T eball de Fi de Màs e
Màs e en Sis emes i Accionamen s Elèc ics
The Role o Renewable Ene gy and S o age
in Elec i ying T anspo a ion: A Case S udy
on Hyb id EV Cha ging In as uc u e
REPORT
Au ho : Hussein Mazeh
Supe iso : F ancisco Diaz Gonzalez
Call: Janua y 2025
Escola Tècnica Supe io
d’Enginye ia Indus ial de Ba celona
Pàg. 2 Repo
Resum
L'adopció accele ada de ehicles elèc ics (VE) eque eix el desen olupamen d'una
in aes uc u a d'es acions de cà ega de ehicles elèc ics (EVCS) e icien i sos enible.
Aques a esi abo da els desa iamen s que plan eja la in eg ació de les EVCS als
sis emes elèc ics, cen an -se en els impac es sob e la xa xa i les es a ègies de
mi igació. Els mè odes p incipals inclouen l'ús de sis emes o o ol aics (PV), sis emes
d'emmaga zema ge d'ene gia amb ba e ies (BESS) i il es ac ius de po ència pe
edui l'es ès a la xa xa i millo a l'es abili a del sis ema.
Es p esen a un manual ècnic exhaus iu que guia el disseny de sis emes PV, la
selecció i mun a ge de ba e ies i la se a in eg ació a les EVCS. Un es udi de cas
a alua sis escena is ope a ius, enin en comp e ince eses com la a iabili a de la
demanda, les ho es d'ope ació, la disponibili a de e eny i la o ça de la xa xa en el
pun de connexió comuna. Aques s escena is anali zen la iabili a de di e en s ni ells
de pene ació ene gè ica dels sis emes PV, BESS i la xa xa.
Les anàlisis econòmiques i ambien als des aquen la endibili a de cada escena i i
quan i iquen els bene icis en e mes de sos enibili a , com la educció d'emissions de
ca boni i els guanys en e iciència ene gè ica. Els esul a s demos en que in eg a
ecnologies d'ene gia eno able i emmaga zema ge po millo a signi ica i amen la
iabili a de les EVCS alho a que es edueix la dependència de la xa xa. L'es udi
conclou amb ecomanacions pe p olonga la ida ú il de les ba e ies i millo a el
endimen del sis ema a lla g e mini.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 3
Resumen
La acele ada adopción de ehículos eléc icos (VE) equie e el desa ollo de una
in aes uc u a de es aciones de ca ga de ehículos eléc icos (EVCS) e icien e y
sos enible. Es a esis abo da los desa íos plan eados po la in eg ación de las EVCS
en los sis emas eléc icos, cen ándose en los impac os sob e la ed y las es a egias
de mi igación. Los mé odos cla e incluyen el uso de sis emas o o ol aicos (PV),
sis emas de almacenamien o de ene gía con ba e ías (BESS) y il os ac i os de
po encia pa a educi el es és en la ed y mejo a la es abilidad del sis ema.
Se p esen a un manual écnico comple o que guía el diseño de sis emas PV, la
selección y ensamblaje de ba e ías, y su in eg ación en las EVCS. Un es udio de caso
e alúa seis escena ios ope a i os, eniendo en cuen a ince idumb es como la
a iabilidad de la demanda, las ho as de ope ación, la disponibilidad de e eno y la
o aleza de la ed en el pun o de conexión común. Es os escena ios analizan la
iabilidad de di e en es ni eles de pene ación ene gé ica de los sis emas PV, BESS y
la ed.
Los análisis económicos y medioambien ales des acan la en abilidad de cada
escena io y cuan i ican los bene icios en é minos de sos enibilidad, como la educción
de emisiones de ca bono y las mejo as en la e iciencia ene gé ica. Los esul ados
demues an que la in eg ación de ecnologías de ene gía eno able y almacenamien o
puede mejo a signi ica i amen e la iabilidad de las EVCS mien as se educe la
dependencia de la ed. El es udio concluye con ecomendaciones pa a ex ende la
ida ú il de las ba e ías y mejo a el endimien o del sis ema a la go plazo.
Pàg. 4 Repo
Abs ac
The accele a ing adop ion o elec ic ehicles (EVs) necessi a es he
de elopmen o e icien and sus ainable elec ic ehicle cha ging s a ion
(EVCS) in as uc u e. This hesis add esses he challenges posed by EVCS
in eg a ion in o powe sys ems, ocusing on g id impac s and mi iga ion
s a egies. Key me hods include he use o pho o ol aic (PV) sys ems, ba e y
ene gy s o age sys ems (BESS), and ac i e powe il e s o educe g id s ess
and imp o e sys em s abili y.
A comp ehensi e echnical handbook is p esen ed, guiding he design o PV
sys ems, he selec ion and assembly o ba e y packs, and hei in eg a ion in o
EVCS. A case s udy e alua es six ope a ional scena ios, accoun ing o
unce ain ies such as demand a iabili y, ope a ing hou s, land a ailabili y, and
g id s eng h a he poin o common coupling. These scena ios assess he
easibili y o di e en ene gy pene a ion le els om PV, BESS, and he g id.
Economic and en i onmen al analyses highligh he p o i abili y o each
scena io and quan i y he sus ainabili y bene i s, including ca bon emission
educ ions and ene gy e iciency gains. The indings demons a e ha
in eg a ing enewable ene gy and s o age echnologies can signi ican ly
enhance EVCS iabili y while educing g id dependence. The s udy concludes
wi h ecommenda ions o ex ending ba e y pack li espan o imp o e long- e m
sys em pe o mance.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 5
Con en s
RESUM _____________________________________________________ 2
RESUMEN __________________________________________________ 3
ABSTRACT _________________________________________________ 4
CONTENTS _________________________________________________ 5
ABBREVIATIONS AND SYMBOLS ______________________________ 8
LIST OF FIGURES ____________________________________________ 9
LIST OF TABLES ___________________________________________ 11
1. PREFACE _____________________________________________ 12
2. INTRODUCTION ________________________________________ 13
2.1. Mo i a ion ..................................................................................................... 13
2.2. P e equisi es ................................................................................................ 13
2.3. Objec i es .................................................................................................... 13
2.3.1. Gene al Objec i e ...........................................................................................13
2.3.2. Speci ic Objec i es ..........................................................................................14
3. SECTION I: THEORETICAL BACKGROUND _________________ 15
3.1. Global Ene gy Mix and GHG Emissions .................................................... 15
3.1.1. Key ini ia i es aimed a achie ing 2030 a ge s .............................................16
3.1.2. Key ini ia i es aimed a achie ing 2050 a ge s .............................................16
3.2. T anspo a ion and EV Adop ion ................................................................ 17
3.2.2. EU measu es ..................................................................................................17
3.2.3. EV Adop ion Wo ldwide [10] ...........................................................................18
3.2.4. Challenges acing EV adop ion in Eu ope .....................................................19
3.3. Desc ip ion o Elec ic Vehicle Cha ging S a ion (EVCS) .......................... 23
3.3.1. Desc ip ion o EVCS ca ego ies .....................................................................23
3.3.2. EVCS In as uc u e ........................................................................................25
3.3.3. Powe Flow Di ec ion: .....................................................................................26
3.3.4. Challenges in EVCS Planning ........................................................................26
3.4. Thesis Desc ip ion ....................................................................................... 26
3.5. P e ious Wo k ............................................................................................. 27
4. SECTION II: IMPACT OF EVCS ON GRID ____________________ 29
4.1. Load Impac On Ac i e Powe (P) .............................................................. 29
4.2. Impac On Reac i e Powe (Q) In The G id ............................................... 30
4.3. Vol age Sags (Unde ol age) ...................................................................... 30
Pàg. 6 Repo
4.4. Ha monics Dis o ions ................................................................................. 31
5. SECTION III: MITIGATION STRATEGIES ____________________ 34
5.1. Shun Ac i e Powe Fil e (SAPF) .............................................................. 34
5.1.1. Synch onous Re e ence F ame (SRF) Theo y ..............................................34
5.2. Pho o ol aic Ene gy In eg a ion .................................................................. 36
5.2.1. Ad an ages .....................................................................................................37
5.2.2. Challenges O In eg a ing PV in o he G id and EVCS .................................37
5.2.3. Impac o Tempe a u e on The Pe o mance o PV Modules .......................37
5.3. Ba e y Ene gy S o age Sys em (BESS) .................................................... 38
5.3.1. Ad an ages o In eg a ing BESS wi h PV In o The G id ...............................38
6. SECTION IV: TECHNICAL HANDBOOKS ____________________ 40
6.1. Hyb id Pho o ol aic Sys em Handbook ...................................................... 40
6.1.1. De e mining Powe Consump ion Demands .................................................40
6.1.2. Sizing PV Modules ..........................................................................................40
6.1.3. In e e Sizing .................................................................................................41
6.1.4. Ba e y Pack Sizing .........................................................................................42
6.2. Ba e y Ene gy Sys em Handbook ............................................................. 42
6.2.1. Unde s anding Ba e y Speci ica ions ............................................................42
6.2.2. Compa ison o Ba e y Technologies .............................................................44
6.3. Ba e y Assembly Handbook ...................................................................... 48
6.3.1. De ining he Ba e y Pack Requi emen s .......................................................48
6.3.2. Cell Con igu a ion ...........................................................................................49
6.3.3. The mal Design ...............................................................................................50
6.3.4. Ba e y Managemen Sys em (BMS) .............................................................50
6.3.5. Elec ical Connec ions ....................................................................................51
6.3.6. Enclosu e Design ............................................................................................52
7. SECTION V: CASE STUDY _______________________________ 53
7.1. Ca ego y A ................................................................................................... 55
7.2. Ca ego y B ................................................................................................... 57
7.3. Hyb id PV Sys em Design........................................................................... 60
7.4. BESS Design ............................................................................................... 63
8. SECTION VI: ECONOMIC AND ENVIRONMENTAL ANALYSIS __ 66
8.1. Cos Analysis o EVCS Ac oss he Six Scena ios .................................... 66
8.1.1. PV Sys em ......................................................................................................66
8.1.2. G id In as uc u e ...........................................................................................67
8.1.3. BESS ...............................................................................................................68
8.2. Compa isons and Conclusions ................................................................... 71
9. SECTION VII: FUTURE WORK AND ENHANCEMENTS ________ 75
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 7
9.1. Recommenda ions Fo Op imal Bess Pe o mance .................................. 75
9.2. Rela ing o EVCS Scalabili y ....................................................................... 76
10. SECTION VIII: PLANNING AND GENDER EQUALITY
ASSESSMENT __________________________________________ 77
10.1. Planning Assessmen .................................................................................. 77
10.2. Gende Pe spec i e..................................................................................... 77
11. ACKNOWLEDGMENTS __________________________________ 78
12. BIBLIOGRAPHY ________________________________________ 79
Pàg. 8 Repo
Abb e ia ions and Symbols
EVCS - Elec ic Vehicle Cha ging S a ion.
BESS - Ba e y Ene gy S o age Sys em.
