- echnical ba ie s and
enable s o wa e and idal s eam comme cialisa ion in i s public deli e able D8.1
[115]. The ac o s lis ed om li e a u e sou ces comp ise p i a e and public
inancing, insu ance, con inued cos educ ion, suppo i e consen ing and
egula ion, in as uc u e, s anda ds and ce i ica ion, inno a ion, c oss-sec o al
in e linkages, and e hical and en i onmen al conce ns.
A ibu es ha cha ac e ise he Sys em D i e s (SDs) a e ai ly co e ed o wa e ene gy,
bu un o una ely, he e is no e e ence o how hese SDs in e ac wi h each o he and a e
p io i ised.
Rega ding he s akeholde analysis, he e iew o he li e a u e e eals e y di e se
classi ica ions o s akeholde s o ma ine ene gy p ojec s, such as:
• Isakhanyan and Wil [116] iden i y six main s akeholde g oups, namely
Designe s & de elope s, Go e nmen s & public au ho i ies, Pa ne companies,
Financial ins i u ions, Knowledge ins i u es, and En i onmen al o ganisa ions
• The FP7 EQUIMAR p ojec [117] conside s s akeholde s du ing he en i e
p ojec li ecycle. A he ini ial s ages o p ojec de elopmen , owne s, de elope s,
supplie s, employees, he go e nmen , unions, and indi iduals o whole
communi ies loca ed nea o in he icini y ha e a c ucial in luence. When
ope a ional, c edi o s and end ene gy use s can be included as well. S akeholde s
a e hen g ouped in o ou ca ego ies: S a u o y consul ees, S a egic
s akeholde s, Communi y s akeholde s, and Symbio ic s akeholde s.
• Mo e ecen ly, in [118], wen y-six wa e ene gy s akeholde s a e iden i ied, who
a e g ouped in o ou ca ego ies: Highes -le el s akeholde s, Co e s akeholde s,
Fi s - ie supplie s, and Low- ie supplie s.
Despi e he unde pinning esea ch ha assis s in iden i ying wa e ene gy s akeholde s,
s akeholde p io i isa ion has no been ca ied ou sys ema ically. S akeholde mapping
echniques, usually based on wo o h ee dimensions (e.g. powe , in e es and u gency),
ha e been used in o he sec o s o de e mine he p io i y o iden i ied s akeholde s [119]
[120].
The elici a ion o S akeholde Requi emen s (SRs) la gely depends on he ype o ma ke
being add essed. As explained in subsec ion 2.3.2, he en i onmen al domain accoun s o
he ac o s linked o he added alue o he in ended ma ke . Bo h Wa ebob [121] and
u ili y company PG&E [122] men ion using SE o e lec end-use needs and de elop op-
le el equi emen s.
A he ime o w i ing, he Wa e-SPARC p ojec [123] has p oduced he mos
comp ehensi e analysis o he wa e ene gy s akeholde domain. Wa e-SPARC has
deli e ed a comple e and agnos ic o mula ion o a u ili y-scale wa e ene gy p ojec
h ough SE and s akeholde analysis. The analysis o s akeholde s’ needs in [118] led o
STATE OF THE ART
33
se en high-le el SRs and a o al o 33 low-le el SRs. Cos s and isks a e iden i ied as wo
o he high-le el equi emen s. The o he i e ca ego ies in he high-le el SRs con ain a
mix u e o bene i s ( eliable o g id ope a ions), oppo uni ies (bene i socie y, deployable
globally) and isks (accep abili y and sa e y). SRs a e no anked/weigh ed acco ding o
hei ela i e impo ance.
To ank SRs, Jahanshahi e al. [124] applied he Delphi me hod o assess he economic
equi emen s and hei ela i e impo ance o de eloping wa e and idal ene gy
echnologies based on he expe 's judgmen . Ope a ional cos s and e enue we e anked
as he mos impo an c i e ia om he expe s' poin s o iew. P e-ope a ion cos s and
in es men , incen i es, p o i abili y and ex e nali ies we e o de ed in he nex p io i ies,
espec i ely. I is wo hwhile no ing ha bo h he incen i es and ex e nali ies a e Sys em
D i e s and hus should belong o he en i onmen al domain.
Fu he esea ch e o s should be de o ed o he de elopmen o a mo e in eg a ed and
objec i e app oach o s akeholde analysis o a ious po en ial ma ke s o wa e ene gy
echnologies.
The unc ional analysis in SE has he objec i e o de ining he unc ional a chi ec u e o
he sys em and cha ac e ising i s unc ional beha iou . Func ional Requi emen s (FRs) a e
he b idge be ween he s akeholde s and echnical eams and shall be speci ied a each s age
o he sys em li ecycle.
• Wa ebob [121] de ined ope a ional scena ios igh h ough om anspo a ion,
assembly, ins alla ion and commissioning o ope a ion, main enance, suppo
and decommissioning. Mo e ecen ly, Baba i e al. [118] iden i ied six li ecycle
s ages o a wa e ene gy a m: Enginee ing, P ocu emen , Cons uc ion,
Ins alla ion, Ope a ions, and Disposal.
• F ench [125], [126] p oposed a sys ema ic app oach o he concep ual design o
WECs du ing i s ope a ional phase, iden i ying he unc ions, selec ing hose
ha ing an impo an bea ing on cos , and ying o ind ways o pe o ming hose
unc ions economically. The design o WECs is exempli ied h ough he analysis
o possible combina ions o h ee main unc ions: p o ide a wo king su ace,
p o ide a eac ion o ce, and ex ac powe .
• The Uni e si y o Uppsala has applied a sys ems app oach o de elop ways o
ha ness wa e ene gy which conside s manu ac u ing, main enance and
compa ibili y wi h he na u al en i onmen ea ly in he design p ocess [127].
These c i e ia a e no gene ally used o down-selec ing a concep om a se o
solu ions ha achie e he desi ed unc ionali y.
• Technology de elope Ma i e [128] implemen ed a SE app oach o
sys ema ically selec candida e a chi ec u es and o de ine FRs o sys em design
and de elopmen . Simila ly, he u ili y company PG&E [122] de eloped a se o
unc ional block diag ams o iden i y unc ional ela ionships be ween sys em
in as uc u e segmen s and ex e nal sys ems in he Wa eConnec p ojec . [129]
STATE OF THE ART
34
desc ibed he unc ions pe o med by he OWC powe plan o con e wa e
powe in o elec ici y.
• Pa ial co e age o FRs can be ound in [130], whe e FRs a e o mula ed in he
con ex o wa e ene gy con e sion, bu only o he moo ing sys em, and [131],
who has p oduced a comp ehensi e landscaping epo o Wa e Ene gy
Sco land (WES) on FRs o WEC con ols. Innosea [132] p esen s a unc ional
analysis o he subme gence sys em o a Spa OWC in he o m o an oc opus
diag am, exposing he elemen s in e ac ing wi h he sys em, and he main
unc ions (se ice and cons ain ). The unc ional analysis esul s in a se o
unc ional speci ica ions, showing he expec ed sys em unc ions, he judgemen
c i e ia, he le els o hese c i e ia, and he lexibili y.
• Bull e al. [133] p esen a ull axonomy o FRs o a wa e ene gy a m. The i e
op-le el unc ions iden i y wha he wa e ene gy a m mus do o mee i s
mission. The sub unc ions below he op le els u he decompose he op-le el
unc ions (e.g. WEC o elec ical subs a ion). These sub unc ions iden i y he
unique aspec s ha mus be achie able o sa is y he highe -le el unc ion.
Fu he b eakdown is gi en o sub unc ions in he o m o sub-sub unc ions,
u he ocusing on he needed de ails (e.g. PTO wi hin a WEC). A each le el,
unc ions a e mapped o capabili ies h ough MOPs.
The analysis o FRs o wa e ene gy sys ems is easonably well co e ed in he li e a u e.
The e is also a g owing awa eness o he need o de ine unc ional pe o mance measu es
o judge he success o wa e ene gy echnologies. Al hough his is e y posi i e, he e is
s ill he need o me hods ha es ablish he ela i e impo ance o FRs and hei
in e ac ions.
The echnical analysis deals wi h he lowe -le el unc ions alloca ed o he sys em’s
physical a chi ec u e [65], which depend on he design solu ion. Hence, he e is li le
in o ma ion on he Technical Requi emen s (TRs) used o ake design decisions and sizing
componen s.
• Scha mann [134] p esen s a comp ehensi e unc ional analysis, echnical
b eakdown and mapping o sys em equi emen s o he main cos cen es o a
pa icula WEC, i.e. o o , PTO, subs uc u e, ins alla ion and main enance
ope a ions.
• Wa ebob [121] and Wa es4Powe [135] a e wo examples o echnology
de elope s whe e sys em decomposi ion and unc ional alloca ion ha e also been
documen ed. In he case o Wa ebob, his p ocess was mainly d i en by eliabili y
conce ns.
• Se e al s anda ds and guidelines ha e been p oduced o assis in he de elopmen
o he TRs and assessmen o echnical pe o mance: EMEC guidelines o G id
Connec ion [136], as well as IEC design equi emen s [137], powe pe o mance
equi emen s [138] and powe quali y equi emen s [139].
STATE OF THE ART
35
Finally, he iden i ica ion o manu ac u ing isks begins a he ea lies s ages o echnology
de elopmen and con inues igo ously h oughou each s age o sys em design.
Un o una ely, he e a e no e e ences in he li e a u e o he de elopmen o
Manu ac u ing Requi emen s (MRs) speci ic o WEC de ices. Manu ac u ing Readiness
Le els (MRLs) a e commonly used o measu e p og ess on he e ec i eness o p oducing
speci ic componen s and assemblies [140]. EMEC has p oduced some guidelines o he
Manu ac u ing, Assembly and Tes ing o Ma ine Ene gy Con e sion Sys ems [141]. This
documen does no con ain a lis o MRs, bu i could be used o inspi e he de elopmen
o MRs.
2.4 Technology Pe o mance Assessmen
2.4.1 An E ol ing F amewo k
E alua ion o echnology pe o mance is a con inuous ac i i y ha should occu a all
de elopmen s ages [63]. A commonly ag eed e alua ion amewo k can b ing signi ican
bene i s o all wa e ene gy s akeholde s, including inc eased cla i y, consis ency and
di ec ion in he de elopmen [142]. Ea ly design decisions based on objec i e c i e ia a e
key o lowe ing de elopmen unce ain ies, cos and ime.
T adi ionally, he e alua ion o wa e ene gy echnologies has hea ily hinged on he
Technology Readiness Le els (TRLs). The TRL scale was ini ially o mula ed a NASA in
1974 (se en le els) and o mally de ined as i s ands oday (nine le els) in 1989 [143]. The
TRL concep was concei ed o assis in he de elopmen o space echnologies and enable
mo e e ec i e communica ion on he ma u i y le el o eme ging echnologies. Howe e ,
TRLs only assess he ma u i y and isks wi hin he wa e ene gy de elopmen p ocess
a he han i s quali y, echnical o economic pe o mance.
Figu e 2.14: Technology Readiness Le els and IEC S ages.
STATE OF THE ART
36
Se e al TRL de ini ions speci ic o wa e ene gy ha e been p oposed [144], [145]. I is usual
in wa e ene gy o g oup he sys ema ic TRL de elopmen in s ages. A de ice o subsys em
mus ul il s age-ga e c i e ia a he end o each s age be o e passing o he nex
de elopmen s age. The mos common amewo k consis s o i e s ages. I was ini ially
p oposed a HMRC o mi iga e inancial and echnical isks du ing he de elopmen o
buoyan de ices [146], la e adop ed as bes p ac ice by IEA-OES [147] and FP7
EQUIMAR [59], and inally ecommended by IEC [148]. Figu e 2.14 p esen s he TRL
scale and i s co ela ion wi h IEC s ages.
The i s a emp o de i e a p ope pe o mance assessmen o wa e ene gy echnologies
was p oposed by Nielsen [19]. Sugges ions included a ios such as he Cap u e Wid h,
Ene gy o Volume o Mass, Powe Take-O E iciency, Capaci y Fac o and Capi al Cos
o Ene gy. La e , he Eu opean p ojec EQUIMAR [59] added o he assessmen igu es o
hese me ics such as he Ope a ing Cos , A ailabili y Fac o and Le elised Cos o Ene gy
(LCOE). In 2009, EMEC in oduced some guidelines o unc ional pe o mance measu es
o ma ine ene gy con e sion sys ems, such as eliabili y, main ainabili y and su i abili y
[149].
E alua ion me hodologies based on he LCOE ha e been a he cen e o wa e ene gy
echnology de elopmen . LCOE combines wo ele an s akeholde equi emen s in a
single me ic: li e ime cos s and ene gy p oduc ion. This is why Ca cas e al. [150] examine
he key pe o mance me ics ha unde pin LCOE (i.e. CAPEX, OPEX, Yield, Reliabili y,
Cos o inance, Su i abili y, Du abili y and P ojec size). Fu he mo e, he LCOE
assessmen me hod is akin o well-known cos -bene i analyses [71].
The e e sed LCOE enginee ing [145] is a me hodology o explo e he limi s o he WEC’s
echnical pa ame e s. In his app oach, an LCOE a ge is se and he uppe -cos limi s o
he main subsys ems o he WEC a e ob ained. Lea ning a es due o ac o s such as
p oduc ion olume and au oma ion can also be conside ed o assess whe he he cos
limi s o a subsys em can be eached om cu en cos s. This me hodology elies on p io
knowledge o alloca ing cos cen es o he physical ealisa ion. I helps exis ing p o o ypes
o imp o e hei comme cial a ac i eness bu does no gua an ee s akeholde alue is
maximised.
Since 2014, he Uni ed S a es has been de eloping and applying a holis ic and quan i a i e
echno-economic assessmen me ic sys em o iden i y echnology weaknesses and
s eng hs, ul ima ely ad ancing echnology owa ds hei ma ke applica ions [133]. This
de- isking app oach applies o all WEC sys ems ha a e cu en ly unde de elopmen and
o he no el sys ems in en ed in he p ojec . Sys em pe o mance is measu ed h ough he
Technology Pe o mance Le els (TPLs) me ic. The de elopmen o he TPL assessmen
c i e ia, me hods and ools was i s in oduced by Webe [151], u he de eloped in
[152], and p ac ically applied and enhanced in he Wa e-SPARC p ojec [123]. The la es
e sion o he TPL Assessmen Tool can be accessed online a NREL’s websi e [153].
STATE OF THE ART
37
The lis o equi emen s de eloped in Wa e-SPARC se es as he componen s o he TPL
me ic [133]. The se en capabili ies g oups mee he se en high-le el SRs and cons i u e
he ul ima e me ics a u ili y-scale wa e ene gy p ojec mus sa is y. The lowes le el
sys em capabili ies in he TPL me hod a e sco ed and p og essi ely agg ega ed ollowing
a ma hema ical calcula ion. The e a e h ee ways o combining he lowes le el sco es:
a i hme ic mean, geome ic mean and mul iplica ion wi h no malisa ion. The o e all
sco e is calcula ed om sco es o he se en high-le el capabili ies a anged in h ee
ca ego ies (weigh ed a e age o indi idual geome ic means). Howe e , his app oach
equi es expe assis ance o pe o m he assessmen due o he sco ing complexi y. In he
public e sion o he ool, he weigh ing o he di e en c i e ia is ixed. The TPL
assessmen canno be adap ed o changing ma ke condi ions o s akeholde s’
expec a ions, which will inciden ally hinde he aceabili y o sys em equi emen s ac oss
domains.
Since 2016, WES has p omo ed he de elopmen o pe o mance me ics and ools o
ocean ene gy echnologies ia wo kshops wi h a b oad in e na ional c oss-sec o inpu
[154]. Simila ly, he Wa e Powe Technologies O ice [155] has con ibu ed o gaining an
in e na ional consensus by compiling a lis o exis ing Ocean Ene gy pe o mance me ics
o he a m le el, he wa e ene gy de ice, and i s main subsys ems (e.g. s uc u e, PTO,
con ol, moo ing).
As men ioned be o e, he concep o s aged de elopmen is inhe en o pe o mance
assessmen . IEA-OES is p omo ing he adop ion o an in e na ional e alua ion and
guidance amewo k o ocean ene gy echnologies based on his concep [142]. S ages a e
loosely ela ed o he TRL scale; a each s age ga e, an e alua ion o he ele an me ics is
done.
Figu e 2.15: E alua ion A eas included in he E alua ion and Guidance F amewo k [142].
STATE OF THE ART
38
The i s -o -kind implemen a ion o his amewo k has been p oduced in he EU H2020-
unded DTOceanPlus sui e o design ools o ocean ene gy sys ems [156]. Assessmen s
a e g ouped in o ou main ca ego ies, namely SPEY (Sys em Pe o mance and Ene gy
Yield), RAMS (Reliabili y, A ailabili y, Main ainabili y and Su i abili y), SLC (Sys em
Li e ime Cos s), and ESA (En i onmen al and Social Accep ance). These assessmen s eed
in o a S age-Ga e ool o he o e all assessmen o ocean ene gy echnologies.
As can be app ecia ed abo e, pe o mance equi emen s a e mo ing om me ely
e alua ing ene gy p oduc ion and cos o a mo e comp ehensi e assessmen . The selec ion
a he in e media e s ages o sys em design con ibu es o educing isks. The i e a ion a
low TRLs un il he desi ed pe o mance is achie ed will con ibu e o he analysis o he
solu ion space and he p oduc ion o mo e cos -e ec i e designs.
Equally, he e alua ion is e ol ing om analysing he basic wa e ene gy subsys ems
in ol ed in he powe con e sion o comple e wa e ene gy a ms including mul iple
de ices, and he balance o plan o ins alla ion and main enance ac i i ies.
Discou agingly, mos no el wa e ene gy concep s a e s ill ocusing hei e o s on
op imising powe cap u e, lea ing ou o he ini ial design conside a ions o he essen ial
pe o mance equi emen s and subsys ems ha la e become expensi e “add-ons” [60].
Expe ience in e y di e se enginee ing sec o s has shown ha he ea ly s ages o
echnology de elopmen a e c ucial o mee cos and pe o mance expec a ions [157] since
enginee ing p oblems a e buil a he concep s age.
2.4.2 Assessmen C i e ia Hie a chy
Wa e ene gy echnologies equi e assessmen c i e ia ha can be applied a di e en
sys em le els o agg ega ion. Hence, a subsys em mus be se in he con ex o a de ice and,
in u n, placed in he con ex o a wa e a m o assess ha subsys em’s impac on global
pe o mance [142]. Figu e 2.16 illus a es se e al ames o e e ence o wa e ene gy
echnologies, including he ex e nal en i onmen o conside he ins alla ion o he wa e
a m in a speci ic deploymen si e and he comme cial aspec s o he wa e ene gy p ojec .
Figu e 2.16: Va ious sys em bounda ies o a wa e ene gy assessmen .
Full aceabili y o assessmen c i e ia is needed o ensu e consis ency in he same way
equi emen s a e aced h oughou bo h he sys em hie a chy and design domains. To do
so, he key design pa ame e s o he echnical solu ion should be selec ed o calcula e he
TPMs; he TPMs in u n conside ed o compu e he MOPs; he MOPs aken o de e mine
he MOEs; las ly, he MOEs can be agg ega ed in o a inal igu e o me i ha dis ils he
STATE OF THE ART
39
wa e ene gy echnology sui abili y. This undamen al hie a chy o assessmen c i e ia
ensu es a holis ic e alua ion ha cap u es he me ics’ di e en le els o de ail and
g anula i y. Func ional ela ionships can be es ablished by analysing he di e en design
domains. FAST diag ams [158] can be used o de elop he hie a chy o equi emen s and
co esponding me ics.
Technology pe o mance should be e alua ed using di e en me ics depending on he
sys em bounda ies (see Figu e 2.16). I is wo h no ing ha he h ee i s le els o he
assessmen hie a chy can be u he expanded by epea ing his mapping p ocess o each
subsys em, assembly o componen . The only hing o conside is ha sys em’s TRs will
become he subsys em’s FRs, hus c ea ing he need o an addi ional laye [81]. This way
he aceabili y o bo h me ics and equi emen s is sa is ac o ily main ained.
Figu e 2.17 p esen s he e alua ion a eas conside ed in IEA-OES Task 12 [142]. I shows
how high-le el me ics can be combined wi h lowe -le el echnology-agnos ic ones un il
eaching a single a o dabili y me ic.
Figu e 2.17: Example o a hie a chy o wa e ene gy me ics (adap ed om [142]).
Fo consis ency, all assessmen c i e ia should be selec ed so hey a e a he same le el o
de ail and co e he ull ex en o echnology equi emen s. Me ics should no be s ongly
co ela ed o each o he o p o ide insigh in o di e en cha ac e is ics o he echnical
solu ion o al e na i es being assessed and o a oid o e lap o double accoun ing o
c i e ia. T ade-o s can be cap u ed and e alua ed when me ic sco es o an embodimen
a e ela ed o c i ical design pa ame e s. Value unc ions shall be used o cha ac e ise he
undamen al ela ionships be ween assessmen c i e ia.
2.4.3 Agg ega ion S uc u e
Ano he impo an aspec o conside in analysing he unc ional ela ionships is he
agg ega ion logic o he assessmen c i e ia.
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47
CHAPTER 3 UNDERSTANDING THE
WAVE ENERGY CONTEXT
3.1 O e iew
This chap e p o ides an awa eness o he b oade con ex and i s po en ial impac on
sys em equi emen s and dependencies o ensu e ha wa e ene gy echnologies can ul il
s akeholde s’ expec a ions.
Sec ion 3.2 in oduces he speci ic me hods and ools used in his s ep o he me hodology.
Ini ially, AHP is used in he en i onmen al domain o p io i ise Sys em D i e s (SD). The
QFD ool wi h Chen no malisa ion is hen used o link SD o S akeholde s (SH) and
p o ide impo ance a ings o wa e ene gy equi emen s in he di e en domains.
Sec ion 3.3 de elops he wa e ene gy con ex , which comp ises mul iple ex e nal o ces
ha ha e no di ec in e ac ion wi h he wa e ene gy sys em, bu may in luence decisions
ela ed o i s concep ion, de elopmen and ope a ion. The iden i ica ion o he ma ke
applica ion, key d i e s and s akeholde s’ conce ns o e s a solid ounda ion o
objec i ely e alua ing wa e ene gy op ions e sus sys em equi emen s.
