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GIS-da a ela ed ou e op imiza ion, hie a chical clus e ing, loca ion op imiza ion, and
ke nel densi y me hods a e use ul o p omo ing dis ibu ed bioene gy plan planning in
u al a eas
© 2019 Else ie L d. All igh s ese ed.
Accep ed e sion (Final d a )
Laasasenaho, K.; Lensu, Anssi; Lauhanen, R.; Rin ala, J.
Laasasenaho, K., Lensu, A., Lauhanen, R., & Rin ala, J. (2019). GIS-da a ela ed ou e
op imiza ion, hie a chical clus e ing, loca ion op imiza ion, and ke nel densi y me hods a e
use ul o p omo ing dis ibu ed bioene gy plan planning in u al a eas. Sus ainable Ene gy
Technologies and Assessmen s, 32, 47-57. h ps://doi.o g/10.1016/j.se a.2019.01.006
2019
GIS-da a ela ed ou e op imiza ion, hie a chical clus e ing, loca ion1
op imiza ion, and ke nel densi y me hods a e use ul o p omo ing2
dis ibu ed bioene gy plan planning in u al a eas3
K. Laasasenahoa*, A. Lensub*, R. Lauhanenc and J. Rin alaa
4
aFacul y o Enginee ing and Na u al Sciences, Tampe e Uni e si y, FI-33014 Tampe e5
Uni e si y , Finland; b Depa men o Biological and En i onmen al Science, Uni e si y6
o Jy äskylä,, Jy äskylä, Finland; cSchool o Food and Ag icul u e, Seinäjoki7
Uni e si y o Applied Sciences, Seinäjoki, Finland8
ka i.laasasenaho@ uni. i (K. Laasasenaho); anssi.lensu@jyu. i (A. Lensu)9
*co esponding au ho s10
11
GIS-da a ela ed ou e op imiza ion, hie a chical clus e ing, loca ion12
op imiza ion, and ke nel densi y me hods a e use ul o p omo ing13
dis ibu ed bioene gy plan planning in u al a eas14
Cu en ly, geog aphic in o ma ion sys em (GIS) models a e popula o s udying15
loca ion-alloca ion- ela ed ques ions conce ning bioene gy plan s. The aim o his16
s udy was o de elop a model o in es iga e op imal loca ions o wo di e en 17
ypes o bioene gy plan s, o a m and cen alized biogas plan s, and o wood18
e minals in u al a eas based on minimizing anspo a ion dis ances. The19
op imal loca ions o biogas plan s we e de e mined using loca ion op imiza ion20
ools in R so wa e, and he op imal loca ions o wood e minals we e de e mined21
using ke nel densi y ools in A cGIS.22
The p esen case s udy showed ha he u ilized GIS ools a e use ul o 23
bioene gy- ela ed decision-making o iden i y po en ial bioene gy a eas and o24
op imise biomass anspo a ion, and help o plan powe plan sizing when25
candida e bioene gy plan loca ions ha e no been de ined in ad ance.26
In he s udy a ea, i was possible o ind logis ically iable loca ions o 13 a m27
biogas plan s (>100 kW) and o 8 cen alized biogas plan s (>300 kW) using a28
10-km h eshold o eeds ock supply. In he case o wood e minals, he esul s29
iden i ied he mos in ensi e wood ese es nea he highes oad classes, and wo30
po en ial loca ions we e de e mined.31
Keywo ds: biogas; ci cula economy; loca ion-alloca ion; ne wo k analysis;32
wood e minal33
1 In oduc ion34
Cu en ly, biomass is he mos used enewable ene gy sou ce in he wo ld [1]. Biomass35
om plan s, o ganic was e, and animal exc e a is equen ly u ilized in bioene gy36
p oduc ion. In u al a eas, se e al ypes o biomass a e a ailable o bioene gy37
p oduc ion depending on local ac o s, such as p esence o ag icul u al esidues (e.g.,38
s aw and manu e) and a ailabili y o o es biomass. Bioene gy and bio uels can be39
c ea ed om biomass h ough se e al echniques, including mechanical, chemical, o 40
biological ea men s such as pelle izing, gasi ica ion, py olysis, o biological p ocesses41
[2]. In ac , he use o biomass o bioene gy p oduc ion appea s o be inc easing, and42
he di e en applica ions o biomass a e expanding because o he shi ing end owa d43
bio and ci cula economies ha eplace adi ional ossil esou ces [2-4]. In di e en 44
u al a eas o Eu ope, in es men in biogas plan s using manu e as uel a e inc easingly45
conside ed while he use o wood biomass as such o as pelle s in bioene gy plan s is46