PV – Pho o ol aic Ene gy
DC: Di ec Cu en
AC: Al e na ing Cu en
V2G: Vehicle- o-G id
ROCOF: Ra e o Change o F equency
VoC: Open Ci cui Vol age
ISC: Sho Ci cui Cu en
SoC: S a e o Cha ge
DoD: Dep h o Discha ge
PCC: Poin o Common Coupling
EU: Eu opean Union
ICE: In e nal Combus ion Engine
BEV: Ba e y Elec ic Vehicle
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 9
Lis o Figu es
Figu e 1 illus a es Global P ima y Ene gy Consump ion in 2023. [2] ............................... 15
Figu e 2 shows GHG Emissions by Sec o in he EU [3] ................................................... 16
Figu e 3 shows he G ow h o EV Sales in he EU. [8] ....................................................... 17
Figu e 4 Expansion o EV Cha ging Poin in he EU. [9] .................................................... 18
Figu e 5 Wo ldwide G ow h in he Numbe o EVs [11] ...................................................... 19
Figu e 6 Compa ison o BEV G ow h s Cha ging In as uc u e [12] ............................... 20
Figu e 7 Dis ibu ion o EV Cha ging Poin s Ac oss he EU ............................................... 20
Figu e 8 Cos Compa ison o ICE and BEV Componen s [14] .......................................... 21
Figu e 9 Impac o Speed and Tempe a u e on EV Range [16]......................................... 22
Figu e 10 EV Sales in he Fi s Hal o 2023 and 2024 [18] ............................................... 23
Figu e 11 EVCS Ca ego ies ................................................................................................ 24
Figu e 12 F equency Con ainmen Measu es .................................................................... 29
Figu e 13 Vol age Sag and Vol age Swell Phenomena ..................................................... 31
Figu e 14 Fundamen al Sine Wa e and Associa ed Ha monics ....................................... 32
Figu e 15 SRF Con olle ..................................................................................................... 36
Figu e 16 PV Powe Ou pu on Sunny s Cloudy Day ....................................................... 37
Figu e 17 Peak Sha ing Theo y .......................................................................................... 39
Figu e 18 Elec ical Speci ica ions o EVESCO Cha ge ................................................... 54
Figu e 19 Elec ical Speci ica ions o Longi PV Panel ........................................................ 61
Figu e 20 Technical Speci ica ions o Huawei In e e [41] ............................................... 62
Figu e 21 Elec ical Speci ica ions o CALB Ba e y Cell .................................................... 63
Figu e 22 Technical Speci ica ions o KACO In e e ........................................................ 64
Figu e 23 Technical Speci ica ions o NUVG5 BMS........................................................... 65
Pàg. 16 Repo
Figu e 2 shows GHG Emissions by Sec o in he EU [3]
To educe g eenhouse gas (GHG) emissions by 2030 and 2050, Eu ope has ou lined
se e al key measu es unde he Eu opean G een Deal and ela ed clima e policies. These
include: [4]
3.1.1. Key ini ia i es aimed a achie ing 2030 a ge s
Ca bon p icing: Following he 2023 e ision o he ETS Di ec i e , he EU
ETS cap is se o b ing emissions down by 62% by 2030 compa ed o 2005 le els.
To achie e his, he educ ion ac o has been inc eased o 4.3% pe yea o e he
pe iod 2024-2027 and o 4.4% pe yea om 2028.
Renewable Ene gy Expansion: Se ing a a ge o enewable ene gy o accoun
o a leas 42.5% o he ene gy mix, wi h ambi ious goals o sola , wind, and
g een hyd ogen deploymen .
Ze o-Emission Vehicles: Phasing ou in e nal combus ion engine ehicles by
2035 and p omo ing elec ic ehicles (EVs) h ough incen i es and in as uc u e
expansion.
Ene gy E iciency: Manda ing ene gy e iciency imp o emen s in buildings,
appliances, and indus ies o cu o e all ene gy consump ion by 13% compa ed o
2020 le els.
3.1.2. Key ini ia i es aimed a achie ing 2050 a ge s
Clima e Neu ali y: Achie ing ne -ze o GHG emissions by balancing esidual
emissions wi h ca bon cap u e and s o age (CCS) echnologies.
Ene gy T ansi ion: Phasing ou ossil uels en i ely and eplacing hem wi h
enewable and low-ca bon ene gy sou ces, including signi ican in es men in
hyd ogen echnologies.
Digi al and Sma Solu ions: Le e aging AI, IoT, and sma g ids o op imize
ene gy use and imp o e e iciencies in anspo and u ban planning.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 17
3.2. T anspo a ion and EV Adop ion
3.2.2. EU measu es
The EU has manda ed ha all new ca s and ans sold in he EU mus be ze o-emission by
2035. This is aligned wi h he Eu opean G een Deal and he “Fi o 55” package, [5], which
aims o a 55% educ ion in g eenhouse gas (GHG) emissions by 2030 and ull clima e
neu ali y by 2050.
Also, Signi ican in es men s a e being made o expand he EV cha ging in as uc u e. The
EU unded o e €424 million o p ojec s deploying EV cha ging poin s and hyd ogen
e ueling s a ions as pa o he Al e na i e Fuels In as uc u e Facili y (AFIF). By 2023, he
EU had ins alled o e 630,000 public cha ging s a ions, wi h a manda e o s a ions e e y
60 km along majo anspo ou es by 2025. [6]
In addi ion, Membe s a es a e o e ing subsidies, ax bene i s, and incen i es o
pu chasing EVs and ins alling p i a e cha ging in as uc u e. Fo example, Spain unde he
MOVES III p og am, [7], p o ides g an s o up o €9,000 o he pu chase o a ca o
comme cial ehicle wi h an ECO o ZERO emissions label. Addi ionally, i subsidizes up o
80% o he cos o ins alling a linked cha ging poin o elec ic ehicles.
The EU suppo s ad ancemen s in ba e y echnology and sus ainable sou cing o aw
ma e ials. New ules p omo e ecycling and he de elopmen o ba e ies wi h educed
en i onmen al impac .
Following such incen i es and people’s g owing awa eness abou clean ene gy, global
sales o EVs ha e con inued o ise signi ican ly.
Figu e 3 shows he G ow h o EV Sales in he EU. [8]
Pàg. 18 Repo
Figu e 4 Expansion o EV Cha ging Poin in he EU. [9]
3.2.3. EV Adop ion Wo ldwide [10]
China: Leads global adop ion wi h an EV sha e o a ound 45% in 2024, p opelled by
ex ensi e domes ic manu ac u ing, lowe cos s, and incen i es. This ep esen s he la ges
EV ma ke globally, con ibu ing o o e 60% o all EV sales.
Uni ed S a es (US): EV adop ion has eached 11% in 2024, boos ed by incen i es om
he In la ion Reduc ion Ac (IRA) and g owing ma ke compe i ion. Despi e his g ow h, he
US lags behind Eu ope and China in e ms o EV ma ke sha e.
Eme ging Ma ke s: Adop ion a es in coun ies like India, B azil, and Sou heas Asia
emain low bu a e imp o ing due o local manu ac u ing incen i es and he a ailabili y o
a o dable EV models. Fo example, India’s EV ma ke sha e s ands a 2%, while B azil’s
is 3%.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 19
Figu e 5 Wo ldwide G ow h in he Numbe o EVs [11]
3.2.4. Challenges acing EV adop ion in Eu ope
Insu icien Cha ging In as uc u e
While Eu ope has made signi ican p og ess, u al and emo e a eas s ill lack adequa e
cha ging s a ions. The a io o cha ge s o EVs is below he EU's a ge s in many coun ies.
O e he pas se en yea s, EV sales in Eu ope g ew h ee imes as e han cha ging poin
ins alla ion.
Pàg. 20 Repo
Figu e 6 Compa ison o BEV G ow h s Cha ging In as uc u e [12]
On op o ha , 75% o all cha ging poin s a e loca ed in jus 4 Eu opean coun ies. [13]
Figu e 7 Dis ibu ion o EV Cha ging Poin s Ac oss he EU
High Up on Cos s
EVs, pa icula ly hose wi h longe anges, emain mo e expensi e han con en ional
in e nal combus ion engine (ICE) ehicles despi e subsidies. Ba e y cos s, al hough
declining, s ill con ibu e o highe ehicle p ices.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 21
Figu e 8 Cos Compa ison o ICE and BEV Componen s [14]
G id Capaci y and Reliabili y
The ise in EV usage demands signi ican upg ades o elec ici y g ids. Coun ies ace
challenges ensu ing g id s abili y and accommoda ing peak loads om cha ging s a ions.
Cha ging an inc easing numbe o EVs globally will equi e mo e elec ici y, and he sha e
o EVs in o al elec ici y consump ion is expec ed o inc ease signi ican ly as a esul . In
2023, he global EV lee consumed abou 130 TWh o elec ici y – oughly he same as
No way’s o al elec ici y demand in he same yea . [15]
Deploymen o EV cha ge s should be coo dina ed wi h powe g id de elopmen s o ensu e
ha new connec ions a e consis en wi h he wide g id-planning ho izon. When no
managed app op ia ely, i may p esen challenges o he elec ici y g id, like luc ua ions in
powe quali y o supply-demand imbalances.
Range Anxie y
Conce ns abou he limi ed ange o EVs and he a ailabili y o as -cha ging s a ions de e
po en ial buye s, especially hose in colde clima es whe e ba e y pe o mance declines.
Pàg. 22 Repo
Figu e 9 Impac o Speed and Tempe a u e on EV Range [16]
F om a echnical pe spec i e, as he empe a u e dec eases, he elec ochemical
eac ions wi hin a ba e y slow down, educing i s abili y o deli e cu en e icien ly.
Addi ionally, highe speeds inc ease he ae odynamic d ag o ce ac ing agains he
mo ion o he ehicle, he eby consuming mo e ene gy.
As illus a ed in he e e enced igu e, an elec ic sedan achie es an op imal ange o
app oxima ely 400 miles a an ambien empe a u e o 20°C. Howe e , a lowe
empe a u es, such as 0°C, his ange signi ican ly d ops o a ound 250 miles.
Fu he mo e, ope a ing he ehicle a high speeds, such as he legal maximum o 120
km/h, educes he ange u he o app oxima ely 200 miles due o inc eased ene gy
demand.
Phase-Ou o Incen i es
The phase-ou o pu chase incen i es o EVs in Eu ope p esen s an addi ional challenge
o adop ion. Al hough subsidies ha e played a c ucial ole in boos ing EV sales, some
coun ies a e g adually educing o elimina ing hese bene i s. [17]
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 23
Figu e 10 EV Sales in he Fi s Hal o 2023 and 2024 [18]
3.3. Desc ip ion o Elec ic Vehicle Cha ging S a ion (EVCS)
3.3.1. Desc ip ion o EVCS ca ego ies
EVCSs can be classi ied in o b oad ca ego ies based on powe le els and ans e
p o ocols, physical appea ance and in as uc u e, mobili y, and powe low di ec ion. Fig. 2
p o ides an o e iew o EVCS ca ego ies.
Pàg. 24 Repo
Figu e 11 EVCS Ca ego ies
Depending on he powe ans e p o ocol, EV cha ge s can be o wo ypes: conduc i e o
plug-in; and induc i e o wi eless. [19]
1) CONDUCTIVE OR PLUG-IN CHARGERS:
The e m conduc i e o plug-in cha ge gene ally e e s o a de ice ha acili a es
powe ans e and cha ges he ehicle’s ba e y by plugging i in o an elec ical
ou le .
They ha e he highes sha e in he EV ma ke .
Can be classi ied as al e na ing cu en (AC) cha ging and di ec cu en (DC)
cha ging.
EV cha ge s can also be classi ied as slow cha ge s (Le el I), medium cha ge s
(Le el II), and ul a- as cha ge s (Le el III).
A slow cha ge akes a ound 10 o 20 hou s, medium cha ge s may ake a ound 3
o 4 hou s, and supe - as cha ge s may ake 20 o 30 minu es o cha ge a ba e y
om 20 o 80% based on he ba e y capaci y.
The Socie y o Au omo i e Enginee s (SAE), Cha ge de Mo e (CHAdeMO), Tesla
Inc., and he In e na ional Elec o echnical Commission (IEC) ha e es ablished
s anda ds o EV cha ge s.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 25
Table 1 Powe Le els Based on Di e en S anda ds
2) INDUCTIVE OR WIRELESS CHARGERS:
Based on induc i e cha ging, which is basically wo en i ies wi h he same
equency exchange ene gy using esonance, which ope a es in he nea - ield
a ea o he an enna ha is non- adia i e.
The e a e 3.3 kW and 7.2 kW e sions o wi eless EV cha ge .
Faces challenges, such as powe ans e a e, cha ging ime, and loss o ene gy.
3.3.2. EVCS In as uc u e
We can b oadly ca ego ize EVCS in as uc u e in o h ee g oups: dis ibu ed cha ging
s a ions, ne wo ked as cha ging s a ions, and ba e y swapping s a ions.
1) Dis ibu ed cha ging s a ions:
A e cha ging s a ions dispe sed ac oss homes, malls, ai po s, bus/ ain s a ions,
axi s ands, business cen e s, and so on.