Sec ion 3.4 desc ibes he p ac ical implemen a ion o his s ep. An anonymous su ey was
designed o p io i ise he ex e nal o ces. Resul s ob ained om he consul a ion o wa e
ene gy ep esen a i es a e p esen ed o he applica ion ma ke s, key d i e s and
s akeholde g oups lis ed in sec ion 3.3.
Finally, sec ion 3.5 summa ises he chap e and discusses some pa ial indings om his
no el me hodology ha migh be o in e es o he wa e ene gy sec o .
“Fo me con ex is he key; om ha comes he
unde s anding o e e y hing”
Kenne h Noland (1924 – 2010)
UNDERSTANDING THE WAVE ENERGY CONTEXT
48
3.2 Me hods and Tools
3.2.1 Analy ic Hie a chy P ocess (AHP)
Complex enginee ing p oblems o en equi e a se o in e dependen and compe ing
c i e ia. The Analy ic Hie a chy P ocess (AHP) is a aluable ool ha p o ides a sys ema ic
app oach o suppo mul i-c i e ia decision-making. De eloped by Saa y in 1980 [102],
AHP cap u es subjec i e and objec i e aspec s o an enginee ing p oblem by b eaking
down decisions in o a se ies o pai wise compa isons and combining hem in o a single
scale. Fu he mo e, AHP includes an e ec i e echnique o check he e alua ion’s
consis ency, hence educing he bias in he inal decision. Since i s eme gence, i has
become one o he mo e widely used mul i-c i e ia analysis me hods.
AHP is o malised in ou main s eps. The wo las s eps a e op ional bu highly
ecommended o con i m he obus ness o he esul s.
S ep 1: Decompose he decision p oblem in o a hie a chy o sub-p oblems. I s a s by
decomposing he decision p oblem in o a hie a chy o sub-p oblems. The o e all goal,
c i e ia and a ibu es a e a anged in o di e en hie a chical le els as illus a ed in Figu e
3.1. The decision p oblem goal si s a he op o he hie a chy. The second le el consis s o
se e al p ima y c i e ia o equal impo ance. I app op ia e, a hi d le el can be added.
Figu e 3.1: An example o a h ee-le el decision hie a chy.
S ep 2: Pe o m pai wise compa isons and es ablish p io i ies. Decision c i e ia a e
placed in an mxm squa ed ma ix, and wo c i e ia a e compa ed each ime o de e mine
which one is mo e impo an . Whene e he c i e ia in ows a e mo e impo an han he
ones in columns, he 9-poin g ada ion scale [102] shown in Table 3.1 is used o quan i y
he compa ison, a
ij
. O he wise, he ecip ocal alue is assigned, a
ji
= 1/a
ij
.
UNDERSTANDING THE WAVE ENERGY CONTEXT
49
Table 3.1: G ada ion scale o pai wise compa isons [102].
Impo ance De ini ion Explana ion
1 Equal Fac o s con ibu e equally o he objec i e
3 Mode a e One ac o is sligh ly a ou ed o e ano he
5 S ong One ac o is s ongly a ou ed o e ano he
7 Ve y s ong E idence exis s o a ac o dominance
9 Ex emely s ong Highes possible alidi y o a ac o
2, 4, 6, 8 In e media e alues Fo a comp omise be ween he abo e alues
S ep 3: Syn hesise judgemen s o ob ain a se o weigh s. Based on each c i e ia’s p io i y,
he o e all anking is de eloped by no malising he judgemen ma ix. The ela i e
impo ance, w
i
, is calcula ed as ollows:
=
∑
,
=
1
,
2
,
…
,
;
=
1
,
2
,
…
,
(1)
=
∑
,
=
1
,
2
,
…
,
(2)
S ep 4: E alua e and check he consis ency o judgemen s. Finally, he deg ee o
consis ency among he pai wise compa isons is measu ed by compu ing he Consis ency
Index and Consis ency Ra io [102]. The Consis ency Index (CI) is calcula ed as
=
−
−
1
(3)
whe e
λ
max
is he maximum eigen alue o he judgemen ma ix. CI is hen compa ed
wi h ha o a Random Index (RI). The a io de i ed, CI/RI, is e med he Consis ency
Ra io (CR). A CR below 0.1 is deemed sa is ac o y.
Table 3.2: Random Index, RI [102].
Fac o s 1 2 3 4 5 6 7 8 9 10
RI
0
0
0.58
0.90
1.12
1.24
1.32
1.41
1.45
1.49
Un il now, AHP has only been applied in wa e ene gy o ank echnology op ions
conce ning echno-economic c i e ia (e.g., ene gy cap u e, cos , eliabili y, en i onmen al
iendliness, adap abili y) in a single s ep [61]. To limi he subjec i i y o and dependence
on expe judgemen s, AHP will be used in he en i onmen al domain o p io i ise Sys em
D i e s (SDs) a he ou se o his no el me hodology.
UNDERSTANDING THE WAVE ENERGY CONTEXT
50
3.2.2 Quali y Func ion Deploymen (QFD)
QFD [76] is ano he well-known design ool de eloped in Japan by he end o he 1960s,
being i s documen ed a he Kobe shipya ds o Mi subishi Hea y Indus ies in 1972. I is
used o ansla e he Voice o he Cus ome (VoC) in o sys em equi emen s employing a
se ies o ma ices called he House o Quali y (HoQ). Sys em equi emen s ini ially
consis ed o jus cus ome needs and echnical equi emen s, bu hey can equally be
unc ions, design pa ame e s o c i ical p ocess a iables. Fu he mo e, QFD ma ices can
be linked in a wa e all manne o ensu e he comple e aceabili y o he equi emen s.
Figu e 3.2: The House o Quali y.
QFD is o malised in 6 main s eps:
S ep 1: De e mine inpu equi emen s and ela i e impo ance a ings (Wha ). In he
p oposed me hodology, AHP is adop ed o p io i ise ini ial ac o s, ha is, Sys em D i e s
(SDs).
S ep 2: Benchma k inpu equi emen s (Now s Wha ). This s ep aims o de e mine how
he equi emen s a e cu en ly sa is ied. E en hough he wa e ene gy sys em is a new
design, he e will always be a compe i i e p oduc ha is in ended o mee he same need.
This s ep c ea es an awa eness o wha al eady exis s and acili a es assigning a ge alues
o hese equi emen s. Please e e o CHAPTER 5 o u he de ails on a ge alloca ion.
S ep 3: Gene a e ou pu equi emen s (How). The ou pu equi emen s es a e he
design p oblem in he co esponding domain. The Func ional Analysis and Sys em
Technique (FAST) can be used o iden i y he ou pu equi emen s [158].
UNDERSTANDING THE WAVE ENERGY CONTEXT
51
S ep 4: Fill in he ela ionship ma ix (Wha s How). The ela ionship ma ix is he
cen e pa o he HoQ and is used o ela e he inpu and ou pu equi emen s. This way
he p io i ies o he inpu equi emen s can be ansla ed in o he ela i e impo ance
a ings o ou pu equi emen s (S ep 6). To do so, he ela ionships adi ionally exp essed
in quali a i e symbols (e.g., s ong, medium, and weak) a e con e ed in o
nume ical coe icien s (e.g., 9-3-1).
S ep 5: Comple e he co ela ion ma ix (How s How). The co ela ion ma ix placed
o e he “ oo ” o he HoQ is added o highligh in e ela ionships be ween ou pu
equi emen s. Posi i e ela ionships ep esen suppo ing equi emen s, whils nega i e
linkages help iden i y con lic s and ade-o s. Quali a i e symbols (e.g., +, −) o nume ical
a ings (e.g., 1, −1) a e used o desc ibe hese ela ionships.
S ep 6: De e mine ela i e impo ance a ings (How Much). The absolu e le el o
impo ance o he ou pu equi emen , w
j
, is ob ained by summing he ela i e impo ance
o he inpu equi emen s, d
i
, mul iplied by he quan i ied nume ical coe icien s,
ij
. The
ela i e impo ance a ing,
, is hen compu ed as:
=
∙
,
=
1
,
2
,
…
,
;
=
1
,
2
,
…
,
(4)
=
∑
(5)
whe e n and m a e he numbe o inpu and ou pu equi emen s, espec i ely.
Some au ho s ha e p oposed no malisa ion models o de e mine he ela i e impo ance
a ings, including he co ela ion ma ix. Chen’s app oach [181] aims o o e come o he
models’ limi a ions ha p oduce un easonable esul s. In his me hod, he nume ical
coe icien s,
ij
, a e no malised acco ding o he ollowing equa ion:
=
∑
!
!
"
∑
∑
!
!
"
,
∈
$
1
,
−
1
%
(6)
whe e c
kj
a e he numbe a ings o he co ela ion ma ix.
In wa e ene gy, QFD has been applied o assess he po en ial o wa e ene gy inno a ions
de ined by i s unc ions, wi hou any no malisa ion and in a single s ep [182]. The QFD
ool wi h Chen no malisa ion will link SDs o S akeholde s (SHs) and assign impo ance
a ings o wa e ene gy equi emen s in he di e en domains.
UNDERSTANDING THE WAVE ENERGY CONTEXT
52
3.3 The Wa e Ene gy Con ex
3.3.1 Backg ound
The enginee ing complexi y and he wide a ie y o wa e ene gy concep s equi e a
comp ehensi e de elopmen app oach [60]. Hence, de ining he ull se o equi emen s
o he design p oblem om he s a is pa amoun o de eloping a success ul wa e ene gy
echnology [62]. Fu he mo e, an ea ly unde s anding o he o e a ching con ex and i s
po en ial impac on sys em equi emen s and dependencies will p o ide a solid basis o
de eloping wa e ene gy echnologies ha mee s akeholde s’ expec a ions [183].
A en ion o con ex is no new o Sys ems Enginee ing (SE), bu i s conside a ion has
inc eased hand in hand wi h he sophis ica ion o enginee ing p oblems. The sys em
con ex comp ises mul iple ex e nal o ces ha ha e no di ec in e ac ion wi h he wa e
ene gy sys em bu may in luence decisions ela ed o i s concep ion, de elopmen and
ope a ion [62]. A s uc u al iew o he sys em should conside he mul iple alue
dimensions o he echnology (o sys em d i e s) oge he wi h he a ious s akeholde s
in e es ed in he echnology [184]. D i e s ha a e associa ed wi h a s akeholde g oup a e
o en called conce ns.
As in oduced in sec ion 2.3.6, he mos comp ehensi e analysis o he wa e ene gy
equi emen s has been p oduced wi hin he Wa e-SPARC p ojec [111]. This wo k led o
a comple e and agnos ic o mula ion o a u ili y-scale wa e ene gy a m h ough SE and
s akeholde analysis. Howe e , he de ini ion o sys em con ex is only pa ially add essed.
The au ho s p esen a con ex diag am used o de ine he ex e nal sys ems ha can di ec ly
in luence he success o a g id-connec ed wa e ene gy a m. I is poin ed ou ha his
o e a ching con ex can in luence he design o he echnology, bu hese ac o s a e no
explici ly analysed.
On he o he hand, Sandbe g e al. [112] in es iga ed he a ious ex e nal o ces ac ing in
he sys em con ex o wa e ene gy o o -g id applica ions. They acknowledged ha he
ex e nal ac o s may no a ec he iabili y o g id-connec ed sys ems in he same way bu
did no analyse his impac .
Despi e he exis ence o esea ch o assis in he iden i ica ion o wa e ene gy s akeholde s,
such as [116], [117], [118] and [185], as a as we a e awa e, he e is no public e e ence o
assis in he p io i isa ion o s akeholde s in he wa e ene gy sec o .
The knowledge gained om analysing he o e a ching con ex comp ising he ma ke
applica ion, key d i e s and s akeholde s’ conce ns p o ides a solid basis o objec i ely
e alua ing wa e ene gy echnologies agains he sys ems equi emen s.
UNDERSTANDING THE WAVE ENERGY CONTEXT
53
3.3.2 Wa e Ene gy Ma ke s
The in ended ma ke applica ion d i es he de elopmen o inno a ions since new
echnologies a e c ea ed o add ess exis ing o unexploi ed ma ke oppo uni ies and
p oblems [186]. Knowledge abou u u e ma ke s is i al a all s ages o he inno a ion
p ocess [187]. The e o e, de ining he a ge ma ke (s) is he i s logical s ep o
cha ac e ising he o e a ching con ex .
Wa e ene gy de ices a e used o ans o m he mo ion o he ocean and wa es in o any
usable o m o ene gy. Howe e , he p ima y p oduc o wa e ene gy is likely o be
elec ici y gene a ion due o he impo an con ibu ion o his ene gy ca ie o he
deca bonisa ion o he global ene gy sys em [115]. Al hough some echnology de elope s
a e in e es ed in o he p oduc s such as eshwa e ( h ough desalina ion) o hyd ogen
( h ough elec olysis), hey mos ly concei e wa e ene gy echnologies o elec ici y
p oduc ion.
Owing o i s size, la ge-scale g id-connec ed elec ici y gene a ion is he mos a ac i e
ma ke o wa e ene gy echnologies [188]. Wa e ene gy p esen s a g ea oppo uni y o
mee in e na ional deca bonisa ion a ge s. Howe e , in eg a ing wa e ene gy
echnologies in o he u ili y-scale ma ke is challenging since hese eme ging echnologies
mus s uggle o compe e in cos wi h mo e ma u e enewable ene gies such as wind o
sola .
Al e na i ely, non-u ili y ma ke s may p esen an appealing op ion o wa e ene gy
echnologies o be exploi ed a a smalle scale in a less compe i i e se ing. In pa icula ,
islands and o he o -g id ma ke s could p o ide a s epping s one suppo ing he
deploymen o wa e ene gy echnologies while p o iding en i onmen ally iendly ene gy
o coas al communi ies. These e i o ies expe ience a much dis inc eali y han hei
con inen al ellows and may equi e bespoke solu ions [189]. Consume s mainly depend
on exchanges wi h mainland o ossil uel-based gene a ion; hey pay high elec ici y p ices
compa ed o mains eam ma ke s and a e mo e ulne able o luc ua ions in he a i .
O he niche applica ions o wa e ene gy sys ems ha e been p oposed, gi en hei co-
loca ion na u e, po en ial syne gies and cos sa ings [188]. Among hem, i is wo h
men ioning he ene gy supply o o sho e oil & gas pla o ms, ma ine aquacul u e and
ocean obse a ion and na iga ion [190]. Howe e , his chap e will no in es iga e hese
ma ke s because o hei lesse size, g ea a ie y o equi emen s and lack o consis en
in o ma ion o cha ac e ise hem.
Table 3.3 summa ises he main ea u es o he wo powe ma ke s analysed in his chap e :
u ili y-scale gene a ion and powe ing emo e communi ies.
UNDERSTANDING THE WAVE ENERGY CONTEXT
54
Table 3.3: Applica ion ma ke cha ac e isa ion.
Id Ma ke Cha ac e is ics
M1 U ili y-scale
gene a ion
• A ac i e bu also e y compe i i e
• WEC design is mainly d i en by his ma ke
• Inc easing demand o enewable elec ici y
• Legal obliga ions o mee deca bonisa ion a ge s
M2
Powe ing
emo e
communi ies
• A na owe span o compe i ion (some imes jus one op ion - diesel)
• Low ene gy secu i y and quali y
• Consume s ulne able o p ice luc ua ion and high ene gy cos s
• Simpli ied ma ke and egula o y condi ions
3.3.3 Sys em D i e s (SDs)
Wa e ene gy d i e s a e an essen ial pa o he con ex whe e he wa e ene gy sys em
ope a es. D i e s a e exogenous o ces ou side he sys em bounda ies ha can cons ain,
enable o al e he design solu ion [80]. The con ex includes he poli ical, economic,
social, echnological, legal and en i onmen al ac o s. The exis ence o a ou able
condi ions in he in ended ma ke will undoub edly s imula e he de elopmen o wa e
ene gy echnologies.
PESTLE analysis is a s anda d ool used by companies o ack he con ex hey a e
ope a ing o a e planning o launch a new p ojec , p oduc o se ice [191]. This ool can
be combined wi h SWOT
1
analysis o p o ide an excellen amewo k o in es iga e wa e
ene gy d i e s om many di e en angles and dimensions [192]. PESTLE is an ac onym
which encompasses six dimensions (see Figu e 3.3) and in i s expanded o m s ands o :
• P o Poli ical. Poli ical d i e s de e mine he ex en o which a go e nmen may
in luence a speci ic indus y.
• E o Economic. Economic d i e s comp ise ac o s ha di ec ly impac
economic iabili y.
• S o Social. Social d i e s sc u inise social ends and a i udes.
• T o Technological. Technological d i e s pe ain o key knowledge and
echnologies ha a ec he indus y.
• L o Legal. Legal d i e s include egula ions ha a ec he business
en i onmen .
• E o En i onmen al. En i onmen al d i e s allude o ac o s de e mined by he
su ounding na u al en i onmen in which he wa e ene gy sys em is placed.
1
S eng hs, Weaknesses, Oppo uni ies and Th ea s
UNDERSTANDING THE WAVE ENERGY CONTEXT
55
Figu e 3.3: The six dimensions o PESTLE analysis.
A ibu es ha cha ac e ise wa e ene gy d i e s a e ai ly co e ed in li e a u e such as [51],
[112], [113], and [193]. Table 3.4 p o ides a summa y o wa e ene gy d i e s pe he main
ca ego y.
Table 3.4: Wa e ene gy d i e s.
Id D i e A ibu es
SD1 Poli ical
• Fa ou able policies (e.g. ene gy secu i y, sus ainabili y, job c ea ion)
• Ma ke suppo mechanisms
• Poli ical s abili y and low bu eauc acy
SD2 Economic • Access o inance, c edi & insu ance
• Ene gy p ice and/o ola ili y
SD3 Social • G owing ene gy demand
• Social accep ance
SD4 Technological
• Technology ma u i y and ce i ica ion
• In as uc u e eadiness
• Supply chain a ailabili y
SD5 Legal • Simpli ied p ocedu es (e.g. consen ing, en i onmen al assessmen )
• S anda ds and egula ion
SD6 En i onmen al • S ic e p o ec ion (e.g. pollu ion, na u al disas e s, clima e change)
• Sui able si e and esou ce condi ions
A su ey o wa e ene gy ep esen a i es was conduc ed o p io i ise wa e ene gy d i e s
and o es ablish he impo ance anking o wa e ene gy d i e s o each applica ion
ma ke . Responden s we e asked o g ade he poli ical, economic, echnological, legal and
en i onmen al ac o s using a Like scale, wi h one being he highes impo ance and six
he lowes . Mo e de ails abou he p ac ical implemen a ion can be ound in sec ion 3.4.
UNDERSTANDING THE WAVE ENERGY CONTEXT
62
3.4.2.2 Powe ing emo e communi ies
Likewise, he dis ibu ion o p io i ies pe ex e nal d i e and he mos equen ly anked
ac o s a e p esen ed in Figu e 3.6. This ime, he ocus is on applying wa e ene gy
echnologies in a emo e communi y gene a ion ma ke .
Figu e 3.6: Key D i e s o Remo e Communi y Gene a ion
I can be obse ed ha he Social d i e s now ha e he op p io i y wi h 26% o esponses,
whe eas he Legal d i e s sco e las . The Economic and Poli ical d i e s a e anked second.
The le el o ag eemen in he esponses is no so ma ked o all d i e s as o he u ili y-
scale gene a ion. This means ha he p io i isa ion o Poli ical (20% o esponses),
Technological (21%) and En i onmen al (25%) d i e s may be sensi i e o he sample size.
The dis ibu ion o esponses is much la e o hese h ee d i e s.
UNDERSTANDING THE WAVE ENERGY CONTEXT
63
P io i isa ion o Poli ical d i e s has a highe deg ee o unce ain y as i can ge a highe
ank (1) o a much lowe ank (5) wi h mino changes in he esponses.
3.4.3 D i e s In e ela ionship wi h S akeholde G oups
3.4.3.1 Poli ical ac o s
The impo ance dis ibu ion o Poli ical conce ns pe wa e ene gy s akeholde g oup and
he mos equen ly anked s akeholde s a e p esen ed in Figu e 3.7.
Figu e 3.7: Poli ical conce ns o he wa e ene gy s akeholde s
While he Go e nmen clea ly shows up in he i s posi ion wi h 70% o esponses, he
EPCI con ac o and O&M p o ide a e he leas impo an s akeholde s in e ms o
poli ical conce ns. These las wo d i e s ha e also ecei ed ewe esponses (15% and 18%,
espec i ely). They could s ep up one posi ion accoun ing o he sample’s ma gin o e o ,
which is insu icien o al e he o e all p io i isa ion. Lende s display he mos signi ican
UNDERSTANDING THE WAVE ENERGY CONTEXT
64
deg ee o unce ain y. They can ei he be anked 4, 5 o 6 wi h mino changes in he
esponses.
3.4.3.2 Economic ac o s
The impo ance dis ibu ion o Economic conce ns pe wa e ene gy s akeholde g oup
and he mos equen ly anked s akeholde s a e p esen ed in Figu e 3.8.
Figu e 3.8: Economic Conce ns o he Wa e Ene gy S akeholde s.
The Owne s ands ou in he i s posi ion wi h 51% o esponses. The e is a high le el o
ag eemen in p io i ising s akeholde s acco ding o Economic ac o s. Gi en he ma gin
o e o in he sample, he only unce ain y is o he Regula o s who could s ep up o he
same posi ion as he Consume s and he P essu e g oups. Howe e , as Regula o s sco e in
he las posi ion wi h ewe esponses (15%), his does no change he o e all anking.
UNDERSTANDING THE WAVE ENERGY CONTEXT
65
3.4.3.3 Social ac o s
The impo ance dis ibu ion o Social conce ns pe wa e ene gy s akeholde g oup and
he mos equen ly anked s akeholde s a e p esen ed in Figu e 3.9.
Figu e 3.9: Social Conce ns o he Wa e Ene gy S akeholde s.
In his case, Consume s a e anked i s acco ding o Social ac o s wi h 33% o esponses.
The e is a i m ag eemen conce ning he impo ance o P essu e g oups (46%), he
Owne (33%) and Regula o s (28%). Howe e , he Go e nmen can swap om he hi d
o he i s posi ion conside ing he ma gin o e o in he sample. Finally, he EPCI
con ac o , Lende s and he O&M p o ide ge ewe esponses (16-20%). Thei anking,
howe e , is una ec ed by his le el o unce ain y.