p omo ed as well. In his con ex , he a ailabili y o biomass o bioene gy p oduc ion47
mus also be gua an eed in he u u e.48
1.1 Planning o bioene gy p oduc ion49
S akeholde s play an impo an ole h oughou he a ious phases o bioene gy50
de elopmen p ojec s om he bioene gy plan planning o p ojec implemen a ion. By51
in eg a ing he di e en s akeholde s, i is possible o iden i y condi ions ha a e52
applicable o bioene gy [5]. Planning loca ions o bioene gy plan s is usually a53
demanding ask because p ecise knowledge abou biomass a ailabili y, yield, and54
chemical cha ac e is ics a e equi ed. Besides he loca ion o he ac ual bioene gy plan ,55
he need o in oduce wood e minals has become especially u gen in No he n56
coun ies o balance he loca ion o wood supplies and o con en ional combined hea 57
and powe (CHP) bioene gy plan s. This is as adi ional win e ime ha es ing o wood58
is becoming di icul due o wa ming win e s, leading o a lack o ha dening os on59
oads wi h low bea ing capaci y [6].60
The ounding o a new bioene gy plan is always a geospa ial ques ion. Biomass61
esou ces a e usually spa sely dis ibu ed, making e e y case unique [7]. Di e en 62
biomasses ha e di e en yields, yea ly schedules, and cha ac e is ics and, acco dingly,63
ha e dis inc economic alues, which in luence, o example, he economic easibili y64
o he equi ed anspo a ion dis ances. The eby, one c ucial s ep o es ablishing65
bioene gy plan s is inding iable loca ions o hem. Me hods based on geog aphic66
in o ma ion sys ems (GISs) ha e been used in many disciplines as decision-making67
ools because hey can sol e loca ion-alloca ion- ela ed p oblems h ough, o example,68
minimizing anspo a ion dis ances [8-9].69
1.2 Feasibili y o GIS ools o alloca ing biomass esou ces o bioene gy70
Globally, se e al s udies ha e mapped biomass esou ces o bioene gy p oduc ion. In71
gene al, s udies can be di ided in o wo GIS-based app oaches: sui abili y analyses and72
op imali y analyses. In sui abili y analyses, which a e some imes called mul i-c i e ia73
e alua ions (MCEs), bu e and spa ial o e lay analyses a e usually used o assess he74
loca ion o po en ial biomass p oduc ion plan s, whe eas op imali y analyses a e used75
o loca ion-alloca ion issues o ma ch biomass supply and he ene gy demands o 76
socie y [9]. Sui abili y analyses ha e been p e iously based on he in eg a ion o 77
di e en models o analy ical echniques in o a GIS en i onmen , including Ma ko 78
chains [10], mul i-c i e ia models [11˗12], analy ic hie a chy p ocess and map algeb a79
[13], and ke nel densi y analysis [14]. Meanwhile, op imali y analyses o bioene gy80
plan s ha e been based on Dijks a’s ou e op imiza ion algo i hm [15], emo e sensing81
da a and GIS-based mixed in ege linea modeling [16], and he modi ied p-median82
p oblem [9]. Many o he s udies using GIS ha e di ec ly examined o assessed gene al83
biomass po en ial o bioene gy p oduc ion [e.g., 17˗22]. Also, some s udies a e84
handling analy ical me hodologies and de elopmen o heu is ics in bioene gy supply85
chain [23]. GIS me hods a e especially use ul in assessing land a ailabili y o ene gy86
c ops [11˗13, 17]. In addi ion, sus ainabili y o bioene gy p ojec s could be imp o ed by87
combining Li e Cycle Assessmen s and GIS ools [24].88

Feasible biomass anspo a ion dis ance is eeds ock dependen and is a ec ed89
by se e al ac o s. The economics o biomass anspo a ion dis ances a e dependen ,90
o example, on biomass composi ion, ene gy alue (e.g., biogas po en ial), mois u e,91
speci ic weigh [25], and aile capaci y. In addi ion, local egula ions a ec was e-92
based managemen p ocedu es and anspo a ion p ac ices, and he e o e ha e a no able93
ole in bioene gy planning [26]. GI Sys ems p o ide se e al ools o sol ing op imal94
logis ic solu ions and minimizing biomass anspo a ion cos s, bu mos o he ools95