Le el-I o le el-II cha ge s a e mainly used in hese s a ions.
2) Ne wo k as cha ging s a ion:
Ope a ed by he go e nmen , p i a e companies, o a ne wo k o ope a o s.
P o ide as and con enien cha ging se ices o EVs.
3) Ba e y swapping s a ion (BSS):
The unde lying p inciple o BSS is ha EVs will a i e a he BSS, eplace hei
exhaus ed ba e y wi h a ully cha ged one, and depa he s a ion in a ma e o
minu es.
In 2021, Shanghai, China ins alled 1,000 BSS, enabling mo e han 100,000
ehicles o exchange hei deple ed ba e ies. [20]
Pàg. 32 Repo
Figu e 14 Fundamen al Sine Wa e and Associa ed Ha monics
Each ha monic has:
I s own equency (highe han he undamen al).
A speci ic ampli ude (smalle han he undamen al o mos p ac ical cases).
A phase shi ela i e o he undamen al wa e.
Ha monics in AC powe sys ems esul om nonlinea loads ha dis o he sinusoidal
wa e o m. In p ac ice, odd ha monics a e much mo e dominan , while e en ha monics a e
o en negligible o absen due o he ollowing eason:
In a balanced h ee-phase sys em, he e en ha monics cancel each o he ou due
o he phase ela ionship be ween he h ee phases.
𝐅(𝐭)= −𝐅(𝐭+𝐓
𝟐)
Eq 1
(whe e T is he undamen al pe iod), e en ha monics a e ze o, lea ing only odd ha monics.
Howe e , e en ha monics (2nd, 4 h, 6 h, e c.) can occu in aul y sys ems o due o
asymme ical dis o ions, such as unbalanced loads, unsymme ical ec i ie s, o damaged
ans o me s.
The p esence o signi ican e en ha monics o en signals a p oblem, such as:
Vol age imbalance.
Asymme y in load cu en .
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 33
Sa u a ion o magne ic co es in ans o me s.
In a powe sys em, impedance inc eases wi h equency. Highe ha monics ace highe
impedance, which na u ally limi s hei ampli udes. The lowe -o de ha monics (3 d) has
highe ampli udes, while highe -o de ha monics (5 h, 7 h, e c.) end o ha e p og essi ely
smalle ampli udes.
The esul an wa e o m is o med by poin -by-poin summa ion o he ins an aneous alues
o he undamen al wa e and i s ha monic componen s a each ime s ep.
Ma hema ically, i we conside he sine wa e illus a ed in Fig. 14 wi h ha monics up o he
7 h o de :
𝐯(𝐭)=𝐀𝟏𝐬𝐢𝐧𝛚𝐭+𝐀𝟑𝐬𝐢𝐧(𝟑𝛚𝐭+𝛟𝟑)+ 𝐀𝟓𝐬𝐢𝐧(𝟓𝛚𝐭+𝛟𝟓)
+𝐀𝟕𝐬𝐢𝐧(𝟕𝛚𝐭+𝛟𝟕)
Eq 2
Whe e:
A1, A3, A5, A7: Ampli udes o he undamen al, 3 d, 5 h and 7 h ha monics.
Omega ω: Angula equency o he undamen al wa e (ω=2π ).
ϕ3, ϕ5 and ϕ7 : Phase angles o he 3 d, 5 h and 7 h ha monics.
Ha monic dis o ions a e quan i ied using To al Ha monic Dis o ion (THD), a key pa ame e
o assessing powe quali y. G id s anda ds ypically limi THD o ensu e s able ope a ion.
Acco ding o he IEEE s anda d 519 s a ed ha o main ain powe quali y, o al ha monics
dis o ion (THD) alue should be below 5% o up o 69 kV powe ne wo k. [32]
𝐓𝐇𝐃=√ (𝐕𝟑)𝟐+(𝐕𝟓)𝟐+⋯+(𝐕𝐧)𝟐
𝐕𝟏 × 𝟏𝟎𝟎
Eq 3
Whe e:
V1 is he RMS alue o he undamen al equency componen (1s ha monic).
Vn a e he RMS alues o he ha monic componen s (e.g., 3 d, 5 h, …. , n h).
n ep esen s he o de o he ha monic (e.g., 3 d, 5 h, 7 h).
Pàg. 34 Repo
5. Sec ion III: Mi iga ion S a egies
In his sec ion, I will discuss he e ec i e s a egies o o e come he challenges associa ed
wi h EV cha ging in as uc u e. I aim o o e insigh s in o op imizing EVCS deploymen o
enhanced accessibili y and e iciency.
5.1. Shun Ac i e Powe Fil e (SAPF)
A Shun Ac i e Powe Fil e (SAPF) is a powe elec onic de ice used o mi iga e powe
quali y issues in elec ical sys ems, such as:
Ha monics
Reac i e Powe .
Unbalanced Cu en s
SAPFs ac as dynamic compensa o s by injec ing compensa ing cu en s in o he g id,
e ec i ely cancelling ou unwan ed ha monics and eac i e cu en s.
Basic ope a ion o SAPF:
1. The SAPF measu es he load cu en s om a nonlinea load.
2. Using a con ol algo i hm, i ex ac s he ha monic and eac i e componen s o he
cu en .
3. A Vol age Sou ce In e e (VSI) gene a es compensa ing cu en s equal in
magni ude bu opposi e in phase o hese unwan ed componen s.
4. These compensa ing cu en s a e injec ed back in o he sys em a he PCC,
ensu ing he sou ce cu en becomes sinusoidal and balanced.
5.1.1. Synch onous Re e ence F ame (SRF) Theo y
The Synch onous Re e ence F ame (SRF) heo y is a widely used con ol me hod o
SAPFs. I ans o ms h ee-phase cu en s in o a o a ing e e ence ame, whe e he
analysis and il e ing o ha monics and eac i e powe become simple .
S eps in SRF:
1. T ans o ma ion o S a iona y α-β F ame (Cla ke T ans o ma ion):
The h ee-phase cu en s (Ia,Ib,Ic) a e i s con e ed o wo-phase cu en s (iα,iβ)
in he s a iona y e e ence ame.
Ma hema ically:
[𝐈𝛂
𝐈𝛃]=
[
𝟏 −(𝟏
𝟐) (𝟏
𝟐)
𝟎 (√𝟑
𝟐) −(√𝟑
𝟐)
]
[𝐈𝐚
𝐈𝐛
𝐈𝐜]
Eq 4
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 35
2. T ans o ma ion o Ro a ing D-Q F ame (Pa k T ans o ma ion):
The iα and iβ componen s a e ans o med in o he D-Q o a ing ame. The
o a ing ame o a es synch onously wi h he sys em ol age (using a Phase-
Locked Loop (PLL), o ex ac he phase angle he a θ).
Ma hema ically:
[𝐈𝐝
𝐈𝐪]=[𝐜𝐨𝐬 𝛉 𝐬𝐢𝐧 𝛉
−𝐬𝐢𝐧 𝛉 𝐜𝐨𝐬 𝛉][𝐈𝛂
𝐈𝛃]
Eq 5
3. Fil e ing Ha monics:
In he D-Q ame:
A Low-Pass Fil e (LPF) is applied o id and iq o isola e he DC componen s
( undamen al ac i e and eac i e cu en s).
The AC componen s ep esen he ha monics.
A e il e ing, he compensa ing cu en s a e calcula ed as:
𝐈𝐝=𝐈𝐝𝐃𝐂+𝐈𝐝𝐀𝐂
Eq 6
𝐈𝐪=𝐈𝐪𝐃𝐂+𝐈𝐪𝐀𝐂
Eq 7
4. T ans o ma ion Back o S a iona y and a-b-c F ames:
The il e ed ha monic componen s a e ans o med back o he s a iona y α-β
ame using he in e se Pa k ans o ma ion.
Ma hema ically:
[𝐈𝛂
𝐈𝛃]=[𝐜𝐨𝐬 𝛉 −𝐬𝐢𝐧 𝛉
𝐬𝐢𝐧 𝛉 𝐜𝐨𝐬 𝛉][𝐈𝐝
𝐈𝐪]
Eq 8
Pàg. 36 Repo
Finally, he cu en s a e con e ed back o he o iginal h ee-phase sys em using he in e se
Cla ke ans o ma ion:
Ma hema ically:
[𝐈𝐚∗
𝐈𝐛∗
𝐈𝐜∗]=√𝟐
𝟑
[
𝟏 𝟎
−𝟏
𝟐√𝟑
𝟐
𝟏
𝟐√𝟑
𝟐
]
[𝐈𝛂
𝐈𝛃]
Eq 9
5. Gene a ion o Compensa ing Cu en s:
The ex ac ed cu en s (Ia∗,Ib∗,Ic∗) a e used o gene a e swi ching signals o he
Vol age Sou ce In e e (VSI).
The VSI injec s compensa ing cu en s in o he g id a he PCC o cancel ou
ha monics and eac i e powe , ensu ing sinusoidal sou ce cu en s.
Figu e 15 SRF Con olle
5.2. Pho o ol aic Ene gy In eg a ion
Elec ic Vehicles (EVs) a e o en ega ded as “g een” ene gy ehicles; howe e , hei
en i onmen al bene i s a e diminished when he elec ici y used o cha ging comes om
ossil uel-based powe gene a ion. By inco po a ing pho o ol aic (PV) sys ems, alongside
he powe g id, he ca bon oo p in o EVs can be signi ican ly educed. PV sys ems, in
pa icula , p o ide a clean and sus ainable ene gy sou ce o EVCSs, o e ing se e al
ad an ages.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 37
5.2.1. Ad an ages
Reducing G id Dependency: Sola powe coincides well wi h day ime cha ging
demand, p o iding cheap and clean ene gy o o se peak loads.
Peak Sha ing: By p o iding powe when demand inc eases, s ess on he g id is
educed.
Ene gy cos sa ing: Cha ging cos s a e educed o end use s.
5.2.2. Challenges O In eg a ing PV in o he G id and EVCS
Despi e i s bene i s, in eg a ing PV ene gy in o he g id and EVCSs poses signi ican
challenges due o i s in e mi en na u e and hea y eliance on wea he condi ions. Sola
powe gene a ion luc ua es based on sunligh a ailabili y, which c ea es supply ins abili y
du ing pe iods o cloud co e , nigh ime, o seasonal a ia ions. This in e mi ency can lead
o g id imbalance and powe quali y issues i no p ope ly managed. Fu he mo e, ol age
egula ion and equency s abili y become mo e complex wi h high PV pene a ion, as PV
in e e s mus coo dina e wi h he g id o p o ide eac i e powe suppo .
Figu e 16 PV Powe Ou pu on Sunny s Cloudy Day
5.2.3. Impac o Tempe a u e on The Pe o mance o PV Modules
The able illus a es how ambien and cell empe a u es in luence he VoC, IsC and powe
ou pu o PV modules, exp essed as pe cen ages o hei nominal alues. As empe a u es
ise, ol age and powe dec ease, while cu en sligh ly inc eases due o he espec i e
empe a u e coe icien s.
Pàg. 38 Repo
Table 2 Tempe a u e Impac on Vol age, Cu en and Powe
5.3. Ba e y Ene gy S o age Sys em (BESS)
The mos p omising app oach o sus ainable anspo a ion and ene gy sys ems is
inco po a ion o BESS and PV oge he wi h EVCSs. These wo oge he can help wi h he
g id’s s abili y and eliabili y by s o ing ene gy du ing o -peak hou s and cha ging EVs
du ing peak hou s. These sys ems can also s o e addi ional ene gy gene a ed by sola
powe when he condi ions a e mo e a o able. They can supply su plus ene gy o he g id
a he ime o ene gy sho age o powe ou age.
5.3.1. Ad an ages o In eg a ing BESS wi h PV In o The G id
Ensu es g id s abili y despi e luc ua ions in sola i adiance and PV ene gy
gene a ion.
Fla ens demand cu e by discha ging s o ed ene gy du ing peak hou s.