UNDERSTANDING THE WAVE ENERGY CONTEXT
66
3.4.3.4 Technological ac o s
The impo ance dis ibu ion o Technological conce ns pe wa e ene gy s akeholde
g oup and he mos equen ly anked s akeholde s a e p esen ed in Figu e 3.10.
Figu e 3.10: Technological Conce ns o he Wa e Ene gy S akeholde s.
As pe he Economic d i e s, he Owne jumps again in o he i s posi ion, bu in his case
wi h he highes numbe o esponses (74%). The e is a high le el o ag eemen in
p io i ising s akeholde s acco ding o Technological ac o s. Gi en he ma gin o e o in
he sample, he only unce ain y is ha he Go e nmen could s ep up o he same posi ion
as Regula o s. Howe e , his does no change he o e all anking as he Go e nmen has
ewe esponses (15%). Finally, P essu e g oups and Consume s close his anking.
UNDERSTANDING THE WAVE ENERGY CONTEXT
67
3.4.3.5 Legal ac o s
The impo ance dis ibu ion o Legal conce ns pe wa e ene gy s akeholde g oup and he
mos equen ly anked s akeholde s a e p esen ed in Figu e 3.11.
Figu e 3.11: Legal Conce ns o he Wa e Ene gy S akeholde s.
Regula o s p esen he highes p io i y wi h 49% o esponses and Consume s wi h he
lowes wi h 30% o esponses. The e is a signi ican le el o ag eemen in he anking o
s akeholde s despi e he ma gin o e o in he sample. The only unce ain y emains wi h
he posi ion o he Owne , which can be swapped om ou o one.
UNDERSTANDING THE WAVE ENERGY CONTEXT
68
3.4.3.6 En i onmen al ac o s
Finally, he impo ance dis ibu ion o En i onmen al conce ns pe wa e ene gy
s akeholde g oup and he mos equen ly anked s akeholde s a e p esen ed in Figu e
3.12.
Figu e 3.12: En i onmen al Conce ns o he Wa e Ene gy S akeholde s.
P essu e g oups and Regula o s sha e he i s posi ion wi h 38% and 34% o esponses,
espec i ely. Lende s a e anked las . The o e all anking is no sensi i e o he ma gin o
e o excep o he Go e nmen , which can ake ei he he hi d o ou h posi ion.
Howe e , he Go e nmen accoun s o ewe esponses (26%) han he Consume s (28%),
which make he ob ained p io i isa ion s ill eliable.
UNDERSTANDING THE WAVE ENERGY CONTEXT
69
3.4.4 P io i isa ion o SDs
Acco ding o he su ey esul s, he anking o wa e ene gy d i e s conside ably di e s
be ween he wo applica ion ma ke s. Economic ac o s a e he p ima y mo i a ions o
de eloping u ili y-scale gene a ion p ojec s, whe eas Social ac o s d i e he emo e
communi y gene a ion ma ke . This esul is in line wi h he ma ke cha ac e isa ion
p esen ed in sec ion 3.3.2 and he quali a i e eedback collec ed om he consul a ion o
wa e ene gy ep esen a i es. In o he wo ds, u ili y-scale gene a ion is a e y compe i i e
ma ke , whils he social demand o clean ene gy and public accep ance d i e powe ing
emo e communi ies.
The applica ion o AHP p o ides mo e g anula i y o compa e his ou come. The weigh s
esul ing om pai wise compa isons a e eliable since he Consis ency Ra io yields a
sa is ac o y alue below 0.1 in bo h cases. As shown in Figu e 3.13, he Economic, Poli ical
and Technological ac o s a e signi ican d i e s in he u ili y-scale gene a ion, accoun ing
o almos 85% o he o al a ings. Howe e , in powe ing emo e communi ies, mo e
d i e s come in o play. Economic, Poli ical and Technological ac o s a e s ill impo an ,
bu Social ac o s domina e. Al oge he , hey accoun o 92% o he o al a ings.
Figu e 3.13: Rela i e impo ance o SD o he applica ion ma ke .
Wa e ene gy u ili y-scale p ojec s a e no a he comme cial s age, as hey equi e
echnological de elopmen o demons a e he necessa y eliabili y and cos -e ec i eness.
This ci cums ance c ea es impo an ba ie s o accessing he equi ed inancial and
insu ance suppo . Hence, public unding is needed o de elop wa e ene gy o he poin
ha he p i a e sec o can pick i up. In his sense, a key poli ical d i e is long- e m
e enue suppo om go e nmen s. Addi ionally, in es men decisions may hinge on
a ailable poli ical a ge s conce ning clima e change, ene gy ansi ion and secu i y o
UNDERSTANDING THE WAVE ENERGY CONTEXT
70
supply. Consequen ly, u ili y-scale de elopmen o wa e ene gy echnologies will la gely
depend on a ac i e economic suppo and a a ou able poli ical amewo k.
In con as , he ma u i y o exis ing wa e ene gy echnologies may be su icien o p o ide
ene gy a a smalle scale in a emo e communi y p ojec . Remo e communi ies al eady
bea a high ene gy cos , opening he way o make wa e ene gy echnologies compe i i e
wi h o he ene gy sou ces. In his sense, he g owing ene gy demand and social accep ance
o he local communi ies a e c ucial d i e s. Mo eo e , local popula ions a e much mo e
engaged and ha e a close app ecia ion o nea by en i onmen al and economic bene i s.
The economic and poli ical ac o s sco e second in a emo e communi y ma ke
applica ion, and he social conce ns highly de e mine hem.
Technological ac o s a e second o he u ili y-scale p ojec s and hi d o he emo e
communi y gene a ion. This e lec s ha echnology ma u i y is somehow assumed o be
in place be o e any signi ican echnology oll-ou can be concei ed. Besides, g id
in as uc u e may be c i ical bu needs s onge pushes in he economic, poli ical and
social d i e s since i is ou o he hands o he echnology de elope s.
Su p isingly, he legal and en i onmen al ac o s a e conside ed o ha e mino impo ance
o bo h ma ke s, and he social ac o s sco e las in he u ili y-scale ma ke when i is he
majo mo i a ion o a emo e communi y ma ke .
Legal and en i onmen al aspec s a e gene ally pe cei ed as ba ie s ins ead o d i e s.
Many p ocedu es a e pa ially in place and da a ga he ed on he po en ial en i onmen al
impac s a e limi ed o poo ly alida ed because o he sho deploymen imes o cu en
echnologies. I will be impo an o add ess hese unce ain ies in he u u e. Howe e , i
is conside ed ha i wa e echnology is p o en o wo k, hen he legal and pe mi ing side
will e en ually ollow. Fac o s ela ing o compe ing uses o esou ce a eas migh also
impac decision-making. S ic e en i onmen al p o ec ion will speed up he ansi ion o
enewables o ene gy companies. The legal ac o is usually equalised once he poli ical
ac o is in place and se s he legal en i onmen .
The p e ious esul s poin ou ha each applica ion ma ke is a cen al issue bu also ha
d i e s a e somehow in e linked. Finance is connec ed o a sui able poli ical amewo k.
Limi ed suppo will delay echnology ma u i y, bu i he echnology is p o en, he legal
side will ollow. The poli ical ac o s will con ibu e o se ing he legal amewo k.
En i onmen al conce ns may be he mo i a o o poli ical and social ac o s. Finally, job
c ea ion is a poli ical aspec bu can also imp o e social accep ance.
3.4.5 P io i isa ion o SHs
In he s akeholde domain, he wa e ene gy p oblem is exp essed in e ms o s akeholde s’
expec a ions. The di e en impo ance anking o hese s akeholde s o each key d i e
and ma ke applica ion will hence de e mine he sys em equi emen s o de eloping wa e
ene gy echnologies ha a e ailo ed o each speci ic use.
UNDERSTANDING THE WAVE ENERGY CONTEXT
71
Acco ding o he su ey esul s, wo b oad clus e s o s akeholde s a ise. On he one hand,
he Owne , Lende s, EPCI con ac o and O&M p o ide a e he mos impo an ac o s
o he Economic and Technological ac o s. On he o he hand, he Go e nmen ,
Regula o s, P essu e g oups and Consume s a e mainly connec ed o Poli ical, Social,
En i onmen al and Legal ac o s. This esul is in line wi h he ew e e ences in he
li e a u e [111], [112] and he quali a i e eedback collec ed om he consul a ion o wa e
ene gy ep esen a i es.
Poli ical ac o s a e o p ima y conce n o he Go e nmen and Regula o s. I is wo h
no ing ha al hough he Poli ical d i e s a e di ec ly s ee ed by he Go e nmen and
Regula o s, he P essu e g oups and he Consume s also ha e a ce ain deg ee o in luence
on he Go e nmen .
Economic and Technological ac o s sha e a simila p o ile o s akeholde s’ conce ns. The
anking s a s wi h he Owne ollowed by he Lende s, EPCI con ac o and O&M
p o ide . Howe e , he Go e nmen is sligh ly mo e conce ned wi h Economic d i e s
han Technological ones. A he cu en s age o de elopmen , Economic and
Technological d i e s a e c ucial o bo h Owne s and Lende s as hei e u n on capi al
is a s ake. EPCI con ac o s and O&M p o ide s will y o educe hei exposu e due o
echnology imma u i y.
Social and En i onmen al d i e s a e mo e connec ed o he public and he e o e a e i al
o he Go e nmen , Regula o s, P essu e g oups and Consume s. These ou s akeholde s
sco e high o he En i onmen al d i e s. Howe e , Consume s and P essu e g oups s and
ou in he case o Social d i e s. Las ly, Legal ac o s a e d i en by hose who can suppo
and de ine he bounda ies o he legal amewo k, namely Regula o s, he Go e nmen
and P essu e G oups.
These esul s show ha he Owne and he Go e nmen a e lead playe s in he wo
s akeholde clus e s. We ha e seen ea lie Economic and Poli ical ac o s domina e u ili y-
scale gene a ion, whils powe ing emo e communi ies is mainly mo i a ed by Social
d i e s. Acco dingly, i can be in e ed ha he de elopmen o wa e ene gy echnologies
will be p ima ily in luenced by he needs o he Owne and he Go e nmen o u ili y-
scale and emo e communi y p ojec s, espec i ely.
This esea ch has some limi a ions, as poin ed ou du ing he discussion o he key d i e s
o wa e ene gy p ojec s. The p io i isa ion o conce ns con ains a ce ain deg ee o
unce ain y due o he sample size and co esponding ma gin o e o . A di e en sample
can educe Lende s’ conce ns abou Poli ical ac o s and En i onmen al ac o s. Simila ly,
Regula o s, he Go e nmen and he Owne can ha e g ea e conce ns abou he
Economic, Social and Legal ac o s, espec i ely.
The quali a i e esponses in he wa e ene gy ep esen a i es’ su ey help o es ablish he
in e ela ionship o SHs wi h SDs. In he p oposed me hod, QFD is adop ed o p io i ise
su ey esul s in o SH weigh s o each applica ion ma ke and SDs. The use o QFD
FORMALISING SYSTEM REQUIREMENTS
78
4. Ve i y he s uc u e o he FAST diag am by s a ing a he lowes -le el unc ions
on he igh and asking he ques ion, “Why is his unc ion included?” The
unc ion o he immedia e le o he unc ion being conside ed should answe
his ques ion.
Responses o each ques ion can be single, mul iple (using AND connec o ) o op ional
(using OR connec o ).
Figu e 4.3: Func ion hie a chy in a FAST diag am
4.2.2 Logical Sco ing o P e e ence (LSP)
The agg ega ion concep is a common ea u e o mul i-c i e ia analysis me hods. E en
hough ools such as AHP o QFD can be used o de i e weigh ings o he a ious
e alua ion c i e ia, combining he lowe -le el e alua ion c i e ia in o an agg ega ed sco e
is no a simple ask. Fo ins ance, he TPL me hodology [133] in oduces h ee di e en
ways o combining he lowes le el sco es (i.e. a i hme ic mean, geome ic mean and
mul iplica ion wi h no malisa ion) and ou deg ees o lexibili y anging om high
lexibili y o none.
The Logical Sco ing o P e e ence (LSP) me hod p oposed by Dujmo ic [159] is used he e
o cap u e he unde lying unc ional ela ionships and add mo e g anula i y o he
agg ega ion s ep by allowing he de ini ion o he deg ee o simul anei y o he
equi emen s o be combined om he o al disjunc ion o ull conjunc ion [209].
Conjunc ion in LSP means ha he ou pu u ili y is p edominan ly a ec ed by he alue
o he smalles inpu , calling o simul aneous high inpu alues. The geome ic and
ha monic means, espec i ely, a e examples o con en ional ope a o s ha p o ide
inc easing le els o simul anei y. Con e sely, disjunc ion means ha he ou pu u ili y
allows he eplaceabili y o low- alue inpu s. The squa e mean is an example o pa ial
eplaceabili y. Neu ali y, which is he pe ec balance be ween conjunc ion and
disjunc ion, is deno ed in LSP by he weigh ed a i hme ic mean. When combining
FORMALISING SYSTEM REQUIREMENTS
79
manda o y and op ional inpu s o su icien and op ional inpu s, conjunc i e o
disjunc i e pa ial abso p ion is used, espec i ely. The in ensi y o he simul anei y o
eplaceabili y can be con inuously adjus ed by selec ing di e en ope a o s as shown in
Figu e 4.4. Weigh ings in LSP a e adjus ed using QFD [76].
Figu e 4.4: Deg ees o simul anei y/ eplaceabili y o logic ope a o s (adap ed om [159]).
Following his app oach, he e alua ion c i e ia can be agg ega ed sequen ially in o highe
hie a chical le els accoun ing o he deg ee o simul anei y o he di e en a ibu es un il
he inal o e a ching me i is ob ained. The o e all sui abili y can be in e p e ed as he
quali a i e deg ee o sa is ac ion wi h all speci ied equi emen s. This sui abili y, s
0
, is
compu ed om he nex le el o e alua ion c i e ia, s
i
, as ollows:
&
'
=
(
∙
&
)
*
)
;
=
1
,
=
1
,
2
,
…
,
(7)
whe e m is he numbe o e alua ion c i e ia, w
n
a e hei weigh ings, and d is a coe icien
ha depends on he deg ee o simul anei y. Values o d ange om −∞ o pu e
conjunc ion o +∞ o pu e disjunc ion. Special cases o weigh ed powe mean o m=2
a e shown in Table 4.1.
FORMALISING SYSTEM REQUIREMENTS
80
Table 4.1: Special cases o weigh ed powe mean m=2 [210]
Agg ega o s
0
d
Maximum
+
(
&
,
&
-
)
+∞
Squa e mean
/
&
-
+
-
&
-
-
2
A i hme ic mean
&
+
-
&
-
1
Geome ic mean
(
&
)
1
2
∙
(
&
-
)
1
3
0
Ha monic mean
1
/
&
+
-
/
&
-
−1
Minimum
(
&
,
&
-
)
−∞
Addi ional alues o d a e p o ided in Table 4.2 o o he al e na i es o pa ial
conjunc ion and disjunc ion. The ‘Andness’ column ep esen s he deg ee o conjunc ion.
Table 4.2: Gene alised conjunc ion-disjunc ion. Values o d [159]
Agg ega o Symbol
Andness
m=2 m=3 m=4
m=5
Ex eme disjunc ion D 0.0000
+∞+∞+∞
+∞
Ve y s ong disjunc ion D++ 0.0625
20.630 24.300 27.110
30.090
S ong disjunc ion D+ 0.1250
9.521 11.095 12.270
13.235
Medium s ong disjunc ion D+- 0.1875
5.802 6.675 7.316
7.819
Medium disjunc ion DA 0.2500
3.929 4.450 4.825
5.111
Medium weak disjunc ion D-+ 0.3125
2.792 3.101 3.318
3.479
Weak disjunc ion D- 0.3750
2.018 2.187 2.302
2.384
Squa e mean S 0.3768
2.000 - -
-
Ve y weak disjunc ion D-- 0.4375
1.449 1.519 1.565
1.596
A i hme ic mean A 0.5000
1.000 1.000 1.000
1.000
Ve y weak conjunc ion C-- 0.5625
0.619 0.573 0.546
0.526
Weak conjunc ion C- 0.6250
0.261 0.192 0.153
0.129
Geome ic mean G 0.6667
0.000 - -
-
Medium weak conjunc ion C-+ 0.6875
−0.148 −0.208 −0.235
−0.251
Medium conjunc ion CA 0.7500
−0.720 −0.732 −0.721
−0.707
Ha monic mean H 0.7726
−1.000
- -
-
Medium s ong conjunc ion
C+- 0.8125
−1.655 −1.550 −1.455
−1.380
S ong conjunc ion C+ 0.8750
−3.510 −3.114 −2.823
−2.606
Ve y s ong conjunc ion C++ 0.9375
−9.060 −7.639 −6.689
−6.013
Ex eme conjunc ion C 1.0000
−∞−∞−∞
−∞
FORMALISING SYSTEM REQUIREMENTS
81
4.3 Wa e Ene gy Sys em Requi emen s
4.3.1 Backg ound
The p e ious chap e analysed he ex e nal o ces in luencing wa e ene gy echnology
de elopmen due o he key ole hey play in es ablishing u he equi emen s. The
hie a chical o mula ion o wa e ene gy equi emen s is buil upon hese esul s.
QFD is used o p oduce aceable mappings be ween he en i onmen al, s akeholde ,
unc ional and echnical domains as ep esen ed in Figu e 4.5. The S akeholde
Requi emen s (SRs) a e ansla ed in o se e al p io i ised Func ional Requi emen s (FRs)
and Design Pa ame e s (DPs) ha he wa e ene gy sys em should mee . This way, he
unc ional analysis p oduces a comple e and unambiguous de ini ion o he design
p oblem space.
Figu e 4.5: App oach o building Wa e Ene gy Sys em Requi emen s.
Once he c i ical sys em p ope ies a e es ablished in he o m o wa e ene gy sys em
equi emen s, e alua ion c i e ia a e assigned o o e a c edible means by which o assess
a ious design op ions. Me ics linked o he SRs a e usually e e ed o as Measu es o
E ec i eness (MOEs). Measu es o Pe o mance (MOPs) a e used o gauge he FRs o a
design solu ion, whils Technical Pe o mance Measu es (TPMs) a e used o demons a e
he success ul deli e y o he TRs. This hie a chy o e alua ion c i e ia ensu es a holis ic
assessmen ha cap u es di e en le els o de ail and g anula i y in he me ics.
To ca y ou his analysis, i is necessa y o delimi he scope o he wa e ene gy sys em.
Mos commonly, echnology de elope s iden i y he sys em o e e ence wi h hei Wa e
Ene gy Con e e (WEC), whe eas supplie s conside i o be one o i s main cons i uen s,
such as he Powe Take-O (PTO) o he moo ing sys em. Howe e , i is mo e app op ia e
and unbiased o designa e he wa e ene gy a m as he baseline sys em o he global
assessmen o echnologies since his is he inal p oduc ha can mee he ma ke need
o sus ainable, a o dable, and secu e ene gy. Mo eo e , his de ini ion is ully consis en
wi h he sys em analysis conduc ed by Baba i e al. o wa e ene gy [118].
FORMALISING SYSTEM REQUIREMENTS
82
4.3.2 S akeholde Requi emen s (SRs)
The mission s a emen o a wa e ene gy sys em is p esen ed in [118] o a u ili y ma ke
applica ion. This o e a ching goal is e o mula ed and gene alised he e o o he elec ici y
gene a ion ma ke s as ollows:
“The wa e ene gy a m con e s ocean wa e ene gy in o consumable powe ”
S a ing wi h his mission s a emen , he oles and expec a ions o he di e en s akeholde
g oups ha e been s uc u ed om a ious li e a u e sou ces such as [116], [117], [118],
and [211]. They a e summa ised in Table 4.3.
Table 4.3: S akeholde oles and expec a ions.
Id S akeholde Roles Expec a ions
SH1 Owne
Ini ia e he p ojec and design he a m
P o ide equi y
Se e u n on in es men a ge s
Manage p ojec isks
Sell elec ici y o consume s
Compe i i e p o i abili y
Low p ojec isks
Access o a o dable c edi
S abili y o policy amewo k
Assess pe o mance le els
Compe i i e cos o elec ici y
P edic able gene a ion
Ma ch consume demand
SH2 Lende s
P o ide deb
Se in e es a e
Assess inancial isk
Low e enue isks
Main ain epu a ion
SH3 EPCI con ac o
Manage a m cons uc ion and ins alla ion
P o ide insu ance du ing cons uc ion
Selec supplie s
Manage end-o -li e ecycling
Selec he bes componen s and sys ems
A oid cos o e uns and delays
Well-unde s ood and manageable isks
SH4 O&M p o ide
P o ide spa e pa s and se ices
Pe o m (un)scheduled main enance
P o ide insu ance du ing he ope a ion
Selec se ice supplie s
Reliabili y o asse s du ing he p ojec 's
li e ime
A oid cos o e uns and delays
Well-unde s ood and manageable isks
Sa e y a sea
SH5 Go e nmen
De elop and implemen sec o al policies
Re iew compliance
P o ide in es men and gene a ion
incen i es
Economic de elopmen
E icien use o public esou ces
Compliance wi h egula ion
Socio-economic bene i s
SH6 Regula o s
Es ablish pe mi ing equi emen s
Re iew p ojec use o ocean space
P o ide concession
Compliance wi h egula ion
Main ain epu a ion
SH7 P essu e g oups Lobby o o agains he p ojec
Imp o e he well-being o he communi y
Accep able en i onmen al impac
No a ec ion o o he ac i i ies
Socio-economic bene i s
SH8 Consume s Se powe quali y equi emen s
Pu chase gene a ed elec ici y
Compe i i e cos o elec ici y
P edic able gene a ion
FORMALISING SYSTEM REQUIREMENTS
83
Posi i e social and economic impac s
Unde lying all s akeholde s’ expec a ions, he e is he need o make wa e ene gy
compe i i e and accep able o he a ge ed ma ke , o exp essed in ano he o m, wa e
ene gy mus add ess he ene gy ilemma, namely ene gy secu i y, sus ainabili y and
a o dabili y [212].
Wi h his in mind, S akeholde Requi emen s (SRs) and Measu es o E ec i eness
(MOEs) ha e been iden i ied h ough an i e a i e p ocess o dis illing s akeholde s’
expec a ions un il a i ing a he condensed lis as shown in Table 4.4.
Table 4.4: S akeholde Requi emen s and Me ics.