P o ides Reac i e powe (Q) o mi iga e ol age luc ua ions.
Reduces ha monics.
Imp o es he economic easibili y o PV plan s and educes ene gy cos s o end
use s by applying Ene gy A bi age Me hod.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 39
Figu e 17 Peak Sha ing Theo y
Pàg. 40 Repo
6. Sec ion IV: Technical Handbooks
6.1. Hyb id Pho o ol aic Sys em Handbook
A hyb id pho o ol aic (PV) sys em in eg a es enewable ene gy gene a ion wi h ene gy
s o age and g id connec i i y o p o ide eliable powe o a ious applica ions. The
design p ocess o a hyb id PV sys em in ol es ou main s eps:
De e mining powe consump ion demands.
Sizing he PV modules.
Sizing in e e
Sizing ba e y.
This guide will explain each s ep in de ail.
6.1.1. De e mining Powe Consump ion Demands
The i s s ep in designing a hyb id PV sys em is o calcula e he o al powe and
ene gy consump ion o all he loads ha he sys em needs o supply.
𝐓𝐨𝐭𝐚𝐥 𝐩𝐨𝐰𝐞𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝= ∑𝐩𝐨𝐰𝐞𝐫 𝐫𝐚𝐭𝐞𝐨𝐟 𝐚𝐥𝐥 𝐚𝐩𝐩𝐥𝐢𝐚𝐧𝐜𝐞𝐬
Eq 10
The o al ene gy consump ion pe day can be es ima ed by mul iplying he powe
equi emen by he hou s o ope a ion, wi h an addi ional ac o o accoun o sys em losses
( ypically 1.3):
𝐓𝐨𝐭𝐚𝐥 𝐞𝐧𝐞𝐫𝐠𝐲 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐩𝐞𝐫 𝐝𝐚𝐲
=∑𝐩𝐨𝐰𝐞𝐫𝐫𝐚𝐭𝐞 𝐨𝐟 𝐞𝐚𝐜𝐡 𝐚𝐩𝐩𝐥𝐢𝐚𝐧𝐜𝐞
× 𝐧𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐫𝐮𝐧𝐧𝐢𝐧𝐠𝐡𝐨𝐮𝐫𝐬
𝐝𝐚𝐲 ×𝟏.𝟑
Eq 11
6.1.2. Sizing PV Modules
The nex s ep is o de e mine he size o he PV sys em equi ed o mee he daily ene gy
needs. To do his, di ide he o al ene gy consump ion by he a e age numbe o sun hou s
a he s a ion's loca ion. Fo ins ance, i he sys em is ins alled in Ba celona, whe e he
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 41
a e age numbe o sun hou s is 5 hou s pe day, he o al PV capaci y equi ed (in e ms o
powe peak) can be calcula ed as:
𝐓𝐨𝐭𝐚𝐥 𝐩𝐨𝐰𝐞𝐫 𝐩𝐞𝐚𝐤 𝐭𝐨 𝐛𝐞 𝐢𝐧𝐬𝐭𝐚𝐥𝐥𝐞𝐝
=𝐓𝐨𝐭𝐚𝐥 𝐞𝐧𝐞𝐫𝐠𝐲 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐩𝐞𝐫 𝐝𝐚𝐲
𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐬𝐮𝐧 𝐡𝐨𝐮𝐫𝐬 𝐢𝐧 𝐝𝐞𝐬𝐢𝐫𝐞𝐝 𝐥𝐨𝐜𝐚𝐭𝐢𝐨𝐧
Eq 12
The nex s ep is o de e mine he numbe o PV panels needed.
𝐌𝐢𝐧𝐢𝐦𝐮𝐦 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐧𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐩𝐚𝐧𝐞𝐥𝐬
=𝐓𝐨𝐭𝐚𝐥 𝐩𝐨𝐰𝐞𝐫 𝐩𝐞𝐚𝐤 𝐭𝐨 𝐛𝐞 𝐢𝐧𝐬𝐭𝐚𝐥𝐥𝐞𝐝
𝐏𝐨𝐰𝐞𝐫 𝐫𝐚𝐭𝐢𝐧𝐠 𝐨𝐟 𝐞𝐚𝐜𝐡 𝐩𝐚𝐧𝐞𝐥
Eq 13
6.1.3. In e e Sizing
In e e sizing is c ucial o ensu ing ha he PV sys em can e icien ly con e DC powe
om he PV panels o usable AC powe o he cha ge s. The inpu a ing o he in e e
mus ma ch o exceed he o al powe demand o he appliances.
𝐏𝐨𝐬𝐬𝐢𝐛𝐥𝐞 𝐧𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐬𝐭𝐫𝐢𝐧𝐠𝐬 𝐢𝐧 𝐩𝐚𝐫𝐚𝐥𝐥𝐞𝐥
=𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐌𝐏𝐏𝐓 ×𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟𝐬𝐭𝐫𝐢𝐧𝐠𝐬
𝐌𝐏𝐏𝐓
Eq 14
𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟𝐬𝐭𝐫𝐢𝐧𝐠𝐬
𝐌𝐏𝐏𝐓 𝐢𝐧 𝐩𝐚𝐫𝐚𝐥𝐥𝐞𝐥≤𝐌𝐚𝐱 𝐢𝐧𝐩𝐮𝐭 𝐜𝐮𝐫𝐫𝐞𝐧𝐭
𝐈𝐦𝐩 𝐨𝐟 𝐚 𝐩𝐚𝐧𝐞𝐥
Eq 15
𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐩𝐚𝐧𝐞𝐥𝐬 𝐢𝐧 𝐬𝐞𝐫𝐢𝐞𝐬≤ 𝐌𝐚𝐱 𝐢𝐧𝐩𝐮𝐭 𝐯𝐨𝐥𝐭𝐚𝐠𝐞
𝐕𝐨𝐜 𝐨𝐟 𝐚 𝐩𝐚𝐧𝐞𝐥 ×𝟏.𝟏
Eq 16
Tempe a u e Fac o = 1.1 o accoun o ol age ise when empe a u e d op o -20 deg ees.
𝐋𝐨𝐰𝐞𝐫 𝐥𝐢𝐦𝐢𝐭 𝐌𝐩𝐩𝐭 𝐫𝐚𝐧𝐠𝐞
≤𝐕𝐦𝐩 𝐨𝐟 𝐚 𝐩𝐚𝐧𝐞𝐥×𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐩𝐚𝐧𝐞𝐥𝐬 𝐢𝐧 𝐬𝐞𝐫𝐢𝐞𝐬
≤ 𝐔𝐩𝐩𝐞𝐫 𝐥𝐢𝐦𝐢𝐭 𝐌𝐩𝐩𝐭 𝐫𝐚𝐧𝐠𝐞
Eq 17
Pàg. 48 Repo
e ec issues. Nickel Manganese Cobal (NMC) ba e ies p o ide high ene gy densi y
and good o e all pe o mance bu all sho in cycle li e, sa e y and cos compa ed o
LiFePO₄.
The e o e, LiFePO₄ ba e ies a e he mos adequa e choice o mode n EVCS
designs, o e ing an op imal balance o sa e y, pe o mance, and du abili y.
6.3. Ba e y Assembly Handbook
Building a ba e y pack independen ly can be 30% o 45% mo e cos -e ec i e
compa ed o pu chasing a p e-assembled ba e y pack. This cos ad an age s ems
om se e al ac o s:
A oidance o Manu ac u e Ma kups
Cus om Sou cing o Componen s
Scalabili y o Design
Exclusion o Unnecessa y Fea u es
Labo and Assembly Cos s
He e’s a echnical design handbook o building a ba e y pack. I includes essen ial
concep s, o mulas, and s eps o ensu e a sa e and unc ional design.
6.3.1. De ining he Ba e y Pack Requi emen s
1. De e mine Ba e y Pack Vol age (V) and Capaci y (Ah):
Ba e y pack o al ene gy (Epack) is al eady de e mined.
Ba e y pack ol age (Vpack) depends on you applica ion's equi emen s (e.g., 12V, 24V,
o 48V sys ems).
Ba e y pack Capaci y (Cpack) depends on he ene gy needed:
𝐂𝐩𝐚𝐜𝐤 (𝐀𝐡)= 𝐄𝐩𝐚𝐜𝐤 (𝐖𝐡)
𝐕𝐩𝐚𝐜𝐤 (𝐕)
Eq 20
2. Es ima e Con inuous Cu en (I con .) o Ba e y pack Capaci y.
𝐈 𝐜𝐨𝐧𝐭.(𝐀)=𝐏𝐨𝐰𝐞𝐫 𝐥𝐨𝐚𝐝 (𝐖)
𝐕𝐩𝐚𝐜𝐤 (𝐕)
Eq 21
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 49
3. Choose Cell Type:
Choose cell based on echnology, capaci y, and C- a ing.
𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐜𝐞𝐥𝐥𝐬 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐩𝐞𝐫 𝐛𝐚𝐭𝐭𝐞𝐫𝐲 𝐩𝐚𝐜𝐤
=𝐓𝐨𝐭𝐚𝐥 𝐞𝐧𝐞𝐫𝐠𝐲 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐢𝐧 𝐖𝐚𝐭𝐭𝐬
𝐂𝐞𝐥𝐥 𝐕𝐨𝐥𝐭𝐚𝐠𝐞 ×𝐂𝐞𝐥𝐥 𝐜𝐚𝐩𝐚𝐜𝐢𝐭𝐲 𝐡𝐨𝐮𝐫
Eq 22
6.3.2. Cell Con igu a ion
1. Se ies Con igu a ion (ns):
Numbe o cells in se ies is de e mined by he in e e DC inpu ol age ange.
𝐌𝐢𝐧𝐢𝐦𝐮𝐦 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐧𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐜𝐞𝐥𝐥𝐬 𝐢𝐧 𝐬𝐞𝐫𝐢𝐞𝐬
≥ 𝐌𝐢𝐧 𝐃𝐂 𝐢𝐧𝐩𝐮𝐭 𝐕𝐨𝐥𝐭𝐚𝐠𝐞
𝐃𝐢𝐬𝐜𝐡𝐚𝐫𝐠𝐞 𝐞𝐧𝐝 𝐯𝐨𝐥𝐭𝐚𝐠𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐂𝐞𝐥𝐥
Eq 23
𝐌𝐚𝐱 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐧𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐜𝐞𝐥𝐥𝐬 𝐢𝐧 𝐬𝐞𝐫𝐢𝐞𝐬
≤ 𝐌𝐚𝐱 𝐃𝐂 𝐢𝐧𝐩𝐮𝐭 𝐕𝐨𝐥𝐭𝐚𝐠𝐞
𝐇𝐢𝐠𝐡𝐞𝐬𝐭 𝐜𝐡𝐚𝐫𝐠𝐢𝐧𝐠 𝐯𝐨𝐥𝐭𝐚𝐠𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐂𝐞𝐥𝐥×𝟏.𝟏
Eq 24
Whe e:
Tempe a u e Fac o = 1.1 o accoun o ol age ise when empe a u e d op o -20 deg ees.
2. Pa allel Con igu a ion (np):
Numbe o cells in pa allel is de e mined by he in e e max inpu cu en .
𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐩𝐚𝐫𝐚𝐥𝐥𝐞𝐥 𝐬𝐭𝐫𝐢𝐧𝐠𝐬≤𝐌𝐚𝐱 𝐃𝐂 𝐢𝐧𝐩𝐮𝐭 𝐜𝐮𝐫𝐫𝐞𝐧𝐭
𝐂𝐜𝐞𝐥𝐥 𝐧𝐨𝐦𝐢𝐧𝐚𝐥
Eq 25
Pàg. 50 Repo
6.3.3. The mal Design
Hea Gene a ion (Q):
𝐐(𝐤𝐖𝐡)=𝐈𝟐𝐜𝐨𝐧𝐭.×𝐑𝐜𝐞𝐥𝐥×𝐍×𝐭÷𝟏𝟎𝟎𝟎
Eq 26
Whe e:
Rcell is he in e nal esis ance o he cell (Ω).
is he discha ge ime (sec)
Hea Coe :
𝐇𝐞𝐚𝐭 𝐜𝐨𝐞𝐟=𝟏+ 𝐈𝟐𝐜𝐨𝐧𝐭.×𝐑𝐜𝐞𝐥𝐥
𝐂𝐜𝐞𝐥𝐥 𝐧𝐨𝐦𝐢𝐧𝐚𝐥×𝐕𝐜𝐞𝐥𝐥 𝐧𝐨𝐦𝐢𝐧𝐚𝐥
Eq 27
Cooling Requi emen s:
𝐐(𝐤𝐖𝐡)=𝐌𝐚𝐬𝐬 𝐟𝐥𝐨𝐰 𝐦˙(𝐤𝐠
𝐬)×𝐂𝐩 ( 𝐊𝐉
𝐊𝐠.𝐊)×𝚫𝐓 (𝐊)
Eq 28
𝐕𝐨𝐥𝐮𝐦𝐞𝐭𝐫𝐢𝐜 𝐅𝐥𝐨𝐰 (𝐦³
𝐬)= 𝐌𝐚𝐬𝐬 𝐟𝐥𝐨𝐰 𝐦˙
𝐂𝐨𝐨𝐥𝐚𝐧𝐭 𝐃𝐞𝐧𝐬𝐢𝐭𝐲 (𝐤𝐠
𝐦³)
Eq 29
I he coolan is ai , selec an exhaus an wi h he calcula ed capaci y (m³/s).
I he coolan is liquid, selec a pump ha suppo s he calcula ed capaci y, along wi h
an exhaus an o se e as a adia o . The an should ha e a capaci y app oxima ely
25% o he exhaus an ha would be equi ed i he coolan we e ai .
6.3.4. Ba e y Managemen Sys em (BMS)
Ensu e he cell ol age is wi hin he BMS allowed ange.
Ve i y he ba e y pack ol age ange is wi hin he BMS inpu ol age ange.
𝐌𝐚𝐱 𝐯𝐨𝐥𝐭𝐚𝐠𝐞 𝐁𝐌𝐒
>𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐜𝐞𝐥𝐥𝐬 𝐢𝐧𝐬𝐞𝐫𝐢𝐞𝐬
𝐬𝐭𝐫𝐢𝐧𝐠×𝐜𝐞𝐥𝐥 𝐯𝐨𝐥𝐭𝐚𝐠𝐞 𝐜𝐮𝐭𝐨𝐟𝐟×𝟏.𝟏
Eq 30
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 51
Ensu e he cell capaci y is wi hin he BMS speci ied limi s.
Check ha he ba e y pack capaci y is wi hin he BMS allowed capaci y ange.
𝐌𝐚𝐱 𝐜𝐮𝐫𝐫𝐞𝐧𝐭 𝐁𝐌𝐒>𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐬𝐭𝐫𝐢𝐧𝐠𝐬 ×𝐜𝐞𝐥𝐥 𝐜𝐚𝐩𝐚𝐜𝐢𝐭𝐲
Eq 31
Con i m he numbe o cells in se ies and pa allel complies wi h he BMS
limi a ions.
6.3.5. Elec ical Connec ions
Wi e Sizing:
1. Selec Wi e Size Based on Cu en -Ca ying Capaci y
2. Calcula e ol age d op o his wi e size.
𝐕𝐝𝐫𝐨𝐩=𝐈𝐜𝐨𝐧𝐭.×𝛒×𝐋
𝐀𝐫𝐞𝐚
Eq 32
Whe e:
ρ is he esis i i y o he wi e ma e ial (Ω·m).
L is he one-way leng h o he wi e (m).
A ea is he c oss-sec ional a ea o he wi e (m²).
3. Check i Vol age D op is Wi hin Limi s:
The allowable ol age d op o DC ci cui s is ypically 2% o he ba e y ol age.
Fo AC ci cui s, he allowable ol age d op is gene ally 1%.
Fuse Sizing:
The use sizing is ypically calcula ed as:
𝐈𝐟𝐮𝐬𝐞=𝐈𝐜𝐨𝐧𝐭.×𝟏.𝟐𝟓
Eq 33
Whe e:
The 1.25 ac o is used o accoun o any in ush cu en o sho - e m su ges.
Pàg. 52 Repo
6.3.6. Enclosu e Design
Sa e y:
Use a i e- esis an enclosu e.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 53
7. Sec ion V: Case S udy
This hesis del es in o he de ailed design and economic easibili y o an EVCS,
ecognizing he challenges posed by a ious unce ain ies inhe en o such p ojec s.
Key ac o s in luencing he design include luc ua ions in ene gy demand, he
dis ibu ion o cha ging hou s h oughou he day, he capaci y and s eng h o he local
powe g id and land a ailabili y o enewable sys em implemen a ion.
Due o hese majo unce ain ies, i is qui e di icul o de elop a single, comp ehensi e
EVCS handbook ha is e icien and adequa e o use anywhe e in he wo ld.
The e o e, his hesis p o ides a speci ic case s udy as an example and discusses six
di e en scena ios ha add ess ealis ic p obabili ies o a ying a iables. The aim is o
o e a mode o design o EVCS in as uc u e ha can guide enginee s in de eloping
hei own s a ions by adap ing he p esen ed amewo k o hei unique se s o
a iables.
The case s udy examines he design and implemen a ion o an Elec ic Vehicle
Cha ging S a ion (EVCS) equipped wi h ou DC as cha ge s, each a ed a 90 kW
(Le el III). To p io i ize sus ainabili y and enhance economic iabili y, he s a ion
inco po a es enewable ene gy gene a ion h ough a pho o ol aic (PV) sys em and a
Ba e y Ene gy S o age Sys em (BESS).
Gi en ha EV cha ging beha io is in luenced by daily commu ing pa e ns and
cha ging in as uc u e a ailabili y, i is assumed ha demand will be highe du ing he
day ime han a nigh ime. Du ing he day, he e is ypically mo e demand o as
cha ging, especially in public and wo kplace loca ions. In con as , a nigh , EV owne s
o en echa ge hei ehicles a home using slowe cha ge s, esul ing in lowe demand
a cha ging s a ions. The e o e, wo- hi ds o he o al demand is alloca ed o day ime,
wi h one- hi d o nigh ime.
The Elec ic Vehicle Cha ging S a ion is equipped wi h ou EV cha ge s, each wi h a
a ed ou pu capaci y o 90 kW, supplied by EVESCO [39]. These cha ge s ope a e on
an AC inpu ol age o 400V. The maximum inpu powe o each cha ge is calcula ed
o be 92 kW, wi h a co esponding maximum inpu cu en o 133A.
Addi ionally, he cha ge s a e compa ible wi h he ollowing connec o con igu a ions:
CHAdeMO + CCS2 o CCS2 + CCS2. This makes hem sui able o a wide ange o
elec ic ehicles (EVs) including Tesla, BMW, Volkswagen, Fo d, Audi, among o he s...
These connec o s anda ds ensu e he cha ge s a e e sa ile and able o se e he
cha ging needs o mos EVs a ailable in he Eu opean and Global ma ke .
Pàg. 54 Repo
Figu e 18 Elec ical Speci ica ions o EVESCO Cha ge
This con igu a ion p o ides a o al cha ging capaci y o :
𝐌𝐚𝐱 𝐇𝐨𝐮𝐫𝐥𝐲 𝐋𝐨𝐚𝐝 𝐂𝐚𝐩𝐚𝐜𝐢𝐭𝐲=𝟗𝟐 𝐤𝐖
𝐜𝐡𝐚𝐫𝐠𝐞𝐫×𝟒 𝐜𝐡𝐚𝐫𝐠𝐞𝐫𝐬=𝟑𝟔𝟖 𝐤𝐖
Eq 34
Each cha ge can se e one elec ic ehicle (EV) simul aneously, meaning he maximum
numbe o EVs ha can be cha ged pe hou is:
𝐌𝐚𝐱𝐢𝐦𝐮𝐦 𝐇𝐨𝐮𝐫𝐥𝐲 𝐂𝐚𝐩𝐚𝐜𝐢𝐭𝐲=𝟒 𝐄𝐕𝐬
𝐡𝐨𝐮𝐫
Eq 35
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 55
O e a 24-hou pe iod, he s a ion can suppo :
𝐌𝐚𝐱 𝐃𝐚𝐢𝐥𝐲 𝐄𝐕 𝐂𝐚𝐩𝐚𝐜𝐢𝐭𝐲=𝟒 𝐄𝐕𝐬
𝐡𝐨𝐮𝐫×𝟐𝟒 𝐡𝐨𝐮𝐫𝐬=𝟗𝟔 𝐄𝐕𝐬
𝐝𝐚𝐲
Eq 36
The co esponding o al daily ene gy consump ion a ull capaci y is:
𝐌𝐚𝐱 𝐃𝐚𝐢𝐥𝐲 𝐄𝐧𝐞𝐫𝐠𝐲 𝐂𝐨𝐧𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧=𝟗𝟔 𝐄𝐕𝐬
𝐝𝐚𝐲×𝟗𝟐 𝐤𝐖
𝐜𝐡𝐚𝐫𝐠𝐞𝐫=𝟖𝟖𝟑𝟐 𝐤𝐖𝐡
𝐝𝐚𝐲
Eq 37
7.1. Ca ego y A
In Ca ego y A, he daily ene gy demand is de ined as 25% o he EVCS's maximum
capaci y, which can be calcula ed as:
𝐃𝐚𝐢𝐥𝐲 𝐃𝐞𝐦𝐚𝐧𝐝=𝟎.𝟐𝟓×𝟖𝟖𝟑𝟐 𝐤𝐖𝐡=𝟐𝟐𝟎𝟖 𝐤𝐖𝐡
𝐝𝐚𝐲
Eq 38
This demand co esponds o cha ging:
𝐓𝐨𝐭𝐚𝐥 𝐄𝐕𝐬 𝐂𝐡𝐚𝐫𝐠𝐞𝐝 𝐩𝐞𝐫 𝐃𝐚𝐲=𝟎.𝟐𝟓×𝟗𝟔 𝐄𝐕𝐬=𝟐𝟒 𝐄𝐕𝐬
𝐝𝐚𝐲
Eq 39
The daily demand is dis ibu ed be ween day ime and nigh ime as ollows:
1. Day ime Demand
Two- hi ds o he o al demand is alloca ed o day ime hou s:
𝐃𝐚𝐲𝐭𝐢𝐦𝐞 𝐃𝐞𝐦𝐚𝐧𝐝=𝟐
𝟑×𝟐𝟐𝟎𝟖 𝐤𝐖𝐡=𝟏𝟒𝟕𝟐 𝐤𝐖𝐡
Eq 40
This co esponds o:
𝐇𝐨𝐮𝐫𝐬 𝐨𝐟 𝐅𝐮𝐥𝐥 𝐋𝐨𝐚𝐝= 𝟏𝟒𝟕𝟐 𝐤𝐖𝐡
𝟑𝟔𝟖 𝐤𝐖
𝐡𝐨𝐮𝐫 =𝟒 𝐡𝐨𝐮𝐫𝐬
Eq 41
which equa es o cha ging:
𝐄𝐕𝐬 𝐂𝐡𝐚𝐫𝐠𝐞𝐝 𝐃𝐮𝐫𝐢𝐧𝐠 𝐃𝐚𝐲𝐭𝐢𝐦𝐞=𝟒 𝐡𝐨𝐮𝐫𝐬×𝟒 𝐜𝐡𝐚𝐫𝐠𝐞𝐫𝐬
𝐡𝐨𝐮𝐫 =𝟏𝟔 𝐄𝐕𝐬.