Id S akeholde Requi emen (SR) Measu e o E ec i eness (MOE)
SR1 Con e wa e ene gy in o consumable powe Capaci y Fac o (CF) [59]
SR2 Ope a e when needed A ailabili y Fac o (AF) [142]
SR3 Reduce up on cos s Capi al Expendi u e (CAPEX) [59]
SR4 Reduce annual cos s Ope a ional Expendi u e (OPEX) [59]
SR5 P e en business isks Fixed Cha ge Ra e (FCR) [213]
I is wo hwhile no ing ha he way SRs a e elici ed g ea ly acili a es he de ini ion o
MOEs. A close look a he uppe sys em me ics e eals pa allelism wi h he simpli ied
LCOE equa ion [214].
567
=
897:
×
<=
+
697:
8
,
766
×
9
×
<
×
8<
(8)
whe e
• CAPEX, Capi al Expendi u e, ep esen s all capi al cos s associa ed wi h he a m
de elopmen , manu ac u ing, ins alla ion and decommissioning a he end o he
p ojec li e.
• FCR, Fixed Cha ge Ra e, is he annual e u n, i.e. he ac ion o CAPEX which is
needed o mee in es o e enue equi emen s.
• OPEX, Annual Ope a ing Expendi u e, include all ou ine main enance,
ope a ions, and moni o ing ac i i y.
• 8,766 is he a e age o al hou s in a yea .
• P, Ra ed Powe , is he nominal ins alled capaci y o he a m.
• CF, Capaci y Fac o , is he g oss annual powe gene a ed by he wa e ene gy a m
as compa ed o i s a ed ou pu a 100% a ailabili y.
• AF, A ailabili y Fac o , is he pe cen age o he ime ha he wa e ene gy a m is
a ailable o p o ide ene gy o he g id. By con en ion, he ze o p oduc ion
pe iods (i.e he wa e esou ce lies below o abo e ce ain limi s) a e coun ed
agains he CF bu no agains he AF.
FORMALISING SYSTEM REQUIREMENTS
84
As can be seen, he nume a o accoun s o he annui ized li e ime cos s and he
denomina o is he ne ene gy p oduc ion pe yea .
In he p oposed me hod, QFD is used o p io i ise he SRs. To main ain aceabili y, he
impo ance anking o SRs o each applica ion ma ke was ob ained in connec ion o he
SHs. The same impo ance a ing scale p e iously shown in Table 3.6 is used o de i e SH–
SR ela ionships.
Addi ionally, LSP is used o agg ega e he MOEs sequen ially accoun ing o he deg ee o
simul anei y o he di e en a ibu es un il a inal measu e o sui abili y is ob ained, which
can be in e p e ed as he global deg ee o sa is ac ion o he SRs.
Figu e 4.6 p esen s he agg ega ion logic o he MOEs in o his Global Me i (GM). The
weigh s abo e each a ow, w
i
, ep esen he ela i e impo ance a ings o he SRs. The
Geome ic mean (G) and A i hme ic mean (A) ope a o s we e chosen o combine
a ibu es wi h a mul iplica i e and addi i e na u e, espec i ely.
Figu e 4.6: Agg ega ion o MOE.
LCOE is he mos common highes -le el me ic used o assess wa e ene gy op ions [142].
Howe e , he eade should bea in mind ha he GM o a wa e ene gy op ion migh di e
om he p e e ence ob ained using he nume ical LCOE alues since he agg ega ion logic
also accoun s o he ela i e impo ance exp essed by he s akeholde s, he unde lying
deg ee o simul anei y and he lexibili y allowed o he a ious equi emen s, all o hem
quali a i e aspec s.
CAPEX and OPEX a y la gely o p o o ype echnologies. Based on he OceanSET Thi d
Annual Repo [205], a CAPEX o €5m pe MW and an OPEX o €500,000 (i.e. 10% o
CAPEX) can be conside ed as h eshold alues o a ze o u ili y, espec i ely.
The simpli ied LCOE exp ession uses he Fixed Cha ge Ra e (FCR):
<=
=
$
1
−
(
1
+
)
A
B
%
(9)
FORMALISING SYSTEM REQUIREMENTS
85
whe e is he discoun a e and C is he p ojec li e ime in yea s. Fo p e-demons a ion
p ojec s wi h a maximum li e ime o 10 yea s, he discoun a e can be as high as 15% [215]
leading o a maximum FCR o 20% (ze o u ili y). On he o he hand, ma u e echnologies
wi h long li e imes (>25 yea s) can achie e an FCR o jus 5% wi h low discoun a es o
3% (i.e. e y low bo owing and in la ion a es).
The CF will gene ally inc ease wi h he highe wa e ene gy lux. Figu e 4.7 p esen s an
illus a i e plo o he uppe CF bound o a ious wa e ene gy le els, based on es ima es
o Baba i e al. [216] o eigh di e en WECs a i e si es along he A lan ic coas o
Eu ope. This e e ence is use ul o se he maximum CF u ili y a 50%.
Figu e 4.7: Fundamen al ela ionship be ween he CF and he wa e ene gy le el (adap ed
om [217], Supplemen al In o ma ion).
Finally, acco ding o he Wo ld Ene gy Council’s Pe o mance o Gene a ing Plan
Commi ee [218], 80% o he gap in he bes achie able AF is due o subop imal O&M
managemen p ac ices. This is suppo ed by OceanSET epo ing an a e age AF o 78%
o 13 wa e ene gy p ojec s [205]. Mo eo e , G ea es and Iglesias [3] iden i ied an
ope a ional a ailabili y h eshold o 75% o ma ine enewable ene gy de ices.
4.3.3 Func ional Requi emen s (FRs)
Func ional Requi emen s (FRs) a e he b idge be ween he s akeholde s and echnical
eams, and hey should be elici ed in all phases o he sys em li ecycle [81]. Func ional
analysis is used o iden i y wha unc ions he wa e ene gy sys em should pe o m, hei
logical s uc u e and in e ac ions o sa is y SRs e icien ly.
Whils he enginee ing sys em exis s only o i s usage, all li e phases mus be conside ed
since hey add impo an cons ain s o he sys em design. Figu e 4.8 shows he ypical
FORMALISING SYSTEM REQUIREMENTS
86
li ecycle o a wa e ene gy sys em and he independen en i ies o which i is physically o
i ually linked, ha is he Ex e nal Sys ems. S ages ha e been adap ed om [118].
Figu e 4.8: Li ecycle o he wa e ene gy sys em and en i ies.
The cons uc ion phase encompasses all manu ac u ing, anspo and assembly ac i i ies
pe o med onsho e. Simila ly, he end-o -li e phase includes eusing, ecycling o sa ely
disposing o he pa s ha make up he wa e ene gy sys em. The ins alla ion, main enance
and e ie al phases comp ise he o sho e anspo . Addi ionally, main enance in ol es
inspec ion, epai , o eplacemen [219]. Mino epai s can be pe o med on-si e. Fo
majo epai s and eplacemen s, he wa e ene gy sys em migh be b ough o sho e and
may equi e speci ic indus ial p ocesses, as o he cons uc ion and end-o -li e phases.
Finally, he ope a ion is he mos impo an phase in he sys em li ecycle since i is he only
one ha di ec ly adds alue o he end-use s. The ope a ion phase includes he s andby,
no mal, mal unc ion and su i al modes o he wa e ene gy de ices.
Fi s ly, he ex e nal analysis o he wa e ene gy a m is ca ied ou o p o ide a gene al
o e iew o he se ice unc ions o he wa e ene gy sys em. The Oc opus diag am is used
o display he in e ac ions o he wa e ene gy sys em wi h he ex e nal sys ems.
Du ing i s ope a ional phase (Figu e 4.9a), he wa e ene gy sys em in e ac s wi h wo
Ex e nal Sys ems, namely he Wa es and he Poin o connec ion whe e he con e ed
ene gy is consumed. Acco dingly, he p ima y unc ion o a wa e ene gy sys em is s a ed
as ollows:
F
p
: Con e wa e ene gy in o consumable powe
This p ima y unc ion is p ecisely elici ed as he mission s a emen p esen ed ea lie . The
emaining ope a ional unc ions a e seconda y:
F
s1
: Ope a e when needed
F
s2
: Con ol ene gy cap u e
F
s3
: T ans e loads o he seabed
F
s4
: Reduce he se e i y o en i onmen al h ea s
F
s5
: A oid isks o ecep o s
FORMALISING SYSTEM REQUIREMENTS
87
These seconda y unc ions connec he wa e ene gy sys em wi h he Ope a o , Seabed,
Ocean En i onmen and Recep o s, espec i ely.
(a) (b)
Figu e 4.9: Oc opus diag am o he ope a ion phase (a) and es o phases (b).
The es o he phases, which add cons ain s o he sys em design, ha e been me ged in o
a single diag am o con enience (Figu e 4.9b) leading o h ee addi ional seconda y
unc ions.
F
s6
: Manu ac u e by indus ial p ocesses
F
s7
: Ins all by se ice essels
F
s8
: Main ain by se ice essels
These new unc ions connec he wa e ene gy sys em wi h he Indus ial p ocesses (F
s6
)
and Se ice essels (F
s7
and
F
s8
). No e ha F
s4
and F
s5
a e p esen in all li e phases o he
sys em.
Fo he in e nal unc ional analysis, he FAST diag am is used o ansla e he high-le el
unc ions in o lowe -le el unc ions ha mus be pe o med by he wa e ene gy sys em.
Figu e 4.10 p esen s he unc ional decomposi ion o he wa e ene gy sys em in o FRs
( i s le el) and TRs (second le el). The se ice unc ions om he ex e nal analysis and
he SRs a e included o he sake o aceabili y. I can be no ed ha he esul an FAST
diag am o ganises he unc ions in o consis en le els o de ail and enginee ing domains.
Se ice unc ions mainly belong o he unc ional domain (F
s5
, F
s6
, F
s7
, F
s8
), bu also some
o he echnical domain (F
s2
, F
s3
, F
s4
) and e en he s akeholde domain (F
s1
).
FORMALISING SYSTEM REQUIREMENTS
94
en i onmen al loads. A hi d s a egy in ol es using highe sa e y ac o s o inc ease
design ma gins as depic ed in Figu e 4.13.
Figu e 4.13: S a egies o minimise ailu es (adap ed om [228]).
Minimising o al down ime (FR5) demands using nea main enance po (TR11),
inc easing wea he accessibili y (TR12) and a oiding unplanned delay ime (TR13). These
equi emen s a e cha ac e ised by T a el ime (
), Wai ing ime (
w
) and Logis ic ime (
l
)
espec i ely. In u n,
w
depends on he si e accessibili y and he se ice ime equi ed o
pe o m he main enance ope a ion. Again, he h ee TPM a e pa ially eplaceable and
hus he neu al A i hme ic mean (A) is used o combine hem.
Manu ac u ing by indus ial p ocesses (FR6) equi es employing ma u e manu ac u ing
p ocesses (TR14) and manu ac u ing in la ge quan i ies (TR15). These equi emen s a e
cha ac e ised by he Cycle ime (
c
) and he Uni cos (UC
m
). These wo a ibu es a e mo e
eplaceable han he pe ec balance and hus he weak disjunc ion (D-) is used o hei
agg ega ion.
UC
m
depends on he in es men cos s incu ed o he manu ac u ing ooling, he a iable
cos o manu ac u ing each uni and he numbe o uni s. In gene al, eplica i e p ocesses
ha e highe in es men cos s and lowe a iable cos s [229]. The Uni cos is gi en by
Equa ion (11) wi h displays a cha ac e is ic hype bolic o m.
F
=
G
+
H
(11)
whe e C
is he ixed cos , C
is he a iable cos and m is he numbe o uni s.
Ins alling and e ie ing by se ice essels (FR7) demands using low-cos essels (TR16)
and educing he numbe o essel ips (TR17). These equi emen s a e cha ac e ised by
he Ins all essel cha e cos (UC
i
) and he No. o ips pe de ice (n
). The mul iplica i e
na u e eques s a combina ion wi h he Geome ic mean (G).
Likewise, main aining by se ice essels (FR8) equi es using low-cos essels (TR18) and
educing he main enance equency (TR19). These equi emen s a e cha ac e ised by
Se ice essel cha e cos (UC
s
) and he No. o ips pe de ice (n
). The mul iplica i e
na u e also calls o agg ega ion h ough he Geome ic mean (G). Long- e m ag eemen s
FORMALISING SYSTEM REQUIREMENTS
95
o one o se e al yea s can signi ican ly educe essel cha e a es compa ed wi h he
spo ma ke [230]. The no. o ips pe de ice depends on he MTTF.
Su i ing he ha sh en i onmen (FR9) needs ans e ing loads o he seabed (TR20),
educing he se e i y o h ea s (TR21) and de ec ing condi ions abo e he h eshold
(TR22). These equi emen s a e cha ac e ised by he Maximum pe missible ounda ion
load (F
), he Load shedding capabili y (L
s
) and he De ec ion le el (DL). Load shedding
and de ec ion equi e a ce ain deg ee o simul anei y and he Geome ic mean (G)
ope a o is used o combine hem. The esul ing u ili y is agg ega ed h ough he
A i hme ic mean (A) as hey can compensa e o each o he .
Las bu no leas , a oiding isks o ecep o s (FR10) demands educing he en i onmen al
p essu e (TR23). The EIS me ic is di ec ly ma ched o he Fa m densi y (FD) as he
p incipal s esso . Figu e 4.14 summa ises he agg ega ion logic o he di e en TPMs.
Figu e 4.14: Agg ega ion o TPM.
FORMALISING SYSTEM REQUIREMENTS
96
4.3.5 Design Pa ame e s (DPs)
The la ge numbe o TRs esul s in a QFD ma ix di icul o manage. To begin wi h,
anking a mul i ude o equi emen s is simply beyond human cogni i e capabili y.
Besides, he analysis o he in o ma ion con ained in he QFD ma ix becomes much mo e
challenging. Finally, TRs may no be independen , as can be obse ed in he lis o TPMs
which sha e some commonali ies.
To a oid his p oblem, TRs a e mapped o he design pa ame e space. Design Pa ame e s
(DPs) a e used in Axioma ic Design [84] o cha ac e ise he physical a ibu es o a sys em.
Gi en ha one DP can be sha ed by wo o mo e TRs, he echnical domain analysis can
be g ea ly simpli ied. This ans o ma ion is also suppo ed by ac o analysis [231], a
ma hema ical echnique o simpli ying he ela ionship among a la ge numbe o
co ela ed a iables by a lowe numbe o unde lying a iables called ac o s.
DPs should be selec ed so hey a e independen o one ano he . To en o ce ac o
independence, a selec ion om TRIZ echnical pa ame e s [232] was conside ed. The 39
echnical pa ame e s iden i y he mos widely used and impo an ea u es o echnical
sys ems (see Appendix C: Lis o TRIZ 39 Technical Pa ame e s). Al shulle ex ac ed
hese a p io i cha ac e is ics a e s udying o e 400,000 wo ldwide pa en s [233].
DPs should be also de ined a he same le el o abs ac ion as FRs. To a oid, as a as
possible, coupled designs, he same numbe o DPs and FRs should be conside ed. A lis
o 10 DPs om he ele an common pa ame e s om TRIZ has been mapped o he TRs
as shown in Table 4.8.
Table 4.8: Mapping o Technical Requi emen s (TRs) o Design Pa ame e s (DPs).
Id Design Pa ame e s TRIZ no. Technical Requi emen s
DP1 A ea o mo ing objec 5 TR1, TR23
DP2 S eng h 14 TR2, TR10, TR20
DP3 Du a ion o ac ion by mo ing objec 15 TR8
DP4 Loss o ene gy 22 TR5, TR7
DP5 Loss o ime 25 TR11, TR12, TR13
DP6 Quan i y o subs ance 26 TR15, TR16, TR18
DP7 Adap abili y 35 TR3, TR9, TR21
DP8 De ice complexi y 36 TR4, TR6
DP9 Di icul y o de ec ing and measu ing 37 TR22
DP10 P oduc i i y 39 TR14, TR17, TR19
FORMALISING SYSTEM REQUIREMENTS
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4.4 P ac ical Implemen a ion
4.4.1 P io i isa ion o SRs
The p ac ical implemen a ion o he p oposed me hodology yields he ela i e impo ance
o SRs plo ed in Figu e 4.15. The comple e ou comes o he QFD anking o he wo
ma ke applica ions can be consul ed in Appendix B: P io i isa ion Ma ices.
Figu e 4.15: Rela i e impo ance o SRs o he applica ion ma ke .
I can be obse ed ha he SRs ha e a ela i ely simila impo ance o he wo applica ion
ma ke s unde conside a ion, wi h a a iabili y below 10%. The con e sion o wa e ene gy
in o consumable powe (SR1), he con inuous ope a ion (SR2) and he educ ion o
annual cos s (SR4) ha e a g ea e in luence on emo e communi y gene a ion.
Al e na i ely, he u ili y-scale gene a ion ma ke pu s mo e emphasis on he p e en ion
o business isks (SR5) and he educ ion in up on cos s (SR3). This quali a i e
assessmen assigns weigh s abo e he a e age impo ance a ing (20%) o SR1 and SR5 o
bo h ma ke s, bu wi h a e e sed anking as p esen ed in Table 4.9. I is wo h no ing ha
he s anda d de ia ion o weigh ings o he i e SRs is below 3%.
Table 4.9: Ranking o S akeholde Requi emen s (SRs).
Rank U ili y-scale Remo e communi y
1 P e en business isks Con e ene gy in o consumable powe
2 Con e ene gy in o consumable powe P e en business isks
3 Reduce up on cos s Ope a e when needed
4 Ope a e when needed Reduce annual cos s
5 Reduce annual cos s Reduce up on cos s
FORMALISING SYSTEM REQUIREMENTS
98
SRs p io i isa ion ein o ces he conclusions d awn om he analysis o he wa e ene gy
con ex in he p e ious chap e . The Economic conce ns o he Owne ha e he g ea es
in luence on he impo ance a ings o he SRs o he u ili y-scale ma ke , whe eas he
Poli ical conce ns om he Go e nmen mainly d i e he SRs o he emo e communi y
gene a ion.
The agg ega ion o SRs' u ili y in o global me i p o ides an addi ional pe spec i e. Figu e
4.16 shows he impac o changes in one MOE u ili y while he es main ain he highes
sco e o each applica ion ma ke .
(a) (b)
Figu e 4.16: Sensi i i y o Global Me i o MOE U ili y o each ma ke applica ion: (a)
U ili y-scale gene a ion; (b) Powe ing emo e communi ies.
In bo h ma ke scena ios, he con e sion o wa e ene gy in o consumable powe (SR1:
CF) has he g ea es in luence on he Global Me i ollowed by ope a ing when needed
(SR2: AF). When de i ing he Global Me i , he logical p e e ence ope a o s used o
combining he MOEs ha e a s onge in luence han hei co esponding weigh ings. The
Geome ic mean penalises low u ili y alues. This logical ope a o is applied wice
consecu i ely o combine SR1: CF and SR2: AF.
Then i ollows he educ ion in up on cos s (SR3: CAPEX) and p e en ion o business
isks (SR5: FCR). Thei in luence is howe e swapped o each applica ion ma ke . Finally,
he less sensi i e MOE o changes in he u ili y is he annual cos s (SR4: OPEX). This is
due o he ac he u ili y is combined h ough he A i hme ic mean, which is a neu al
ope a o . OPEX has he leas in luence un il i eaches medium u ili y, whe e i becomes
mo e p edominan , pa icula ly o he u ili y-scale gene a ion ma ke .
FORMALISING SYSTEM REQUIREMENTS
99
4.4.2 P io i isa ion o FRs
Figu e 4.17 depic s he esul s om he p ac ical implemen a ion o he me hodology in
he unc ional domain. Likewise, he comple e ou comes o QFD anking o he wo
ma ke applica ions can be consul ed in Appendix B: P io i isa ion Ma ices.
Figu e 4.17: Rela i e impo ance o FR o he applica ion ma ke .
FRs ha e ela i ely equal impo ance o he wo applica ion ma ke s unde conside a ion,
wi h a a iabili y lowe han 9%. The unc ions con ibu ing o each SR ollow he same
pa e n as be o e. Howe e , we can app ecia e ha cap u ing (FR1) and ans o ming
(FR2) wa e ene gy, minimising o al down ime (FR5) and su i ing he ha sh
en i onmen (FR9) a e he mos ele an equi emen s, all o hem abo e he a e age
impo ance a ing (10%) o bo h ma ke s. The ull anking o FRs is shown in Table 4.10.
Table 4.10: Ranking o Func ional Requi emen s (FRs).
Rank U ili y-scale Remo e communi y
1 Su i e he ha sh en i onmen al Cap u e ene gy om wa es
2 Cap u e ene gy om wa es Su i e he ha sh en i onmen al
3 Minimise o al down ime Minimise o al down ime
4 T ans o m in o ene gy T ans o m in o ene gy
5 A oid isks o ecep o s Maximise o al up ime
6 Maximise o al up ime A oid isks o ecep o s
7 Manu ac u e by indus ial p ocesses Main ain by se ice essels
8 Main ain by se ice essels Deli e ene gy o poin o consump ion
9 Deli e ene gy o poin o consump ion Manu ac u e by indus ial p ocesses
10 Ins all by se ice essels Ins all by se ice essels
FORMALISING SYSTEM REQUIREMENTS
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Su i ing he ha sh en i onmen (FR9) is anked i s o he u ili y-scale ma ke ollowed
by cap u ing wa e ene gy (FR1), whe eas hese FRs a e swapped o he emo e
communi y gene a ion. I is wo h no ing ha he s anda d de ia ion o weigh ings is
sligh ly abo e 2% indica ing ha his anking may be al e ed wi h small changes in he
s akeholde p e e ence.
The p oposed me hod di e s om he TPL sco ing me hodology [133] as he la e
conside s ha mos o he capabili ies ha e equal in luence. Fo ins ance, he same weigh s
a e assigned o equi alen pai s o equi emen s FR6 and FR7, FR2 and FR3, and FR4 and
FR5. The aceabili y o design in o ma ion and equi emen s h ough he di e en
domains o e s a mo e objec i e way o accoun o hose di e ences wi hou assuming
ei he a la dis ibu ion o any o he a bi a y dis ibu ion o weigh s.
(a) (b)
(c) (d)
Figu e 4.18: MOE Sensi i i y o U ili y-scale Gene a ion: (a) Con e wa e ene gy; (b)
Ope a e when needed; (c) Reduce up on cos s; (d) P e en business isks.
FORMALISING SYSTEM REQUIREMENTS
101
The agg ega ion o FRs’ u ili y in o s akeholde alue p o ides addi ional insigh s. Figu e
4.18 shows he impac o changes in one MOP u ili y while he es main ain he highes
sco e o he u ili y-scale ma ke . Due o he low a ia ion o weigh ings, he changes in
u ili y a e insigni ican be ween he wo applica ions conside ed.
Cap u ing ene gy om wa es (FR1: C
wn
), minimising o al down ime (FR4: MTTR),
manu ac u ing by indus ial p ocesses (FR6: CAPEX) and su i ing he ha sh
en i onmen (FR9: SURV) ha e he g ea es in luence in hei espec i e MOE. Howe e ,
FR4 and FR9 ha e he wides u ili y a ia ion as a esul o he logical ope a o chosen
(ha monic mean and s ong conjunc ion espec i ely).
Figu e 4.19 depic s he sensi i i y o Global Me i o each FR o bo h ma ke scena ios. In
line wi h he anking o FRs, he ins alla ion by se ice essels (FR7) has a lesse impac on
he Global Me i . Low u ili y alues o ans o ming (FR2) and deli e ing (FR3) ene gy
ha e a bigge impac on he Global Me i han manu ac u ing (FR6). The impac o
cap u ing wa e ene gy is kep be ween manu ac u ing (FR6) and main enance (FR8) o a
wide ange o u ili y alues, pa icula ly o he emo e communi y gene a ion which has
a highe weigh ing. Finally, low u ili y alues o minimising down ime (FR5), su i ing
he ha sh en i onmen (FR9), a oiding isks o ecep o s (FR10) and maximising up ime
(FR4) ha e he g ea es in luence on he Global Me i . As he u ili y o hese MOPs
inc eases, main enance (FR8) becomes mo e penalising o he Global Me i . As can be
seen in Figu e 4.19, he sensi i i y o low MOP u ili y is longe main ained o he emo e
communi y gene a ion.
(a) (b)
Figu e 4.19: Sensi i i y o Global Me i o MOP U ili y o each ma ke applica ion: (a)
U ili y-scale gene a ion; (b) Powe ing emo e communi ies.
FORMALISING SYSTEM REQUIREMENTS
102
4.4.3 P io i isa ion o DPs
As said be o e, he la ge numbe o TRs esul s in a QFD ma ix di icul o manage. The
anking o 23 equi emen s is simply beyond he human cogni i e capabili y and, i i we e
possible, he in e p e a ion would become much mo e challenging.
Suppo ed by he s akeholde and unc ional domain esul s, i can be assumed ha he
impo ance o he weigh ings would be mino and ha he wo ma ke s conside ed will
yield qui e simila ela i e impo ance. Mo eo e , logical ope a o s which equi e highe
conjunc ion will in luence mo e he Global Me i . Taking as e e ence he sensi i i y
analysis o FRs wi h alues g ea e han 0.3 (Figu e 4.19), we can an icipa e ha he
ollowing TPMs will be key o achie ing high me i :
• The Uni se ice essel cos and Numbe o ips o REPEX.
• Load shedding and De ec ion le el o SURV.
• The Fa m densi y o EIS.
• T a el, Wai ing and Logis ic imes o MTTR.
• Technology class, Load shedding and Sa e y ac o o MTTF.
• Maximum pe missible load o Cwn.
Figu e 4.20 shows he esul s om he p ac ical implemen a ion o he me hodology o
he mapping o Design Pa ame e s (DPs). The comple e ou comes o he QFD anking o
he wo ma ke applica ions can be consul ed in Appendix B: P io i isa ion Ma ices.
Figu e 4.20: Rela i e impo ance o DPs o he applica ion ma ke .
Again, DPs ha e ela i ely equal impo ance o he wo applica ion ma ke s unde
conside a ion, wi h a a iabili y lowe han 4%. The op p io i y DPs, all o hem abo e
he a e age impo ance a ing (10%), a e he S eng h (DP2), A ea o mo ing objec
(DP1), Adap abili y (DP7), Loss o ene gy (DP4) and Quan i y o subs ance (DP6). The
FORMALISING SYSTEM REQUIREMENTS
103
ull anking o FRs is shown in Table 4.11, which emains he same o he wo ma ke
applica ions.
Table 4.11: Ranking o Design Pa ame e s (DPs).
Rank U ili y-scale & Remo e communi y
1 S eng h
2 A ea o mo ing objec
3 Adap abili y
4 Loss o ene gy
5 Quan i y o subs ance
6 De ice complexi y
7 P oduc i i y
8 Di icul y o de ec ing
9 Loss o ime
10 Du a ion o he ac ion
We can obse e ha he h ee op- anked design pa ame e s, namely S eng h (DP2), A ea
o mo ing objec (DP1) and Adap abili y (DP7), a e ela ed o he p ima y s akeholde
equi emen , con e ing wa e ene gy in o consumable powe (SR1). Mo eo e , hey also
con ibu e o ope a ing when needed (SR2) and p e en ing business isks (SR5). This
esul is consis en wi h Figu e 4.16 in sec ion 4.4.1 since hese we e he mos sensi i e
MOE. Loss o ene gy (DP4) is linked o ans o ming (FR2) and deli e ing (FR3) ene gy,
bo h o which a e connec ed o SR1. Finally, Quan i y o subs ance (DP6) con ibu es o
manu ac u ing (FR6), ins alling (FR7) and main aining (FR8), which a e linked wi h he
o he wo s akeholde equi emen s.
4.5 Conclusions
The c ea ion o a s anda d amewo k o wa e ene gy echnologies cons uc ed a ound
he no ion o design domains assis s in he o ganiza ion o da a on equi emen s and
me ics o make sys em alida ion and e i ica ion easie . This common amewo k can
be applied o di e en le els o sys em agg ega ion, echnology ma u i y and ma ke s
ensu ing a consis en and ully aceable assessmen . By epea ing he domain mapping
p ocess and adding addi ional laye s o he equi emen s hie a chy, aceabili y o e s
lexibili y o adap his amewo k o apidly changing ma ke condi ions and s akeholde
p io i ies o o ocus he analysis on pa icula wa e ene gy sub-sys ems, assemblies o
componen s.
The LSP echnique allows o g ea e g anula i y in he o mula ion o he agg ega ion
logic and enables he seamless combina ion o manda o y, su icien and op ional me ics.
This me hod can amalgama e dispa a e a ibu es and c i e ia exp essed by a a ie y o
GUIDING THE DESIGN DECISIONS
110
way o illus a ion, in [145], he maximum CAPEX o a wa e ene gy echnology wi h a
ce ain annual ene gy p oduc ion is de e mined o each he a ge LCOE.
In his alloca ion, espec ing he heo e ical o undamen al limi s ha canno be
su passed is pa amoun . Fo ins ance, physical limi s o powe cap u e, such as he Budal
uppe bound [224] and he maximum cap u e wid h [238], should be espec ed.
Unde pe o mance in an in e media e me ic can c ea e an issue a a highe le el and,
he e o e, should be ho oughly checked. Howe e , i may be compensa ed by o he
me ics wi h be e sco es a he same le el, due o he exis ence o mul iple solu ions in
he alloca ion o g oup c i e ia a ge s.
Alloca ion o a ge alues will signi ican ly depend on he speci ic echnology op ion
being conside ed. Howe e , a ge alues o he echnology's mos inno a i e aspec s
should p e e ably be abo e he maximum benchma k alues. O he wise, in es o s may
no be willing o ake he isk. On he o he hand, a ge alues no essen ial o he
inno a ion can be wi hin he achie able ange om he echnology spec um known.
A h eshold alue can be sugges ed whene e guidance on he possible maximum and
minimum ange o alues can be ob ained om he s a e-o - he-a . Acco ding o
Chebyshe ’s inequali y [239], no mo e han 1/k
2
o he benchma k alues can be k o mo e
s anda d de ia ions (σ) away om he mean (μ) o any p obabili y dis ibu ion and any
cons an k g ea e han 1. This p obabilis ic s a emen can be w i en as ollows:
9
(
|
:
−
S
|
≥
UV
)
≤
1
U
-
(16)
wi h X being he pe o mance a iable unde conside a ion wi h mean alue μ and
s anda d de ia ion σ.
The p obabili y ha benchma k alues lie ou side he in e al (μ - k×σ, μ + k×σ) does no
exceed 1/k
2
(see Figu e 5.4). Fo example, o iden i y a h eshold alue wi hin 75% o
benchma ks, he alue o k = 2 can be ob ained by sol ing 0.75 = 1- 1/k
2
.
Li e a u e e iew such as [240] is qui e help ul o syn hesise he ange o alues ha migh
be conside ed o key assessmen c i e ia. P ac ical Cap u e Wid h Ra ios (CWR) o
hea ing de ices esul in a mean alue o 17.5% and a s anda d de ia ion o 12%. Assuming
k = 2, he sugges ed h eshold CWR should be se a 41.5%. O he use ul li e a u e sou ces
p o ide ela ionships be ween he a ailabili y and esou ce le el [241], he abso bed powe
and displaced olume [242], o he s eel mass and o al WEC olume [243].
In he lack o benchma ks in he exis ing li e a u e, comme cial alues in known akin
applica ions could also be conside ed e e ence alues o es ablish he a ge s.
GUIDING THE DESIGN DECISIONS
111
5.3 Assessmen o Wa e Ene gy Capabili ies
5.3.1 Backg ound
S aged de elopmen p ocesses a e employed in many enginee ing sec o s o ensu e ha
echnologies a e de eloped in a con olled manne , he e o e managing isk and
unce ain y [244]. A s aged de elopmen p ocess de ines sui able e alua ion me ics ha
should be moni o ed h oughou echnology de elopmen , and h esholds o hese
me ics ha mus be me o demons a e success ul p og ess [245]. Wi h clea e alua ion
me ics, p og ess can be quan i ied, and he de elopmen p ocess guided o p oduce he
desi ed ou come. Mo eo e , by iden i ying he weakes and s onges a eas o he
echnology, he de elopmen e o s can be alloca ed mo e app op ia ely, and mo e cos -
e ec i e designs can be p oduced h ough a ious design i e a ions.
The p e ious chap e p esen ed a common e alua ion amewo k o wa e ene gy
echnologies based on h ee le els o me ics. Sa is ac ion o wa e ene gy equi emen s is
exp essed a di e en hie a chical le els h ough MOEs, MOPs and TPMs. Fu he mo e,
agg ega ing sys em equi emen s in o a inal igu e, o Global Me i (GM), enables a
quali a i e assessmen o he o e all sui abili y o he wa e ene gy echnology.
E alua ion o echnology pe o mance is inhe en ly a con inuous ac i i y [63]. As he wa e
ene gy echnology ma u es, howe e , he pu pose o his assessmen will shi om
s a egic e alua ion and easibili y s udies o unding au ho isa ion, budge ing and p ojec
con ol.
No ably, mos wa e ene gy assessmen s ca ied ou o da e ha e been based on p ojec ed
da a and we e no de i ed om di ec open-sea deploymen expe ience [246]. The eliance
on p ojec ed igu es leads o u he unce ain ies in he assessmen p ocess, which can be
subs an ial depending on he s age o echnology de elopmen , he deg ee o inno a ion,
he da a quali y o assump ions, and he le el o de ail in he assessmen . To he bes o ou
knowledge, he quan i ica ion o he assessmen unce ain y is a opic ha has no been
add essed in wa e ene gy.
The ea lie he s age o echnology de elopmen is, he lowe he accu acy can be achie ed
du ing he e alua ion due o he limi ed knowledge. Many e alua ion a eas may no ha e
been adequa ely add essed a he ini ial ma u i y le el whe e he concep is o mula ed (i.e.
TRL1). They will equi e aking nume ous assump ions leading o signi ican
unce ain ies. Howe e , he accu acy o hese es ima es will be p og essi ely e ined in
subsequen de elopmen s ages. Thus, he unce ain y band will na ow.
The alue assigned o he assessmen c i e ia o a wa e ene gy echnology should be
suppo ed by e idence o he ac i i ies ca ied ou a each de elopmen s age [142]. Fo
ins ance, he H2020- unded DTOceanPlus p ojec p oposes a se ies o ac i i ies a
echnology de elope mus comple e a each main de elopmen s age [156].
GUIDING THE DESIGN DECISIONS
112
The s a e-o - he-a alues in wa e ene gy o any o he closed- ela ed sec o applica ion
could be used as a e e ence o a holis ic e alua ion. Ne e heless, un il i becomes easible
o collec p ac ical e idence on he me ics, hey will be ob iously aken as con ol alues;
i he echnology solu ion di e ges much om i s a ge , he o e all pe o mance migh be
comp omised.
I can be easily in e ed ha he la ge he gap om he expec ed a ge s, he g ea e he
challenges ahead, which can comp omise he echnological easibili y o ma ke en y.
The de elopmen ajec o y mus ensu e ha each iden i ied challenge is add essed a he
ea lies s age since he same pe o mance gap will be ha de o o e come a he nex TRL.
5.3.2 Pe o mance Ra io (PR)
Sys em pe o mance needs o be measu ed agains a speci ied e e ence o p o ide a
quan i a i e assessmen . QFD conside s a pa icula s ep o benchma k how he sys em
equi emen s a e cu en ly sa is ied. Besides, awa eness o bes p ac ices in wa e ene gy
helps o assign accep able, achie able and desi able anges o sys em equi emen s, as
men ioned in sec ion 5.2.2 o he cap u e wid h [240]. These a ge alues enable
benchma king o he ela i e pe o mance o wa e ene gy echnologies in a quan i a i e
manne .
E alua ion c i e ia a ge s di ide echnology pe o mance in o wo sepa a e egions. The e
is a egion o accep able pe o mance whe e he echnology mee s o exceeds he speci ied
e e ence o he co esponding me ic. By con as , unaccep able pe o mance occu s
when he echnology alls sho conce ning his e e ence alue [247]. Any wa e ene gy
de elope aims o each he accep able pe o mance egion o all manda o y me ics.
No wi hs anding he me ic unde conside a ion, e alua ion c i e ia can p esen wo
di e en pe o mance beha iou s. Whe eas some me ics in he e alua ion hie a chy mus
dec ease o mee he es ablished a ge (see Figu e 5.5), o he me ics display an inc easing
pe o mance pa e n (see Figu e 5.6). M1 o M5 s ands o measu ed alues a each
de elopmen s age.
GUIDING THE DESIGN DECISIONS
113
Figu e 5.5: Me ic exhibi ing a dec easing pe o mance beha iou (lowe is be e ).
Le us de ine he Pe o mance Ra io (PR) o o e come his opposing beha iou . Fo
me ics ha exhibi dec easing pe o mance (i.e., lowe is be e ), he PR
i
is calcula ed as
ollows:
9=
=
E
D
(17)
whe e T
i
and M
i
a e he a ge and measu ed pe o mance alues, espec i ely, o he
e alua ion c i e ia i. Typical examples o his ca ego y o me ics a e he Le elized Cos o
Ene gy (LCOE), Mean Time o Repai (MTTR) and Wai ing ime (
w
).
Al e na i ely, o me ics ha show an inc easing pe o mance pa e n (i.e., highe is
be e ), he PR
i
is calcula ed by e e sing his quo ien , which accoun s o he pe cen age
ha he measu ed pe o mance exceeds he a ge alue.
9=
=
D
E
(18)
Some examples o his ca ego y o me ics a e he A ailabili y Fac o (AF), Mean Time To
Failu es (MTTF) and Rela i e bandwid h (B
).
Figu e 5.6: Me ic exhibi ing an inc easing pe o mance beha iou (highe is be e ).
The ou come o pe o mance benchma king o a wa e ene gy concep es ima es how
close o a he echnology is o achie ing i s p e iously es ablished echnical goals. A PR
i
≥ 1 means ha he wa e ene gy echnology is in he accep able pe o mance egion o he
e alua ion c i e ia i. Con e sely, a PR
i
< 1 deno es an unaccep able pe o mance o his
e alua ion c i e ia.
GUIDING THE DESIGN DECISIONS
114
Technologies wi h all manda o y equi emen s in he accep able pe o mance egion can
be benchma ked ega ding hei Comme cial A ac i eness (CA). O he wise, he
Technical Achie abili y (TA) should be in es iga ed.
5.3.3 Comme cial A ac i eness (CA)
Comme cial A ac i eness (CA) is a b oad concep encompassing a ious aspec s anging
om economic p o i abili y o s akeholde accep abili y and size o he ma ke
oppo uni y.
In wa e ene gy, CA has been de ined as he a io o he a ge LCOE alue o he calcula ed
one o explo e concep s beyond he exis ing echnologies [248]. No e ha his a io i s
pe ec ly wi hin he gene ic PR de ini ion om Eq. (22) & (23), bu in his case applied o
he Le elised Cos o Ene gy (LCOE), which is he mos common high-le el a o dabili y
me ic.
The assessmen o CA is also men ioned in he In e na ional E alua ion F amewo k o
Ocean Ene gy Technologies [142], his ime comp ising bo h he cos o ene gy and
sus ainabili y aspec s such as en i onmen al and social accep ance. The guideline,
howe e , nei he p o ides any me ic o sus ainabili y no a p ocedu e o he
compu a ion o he CA.
To ake in o conside a ion he quali a i e aspec s beyond me e a o dabili y (i.e.
s akeholde s’ p e e ence), he p oposed me hodology will de ine CA as he p oduc o he
Global Me i (GM), de i ed om he quali a i e assessmen , and he Pe o mance Ra io
(PR), esul ing om he quan i a i e es ima ions o he LCOE, whene e PR ≥ 1. The
p e ious s a emen can be w i en as ollows:
I PR
≥
1
8
=
XD
×
9=
; else
8
=
0
(19)
The Geome ic mean (G) ope a o is chosen o combine hese a ibu es o p e en
compensa ion. This de ini ion has he ad an age o enabling an objec i e compa ison o
wa e ene gy echnologies in a ious ma ke s p esen ing dissimila ene gy p ices and
esponding o di e en s akeholde demands and p io i ies.
Al hough CA is mainly a use ul concep o compa ing he a o dabili y o wa e ene gy
sys ems, i can be equally applied o he pa ial e alua ion o lowe -le el design a ibu es
in wa e ene gy echnologies, such as MOEs, MOPs o TPMs. I only equi es subs i u ing
he GM o he pa ial u ili y o he pe o mance me ic unde conside a ion esul ing
om he QFD analysis.
Figu e 5.7 exempli ies he concep o CA o assessing wo illus a i e wa e ene gy op ions.
Whe eas he single quan i a i e assessmen will ank Op ion 2 on op o Op ion 1, he
quali a i e assessmen e e ses his o de o p e e ence. The ha ched a ea (PR < 1)
highligh s he need o imp o e some wa e ene gy capabili ies.
GUIDING THE DESIGN DECISIONS
115
Figu e 5.7: Comme cial A ac i eness (CA).
5.3.4 Technical Achie abili y (CA)
Fo wa e ene gy echnologies ha canno mee one o mo e o he manda o y
equi emen s and, he e o e, echnological imp o emen s a e needed, he Technical
Achie abili y (TA) concep is in oduced. I measu es he echnology de elopmen isk,
ime o e o o mee he a ge pe o mance. This concep is pa icula ly use ul when
guiding echnologies wi h long de elopmen imes such as wa e ene gy.
TA has been o mula ed in [248] o powe pe o mance and subsys em cos me ics.
Imp o emen ac o s and lea ning a es a e used o assess he deg ee o e o needed.
Likewise, he e e se LCOE enginee ing me hod [6] was p oposed o explo e he limi s o
he echnical pa ame e s o wa e ene gy echnologies. This is a unidimensional analysis in
which all pa ial e alua ion c i e ia a e ixed. The cos educ ion is in es iga ed o achie e
a PR = 1.
This me hodology p oposes an al e na i e bu mo e comp ehensi e de ini ion ha can be
used o assess wa e ene gy pe o mance a any hie a chical le el. The TA de ini ion has
been adap ed om [249], whe e i is used o suppo decisions o new de ence echnologies
h ough hei de elopmen li ecycle based on pe o mance assessmen .
TA combines he Pe o mance Ra io (PR) and Deg ee o Di icul y (DD) as shown in
Equa ion (20). In his exp ession, DD e ec i ely measu es he isk p obabili y, whils he
unme pe o mance (1 − PR) measu es he isk se e i y o impo ance.
GUIDING THE DESIGN DECISIONS
116
E8
=
9=
1
+
(
1
−
9=
)
ZZ
(20)
Table 5.1 p esen s he DD le els and hei co esponding nume ical alues. The isk le els
a e based on [249]. Howe e , he assigned nume ical alues ha e been esized o a 9-poin
scale o consis ency wi h he QFD anking me hods. The lowe bound (0) indica es no
isk in mee ing he pe o mance equi emen , and success is gua an eed. Con e sely, he
uppe bound (9) means ha i is impossible o mee his equi emen . In e media e le els
deno e di e en deg ees o di icul y.
Table 5.1: Technical Di icul y (adap ed om [249]).
Le el
Deg ee o Di icul y (DD) Value
1 Ve y low unce ain y (ce ain easibili y) 0
2 Mode a e unce ain y 1
3 High unce ain y 3
4 Ve y high unce ain y ( undamen al b eak h ough)
9
Figu e 5.8 illus a es ou achie abili y cu es o di e en DD le els. Fo ins ance, he TA
o one echnology wi h e y low unce ain y and PR = 0.6 (poin a) is analogous o a
echnology wi h a PR = 0.94 (poin c) and e y high unce ain y, which equi es a
undamen al b eak h ough. Simila ly, a echnology wi h e y high unce ain y bu he
same PR = 0.6 (poin b) will se e ely dec ease i s TA o 0.13.
Figu e 5.8: Technical Achie abili y (TA).
Assigning he DD le el o he sys em equi emen s o a wa e ene gy echnology unde
de elopmen may seem en i ely subjec i e and challenging. Despi e he di icul ies, oo
li le ime spen in he ea ly design phases can lead o gaps in unde s anding he p oblem
GUIDING THE DESIGN DECISIONS
117
equi emen s, limi ed oppo uni ies o no el concep gene a ion and was ed ime and
money de eloping a concep ha canno pe o m well enough o become a iable solu ion
[17].
In p ac ical e ms, he abili y o new echnology o mee i s pe o mance a ge s will
depend on i s inno a ion capabili y and i is limi ed by undamen al limi s (ideali y). In
he ea ly s ages, eme ging echnologies will ha e signi ican imp o emen po en ial. In
con as , ma u e echnologies in he la e de elopmen s ages will ha e limi ed
imp o emen po en ial. Thus, DD indica es he Lea ning Ra e (LR) needed o achie e a
PR = 1.