Eq 42
2. Nigh ime Demand
One- hi d o he o al demand is alloca ed o nigh ime hou s:
Pàg. 56 Repo
𝐍𝐢𝐠𝐡𝐭𝐭𝐢𝐦𝐞 𝐃𝐞𝐦𝐚𝐧𝐝=𝟏
𝟑×𝟐𝟐𝟎𝟖 𝐤𝐖𝐡=𝟕𝟑𝟔 𝐤𝐖𝐡
Eq 43
This co esponds o:
𝐇𝐨𝐮𝐫𝐬 𝐨𝐟 𝐅𝐮𝐥𝐥 𝐋𝐨𝐚𝐝= 𝟕𝟑𝟔 𝐤𝐖𝐡
𝟑𝟔𝟖 𝐤𝐖
𝐡𝐨𝐮𝐫 =𝟐 𝐡𝐨𝐮𝐫𝐬
Eq 44
which equa es o cha ging:
𝐄𝐕𝐬 𝐂𝐡𝐚𝐫𝐠𝐞𝐝 𝐃𝐮𝐫𝐢𝐧𝐠 𝐍𝐢𝐠𝐡𝐭𝐭𝐢𝐦𝐞=𝟐 𝐡𝐨𝐮𝐫𝐬×𝟒 𝐜𝐡𝐚𝐫𝐠𝐞𝐫𝐬
𝐡𝐨𝐮𝐫 =𝟖 𝐄𝐕𝐬.
Eq 45
Ca ego y A Scena ios:
1. Scena io A-1: G id + 2 BPs
Du ing he day, he g id supplies powe o mee he EVCS demand.
A nigh , wo ba e y packs (BPs), each supplying ene gy o one hou o ull load
(368 kWh), co e he en i e nigh ime load.
The BPs a e echa ged om he g id du ing o -peak hou s (00:00 o 6:00) when
elec ici y p ices a e a hei lowes .
2. Scena io A-2: PV + 2 BPs
A pho o ol aic (PV) sys em gene a es su icien ene gy o mee he en i e daily
demand, including echa ging he wo BPs.
A nigh , he BPs supply powe o co e he en i e nigh ime load.
Pu pose o Scena io A-1 s Scena io A-2:
A-1 s A-2 highligh s he impo ance o in eg a ing PV o educe g id dependency
in mee ing o al demand.
3. Scena io A-3: G id + 6 BPs
Six BPs a e used, each capable o supplying one hou o ull load (368 kWh).
The BPs a e echa ged om he g id du ing o -peak hou s (00:00 o 6:00) when
elec ici y p ices a e lowes .
Once cha ged, he BPs supply he en i e EVCS load du ing bo h day ime and
nigh ime, wi h no di ec g id consump ion du ing he ope a ional hou s.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 57
4. Scena io A-4: G id Only
The g id solely supplies powe o he EVCS o bo h day ime and nigh ime loads.
No PV sys em o BPs a e u ilized.
Pu pose o Scena io A-3 s Scena io A-4:
A-3 s A-4 emphasizes he ole o BESS in educing g id eliance, especially
du ing peak hou s.
7.2. Ca ego y B
In Ca ego y B, he daily ene gy demand is de ined as 75% o he EVCS's maximum
capaci y. This can be calcula ed as:
𝐃𝐚𝐢𝐥𝐲 𝐃𝐞𝐦𝐚𝐧𝐝=𝟎.𝟕𝟓×𝟖𝟖𝟑𝟐 𝐤𝐖𝐡=𝟔𝟔𝟐𝟒 𝐤𝐖𝐡
𝐝𝐚𝐲
Eq 46
This demand co esponds o cha ging:
𝐓𝐨𝐭𝐚𝐥 𝐄𝐕𝐬 𝐂𝐡𝐚𝐫𝐠𝐞𝐝 𝐩𝐞𝐫 𝐃𝐚𝐲=𝟎.𝟕𝟓×𝟗𝟔 𝐄𝐕𝐬=𝟕𝟐 𝐄𝐕𝐬
𝐝𝐚𝐲
Eq 47
The daily demand is dis ibu ed be ween day ime and nigh ime as ollows:
1. Day ime Demand
Two- hi ds o he o al demand is alloca ed o day ime hou s:
𝐃𝐚𝐲𝐭𝐢𝐦𝐞 𝐃𝐞𝐦𝐚𝐧𝐝=𝟐
𝟑×𝟔𝟔𝟐𝟒 𝐤𝐖𝐡=𝟒𝟒𝟏𝟔 𝐤𝐖𝐡
Eq 48
This co esponds o:
𝐇𝐨𝐮𝐫𝐬 𝐨𝐟 𝐅𝐮𝐥𝐥 𝐋𝐨𝐚𝐝= 𝟒𝟒𝟏𝟔 𝐤𝐖𝐡
𝟑𝟔𝟖 𝐤𝐖
𝐡𝐨𝐮𝐫 =𝟏𝟐 𝐡𝐨𝐮𝐫𝐬
Eq 49
which equa es o cha ging:
𝐄𝐕𝐬 𝐂𝐡𝐚𝐫𝐠𝐞𝐝 𝐃𝐮𝐫𝐢𝐧𝐠 𝐃𝐚𝐲𝐭𝐢𝐦𝐞=𝟏𝟐 𝐡𝐨𝐮𝐫𝐬×𝟒 𝐜𝐡𝐚𝐫𝐠𝐞𝐫𝐬
𝐡𝐨𝐮𝐫 =𝟒𝟖 𝐄𝐕𝐬.
Eq 50
Pàg. 64 Repo
Using [Eq 19],
𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐬𝐢𝐳𝐞 (𝐤𝐖𝐡)=𝟗𝟐 𝐤𝐖𝐡 ×𝟏.𝟎𝟑𝟓𝟐
𝟎.𝟖 ×𝟎.𝟗𝟓 =𝟏𝟐𝟓.𝟑𝟐 𝐤𝐖𝐡
Eq 61
This implies ha o he ba e y o sus ain he 92 kW load, i mus ha e a minimum
capaci y o 125.32 kWh, assuming a C- a ing o 1C.
Using [Eq 22],
𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐜𝐞𝐥𝐥𝐬 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐩𝐞𝐫 𝐛𝐚𝐭𝐭𝐞𝐫𝐲 𝐩𝐚𝐜𝐤=𝟏𝟐𝟓.𝟑𝟐×𝟏𝟎𝟎𝟎
𝟑.𝟐 ×𝟏𝟐𝟓 =𝟑𝟏𝟑.𝟑
Eq 62
The calcula ed numbe o cells equi ed is 313.3; hus, he alue is ounded up o 315
cells.
Consequen ly, he e ised sub-ba e y pack capaci y is 126 kWh.
Each EV cha ge equi es 92 kW, necessi a ing an in e e wi h a minimum 92 kW AC
ou pu capaci y.
Fo his p ojec , a 92 kW in e e om KACO new ene gy GmbH has been selec ed.
[43]
Figu e 22 Technical Speci ica ions o KACO In e e
Cells connec ions:
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 65
Using [Eq 23], [Eq 24] and [Eq 25],
𝐌𝐢𝐧𝐢𝐦𝐮𝐦 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐧𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐜𝐞𝐥𝐥𝐬 𝐢𝐧 𝐬𝐞𝐫𝐢𝐞𝐬≥𝟔𝟔𝟖 𝐕
𝟐.𝟓 𝐕
= 𝟐𝟔𝟕.𝟐 𝐜𝐞𝐥𝐥𝐬 𝐢𝐧 𝐬𝐞𝐫𝐢𝐞𝐬
Eq 63
𝐌𝐚𝐱 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐧𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐜𝐞𝐥𝐥𝐬 𝐢𝐧 𝐬𝐞𝐫𝐢𝐞𝐬≤ 𝟏𝟑𝟏𝟓 𝐕
𝟑.𝟔𝟓 𝐕 ×𝟏.𝟏
=𝟑𝟐𝟕.𝟓 𝐜𝐞𝐥𝐥𝐬 𝐢𝐧 𝐬𝐞𝐫𝐢𝐞𝐬
Eq 64
𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐩𝐚𝐫𝐚𝐥𝐥𝐞𝐥 𝐬𝐭𝐫𝐢𝐧𝐠𝐬≤𝟏𝟒𝟓 𝐀𝐡
𝟏𝟐𝟓 𝐀𝐡=𝟏.𝟏𝟔 𝐬𝐭𝐫𝐢𝐧𝐠
Eq 65
The con igu a ion o each sub-ba e y pack will consis o one s ing o 315 cells
connec ed in se ies, esul ing in a nominal ol age o 1008 V and a capaci y o 125 Ah,
p o iding a o al ene gy s o age o 126 kWh.
BMS:
Fo he ba e y pack hos ing 315 cells, he Nu a ion Ene gy G5 S ack Swi chgea
(model: NUVG5-SSG-1500-200-x) will be u ilized. [44]
This BMS suppo s a maximum ol age o 1500V and a maximum cu en o 200A.
Figu e 23 Technical Speci ica ions o NUVG5 BMS
Using [Eq 30] and [Eq 31]:
𝟏𝟓𝟎𝟎𝐕>𝟑𝟏𝟓×𝟑.𝟔𝟓×𝟏.𝟏=𝟏𝟐𝟔𝟓𝐕
Eq 66
𝟐𝟎𝟎𝐀>𝟏 ×𝟏𝟐𝟓=𝟏𝟐𝟓𝐀
Eq 67
Pàg. 66 Repo
8. Sec ion VI: Economic and En i onmen al
Analysis
8.1. Cos Analysis o EVCS Ac oss he Six Scena ios
8.1.1. PV Sys em
Capi al Expendi u e (CAPEX): The up on cos o ins alling he PV sys em,
including panels, in e e s, wi ing, moun ing s uc u es, and ins alla ion labo .
𝐂𝐀𝐏𝐄𝐗_𝐏𝐕 ( $
𝐤𝐖)=∑(𝐂𝐨𝐬𝐭 𝐨𝐟 𝐂𝐨𝐦𝐩𝐨𝐧𝐞𝐧𝐭𝐬)+𝐈𝐧𝐬𝐭𝐚𝐥𝐥𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐬𝐭
Eq 68
Ope a ional Expendi u e (OPEX): The annual cos o main aining and
ope a ing he PV sys em, including cleaning, inspec ion, and mino epai s.
𝐎𝐏𝐄𝐗_𝐏𝐕 ( $
𝐤𝐖×𝐲𝐞𝐚𝐫)=𝐀𝐧𝐧𝐮𝐚𝐥 𝐌𝐚𝐢𝐧𝐭𝐞𝐧𝐚𝐧𝐜𝐞 𝐂𝐨𝐬𝐭
Eq 69
Annual Ene gy P oduc ion (AEP): The o al ene gy gene a ed annually by he
PV sys em, conside ing loca ion-speci ic sola i adiance, sys em e iciency, and
deg ada ion.
𝐀𝐄𝐏 (𝐤𝐖𝐡)=𝐒𝐮𝐧𝐥𝐢𝐠𝐡𝐭𝐇𝐨𝐮𝐫𝐬
𝐃𝐚𝐲 ×𝐏𝐕 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲×𝐒𝐲𝐬𝐭𝐞𝐦 𝐏𝐞𝐚𝐤 𝐂𝐚𝐩𝐚𝐜𝐢𝐭𝐲
×𝟑𝟔𝟓
Eq 70
Le elized Cos o Ene gy (LCOE): The a e age cos pe kilowa -hou (kWh)
gene a ed o e he li e ime o he PV sys em.
𝐋𝐂𝐎𝐄_𝐏𝐕 ( $
𝐤𝐖𝐡)=𝐂𝐀𝐏𝐄𝐗𝐏𝐕+∑𝐎𝐏𝐄𝐗𝐏𝐕
∑𝐀𝐄𝐏
Eq 71
Based on alues e ie ed om he Na ional Renewable Ene gy Labo a o y (NREL), which
ope a es unde he U.S. Depa men o Ene gy, he ollowing benchma ks o pho o ol aic
(PV) sys ems a e no ed:
𝐂𝐀𝐏𝐄𝐗𝐏𝐕=𝟏𝟐𝟎𝟎 $
𝐤𝐖𝐩
Eq 72
𝐎𝐏𝐄𝐗𝐏𝐕=𝟓 $
𝐤𝐖×𝐲𝐞𝐚𝐫
Eq 73
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 67
In all scena ios in ol ing he inclusion o PV sys ems, he sys em capaci y emains
consis en a 576 kWp, esul ing in
𝐋𝐂𝐎𝐄𝐏𝐕=𝟎.𝟎𝟑𝟎𝟗 $
𝐤𝐖𝐡
Eq 74
8.1.2. G id In as uc u e
G id CAPEX: This includes he cos o equipmen and in as uc u e equi ed o
connec he EVCS o he g id, such as ans o me s, swi chgea , and cabling.