Di e en lea ning mechanisms ha e been desc ibed in he li e a u e, as will be u he
discussed in CHAPTER 6. Howe e , in he con ex o echnology de elopmen ,
echnological lea ning e e s o he a e a which new knowledge is e ec i ely acqui ed o
imp o e i s pe o mance.
As echnology de elopmen p og esses, new knowledge is acqui ed, he sou ces o
a iabili y o he a ious e alua ion c i e ia a e pinned down, and he unce ain y o he
es ima es is na owed. This phenomenon is known as he “cone o unce ain y”. De ined
ini ially o so wa e de elopmen [250], his concep has been used in P ojec
Managemen o decades o desc ibe unce ain y educ ion as enginee ing sys ems e ol e.
Figu e 5.9: Cone o unce ain y and DD le els.
A he concep s age, he ini ial es ima e is based on minimal in o ma ion. This es ima e
is a ough o de o magni ude, whose a iance can be as much as 100% depending on he
sou ce o e idence. Then he a iance will be p og essi ely diminished in subsequen
GUIDING THE DESIGN DECISIONS
118
phases un il he echnology is inally deployed and he e is no unce ain y emaining. The
cone o unce ain y delimi s he uppe and lowe bounds o i e de elopmen s ages as
illus a ed in Figu e 5.9.
All he es ima ions wi h PR < 1 ha lie wi hin he cone o unce ain y would be assigned
a low DD. Howe e , he same es ima ion should inc ease i s DD i he PR does no
imp o e. Fo ins ance, a PR = 0.7 can be assigned a DD le el 1 a concep design (S age 1)
bu inc eased o 3 in he design phase (S age 2) o e en a ed 9 o la e s ages. The
inno a ion capabili y is limi ed as he echnology ma u es. The e o e, he PR should be
penalised wi h a highe DD a la e design s ages.
Con e sely, an ea ly TRL opens he oom o imp o emen s h ough inno a ion. Webe
[151] exp esses he same unde lying idea in he gene ic WEC de elopmen ajec o ies
displayed o e a TRL-TPL ma ix. Fundamen al sys em changes a e only easible and
a o dable a low TRLs. Cos educ ion and imp o ed pe o mance o ma u e
echnologies a e mainly limi ed o lea ning by doing and economies o scale.
5.4 P ac ical Implemen a ion
5.4.1 Benchma k Cases
The p ac ical implemen a ion o he p oposed me hodology is showcased wi h six
illus a i e cases o hypo he ical wa e ene gy echnologies. These benchma k cases a e
de ined wi h an iden ical ins alled capaci y (1 MW) bu di e en combina ions o MOE,
leading o a plu ali y o LCOE alues.
The nume ical alues o he di e en e alua ion c i e ia a e summa ised in Table 5.2. The
LCOE is calcula ed using Equa ion (8), p esen ed in he p e ious chap e .
Table 5.2: Illus a i e benchma k cases.
E al C i e ia (MOE)
Case 1 Case 2 Case 3 Case 4 Case 5 Case 6
P (MW) 1 1 1 1 1 1
CF (%) 30 25 50 40 20 25
AF (%) 95 97 99 98 92 85
CAPEX (M€) 1 1.2 3 3 1.9 3.5
OPEX (k€) 45 92 150 210 114 140
FCR (%) 8 10 9.4 10.2 11 9.3
LCOE (€/MWh) 50 100 100 150 200 250
Case 1 ep esen s a high-pe o ming wa e ene gy echnology in all e alua ion c i e ia. I
leads o he lowes LCOE o 50 €/MWh, which could compe e in cos e ms wi h
adi ional ene gy sou ces e en wi hou addi ional subsidies.
GUIDING THE DESIGN DECISIONS
119
Case 2 and Case 3 in ol e wo wa e ene gy op ions ha each he same LCOE o 100
€/MWh h ough al e na i e pe o mance pa hs. Whe eas Case 2 has a mode a ely low-
capaci y ac o coupled wi h compe i i e li e ime cos s, Case 3 displays he highes ne
ene gy p oduc ion bu also ca ies high CAPEX and OPEX cos s. Depending on he
inno a ion po en ial o hese echnologies, hey could ha e scope o u he ene gy cos
educ ion.
Case 4 explo es a wa e ene gy echnology ha canno compensa e o he high li e ime
cos s despi e he signi ican ne ene gy p oduc ion. Hence, Case 4 leads o an LCOE o 150
€/MWh. The EU’s SET Plan implemen a ion plan o Ocean Ene gy [226] es ablishes a
a ge LCOE o 150 €/MWh by 2030 and 100 €/MWh by 2035 o wa e ene gy
echnologies.
Howe e , he wo las benchma k cases ha e an LCOE beyond he EU’s SET Plan
implemen a ion plan a ge s. Case 5 has a e y low-capaci y ac o and mode a ely high
cos s, which esul s in an LCOE o 200 €/MWh. Finally, Case 6 has he highes in es men
cos s and lowes a ailabili y esul ing in he leas a o dable op ion, which leads o he
highes LCOE o 250 €/MWh.
5.4.2 Global Me i (GM)
A alue unc ion is de ined o each MOE o compa e he di e en wa e ene gy op ions.
The unc ion is no malised conside ing maximum (1) and minimum (0) u ili y alues as
shown in Table 5.3. Maximum and minimum bounds o he MOE ha e been assigned
examining wa e ene gy li e a u e, as desc ibed in sec ion 4.3.2.
Table 5.3: S akeholde Requi emen s and U ili y.
MOE Min = 0 Max = 1 Value Func ion
CF (%) 0% ≥50% Maximisa ion ype, Con ex
AF (%) ≤75% 100% Maximisa ion ype, Conca e
CAPEX (M€) ≥5 M€ 0 M€ Minimisa ion ype, Conca e
OPEX (k€) ≥500 k€ 0 k€ Minimisa ion ype, Con ex
FCR (%) ≥20% ≤5% Cons ain ype
CF is modelled wi h a maximisa ion ype alue unc ion. I has a sligh ly con ex shape:
his e lec s he inc easing di icul y o imp o ing u ili y as he CF ge s close o i s
maximum alue. The neu al poin is se o 17.5%, he a e age alue epo ed o hea ing
poin abso be s in [240]. Figu e 5.10-a) depic s he unc ion and he alues o he six
benchma k cases.
APPENDICES
222
Appendix C: Lis o TRIZ 39 Technical Pa ame e s
F ee access a h ps://onlinelib a y.wiley.com/doi/10.1002/9780470684320.app1 [232].
Table A.11: Lis o TRIZ 39 Technical Pa ame e s.
No. Ti le Explana ion
1 Weigh o mo ing objec The mass o he objec , in a g a i a ional ield. The o ce
ha he body exe s on i s suppo o suspension
2 Weigh o s a iona y objec
The mass o he objec , in a g a i a ional i eld. The o ce
ha he body exe s on i s suppo o suspension, o on he
su ace on which i es s.
3 Leng h o mo ing objec Any one linea dimension, no necessa ily he longes , is
conside ed a leng h.
4 Leng h o s a iona y objec Same.
5 A ea o mo ing objec A geome ical cha ac e is ic desc ibed by he pa o a
plane enclosed by a line. The pa o a su ace occupied by
he objec OR he squa e measu e o he su ace, ei he
in e nal o ex e nal, o an objec .
6 A ea o s a iona y objec Same.
7 Volume o mo ing objec The cubic measu e o space occupied by he objec . Leng h
x wid h x heigh o a ec angula objec , heigh x a ea o
a cylinde , e c.
8 Volume o s a iona y
objec
Same.
9 Speed The eloci y o an objec ; he a e o a p ocess o ac ion in
ime.
10 Fo ce Fo ce measu es he in e ac ion be ween sys ems. In
New onian physics, o ce = mass x accele a ion. In TRIZ,
o ce is any in e ac ion ha is in ended o change an
objec ’s condi ion.
11 S ess o p essu e Fo ce pe uni a ea. Also, ension.
12 Shape The ex e nal con ou s, appea ance o a sys em.
13 S abili y o he objec ’s
composi ion
The wholeness o in eg i y o he sys em; he ela ionship
o he sys em’s cons i uen elemen s. Wea , chemical
decomposi ion, and disassembly a e all dec eases in
s abili y. Inc easing en opy is dec easing s abili y.
14 S eng h The ex en o which he objec is able o esis changing in
esponse o o ce. Resis ance o b eaking.
15
Du a ion o ac ion by a
mo ing objec
The ime ha he objec can pe o m he ac ion. Se ice
li e. Mean ime be ween ailu e is a measu e o he
du a ion o ac ion. Also, du abili y.
APPENDICES
223
No. Ti le Explana ion
16 Du a ion o ac ion by a
s a iona y objec
Same.
17 Tempe a u e The he mal condi ion o he objec o sys em. Loosely
includes o he he mal pa ame e s, such as hea capaci y,
ha a ec he a e o change o empe a u e.
18 Illumina ion in ensi y Ligh lux pe uni a ea, also any o he illumina ion
cha ac e is ics o he sys em such as b igh ness, ligh
quali y, e c.
19
Use o ene gy by mo ing
objec
The measu e o he objec ’s capaci y o doing wo k. In
classical mechanics, Ene gy is he p oduc o o ce x
dis ance. This includes he use o ene gy p o ided by he
supe - sys em (such as elec ical ene gy o hea .) Ene gy
equi ed o do a pa icula job.
20 Use o ene gy by s a iona y
objec
Same.
21 Powe The ime a e a which wo k is pe o med. The a e o use
o ene gy.
22 Loss o ene gy Use o ene gy ha does no con ibu e o he job being
done. See 19. Reducing he loss o ene gy some imes
equi es di e en echniques om imp o ing he use o
ene gy, which is why his is a sepa a e ca ego y.
23 Loss o subs ance Pa ial o comple e, pe manen o empo a y, loss o some
o a sys em’s ma e ials, subs ances, pa s o subsys ems.
24 Loss o in o ma ion Pa ial o comple e, pe manen o empo a y, loss o da a
o access o da a in o by a sys em. F equen ly includes
senso y da a such as a oma, ex u e, e c.
25 Loss o ime Time is he du a ion o an ac i i y. Imp o ing he loss o
ime means educing he ime aken o he ac i i y. ‘Cycle
ime educ ion’ is a common e m.
26
Quan i y o subs ance/ he
ma e
The numbe o amoun o a sys em’s ma e ials,
subs ances, pa s o subsys ems which migh be changed
ully o pa ially, pe manen ly o empo a ily.
27 Reliabili y A sys em’s abili y o pe o m i s in ended unc ions in
p edic able ways and condi ions.
28 Measu emen accu acy The closeness o he measu ed alue o he ac ual alue o
a p ope y o a sys em. Reducing he e o in a
measu emen inc eases he accu acy o he measu emen .
29 Manu ac u ing p ecision
The
ex en o which he ac ual cha ac e is ics o he sys em
o objec ma ch he speci ied o equi ed cha ac e is ics.
30 Ex e nal ha m a ec s he
objec
Suscep ibili y o a sys em o ex e nally gene a ed (ha m ul)
e ec s.
31
Objec
-
gene a ed ha m ul
ac o s
A ha m ul e ec is one ha educes he e iciency o
quali y o he unc ioning o he objec o sys em. These
APPENDICES
224
No. Ti le Explana ion
ha m ul e ec s a e gene a ed by he objec o sys em, as
pa o i s ope a ion.
32 Ease o manu ac u e The deg ee o acili y, com o o e o lessness in
manu ac u ing o ab ica ing he objec /sys em.
33 Ease o ope a ion
Simplici y: The p ocess is no easy i i equi es a la ge
numbe o people, la ge numbe o s eps in he ope a ion,
needs special ools, e c. ‘Ha d’ p ocesses ha e low yield
and ‘easy’ p ocess ha e high yield; hey a e easy o do
igh .
34 Ease o epai Quali y cha ac e is ics such as con enience, com o ,
simplici y, and ime o epai aul s, ailu es o de ec s in a
sys em.
35 Adap abili y o e sa ili y
The ex en o which a sys em/objec posi i ely esponds o
ex e nal changes. Also, a sys em ha can be used in
mul iple ways o unde a a ie y o ci cums ances.
36 De ice complexi y The numbe and di e si y o elemen s and elemen
in e ela ionships wi hin a sys em. The use may be an
elemen o he sys em ha inc eases he complexi y. The
di icul y o mas e ing he sys em is a measu e o i s
complexi y.
37
Di icul y o de ec ing and
measu ing
Measu ing o m
oni o ing sys ems ha a e complex, cos ly,
equi e much ime and labou o se up and use, o ha
ha e complex ela ionships be ween componen s o
componen s ha in e e e wi h each o he all demons a e
‘di icul y o de ec ing and measu ing’. Inc easing cos o
measu ing o a sa is ac o y e o is also a sign o inc eased
di icul y o measu ing.
38 Ex en o au oma ion The ex en o which a sys em o objec pe o ms i s
unc ions wi hou human in e ace. The lowes le el o
au oma ion is he use o a manually ope a ed ool. Fo
in e media e le els, humans p og am he ool, obse e i s
ope a ion, and in e up o e-p og am as needed. Fo he
highes le el, he machine senses he ope a ion needed,
p og ams i sel and moni o s i s own ope a ions.
39 P oduc i i y The numbe o unc ions o ope a ions pe o med by a
sys em pe uni ime. The ime o a uni unc ion o
ope a ion. The ou pu pe uni ime, o he cos pe uni
ou pu .
APPENDICES
225
Appendix D: Con adic ion Ma ix
F ee access a h ps://www. iz.co.uk/lea ning-cen e-inno a ion-ma e ials [232].
Table A.12: Con adic ion Ma ix.
Weigh o mo ing objec
Weigh o s a iona y
objec
Leng h o mo ing objec
Leng h o s a iona y
objec
A ea o mo ing objec
A ea o s a iona y objec
Volume o mo ing objec
Volume o s a iona y
objec
Speed
Fo ce (In ensi y)
S ess o p essu e
Shape
S abili y o he objec 's
composi ion
S eng h
Du a ion o ac ion o
mo ing objec
Du a ion o ac ion o
s a iona y objec
Tempe a u e
Illumina ion in ensi y
Use o ene gy by mo ing
objec
Use o ene gy by
s a iona y objec
Powe
Loss o Ene gy
Loss o Subs ance
Loss o In o ma ion
Loss o Time
Quan i y o subs ance
Reliabili y
Measu emen accu acy
Manu ac u ing p ecision
Objec -a ec ed ha m ul
ac o s
Objec -gene a ed ha m ul
ac o s
Ease o manu ac u e
Ease o ope a ion
Ease o epai
Adap abili y o e sa ili y
De ice complexi y
Di icul y o de ec ing and
measu ing
Ex en o au oma ion
P oduc i i y
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39
Weigh o mo ing objec 1 +
15, 8,
29,34
29, 17,
38, 34
29, 2,
40, 28
2, 8,
15, 38
8, 10,
18, 37
10, 36,
37, 40
10, 14,
35, 40
1, 35,
19, 39
28, 27,
18, 40
5, 34,
31, 35
6, 29,
4, 38
19, 1,
32
35, 12,
34, 31
12, 36,
18, 31
6, 2,
34, 19
5, 35,
3, 31
10, 24,
35
10, 35,
20, 28
3, 26,
18, 31
1, 3,
11, 27
28, 27,
35, 26
28, 35,
26, 18
22, 21,
18, 27
22, 35,
31, 39
27, 28,
1, 36
35, 3,
2, 24
2, 27,
28, 11
29, 5,
15, 8
26, 30,
36, 34
28, 29,
26, 32
26, 35
18, 19
35, 3,
24, 37
Weigh o s a iona y objec 2 +
10, 1,
29, 35
35, 30,
13, 2
5, 35,
14, 2
8, 10,
19, 35
13, 29,
10, 18
13, 10,
29, 14
26, 39,
1, 40
28, 2,
10, 27
2, 27,
19, 6
28, 19,
32, 22
19, 32,
35
18, 19,
28, 1
15, 19,
18, 22
18, 19,
28, 15
5, 8,
13, 30
10, 15,
35
10, 20,
35, 26
19, 6,
18, 26
10, 28,
8, 3
18, 26,
28
10, 1,
35, 17
2, 19,
22, 37
35, 22,
1, 39
28, 1,
9
6, 13,
1, 32
2, 27,
28, 11
19, 15,
29
1, 10,
26, 39
25, 28,
17, 15
2, 26,
35
1, 28,
15, 35
Leng h o mo ing objec 3
8, 15,
29, 34
+
15, 17,
4
7, 17,
4, 35
13, 4,
8
17, 10,
4
1, 8,
35
1, 8,
10, 29
1, 8,
15, 34
8, 35,
29, 34
19
10, 15,
19
32
8, 35,
24
1, 35
7, 2,
35, 39
4, 29,
23, 10
1, 24
15, 2,
29
29, 35
10, 14,
29, 40
28, 32,
4
10, 28,
29, 37
1, 15,
17, 24
17, 15
1, 29,
17
15, 29,
35, 4
1, 28,
10
14, 15,
1, 16
1, 19,
26, 24
35, 1,
26, 24
17, 24,
26, 16
14, 4,
28, 29
Leng h o s a iona y objec 4
35, 28,
40, 29 +
17, 7,
10, 40
35, 8,
2,14 28, 10
1, 14,
35
13, 14,
15, 7
39, 37,
35
15, 14,
28, 26
1, 10,
35
3, 35,
38, 18 3, 25 12, 8 6, 28
10, 28,
24, 35
24, 26,
30, 29,
14
15, 29,
28
32, 28,
3
2, 32,
10 1, 18
15, 17,
27 2, 25 3 1, 35 1, 26 26
30, 14,
7, 26
A ea o mo ing objec 5
2, 17,
29, 4
14, 15,
18, 4
+
7, 14,
17, 4
29, 30,
4, 34
19, 30,
35, 2
10, 15,
36, 28
5, 34,
29, 4
11, 2,
13, 39
3, 15,
40, 14
6, 3
2, 15,
16
15, 32,
19, 13
19, 32
19, 10,
32, 18
15, 17,
30, 26
10, 35,
2, 39
30, 26 26, 4
29, 30,
6, 13
29, 9
26, 28,
32, 3
2, 32
22, 33,
28, 1
17, 2,
18, 39
13, 1,
26, 24
15, 17,
13, 16
15, 13,
10, 1
15, 30
14, 1,
13
2, 36,
26, 18
14, 30,
28, 23
10, 26,
34, 2
A ea o s a iona y objec 6
30, 2,
14, 18
26, 7,
9, 39
+
1, 18,
35, 36
10, 15,
36, 37
2, 38 40
2, 10,
19, 30
35, 39,
38
17, 32
17, 7,
30
10, 14,
18, 39
30, 16
10, 35,
4, 18
2, 18,
40, 4
32, 35,
40, 4
26, 28,
32, 3
2, 29,
18, 36
27, 2,
39, 35
22, 1,
40
40, 16 16, 4 16 15, 16
1, 18,
36
2, 35,
30, 18
23
10, 15,
17, 7
Volume o mo ing objec 7
2, 26,
29, 40
1, 7, 4,
35
1, 7, 4,
17 +
29, 4,
38, 34
15, 35,
36, 37
6, 35,
36, 37
1, 15,
29, 4
28, 10,
1, 39
9, 14,
15, 7
6, 35,
4
34, 39,
10, 18
2, 13,
10 35
35, 6,
13, 18
7, 15,
13, 16
36, 39,
34, 10 2, 22
2, 6,
34, 10
29, 30,
7
14, 1,
40, 11
25, 26,
28
25, 28,
2, 16
22, 21,
27, 35
17, 2,
40, 1
29, 1,
40
15, 13,
30, 12 10 15, 29 26, 1
29, 26,
4
35, 34,
16, 24
10, 6,
2, 34
Volume o s a iona y objec 8
35, 10,
19, 14
19, 14
35, 8,
2, 14
+
2, 18,
37
24, 35
7, 2,
35
34, 28,
35, 40
9, 14,
17, 15
35, 34,
38
35, 6,
4
30, 6
10, 39,
35, 34
35, 16,
32 18
35, 3
2, 35,
16
35, 10,
25
34, 39,
19, 27
30, 18,
35, 4
35 1 1, 31
2, 17,
26
35, 37,
10, 2
Speed 9
2, 28,
13, 38
13, 14,
8
29, 30,
34
7, 29,
34
+
13, 28,
15, 19
6, 18,
38, 40
35, 15,
18, 34
28, 33,
1, 18
8, 3,
26, 14
3, 19,
35, 5
28, 30,
36, 2
10, 13,
19
8, 15,
35, 38
19, 35,
38, 2
14, 20,
19, 35
10, 13,
28, 38
13, 26
10, 19,
29, 38
11, 35,
27, 28
28, 32,
1, 24
10, 28,
32, 25
1, 28,
35, 23
2, 24,
35, 21
35, 13,
8, 1
32, 28,
13, 12
34, 2,
28, 27
15, 10,
26
10, 28,
4, 34
3, 34,
27, 16
10, 18
Fo ce (In ensi y) 10
8, 1,
37, 18
18, 13,
1, 28
17, 19,
9, 36 28, 10
19, 10,
15
1, 18,
36, 37
15, 9,
12, 37
2, 36,
18, 37
13, 28,
15, 12 +
18, 21,
11
10, 35,
40, 34
35, 10,
21
35, 10,
14, 27 19, 2
35, 10,
21
19, 17,
10
1, 16,
36, 37
19, 35,
18, 37 14, 15
8, 35,
40, 5
10, 37,
36
14, 29,
18, 36
3, 35,
13, 21
35, 10,
23, 24
28, 29,
37, 36
1, 35,
40, 18
13, 3,
36, 24
15, 37,
18, 1
1, 28,
3, 25
15, 1,
11
15, 17,
18, 20
26, 35,
10, 18
36, 37,
10, 19 2, 35
3, 28,
35, 37
S ess o p essu e 11
10, 36,
37, 40
13, 29,
10, 18
35, 10,
36
35, 1,
14, 16
10, 15,
36, 28
10, 15,
36, 37
6, 35,
10
35, 24
6, 35,
36
36, 35,
21
+
35, 4,
15, 10
35, 33,
2, 40
9, 18,
3, 40
19, 3,
27
35, 39,
19, 2
14, 24,
10, 37
10, 35,
14
2, 36,
25
10, 36,
3, 37
37, 36,
4
10, 14,
36
10, 13,
19, 35
6, 28,
25
3, 35
22, 2,
37
2, 33,
27, 18
1, 35,
16
11 2 35
19, 1,
35
2, 36,
37
35, 24
10, 14,
35, 37
Shape 12
8, 10,
29, 40
15, 10,
26, 3
29, 34,
5, 4
13, 14,
10, 7
5, 34,
4, 10
14, 4,
15, 22
7, 2,
35
35, 15,
34, 18
35, 10,
37, 40
34, 15,
10, 14
+
33, 1,
18, 4
30, 14,
10, 40
14, 26,
9, 25
22, 14,
19, 32
13, 15,
32
2, 6,
34, 14
4, 6, 2 14
35, 29,
3, 5
14, 10,
34, 17
36, 22
10, 40,
16
28, 32,
1
32, 30,
40
22, 1,
2, 35
35, 1
1, 32,
17, 28
32, 15,
26
2, 13,
1
1, 15,
29
16, 29,
1, 28
15, 13,
39
15, 1,
32
17, 26,
34, 10
S abili y o he objec 's
composi ion 13
21, 35,
2, 39
26, 39,
1, 40
13, 15,
1, 28 37
2, 11,
13 39
28, 10,
19, 39
34, 28,
35, 40
33, 15,
28, 18
10, 35,
21, 16
2, 35,
40
22, 1,
18, 4 +
17, 9,
15
13, 27,
10, 35
39, 3,
35, 23
35, 1,
32
32, 3,
27, 16 13, 19
27, 4,
29, 18
32, 35,
27, 31
14, 2,
39, 6
2, 14,
30, 40 35, 27
15, 32,
35 13 18
35, 24,
30, 18
35, 40,
27, 39 35, 19
32, 35,
30
2, 35,
10, 16
35, 30,
34, 2
2, 35,
22, 26
35, 22,
39, 23
1, 8,
35
23, 35,
40, 3
S eng h 14
1, 8,
40, 15
40, 26,
27, 1
1, 15,
8, 35
15, 14,
28, 26
3, 34,
40, 29
9, 40,
28
10, 15,
14, 7
9, 14,
17, 15
8, 13,
26, 14
10, 18,
3, 14
10, 3,
18, 40
10, 30,
35, 40
13, 17,
35
+
27, 3,
26
30, 10,
40
35, 19
19, 35,
10
35
10, 26,
35, 28
35
35, 28,
31, 40
29, 3,
28, 10
29, 10,
27
11, 3
3, 27,
16
3, 27
18, 35,
37, 1
15, 35,
22, 2
11, 3,
10, 32
32, 40,
25, 2
27, 11,
3
15, 3,
32
2, 13,
25, 28
27, 3,
15, 40
15
29, 35,
10, 14
Du a ion o ac ion o
mo ing objec
15
19, 5,
34, 31
2, 19,
9
3, 17,
19
10, 2,
19, 30
3, 35,
5
19, 2,
16
19, 3,
27
14, 26,
28, 25
13, 3,
35
27, 3,
10
+
19, 35,
39
2, 19,
4, 35
28, 6,
35, 18
19, 10,
35, 38
28, 27,
3, 18
10
20, 10,
28, 18
3, 35,
10, 40
11, 2,
13
3
3, 27,
16, 40
22, 15,
33, 28
21, 39,
16, 22
27, 1,
4
12, 27
29, 10,
27
1, 35,
13
10, 4,
29, 15
19, 29,
39, 35
6, 10
35, 17,
14, 19
Du a ion o ac ion by
s a iona y objec 16
6, 27,
19, 16
1, 40,
35
35, 34,
38
39, 3,
35, 23 +
19, 18,
36, 40 16
27, 16,
18, 38 10
28, 20,
10, 16
3, 35,
31
34, 27,
6, 40
10, 26,
24
17, 1,
40, 33 22 35, 10 1 1 2
25, 34,
6, 35 1
20, 10,
16, 38
Tempe a u e 17
36,22,
6, 38
22, 35,
32
15, 19,
9
15, 19,
9
3, 35,
39, 18 35, 38
34, 39,
40, 18
35, 6,
4
2, 28,
36, 30
35, 10,
3, 21
35, 39,
19, 2
14, 22,
19, 32
1, 35,
32
10, 30,
22, 40
19, 13,
39
19, 18,
36, 40 +
32, 30,
21, 16
19, 15,
3, 17
2, 14,
17, 25
21, 17,
35, 38
21, 36,
29, 31
35, 28,
21, 18
3, 17,
30, 39
19, 35,
3, 10
32, 19,
24 24
22, 33,
35, 2
22, 35,
2, 24 26, 27 26, 27
4, 10,
16
2, 18,
27
2, 17,
16
3, 27,
35, 31
26, 2,
19, 16
15, 28,
35
Illumina ion in ensi y 18
19, 1,
32
2, 35,
32
19, 32,
16
19, 32,
26
2, 13,
10
10, 13,
19
26, 19,
6
32, 30
32, 3,
27
35, 19
2, 19,
6
32, 35,
19
+
32, 1,
19
32, 35,
1, 15
32
13, 16,
1, 6
13, 1 1, 6
19, 1,
26, 17
1, 19
11, 15,
32
3, 32 15, 19
35, 19,
32, 39
19, 35,
28, 26
28, 26,
19
15, 17,
13, 16
15, 1,
19
6, 32,
13
32, 15
2, 26,
10
2, 25,
16
Use o ene gy by mo ing
objec
19
12,18,
28,31
12, 28
15, 19,
25
35, 13,
18
8, 35,
35
16, 26,
21, 2
23, 14,
25
12, 2,
29
19, 13,
17, 24
5, 19,
9, 35
28, 35,
6, 18
-
19, 24,
3, 14
2, 15,
19
+ -
6, 19,
37, 18
12, 22,
15, 24
35, 24,
18, 5
35, 38,
19, 18
34, 23,
16, 18
19, 21,
11, 27
3, 1,
32
1, 35,
6, 27
2, 35,
6
28, 26,
30
19, 35
1, 15,
17, 28
15, 17,
13, 16
2, 29,
27, 28
35, 38 32, 2
12, 28,
35
Use o ene gy by s a iona y
objec 20
19, 9,
6, 27 36, 37
27, 4,
29, 18 35
19, 2,
35, 32 - +
28, 27,
18, 31
3, 35,
31
10, 36,
23
10, 2,
22, 37
19, 22,
18 1, 4
19, 35,
16, 25 1, 6
Powe 21
8, 36,
38, 31
19, 26,
17, 27
1, 10,
35, 37
19, 38
17, 32,
13, 38
35, 6,
38
30, 6,
25
15, 35,
2
26, 2,
36, 35
22, 10,
35
29, 14,
2, 40
35, 32,
15, 31
26, 10,
28
19, 35,
10, 38
16
2, 14,
17, 25
16, 6,
19
16, 6,
19, 37
+
10, 35,
38
28, 27,
18, 38
10, 19
35, 20,
10, 6
4, 34,
19
19, 24,
26, 31
32, 15,
2
32, 2
19, 22,
31, 2
2, 35,
18
26, 10,
34
26, 35,
10
35, 2,
10, 34
19, 17,
34
20, 19,
30, 34
19, 35,
16
28, 2,
17
28, 35,
34
Loss o Ene gy 22
15, 6,
19, 28
19, 6,
18, 9
7, 2, 6,
13
6, 38,
7
15, 26,
17, 30
17, 7,
30, 18
7, 18,
23
7
16, 35,
38
36, 38
14, 2,
39, 6
26
19, 38,
7
1, 13,
32, 15
3, 38 +
35, 27,
2, 37
19, 10
10, 18,
32, 7
7, 18,
25
11, 10,
35
32
21, 22,
35, 2
21, 35,
2, 22
35, 32,
1
2, 19 7, 23
35, 3,
15, 23
2
28, 10,
29, 35
Loss o subs ance 23
35, 6,
23, 40
35, 6,
22, 32
14, 29,
10, 39
10,
28,24
35, 2,
10, 31
10, 18,
39, 31
1, 29,
30, 36
3, 39,
18, 31
10, 13,
28, 38
14, 15,
18, 40
3, 36,
37, 10
29, 35,
3, 5
2, 14,
30, 40
35, 28,
31, 40
28, 27,
3, 18
27, 16,
18, 38
21, 36,
39, 31
1, 6,
13
35, 18,
24, 5
28, 27,
12, 31
28, 27,
18, 38
35, 27,
2, 31 +
15, 18,
35, 10
6, 3,
10, 24
10, 29,
39, 35
16, 34,
31, 28
35, 10,
24, 31
33, 22,
30, 40
10, 1,
34, 29
15, 34,
33
32, 28,
2, 24
2, 35,
34, 27
15, 10,
2
35, 10,
28, 24
35, 18,
10, 13
35, 10,
18
28, 35,
10, 23
Loss o In o ma ion 24
10, 24,
35
10, 35,
5
1, 26 26 30, 26 30, 16 2, 22 26, 32 10 10 19 10, 19 19, 10 +
24, 26,
28, 32
24, 28,
35
10, 28,
23
22, 10,
1
10, 21,
22
32 27, 22 35, 33 35
13, 23,
15
Loss o Time 25
10, 20,
37, 35
10, 20,
26, 5
15, 2,
29
30, 24,
14, 5
26, 4,
5, 16
10, 35,
17, 4
2, 5,
34, 10
35, 16,
32, 18
10, 37,
36,5
37,
36,4
4, 10,
34, 17
35, 3,
22, 5
29, 3,
28, 18
20, 10,
28, 18
28, 20,
10, 16
35, 29,
21, 18
1, 19,
26, 17
35, 38,
19, 18
1
35, 20,
10, 6
10, 5,
18, 32
35, 18,
10, 39
24, 26,
28, 32
+
35, 38,
18, 16
10, 30,
4
24, 34,
28, 32
24, 26,
28, 18
35, 18,
34
35, 22,
18, 39
35, 28,
34, 4
4, 28,
10, 34
32, 1,
10
35, 28 6, 29
18, 28,
32, 10
24, 28,
35, 30
Quan i y o subs ance/ he
ma e 26
35, 6,
18, 31
27, 26,
18, 35
29, 14,
35, 18
15, 14,
29
2, 18,
40, 4
15, 20,
29
35, 29,
34, 28
35, 14,
3
10, 36,
14, 3 35, 14
15, 2,
17, 40
14, 35,
34, 10
3, 35,
10, 40
3, 35,
31
3, 17,
39
34, 29,
16, 18
3, 35,
31 35
7, 18,
25
6, 3,
10, 24
24, 28,
35
35, 38,
18, 16 +
18, 3,
28, 40
13, 2,
28 33, 30
35, 33,
29, 31
3, 35,
40, 39
29, 1,
35, 27
35, 29,
25, 10
2, 32,
10, 25
15, 3,
29
3, 13,
27, 10
3, 27,
29, 18 8, 35
13, 29,
3, 27
Reliabili y 27
3, 8,
10, 40
3, 10,
8, 28
15, 9,
14, 4
15, 29,
28, 11
17, 10,
14, 16
32, 35,
40, 4
3, 10,
14, 24
2, 35,
24
21, 35,
11, 28
8, 28,
10, 3
10, 24,
35, 19
35, 1,
16, 11
11, 28
2, 35,
3, 25
34, 27,
6, 40
3, 35,
10
11, 32,
13
21, 11,
27, 19
36, 23
21, 11,
26, 31
10, 11,
35
10, 35,
29, 39
10, 28
10, 30,
4
21, 28,
40, 3
+
32, 3,
11, 23
11, 32,
1
27, 35,
2, 40
35, 2,
40, 26
27, 17,
40
1, 11
13, 35,
8, 24
13, 35,
1
27, 40,
28
11, 13,
27
1, 35,
29, 38
Measu emen accu acy 28
32, 35,
26, 28
28, 35,
25, 26
28, 26,
5, 16
32, 28,
3, 16
26, 28,
32, 3
26, 28,
32, 3
32, 13,
6
28, 13,
32, 24
32, 2
6, 28,
32
6, 28,
32
32, 35,
13
28, 6,
32
28, 6,
32
10, 26,
24
6, 19,
28, 24
6, 1,
32
3, 6,
32
3, 6,
32
26, 32,
27
10, 16,
31, 28
24, 34,
28, 32
2, 6,
32
5, 11,
1, 23
+
28, 24,
22, 26
3, 33,
39, 10
6, 35,
25, 18
1, 13,
17, 34
1, 32,
13, 11
13, 35,
2
27, 35,
10, 34
26, 24,
32, 28
28, 2,
10, 34
10, 34,
28, 32
Manu ac u ing p ecision 29
28, 32,
13, 18
28, 35,
27, 9
10, 28,
29, 37
2, 32,
10
28, 33,
29, 32
2, 29,
18, 36
32, 23,
2
25, 10,
35
10, 28,
32
28, 19,
34, 36 3, 35
32, 30,
40 30, 18 3, 27
3, 27,
40 19, 26 3, 32 32, 2 32, 2
13, 32,
2
35, 31,
10, 24
32, 26,
28, 18 32, 30
11, 32,
1+
26, 28,
10, 36
4, 17,
34, 26
1, 32,
35, 23 25, 10
26, 2,
18
26, 28,
18, 23
10, 18,
32, 39
Objec -a ec ed ha m ul
ac o s
30
22, 21,
27, 39
2, 22,
13, 24
17, 1,
39, 4
1, 18
22, 1,
33, 28
27, 2,
39, 35
22, 23,
37, 35
34, 39,
19, 27
21, 22,
35, 28
13, 35,
39, 18
22, 2,
37
22, 1,
3, 35
35, 24,
30, 18
18, 35,
37, 1
22, 15,
33, 28
17, 1,
40, 33
22, 33,
35, 2
1, 19,
32, 13
1, 24,
6, 27
10, 2,
22, 37
19, 22,
31, 2
21, 22,
35, 2
33, 22,
19, 40
22, 10,
2
35, 18,
34
35, 33,
29, 31
27, 24,
2, 40
28, 33,
23, 26
26, 28,
10, 18
+
24, 35,
2
2, 25,
28, 39
35, 10,
2
35, 11,
22, 31
22, 19,
29, 40
22, 19,
29, 40
33, 3,
34
22, 35,
13, 24
Objec -gene a ed ha m ul
ac o s
31
19, 22,
15, 39
35, 22,
1, 39
17, 15,
16, 22
17, 2,
18, 39
22, 1,
40
17, 2,
40
30, 18,
35, 4
35, 28,
3, 23
35, 28,
1, 40
2, 33,
27, 18
35, 1
35, 40,
27, 39
15, 35,
22, 2
15, 22,
33, 31
21, 39,
16, 22
22, 35,
2, 24
19, 24,
39, 32
2, 35,
6
19, 22,
18
2, 35,
18
21, 35,
2, 22
10, 1,
34
10, 21,
29
1, 22
3, 24,
39, 1
24, 2,
40, 39
3, 33,
26
4, 17,
34, 26
+
19, 1,
31
2, 21,
27, 1
2
22, 35,
18, 39
Ease o manu ac u e 32
28, 29,
15, 16
1, 27,
36, 13
1, 29,
13, 17
15, 17,
27
13, 1,
26, 12 16, 40
13, 29,
1, 40 35
35, 13,
8, 1 35, 12
35, 19,
1, 37
1, 28,
13, 27
11, 13,
1
1, 3,
10, 32
27, 1,
435, 16
27, 26,
18
28, 24,
27, 1
28, 26,
27, 1 1, 4
27, 1,
12, 24 19, 35
15, 34,
33
32, 24,
18, 16
35, 28,
34, 4
35, 23,
1, 24
1, 35,
12, 18 24, 2 +
2, 5,
13, 16
35, 1,
11, 9
2, 13,
15
27, 26,
1
6, 28,
11, 1
8, 28,
1
35, 1,
10, 28
Ease o ope a ion 33
25, 2,
13, 15
6, 13,
1, 25
1, 17,
13, 12
1, 17,
13, 16
18, 16,
15, 39
1, 16,
35, 15
4, 18,
39, 31
18, 13,
34
28, 13
35
2, 32,
12
15, 34,
29, 28
32, 35,
30
32, 40,
3, 28
29, 3,
8, 25
1, 16,
25
26, 27,
13
13, 17,
1, 24
1, 13,
24
35, 34,
2, 10
2, 19,
13
28, 32,
2, 24
4, 10,
27, 22
4, 28,
10, 34 12, 35
17, 27,
8, 40
25, 13,
2, 34
1, 32,
35, 23
2, 25,
28, 39
2, 5,
12 +
12, 26,
1, 32
15, 34,
1, 16
32, 26,
12, 17
1, 34,
12, 3
15, 1,
28
Ease o epai 34
2, 27
35, 11
2, 27,
35, 11
1, 28,
10, 25
3, 18,
31
15, 13,
32
16, 25
25, 2,
35, 11
1 34, 9
1, 11,
10
13
1, 13,
2, 4
2, 35
11, 1,
2, 9
11, 29,
28, 27
1 4, 10
15, 1,
13
15, 1,
28, 16
15, 10,
32, 2
15, 1,
32, 19
2, 35,
34, 27
32, 1,
10, 25
2, 28,
10, 25
11, 10,
1, 16
10, 2,
13
25, 10
35, 10,
2, 16
1, 35,
11, 10
1, 12,
26, 15
+
7, 1, 4,
16
35, 1,
13, 11
34, 35,
7, 13
1, 32,
10
Adap abili y o e sa ili y 35
1, 6,
15, 8
19, 15,
29, 16
35, 1,
29, 2
1, 35,
16
35, 30,
29, 7 15, 16
15, 35,
29
35, 10,
14
15, 17,
20 35, 16
15, 37,
1, 8
35, 30,
14
35, 3,
32, 6
13, 1,
35 2, 16
27, 2,
3, 35
6, 22,
26, 1
19, 35,
29, 13
19, 1,
29
18, 15,
1
15, 10,
2, 13 35, 28
3, 35,
15
35, 13,
8, 24
35, 5,
1, 10
35, 11,
32, 31
1, 13,
31
15, 34,
1, 16
1, 16,
7, 4 +
15, 29,
37, 28 1
27, 34,
35
35, 28,
6, 37
De ice complexi y 36
26, 30,
34, 36
2, 26,
35, 39
1, 19,
26, 24 26
14, 1,
13, 16 6, 36
34, 26,
61, 16
34, 10,
28 26, 16
19, 1,
35
29, 13,
28, 15
2, 22,
17, 19
2, 13,
28
10, 4,
28, 15
2, 17,
13
24, 17,
13
27, 2,
29, 28
20, 19,
30, 34
10, 35,
13, 2
35, 10,
28, 29 6, 29
13, 3,
27, 10
13, 35,
1
2, 26,
10, 34
26, 24,
32
22, 19,
29, 40 19, 1
27, 26,
1, 13
27, 9,
26, 24 1, 13
29, 15,
28, 37 +
15, 10,
37, 28
15, 1,
24
12, 17,
28
Di icul y o de ec ing and
measu ing
37
27, 26,
28, 13
6, 13,
28, 1
16, 17,
26, 24
26
2, 13,
18, 17
2, 39,
30, 16
29, 1,
4, 16
2, 18,
26, 31
3, 4,
16, 35
30, 28,
40, 19
35, 36,
37, 32
27, 13,
1, 39
11, 22,
39, 30
27, 3,
15, 28
19, 29,
39, 25
25, 34,
6, 35
3, 27,
35, 16
2, 24,
26
35, 38
19, 35,
16
18, 1,
16, 10
35, 3,
15, 19
1, 18,
10, 24
35, 33,
27, 22
18, 28,
32, 9
3, 27,
29, 18
27, 40,
28, 8
26, 24,
32, 28
22, 19,
29, 28
2, 21
5, 28,
11, 29
2, 5 12, 26 1, 15
15, 10,
37, 28
+ 34, 21 35, 18
Ex en o au oma ion 38
28, 26,
18, 35
28, 26,
35, 10
14, 13,
17, 28
23
17, 14,
13
35, 13,
16
28, 10 2, 35 13, 35
15, 32,
1, 13
18, 1 25, 13 6, 9
26, 2,
19
8, 32,
19
2, 32,
13
28, 2,
27
23, 28
35, 10,
18, 5
35, 33
24, 28,
35, 30
35, 13
11, 27,
32
28, 26,
10, 34
28, 26,
18, 23
2, 33 2
1, 26,
13
1, 12,
34, 3
1, 35,
13
27, 4,
1, 35
15, 24,
10
34, 27,
25
+
5, 12,
35, 26
P oduc i i y 39
35, 26,
24, 37
28, 27,
15, 3
18, 4,
28, 38
30, 7,
14, 26
10, 26,
34, 31
10, 35,
17, 7
2, 6,
34, 10
35, 37,
10, 2
28, 15,
10, 36
10, 37,
14
14, 10,
34, 40
35, 3,
22, 39
29, 28,
10, 18
35, 10,
2, 18
20, 10,
16, 38
35, 21,
28, 10
26, 17,
19, 1
35, 10,
38, 19 1
35, 20,
10
28, 10,
29, 35
28, 10,
35, 23
13, 15,
23 35, 38
1, 35,
10, 38
1, 10,
34, 28
18, 10,
32, 1
22, 35,
13, 24
35, 22,
18, 39
35, 28,
2, 24
1, 28,
7, 10
1, 32,
10, 25
1, 35,
28, 37
12, 17,
28, 24
35, 18,
27, 2
5, 12,
35, 26 +
Wo sening Fea u e
Imp o ing
Fea u e
APPENDICES
226
Appendix E: Lis o TRIZ 40 In en i e P inciples
Lis o 40 in en i e p inciples and 160 elemen a y ope a o s based on he ex ensi e
expe ience o TRIZ applica ion in indus ial companies [315].
Table A.13: Lis o TRIZ 40 In en i e P inciples.
No. In en i e P inciple In en i e Ope a o
1 Segmen a ion a) Di ide he objec in o independen objec s o pa s.
b) Design he objec o be sec ional o dismoun able.
c) Inc ease he objec ’s deg ee o agmen a ion o segmen a ion: educe size
up o g anules and powde , mic o- and nano-le el, molecules and a oms.
d) Di ide he unc ion o he objec o sys em in o independen sub- unc ions.
e) Di ide he p ocess s eps in o sub-s eps, make wo o mo e p ocess s eps
ins ead o one.