G id Ene gy Cos ($/kWh): a ies based on he ime o day and ma ke
luc ua ions.
G id Ene gy Supply Cos ($/kWh)
𝐆𝐫𝐢𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐮𝐩𝐩𝐥𝐲 𝐜𝐨𝐬𝐭 ( $
𝐤𝐖𝐡)
=𝐆𝐫𝐢𝐝 𝐂𝐚𝐩𝐞𝐱 × 𝐂𝐚𝐩𝐚𝐜𝐢𝐭𝐲 𝐢𝐧𝐬𝐭𝐚𝐥𝐥𝐞𝐝
𝐓𝐨𝐭𝐚𝐥 𝐇𝐨𝐮𝐫𝐬 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 𝐎𝐯𝐞𝐫 𝐋𝐢𝐟𝐞𝐭𝐢𝐦𝐞
+𝐆𝐫𝐢𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐂𝐨𝐬𝐭
Eq 75
Whe e,
𝐓𝐨𝐭𝐚𝐥 𝐇𝐨𝐮𝐫𝐬 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝
=𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐋𝐢𝐟𝐞𝐬𝐩𝐚𝐧 (𝐲𝐞𝐚𝐫𝐬)×𝐀𝐧𝐧𝐮𝐚𝐥 𝐔𝐭𝐢𝐥𝐢𝐳𝐞𝐝 𝐇𝐨𝐮𝐫𝐬.
Eq 76
In his p ojec , he o al capaci y o he sys em is designed o accommoda e 368 kW,
wi h a planned ope a ional li espan o 30 yea s.
Based on da a e ie ed om ENDESA, a Spanish mul ina ional elec ic u ili y
company, he g id connec ion capi al expendi u e (Capex) is es ima ed a 37 €/kW [45],
which is app oxima ely
𝐂𝐀𝐏𝐄𝐗𝐆𝐑𝐈𝐃 =𝟒𝟎.𝟕 $
𝐤𝐖
Eq 77
Acco ding o 2024 g id ene gy cos da a in Spain,
𝐀𝐯.𝐠𝐫𝐢𝐝 𝐞𝐧𝐞𝐫𝐠𝐲 𝐜𝐨𝐬𝐭=𝟎.𝟏𝟒𝟐𝟏 $
𝐤𝐖𝐡
Eq 78
Pàg. 68 Repo
𝐀𝐯.𝐎𝐅𝐅 𝐏𝐄𝐀𝐊 𝐠𝐫𝐢𝐝 𝐞𝐧𝐞𝐫𝐠𝐲 𝐜𝐨𝐬𝐭=𝟎.𝟎𝟔𝟔 $
𝐤𝐖𝐡
Eq 79
U ilizing an a bi age me hod, whe e he BESS cha ges du ing o -peak hou s and
discha ges du ing peak hou s, he EVCS can:
1. Lowe ene gy supply cos s o EV cha ge s.
2. Balance g id load and educe demand cha ges.
In scena ios classi ied unde Ca ego y A ha inco po a e g id ene gy, he g id deli e s
a o al o 6 hou s o ene gy pe day. This esul s in:
𝐆𝐫𝐢𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐮𝐩𝐩𝐥𝐲 𝐜𝐨𝐬𝐭 𝐭𝐨 𝐭𝐡𝐞 𝐥𝐨𝐚𝐝= 𝟎.𝟑𝟕𝟎𝟏 $
𝐤𝐖𝐡
Eq 80
𝐆𝐫𝐢𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐮𝐩𝐩𝐥𝐲 𝐜𝐨𝐬𝐭 𝐭𝐨 𝐭𝐡𝐞 𝐁𝐏𝐬= 𝟎.𝟐𝟗𝟒𝟎 $
𝐤𝐖𝐡
Eq 81
Howe e , in scena ios classi ied unde Ca ego y B, he g id deli e s a o al o 12 hou s
o ene gy pe day. This esul s in:
𝐆𝐫𝐢𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐮𝐩𝐩𝐥𝐲 𝐜𝐨𝐬𝐭 𝐭𝐨 𝐭𝐡𝐞 𝐥𝐨𝐚𝐝= 𝟎.𝟐𝟓𝟔𝟏 $
𝐤𝐖𝐡
Eq 82
𝐆𝐫𝐢𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐮𝐩𝐩𝐥𝐲 𝐜𝐨𝐬𝐭 𝐭𝐨 𝐭𝐡𝐞 𝐁𝐏𝐬= 𝟎.𝟏𝟖 $
𝐤𝐖𝐡
Eq 83
8.1.3. BESS
CAPEX o BESS: The ini ial cos o he ba e y pack, including he cos o
cells, Ba e y Managemen Sys em (BMS), he mal managemen , and
ins alla ion.
𝐂𝐀𝐏𝐄𝐗𝐁𝐄𝐒𝐒=∑(𝐂𝐨𝐬𝐭 𝐨𝐟 𝐂𝐨𝐦𝐩𝐨𝐧𝐞𝐧𝐭𝐬)+𝐈𝐧𝐬𝐭𝐚𝐥𝐥𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐬𝐭
Eq 84
OPEX o BESS: The annual cos o main aining and ope a ing he ba e y
sys em, including inspec ions, epai s, and cooling ene gy consump ion.
𝐎𝐏𝐄𝐗𝐁𝐄𝐒𝐒=𝐀𝐧𝐧𝐮𝐚𝐥 𝐌𝐚𝐢𝐧𝐭𝐞𝐧𝐚𝐧𝐜𝐞 𝐂𝐨𝐬𝐭
Eq 85
Li ecycle Cos : The o al cos o he ba e y o e i s use ul li e ime, conside ing
eplacemen a e a de ined numbe o cycles.
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 69
𝐋𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞 𝐜𝐨𝐬𝐭 ( $
𝐤𝐖𝐡)= 𝐂𝐀𝐏𝐄𝐗𝐁𝐄𝐒𝐒+𝐎𝐏𝐄𝐗𝐁𝐄𝐒𝐒
𝐂𝐚𝐩𝐚𝐜𝐢𝐭𝐲×𝐃𝐨𝐃×𝐂𝐲𝐜𝐥𝐞𝐬×𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲
Eq 86
Ene gy Deli e ed cos ($/kWh):
I echa ged by PV sys em:
𝐄𝐧𝐞𝐫𝐠𝐲 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 𝐜𝐨𝐬𝐭 ( $
𝐤𝐖𝐡)=𝐋𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞 𝐜𝐨𝐬𝐭+𝐋𝐂𝐎𝐄_𝐏𝐕
Eq 87
I echa ged by G id Ene gy:
𝐄𝐧𝐞𝐫𝐠𝐲 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 𝐜𝐨𝐬𝐭 ( $
𝐤𝐖𝐡)
=𝐋𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞 𝐜𝐨𝐬𝐭+𝐆𝐫𝐢𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐮𝐩𝐩𝐥𝐲 𝐜𝐨𝐬𝐭
Eq 88
A bi age me hod P o i ($/kWh)
𝐀𝐫𝐛𝐢𝐭𝐫𝐚𝐠𝐞 𝐩𝐫𝐨𝐟𝐢𝐭( $
𝐤𝐖𝐡)
=𝐀𝐯.𝐆𝐫𝐢𝐝(𝐄𝐧𝐞𝐫𝐠𝐲 𝐜𝐨𝐬𝐭− 𝐎𝐅𝐅 𝐏𝐄𝐀𝐊 𝐞𝐧𝐞𝐫𝐠𝐲 𝐜𝐨𝐬𝐭)
−𝐋𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞 𝐜𝐨𝐬𝐭
Eq 89
O e he nex h ee decades, ba e y p ices a e p ojec ed o decline signi ican ly, d i en
by echnological ad ancemen s, economies o scale, and inc eased ma ke demand.
Bloombe gNEF o ecas s a 68% educ ion in he cos o li hium-ion ba e y sys ems in
2050 compa ed o oday’s p ices. [46]
Pàg. 70 Repo
Figu e 24 P edic ed T ends in Ba e y P ices [47]
The ba e y pack has a minimum li espan o 5,000 cycles. Based on he ope a ional
scena ios, i is expec ed o comple e app oxima ely one cycle pe day. The e o e, he
ba e y pack is p ojec ed o las a leas :
𝟓,𝟎𝟎𝟎 𝐜𝐲𝐜𝐥𝐞𝐬
𝟑𝟔𝟓𝐃𝐚𝐲𝐬
𝐲𝐞𝐚𝐫 ≈𝟏𝟑.𝟔𝟗 𝐲𝐞𝐚𝐫𝐬
Eq 90
Fo simplici y, we assume a li espan o 15 yea s. Howe e , he p ojec is designed o a
o al li espan o 30 yea s, meaning he ba e y pack will equi e one eplacemen a e 15
yea s.
Addi ionally, conside ing he an icipa ed decline in ba e y p ices o e he nex 30 yea s, i
is assumed ha ba e y cos s will ha e allen by 50% in 15 yea s compa ed o cu en p ices.
Based on cu en ba e y ma ke ends, he Capex o ba e y packs is app oxima ely
176 $/kWh, wi h an Opex o 5 $/kWh pe yea . Howe e , in his p ojec , he ba e y
packs will cos 40% less, educing he Capex o 105.6 $/kWh.
𝐂𝐀𝐏𝐄𝐗𝐁𝐄𝐒𝐒 =𝟏𝟎𝟓.𝟔 $
𝐤𝐖𝐡
Eq 91
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 71
𝐎𝐏𝐄𝐗𝐁𝐄𝐒𝐒 =𝟓 $
𝐤𝐖×𝐲𝐞𝐚𝐫
Eq 92
Accoun ing o a eplacemen a he 15-yea ma k, he li ecycle cos o he ba e y
packs, including all associa ed expenses, is calcula ed o be:
𝐋𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞 𝐜𝐨𝐬𝐭 =𝟎.𝟎𝟒𝟎𝟖 $
𝐤𝐖𝐡
Eq 93
𝐀𝐫𝐛𝐢𝐭𝐫𝐚𝐠𝐞 𝐦𝐞𝐭𝐡𝐨𝐝 𝐩𝐫𝐨𝐟𝐢𝐭=𝟎.𝟎𝟑𝟓𝟓 $
𝐤𝐖𝐡
Eq 94
The ene gy deli e ed cos echa ged om he PV sys em is:
𝐄𝐧𝐞𝐫𝐠𝐲 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 𝐜𝐨𝐬𝐭 (𝐏𝐕)=𝟎.𝟎𝟕𝟒 $
𝐤𝐖𝐡
Eq 95
Fo scena ios whe e he ba e y packs a e echa ged om he g id:
In Ca ego y A,
𝐄𝐧𝐞𝐫𝐠𝐲 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 𝐜𝐨𝐬𝐭 (𝐆𝐫𝐢𝐝)=𝟎.𝟑𝟑𝟒𝟓 $
𝐤𝐖𝐡
Eq 96
In Ca ego y B,
𝐄𝐧𝐞𝐫𝐠𝐲 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 𝐜𝐨𝐬𝐭 (𝐆𝐫𝐢𝐝)=𝟎.𝟐𝟐𝟎𝟔 $
𝐤𝐖𝐡
Eq 97
8.2. Compa isons and Conclusions
Figu e 25 Ene gy Supply Hou s By Sou ce Ac oss Scena ios
0
2
4
6
8
10
12
14
16
18
20
A1 A2 A3 A4 B1 B2
Ene gy Sou ce Con ibu ion Hou s o he Load
PV GRID BP
Pàg. 72 Repo
Figu e 26 P o i Pe kWh Ene gy By Sou ce Ac oss Scena ios
Figu e 27 Daily P o i By Sou ce Ac oss Scena ios
Pho o ol aics (PV) demons a e he highes p o i abili y as an ene gy sou ce, wi h a e enue
gene a ion o app oxima ely $0.4/kWh, as seen in Scena io A2.