2 Lea ing ou /
T imming
a) Take ou o emo e he dis u bing pa s o subs ances om he sys em.
b) Check which sys em componen s, pa s o subs ances can be omi ed.
c) Take ou o emo e he dis u bing unc ions om he sys em. Check which
unc ions can be omi ed.
d) Take ou o emo e one o he p ocess s eps.
e) Ex ac o single ou he only one necessa y pa , subs ance, p ope y o
unc ion om he sys em.
3 Local quali y a) Change he uni o m s uc u e o p ope ies o an objec o a non-uni o m.
b) Change he uni o m s uc u e o p ope ies o su ounding medium
(ex e nal en i onmen ) o non-uni o m.
c) The a ious pa s o he objec should ul il di e en unc ions.
d) Each pa o he objec should unc ion unde condi ions which a e mos
sui able o i s ope a ion.
e) Di e en pa s o he objec can ha e opposi e p ope ies (e.g. one pa ho ,
ano he pa cold).
4 Asymme y a) Replace he symme ical shape o p ope y o an objec wi h one ha is
asymme ical.
b) I he objec is al eady asymme ical, inc ease i s deg ee o asymme y.
c) Con e he asymme ical shape o p ope y o an objec back o
symme ical one.
5 Combining a) Combine iden ical objec s in space o pe o m pa allel ope a ions.
b) Combine unc ions o p ocess s eps in ime o pe o m pa allel o
con iguous ope a ions.
c) Combine simila objec s wi h di e en cha ac e is ics, p ope ies o
pa ame e s.
d) Combine di e en objec s complemen ing each o he and enhancing
posi i e p ope ies.
e) Combine objec s wi h compe ing, al e na i e o opposing p ope ies (e.g.
caus ic and acid).
6 Uni e sali y a) Make a pa o objec uni e sal, pe o ming mul iple unc ions, and hus
elimina e unnecessa y objec s.
b) Make a p ocess uni e sal, o example sui able o di e en subs ances,
condi ions, ope a ions, e c.
7 Nes ing /
In eg a ion
a) Place an objec inside ano he one, which, in u n, is placed inside a hi d
objec and so on (Nes ed Doll p inciple).
b) An objec is passed h ough he ca i ies in ano he objec .
APPENDICES
227
No. In en i e P inciple In en i e Ope a o
c) Telescopic objec s o sys ems.
8 An i-weigh a) Compensa e he objec ’s weigh by coun e weigh .
b) Compensa e he objec ’s weigh by me ging i wi h ano he objec ha
p o ides a li ing o ce /buoyancy (e.g. loa ing objec o ho -ai balloon).
c) Compensa e he objec ’s weigh by in e ac ion wi h ano he medium (e.g.
by means o ae odynamic o hyd odynamic o ces).
d) Use g a i a ional o ce o cen i ugal o ce.
9 P io coun e ac ion
o ha m
a) I i is necessa y o pe o m an ac ion wi h bo h ha m ul and use ul e ec s,
b) coun e ac ion measu es agains ha m mus be aken in ad ance.
c) I he objec will be unde wo king s ess, c ea e be o ehand s ess in
di ec ion which is opposi e he undesi able wo king s ess. Thus, he
wo king s ess can be compensa ed.
d) I he objec will be exposed o high empe a u es, cool i be o ehand o
a oid o e hea ing.
e) Use igid cons uc ions, highly s able s uc u es (e.g. honeycomb) o
wi hs and ex eme ope a ing condi ions like high empe a u e, high
p essu e, high olume.
10 P io use ul ac ion ) Pe o m he equi ed ac ion o use ul unc ion in ad ance, ei he ully o
pa ially.
g) P e-a ange he objec s so hey can come in o ac ion a he mos con enien
posi ion and wi hou losing ime.
h) Pe o m pa o he p ocess s ep o ope a ion be o ehand.
11 P e en i e measu e
/ Cushion in
ad ance
a) Compensa e he low eliabili y o an objec by p epa ing eme gency
coun e measu es in ad ance.
b) Inc ease p ocess eliabili y by p epa ing eme gency coun e measu es in
ad ance.
12 Equipo en iali y a) Change he wo king condi ions so ha an objec doesn’ ha e o be aised
o lowe ed.
b) A oid changes o po en ial ene gy in he sys em.
c) A oid s ong luc ua ions o p ocess pa ame e , peaks and alleys in ene gy
d) consump ion, he mal shocks, e c.
13 In e sion a) Ins ead o cu en ly used ac ion, ca y ou he in e sed ac ion wi h opposi e
di ec ion o p ope ies (e.g. hea ing ins ead o cooling, downwa ds ins ead
upwa ds, e c).
b) Make mo ing pa s o he objec ixed, and he ixed pa s mo able.
c) Tu n he objec o p ocess upside down.
d) Pe o m he p ocess o i s phases in he e e sed o de . Change sequence o
ope a ions.
e) Change p ope ies o ac ion mode o he ex e nal en i onmen o he
opposi e (e.g. mo ing o ixed, high p essu e o acuum, e c).
14 Sphe ici y and
o a ion
a) Replace ec ilinea pa s o o ms wi h cu ed, ball-shaped o ms o
s uc u es.
b) Use balls, olle s, sphe es, domes o spi als. Apply cylind ical, conical o
mul i-conical con igu a ions.
c) P o ide o a y mo ion o pa s, subs ances o o ce ields. Replace a linea
mo ion o objec s o subs ances wi h o a ion.
d) Use o ex lows and swi ling mo ion o cyclonic sepa a ion, cooling o
hea ing.
e) Use cen i ugal and Co iolis o ces.
APPENDICES
228
No. In en i e P inciple In en i e Ope a o
15 Dynamism a) Make an objec , ex e nal en i onmen o p ocess adjus able o enable
op imal pe o mance pa ame e a each s age o ope a ion.
b) Di ide an objec in o elemen s whose posi ion changes ela i e o one
ano he . Make objec mo able and adap i e.
c) I a p ocess is igid o in lexible, make i adap i e.
d) Use adap i e and lexible elemen s like join s, sp ings, elas ome s, luids,
gases, magne s/elec omagne s.
e) Change s a ic o ce ields o mo able o dynamics ields, which change in
ime o in s uc u e.
16 Pa ial o excessi e
ac ion
a) I i is di icul o ob ain exac ly 100% o a desi ed e ec , hen ob ain
sligh ly mo e o sligh ly less. The p oblem may be conside ably easie o
sol e.
b) I i is di icul o ob ain he op imal o exac amoun o subs ance, apply an
excessi e amoun . Remo e su plus subs ance by using addi ional o ce o
ene gy ield.
c) I i is di icul o ob ain he op imal o exac ac ion ( o ce o ene gy ield),
apply an excessi e ac ion. Compensa e su plus ac ion by using p o ec i e
shield.
17 Shi o ano he
dimension
a) Change he s aigh line o a 2D o 3D cu e, o plane o m o mo emen
o he h ee-dimensional.
b) Reduce objec size o dimensions o mini-, mic o- o nano-le el.
c) Use a mul i-laye ed o mul i-s o ey s uc u e o objec s o p ocesses.
d) Til he objec , lay i on i s side, use e e sed side o in e nal su aces
(hollows).
e) Inc ease con ac a ea be ween objec s o subs ances om he con ac along
a line o on a su ace o in e ac ion in 3D-space.
18 Mechanical
ib a ion
a) Cause an objec o oscilla e o ib a e.
b) I oscilla ion al eady exis s, change, o inc ease i s equency (e en up o he
ul asonic).
c) Use he esonan equency o an objec and sel -oscilla ions.
d) Use piezo-elec ic ib a o s ins ead o mechanical ones.
e) Combine ul asonic oscilla ions wi h o he ields: ul asonic and
elec omagne ic ib a ions; ul asonic wi h hea sou ce; ul asonic wi h
capilla y e ec .
19 Pe iodic ac ion a) Replace a con inuous ac ion wi h a pe iodic o pulsed one.
b) I an ac ion is al eady pe iodic, change i s equency, ampli ude, and mean
alue.
c) Use pauses be ween impulses o pe o m addi ional ac ions. The
equencies o all pe iodic ac ions should be ma ched o in en ionally
misma ched.
d) A oid o use esonance. The equencies o he pe iodic ac ion should be
ma ched o in en ionally misma ched o he na u al equency o one o he
objec s.
e) Apply mu ually exclusi e pe iodic ac ions al e na ely. Sepa a e
con adic o y p ope ies in ime.
20 Con inui y o
use ul ac ion
a) Ca y on a p ocess con inuously (wi hou pauses).
b) All pa s o an objec o equipmen should ope a e a ull load.
c) Elimina e all idle and in e mi en ac ions o wo k.
21 Skipping / Rushing
h ough
a) Pe o m a p ocess, o indi idual s ages a e y high speed o skip
des uc ible o haza dous ope a ions.
b) Inc ease d ama ically he speed o powe in a p ocess ha may esul in
new use ul p ope ies o he sys em.
APPENDICES
229
No. In en i e P inciple In en i e Ope a o
22 Con e ing ha m
in o bene i
a) U ilize ha m ul ac o s o nega i e en i onmen al e ec s o ob ain a
posi i e e ec .
b) Remo e a ha m ul ac o by combining i wi h ano he ha m ul ac o .
c) Ampli y a ha m ul ac ion o such a deg ee ha i is no longe ha m ul.
23 Feedback and
au oma ion
a) In oduce eedback o imp o e a p ocess o ac ion.
b) I eedback al eady exis s, change i (e.g. i s magni ude o in luence).
c) Inc ease a deg ee o au oma ion and con ollabili y o he sys em, use
adap i e eedback con ol and a i icial in elligence.
d) U ilize in o ma ion and da a p ocessing.
24 Media o a) In oduce an in e media e objec o ans e o ca y ou an ac ion.
b) Me ge one objec empo a ily wi h ano he in e media e objec ha can be
easily emo ed.
c) Use an in e media y p ocess o p ocess s ep.
25 Sel -se ice / Use o
esou ces
a) Make he objec se e i sel and ca y ou supplemen a y and epai
ope a ions.
b) U ilize was e esou ces, ene gy, o subs ances.
c) Use a ailable en i onmen al esou ces: subs ances, ene gy, space,
in o ma ion, and da a.
26 Copying and
modelling
a) Use simple inexpensi e copies ins ead o una ailable, expensi e, agile
objec s.
b) Replace an objec o p ocess wi h i s op ical copies (g aphical images, h ee-
dimensional images, holog ams).
c) I isible op ical copies a e al eady used, mo e o in a ed, ul a iole , X- ay
copies, op ical o adio shadows.
d) Use digi al models and compu e simula ions.
e) Use i ual eali y, compu e augmen ed eali y, e c.
27 Disposabili y /
Cheap sho -li ing
objec s
a) Use cheap sho -li ing objec s o subs ances.
b) Replace an expensi e objec by a mul iple inexpensi e one, o going ce ain
quali ies (e.g. longe i y).
c) Use one-way disposable o empo a y objec s.
d) C ea e cheap sho -li ing objec s om a ailable esou ces, such as was e,
wa e , ai , en i onmen , e c.
28 Replacemen o he
mechanical
wo king
p inciple
a) Replace he mechanical wo king p inciple by elec ic, magne ic, o
elec omagne ic one.
b) Use op ical wo king p inciple (e.g. IR, UV, Lase , LED).
c) Use an acous ic o sound sys em (e.g. ul asonic, in asonic, e c).
d) Use he mal, chemical, ol ac o y (smell) o biological sys em.
e) Use elec omagne ic ields in conjunc ion wi h e omagne ic pa icles,
magne ic o elec o- heological luids.
29 Pneuma ic o
hyd aulic
cons uc ions
a) Use gas o liquid as wo king elemen s, o example gas and liquid lows,
ae o- and hyd os a ics o dynamics, hyd o- eac i e sys ems, e c.
b) Replace solid pa s by gas o liquid (e.g. in la able elemen s, ai cushion,
pa s illed wi h liquids unde p essu e).
c) Use nega i e p essu e, pa ial acuum, and acuum chambe s.
d) Use luidisa ion o powde s, dus s o g anula es in he ai low, o example
in he luidised bed.
e) Use luids and gases o hea and ene gy ans e : hea pipe, hea exchange ,
o ex coole ube, shock wa es, ca i a ion, e c.
APPENDICES
230
No. In en i e P inciple In en i e Ope a o
30 Flexible shells o
hin ilms
a) Replace adi ional cons uc ions wi h hose made o lexible shells o hin
ilms.
b) Isola e he objec o pa s om i s en i onmen using lexible shells o hin
ilms.
c) Use piezoelec ic oils.
d) Apply lexible b ushes o guiding, cleaning, ib a ion damping.
e) Use memb anes, memb ane ope a ions and p ocessing.
31 Po ous ma e ials a) Make an objec o i s su ace po ous, o add po ous elemen s (inse s,
co e s, e c). U ilize objec s wi h hollow spaces o ca i ies.
b) I an objec is al eady po ous, ill he po es wi h a use ul subs ance.
c) U ilize capilla y and mic o-capilla y e ec s in po ous ma e ials.
d) Use he ille in combina ion wi h physical e ec s (e.g. ul asound,
elec omagne ic ield, empe a u e di e ences, osmosis, e c).
e) Use s uc u ed po osi y, like honeycombed s uc u e, pipes o canals,
capilla ies on he molecula le el.
32 Changing colou a) Change he colou o an objec o i s ex e nal en i onmen .
b) Change he deg ee o anspa ency o an objec o i s ex e nal en i onmen .
c) Use colou ed addi i es o obse e an objec o p ocess which is di icul o
see.
d) I such addi i es a e al eady being used, add luminescen aces o o he
ace elemen s.
33 Homogenei y a) Make objec s in e ac ing wi h a gi en objec o he same ma e ial, o
ma e ial wi h iden ical p ope ies.
b) The in e ac ing objec s should ha e simila p ope ies such as size, weigh ,
empe a u e, op ical o magne ic p ope ies, e c.
c) Homogeneous o uni o m dis ibu ion o ma e ial o p ope ies
( empe a u e, concen a ion, iscosi y, e c).
34 Disca ding and
es o ing
a) Rejec o modi y (disca d, dissol e, e apo a e, e c) a pa o an objec a e
i has comple ed i s unc ion o become useless.
b) Res o e any pa o an objec which has become exhaus ed o deple ed
di ec ly in ope a ion.
c) Gene a e objec o ma e ial jus on ime and on si e, ha can be mo e
e icien and less expensi e.
35 T ans o ma ion o
he physical and
chemical p ope ies
a) Change an objec ’s agg ega e s a e (e.g. solid o liquid o liquid o gas - o
ice e sa).
b) Change he objec ’s concen a ion o consis ency.
c) Change o he ele an physical p ope ies o ope a ional condi ions
(p essu e, densi y, ha dness, iscosi y, conduc i i y, magne ism, e c),
sepa a ely o oge he .
d) Change he objec ’s empe a u e.
e) Change o he chemical p ope ies o ope a ional condi ions ( o mula ion,
pH, solubili y, e c), change p ocess chemis y.
36 Phase ansi ions a) Use phenomena accompanying he phase ansi ions o a subs ance (e.g.
he emission o abso p ion o hea ene gy, densi y o olume changes, e c).
b) Use he second-o de phase ansi ions: shape memo y o me als and
polyme s, ansi ion beyond he Cu ie poin in e omagne ic subs ances,
con e sion o a c ys alline s uc u e, e c.
APPENDICES
231
No. In en i e P inciple In en i e Ope a o
37 The mal expansion
and con ac ion
a) Use he mal expansion o con ac ion o ma e ials (solids, luids o gases).
b) Use cons uc ions made o mul iple ma e ials wi h di e en coe icien s o
he mal expansion (e.g. bi-me als).
c) Use hea sh inkable ma e ials (e.g. hea sh inkable ubing).
d) Use he mo-mechanical shape memo y o me als and polyme s.
38 S ong oxidan s a) Replace common ai wi h oxygen-en iched ai .
b) Replace oxygen-en iched ai wi h pu e oxygen.
c) Expose ai o oxygen o ionising adia ion, use ionized oxygen.
d) Raise he ozone le el. Replace ozonized (o ionized) oxygen wi h ozone.
e) Use o he s ong o ex eme oxidan s.
39 Ine en i onmen a) Replace he no mal en i onmen wi h an ine one.
b) Ca y ou he p ocess in ine a mosphe e o (e.g. helium o a gon).
c) Ca y ou he p ocess in a acuum.
d) Use ine , p o ec i e o an ioxidan coa ings o addi i es.
e) Use oams o oamed subs ances o p o ec o isola e objec s.
40 Composi e
ma e ials
a) Replace a homogeneous, uni o m ma e ial wi h a composi e one (e.g.
ca bon- ib e composi e, lamina es, e c).
b) Take ad an age o he aniso opic p ope ies o he composi e ma e ials,
like mechanical, elec ical, he mal.
c) Use addi i es o p o ide speci ic p ope ies o he composi es (e.g. i e
e a dan addi i es in polyme ma ix composi es).
d) Use ma e ials wi h composi e mic os uc u e, con ollable by ex e nal ield.
e) Use a composi ion o ma e ials in di e en agg ega e s a es (e.g. mix u e o
liquid and gas).
This page in en ionally le blank
239
PUBLICATIONS
The PhD p ocess equi es ac i ely dissemina ing he indings o he esea ch in he o m
o epo s, con e ence communica ions, pee - e iewed jou nal publica ions o books. In
his chap e , he main esea ch ou comes ela ed o he subjec o his hesis a e lis ed.
JOURNAL PAPERS
P. Ruiz-Minguela, D. R. Noble, V. Na a, S. Pennock, J. M. Blanco, H. Je ey. "Es ima ing
Fu u e Cos s o Eme ging Wa e Ene gy Technologies". Sus ainabili y, ol 15, nº 1, p. 215,
Dec. 2022. h ps://doi.o g/10.3390/su15010215
P. Ruiz-Minguela, J. Blanco, V. Na a, H. Je ey. “Technology-Agnos ic Assessmen o
Wa e Ene gy Sys em Capabili ies”. Ene gies, ol. 15, nº 7, p. 2624, Ap . 2022.
h ps://doi.o g/10.3390/en15072624
P. Ruiz-Minguela, V. Na a, J. Hodges y J. Blanco, “Re iew o Sys ems Enginee ing (SE)
Me hods and Thei Applica ion o Wa e Ene gy Technology De elopmen ”, Jou nal o
Ma ine Science and Enginee ing, ol. 8, nº 10, p. 823, Oc . 2020.
h ps://doi.o g/10.3390/jmse8100823
CONFERENCE PAPERS
P. Ruiz-Minguela, J. M. Blanco, V. Na a. “Success ul inno a ion s a egies o o e come
he echnical challenges in he de elopmen o wa e ene gy echnologies”. P oceedings o
he 15
h
Eu opean Wa e and Tidal Ene gy Con e ence, 3-7 Sep embe 2023, Bilbao (Spain)
– Publica ion pending.
P. Ruiz-Minguela, J. M. Blanco, V. Na a. “On he ele an , ealis ic and e ec i e c i e ia
o wa e ene gy echnology assessmen – a dialogue wi h EWTEC2019 pape ID 1426”.
P oceedings o he 14
h
Eu opean Wa e and Tidal Ene gy Con e ence, 5-9 Sep embe
2021, Plymou h (UK).
P. Ruiz-Minguela, J. M. Blanco, V. Na a. “No el Me hodology o Holis ic Assessmen o
Wa e Ene gy Design Op ions”. P oceedings o he 13 h Eu opean Wa e and Tidal Ene gy
Con e ence, 1-6 Sep embe 2019, Naples (I aly).
REPORTS AND BOOK CHAPTERS
P. Ruiz-Minguela, V. Na a, J. M. Blanco. “Ex e nal Fo ces In luencing he De elopmen
o Wa e Ene gy Technologies o Powe Ma ke s”. Zenodo: Gene a, Swi ze land, Feb.
2022. h ps://doi.o g/10.5281/zenodo.6168328
PUBLICATIONS
240
Hodges J., Hende son J., Ruedy L., Soede M., Webe J., Ruiz-Minguela P., Je ey H.,
Bannon E., Holland M., Maci e R., Hume D., Villa e J-L, Ramsey T., “An In e na ional
E alua ion and Guidance F amewo k o Ocean Ene gy Technology”, IEA-OES 2021.
h ps://www.ocean-ene gy-sys ems.o g/documen s/47763-e alua ion-guidance-ocean-
ene gy- echnologies2.pd
RESEARCH PROJECTS
SEETIP OCEAN: Suppo o SET Plan Implemen a ion Wo king G oup and Eu opean
Technology and Inno a ion Pla o m o Ocean Ene gy. EU Ho izon Eu ope, no
101075412, 2022-2025. h ps://co dis.eu opa.eu/p ojec /id/101075412
VALID: Ve i ica ion h ough Accele a ed es ing Leading o Imp o ed wa e ene gy
Designs. EU H2020, no 101006927, 2019-2021.
h ps://co dis.eu opa.eu/p ojec /id/101006927/ esul s
ETIP OCEAN: Eu opean Technology and Inno a ion Pla o m o Ocean Ene gy. EU
H2020, no 727483, 2019-2021. h ps://co dis.eu opa.eu/p ojec /id/727483/ esul s
DTOceanPlus: Ad anced Design Tools o Ocean Ene gy Sys ems Inno a ion,
De elopmen and Deploymen . EU H2020, no 785921, 2018-2021.
h ps://co dis.eu opa.eu/p ojec /id/785921/ esul s
OPERA: Open Sea Ope a ing Expe ience o Reduce Wa e Ene gy Cos . EU H2020, no
654444, 2016-2019. h ps://co dis.eu opa.eu/p ojec /id/654444/ esul s
J. Pablo Ruiz Minguela
A no el me hodology o he holis ic assessmen o wa e ene gy echnologies a ea ly design s ages
PhD Thesis, May 2023
Supe iso s: P o Jesús Ma ía Blanco Ilza be and D Vincenzo Na a
Uni e sidad del País Vasco / Euskal He iko Unibe si a ea
Ene gy Enginee ing Depa men
Plaza Ingenie o To es Que edo, 1
E-48013 Bilbao
TECNALIA, Basque Resea ch and Technology Alliance (BRTA)
O sho e Renewable Ene gy G oup
Ene gy, Clima e and U ban T ansi ion Uni
Pa que Cien í ico y Tecnológico de Bizkaia, As ondo Bidea, Edi icio 700
E-48160 De io
Open Access
This PhD hesis is dis ibu ed unde he e ms o he C ea i e Commons
A ibu ion-Sha eAlike 4.0 License (h ps://c ea i ecommons.o g/licenses/by-
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