Ba e y packs (BPs) o e wo key economic ad an ages:
1. Load Supply Du ing Nigh ime: Ensu ing ene gy a ailabili y when sola gene a ion
is una ailable.
2. A bi age Me hod: Maximizing cos sa ings by s a egically cha ging du ing o -
peak hou s and discha ging du ing peak hou s.
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
A1 A2 A3 A4 B1 B2
PROFIT ($/kWh)
PV GRID BESS
0
200
400
600
800
1000
1200
1400
1600
1800
2000
A1 A2 A3 A4 B1 B2
Daily P o i Con ibu ion
PV GRID BESS
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 73
A1 s. A2:
A2 achie es highe p o i abili y by elying en i ely on PV as he p ima y ene gy sou ce,
suppo ed by BPs o nigh ime load co e age. In con as , A1, which combines g id
ene gy wi h BPs, gene a es lowe e enues. This highligh s PV's economic ad an age
as a cos -e ec i e and sus ainable ene gy sou ce when in eg a ed wi h ba e y s o age.
A3 s. A4:
A3, wi h six BPs echa ged om he g id, ou pe o ms A4, which elies solely on g id
ene gy. The in eg a ion o mo e BPs in A3 allows o highe p o i abili y h ough
educed g id dependency and ene gy a bi age. This demons a es he inancial and
ope a ional bene i s o scaling up ba e y s o age in g id-dependen sys ems.
B1 s. B2:
Bo h scena ios u ilize PV o one- hi d o he demand, bu B2 achie es highe
p o i abili y by op imizing he a bi age me hod. By s a egically managing ba e y
ope a ions and g id usage, B2 highligh s how ad anced ene gy managemen can
maximize e enue in hyb id ene gy sys ems.
Ca ego y A s. Ca ego y B:
Ca ego y B, wi h highe daily demand (18 hou s o ull load), e lec s mo e ealis ic and
la ge-scale scena ios compa ed o Ca ego y A (6 hou s o ull load). The esul s show
ha as demand inc eases, ne e enues also inc ease, showcasing he scalabili y and
inancial bene i s o hyb id sys ems designed o highe ene gy consump ion. Ca ego y
B u he demons a es he impo ance o in eg a ing PV, BPs, and g id ene gy o cos
op imiza ion and eliabili y.
Ca bon Sa ings:
Ca bon sa ings a e only achie ed in scena ios whe e PV in eg a ion is included because
PV sys ems gene a e elec ici y om enewable sola ene gy, displacing he need o g id
ene gy gene a ed om ossil uels.
Pàg. 80 Repo
[10]
«T ends in elec ic ca s,» IEA, [En línea]. A ailable:
h ps://www.iea.o g/ epo s/global-e -ou look-2024/ ends-in-elec ic-ca s.
[11]
«Global EV ou look 2024: EV sales se o each 17 million,» In e na ional Ene gy
Agency, 24 Ap il 2024. [En línea]. A ailable: h ps://e boos e s.com/e -cha ging-
news/global-e -ou look-2024-e -sales-se - o- each-17-million/.
[12]
«Cha ging poin deploymen e sus sales o elec ically-cha geable ca s,» ACEA
D i ing Mobili y Fo Eu ope, 27 Feb ua y 2023. [En línea]. A ailable:
h ps://www.acea.au o/ igu e/cha ging-poin -deploymen - e sus-sales-o -elec ically-
cha geable-ca s/.
[13]
«In e ac i e map – Co ela ion be ween elec ic ca sales and cha ging poin
a ailabili y (2023 da a),» ACEA, [En línea]. A ailable:
h ps://www.acea.au o/ igu e/in e ac i e-map-co ela ion-be ween-elec ic-ca -sales-
and-cha ging-poin -a ailabili y-2023-da a/.
[14]
«EVs A e S ill 45% Mo e Expensi e To Make Than Combus ion-Engined Ca s,»
Oli e Wyman, Sep embe 2020. [En línea]. A ailable:
h ps://insidee s.com/news/444542/e s-45-pe cen -mo e-expensi e-make-ice/.
[15]
«Elec ic Vehicles,» IEA, [En línea]. A ailable: h ps://www.iea.o g/ene gy-
sys em/ anspo /elec ic- ehicles.
[16]
Cha lo e A gue, «Digging deepe in o how empe a u e and speed impac EV ange,»
GeoTab, 30 No embe 2023. [En línea]. A ailable: h ps://www.geo ab.com/blog/e -
ange-impac -o -speed-and- empe a u e/.
[17]
«Some coun ies a e ending suppo o EVs. Is i oo soon?,» MIT Technology
Re iew , 23 Sep embe 2024. [En línea]. A ailable:
h ps://www. echnology e iew.com/2024/09/23/1104247/ending-e -subsidies/.
[18]
«Ge many Held Back EU Elec ic Ca Ma ke in Fi s Hal o 2024 — T&E Analysis,»
Clean Technica, June 2024. [En línea]. A ailable:
h ps://clean echnica.com/2024/07/20/ge many-held-back-eu-elec ic-ca -ma ke -in-
i s -hal -o -2024- e-analysis/.
[19]
A. K. M. Yousu , Z. Wang, R. Pa anjape y Y. Tang, «An In-Dep h Explo a ion o
Elec ic Vehicle Cha ging S a ion In as uc u e: A Comp ehensi e Re iew o
Challenges, Mi iga ion App oaches, and Op imiza ion S a egies».
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 81
[20]
Deu sche Gesellscha ü In e na ionale Zusammena bei (GIZ) GmbH, «O e iew
on Ba e y Swapping and Ba e y as a Se ice in China,» Beijing, 2022.
[21]
S. R. a. M. R. A. A. K. Ka make , «Analysis o he impac o elec ic ehicle cha ging
s a ion on powe quali y issues,» 2019.
[22]
A. E. T. A. Y. a. O. M. S. Faddel, «Expe imen al e i ica ion o he e ec o
uncoo dina ed cha ging o elec ic ehicles on powe g ids,» 2019.
[23]
«Comp ehensi e Op imiza ion Model o Sizing and Si ing o DG Uni s, EV Cha ging
S a ions, and Ene gy S o age Sys ems.».
[24]
S. M. a. F. Ma iasiu, «Elec ic ehicle ba e y echnologies: F om p esen s a e o
u u e sys ems,» 2015.
[25]
J. T. S. M. B. M. T. Mu ayab Khalid, «Impac o public and esiden ial sma EV
cha ging on dis ibu ion powe g id equipped wi h s o age».
[26]
P. T. I. P. a. I. K. J. Nii soo, «Modeling EVs in esiden ial dis ibu ion g id wi h o he
nonlinea loads,» 2015.
[27]
Y. X. Z. C. F. P. a. M. B. Y. Xu, «Ha monic analysis o elec ic ehicle loadings on
dis ibu ion sys em,» 2014.
[28]
J. R. P. H. K. A. a. L. S. P. G ahn, «A me hod o e alua ing he impac o elec ic
ehicle cha ging on ans o me ho spo empe a u e,» 2011.
[29]
«Enhancing Elec ic Vehicle Cha ging In as uc u e: A Techno-Economic Analysis o
Dis ibu ed Ene gy Resou ces and Local G id In eg a ion».
[30]
«Elec ic ehicle cha ging echnologies, in as uc u e expansion, g id in eg a ion
s a egies, and hei ole in p omo ing sus ainable e-mobili y».
[31]
IEEE, «IEEE 1547: S anda d o In e connec ion and In e ope abili y o Dis ibu ed
Ene gy Resou ces wi h Associa ed Elec ic Powe Sys ems In e aces,» 2018.
[32]
«Unde s anding he IEEE 519 – 2014 s anda d o Ha monics,» ELSPEC LTD, [En
línea]. A ailable: h ps://www.elspec-l d.com/ieee-519-2014-s anda d- o -ha monics/.
[33]
«Unde s anding Li hium-Ion Ba e y Cha ac e is ics: A Comp ehensi e Guide,»
MENRED ESS, No embe 2024. [En línea]. A ailable: h ps://www.men ed-
Pàg. 82 Repo
ess.com/unde s anding-li hium-ion-ba e y-cha ac e is ics-a-comp ehensi e-guide/.
[34]
L. Dong, «Li hium I on Phospha e Ba e y Cha ac e is ics,» Augus 2023. [En línea].
A ailable: h ps://www.linkedin.com/pulse/li hium-i on-phospha e-ba e y-
cha ac e is ics-lesley-dong/.
[35]
«Typical cycle li e: Gel s AGM s Lead Acid s Li hium,» RED POLE ENERGY, [En
línea]. A ailable: h ps:// edpoleene gy.co.za/ ypical-cycle-li e-gel- s-agm- s-lead-
acid- s-li hium/.
[36]
«AGM (VRLA) ba e ies: main enance- ee 12V ba e ies and hei ad an ages,»
A mac Ene gy, Sep embe 2024. [En línea]. A ailable: h ps://a mac-
ene gy.eu/news/ba e ies-agm- la-unmanned-ba e ies-12 -and- hei -bene i s.
[37]
«MAXIMIZING THE CYCLE LIFE OF NICKEL CADMIUM BATTERIES,» Alnakhi
Powe , [En línea]. A ailable: h ps://alnakhipowe .com/maximizing- he-cycle-li e-o -
nickel-cadmium-ba e ies/.
[38]
«Nickel Manganese Cobal ,» HBL, [En línea]. A ailable:
h p://www.hblbess.com/Nickel-Manganese-Cobal .h ml.
[39]
«EVDC-90NA,» EVESCO , [En línea]. A ailable: h ps://www.powe -
sonic.com/p oduc /e dc-90-na/.
[40]
«Hi-MO-5,» LONGI , [En línea]. A ailable:
h ps://www.longi.com/mx/p oduc s/modules/hi-mo-5/.
[41]
«Huawei SUN2000-150K-MG0,» Huawei , [En línea]. A ailable:
h ps://www.sola ade s.com/es/p oduc s/in e so /huawei-sun2000-150k-mg0.
[42]
«CALB L173F125B 3.2V 125Ah Li epo4 Cell,» CALB , [En línea]. A ailable:
h ps://ly hba e y.com/calb-l p-ba e y-l173 125-3-2 -125ah-li hium-ba e y-2/.
[43]
«blueplane g idsa e 92.0 - 137 TL3-S,» KACO NEW ENERGY, [En línea]. A ailable:
h ps://kaco-newene gy.com/es/p oduc os/blueplane -870- l3-125- l3.
[44]
«G5 S ack Swi chgea ,» NUVATIONENERGY, [En línea]. A ailable:
h ps://ns o e.nu a ionene gy.com/p oduc s/g5-s ack-swi chgea .
[45]
«Find ou how much i cos s o connec o he g id o inc ease you powe ,» UFD
GRUPO NATURGY, 17 Feb ua y 2023. [En línea]. A ailable:
h ps://www.u d.es/en/blog/conoce-los-cos es-pa a-conec a e-a-la- ed-o-amplia - u-
A Case S udy on Hyb id EV Cha ging In as uc u e Pág. 83
po encia/?u m_sou ce=cha gp .com.
[46]
«Ene gy S o age o S eal $277B F om Powe G ids by 2050,» Bloombe gNEF, [En
línea]. A ailable: h ps://abou .bne .com/blog/ene gy-s o age- o-s eal-277b- om-
powe -g ids-by-2050/.
[47]
«Elec ic ehicle ba e y p ices a e expec ed o all almos 50% by 2026,» Goldman
Sachs, 7 Oc obe 2024. [En línea]. A ailable:
h ps://www.goldmansachs.com/insigh s/a icles/elec ic- ehicle-ba e y-p ices-a e-
expec ed- o- all-almos -50-pe cen -by-2025.
[48]
«Li hium I on Phospha e (LFP o LiFePO4),» Powe Tech Sys ems, [En línea].
A ailable: h ps://www.powe echsys ems.eu/home/ ech-co ne /li hium-i on-
phospha e-li epo4/.