equi e ha he use speci ies bo h sou ce and des ina ion loca ions o he anspo s.96
When planning a loca ion o a new acili y, his would equi e p o iding se e al97
possible plan loca ions (des ina ion candida es), and hen we could choose he bes 98
candida e. I such candida es do no exis o i we do no wan o limi he sea ch o 99
bes loca ion o such se o candida es, he ou e op imiza ion me hodology needs o be100
al e ed o op imize ou es om he sou ce poin s o all o he loca ions in he oad101
ne wo k, as we ha e done in his s udy. Taking bo h anspo a ion dis ances and102
biomass supply in o accoun , he op imal size and loca ion o plan s can be de e mined.103
The aim o he p esen s udy was o de elop and assess he easibili y o a GIS-104
based solu ion o selec ing he op imal loca ion o biogas plan s and wood e minals in105
a u al a ea based on minimizing he anspo a ion needs o di e en biomasses. The106
op imal loca ions o biogas plan s and wood e minals we e he e o e de e mined in he107
s udy a ea conside ing spa sely dis ibu ed biomasses. The aim was o c ea e a model108
ha can help local s akeholde s o op imize bioene gy plan loca ions and o de elop109
bioene gy and bio- e ining-based business ac i i ies in u al a eas.110
2 Ma e ials and me hods111
2.1 S udy a ea112
The s udy a ea co esponded wi h he u al Kuudes aan egion in Sou h Os obo hnia,113
Finland. The o al a ea o he egion is 3,121 km2, and he egion con ains 23,646114
inhabi an s [27˗28] ha mos ly li e in wo majo owns (Äh ä i and Ala us wi h 5,968115
and 11,746 inhabi an s, espec i ely). One hund ed and hi y- i e la ge a ms116
(desc ibed in mo e de ail la e ) a e p esen in he egion, and he economy o he egion117
has been adi ionally based on o es y ac i i ies. Cu en ly, he po en ial eeds ocks o 118
bioene gy p oduc ion a e wood, ag icul u al esidues (e.g., s aw and manu e), and119
municipal o ganic was es. Wood is commonly used as uel o hea p oduc ion in120
dis ic hea ing plan s (12 plan s) and in p i a e houses, including a mhouses. The e a e121
h ee majo wood e minals (1–2 ha in size, Me sä G oup) whe e wood is empo a ily122
s o ed and hen anspo ed o a pulp mill and bio e ine y loca ed in Äänekoski, Cen al123
Finland (a e age dis ance o 100 o 150 km). Howe e , so a , no biogas plan s a e124
p esen in he s udy a ea.125
126
Figu e 1. Loca ion o he s udied Kuudes aan egion in Finland. Popula ion cen es127
(adminis a i e bo de s) a e indica ed in da k g ey. Municipali y names a e indica ed by128
capi al le e s, and some majo illages by lowe case le e s.129
2.2 Scena ios and da a o biomass esou ces130
In his s udy, wo biomass use scena ios we e s udied. The i s one aimed o ind131
loca ions o biogas plan s wi h capaci ies om 100 o o e 300 kW. The capaci ies132
we e based on economically easible a m biogas plan and cen alized biogas plan 133
sizing in Finland acco ding o Na u al Resou ce Ins i u e Finland [29]. The o he 134
scena io aimed o loca e wood e minals in he s udy a ea (Fig. 4).135
In he biogas scena io, eeds ocks included di e en manu es om a ms,136
sepa a ed biowas es om municipali ies, oca ional schools, g oce y s o es, and ou is 137
cen es (which is biowas e om ca e ing se ices, bu also includes biowas e and animal138
manu e om Äh ä i Zoo); and sludge om was ewa e ea men plan s (Table 1).139
Fu he mo e, he use o eed cana y g ass (RCG; Phala is a undinacea), which can be140
po en ially g own on cu away pea lands, was conside ed [30]. In ensi e pea ex ac ion141
egions a e p esen in he s udy a ea, and hund eds o hec a es o hese si es will en e 142
in o he a e -use phase in he nea u u e and hus ep esen po en ial g owing si es o 143
ene gy c ops.144
Manu es ( o al 264,273 ) om la ge a ms wi h mo e han 50 heads o ca le,145
500 pigs, 30 ho ses, o 500 heads o poul y in 2016 we e included in he s udy. Thei 146
loca ions (add esses) we e ob ained om he da abases o he Finnish Food Sa e y147
Au ho i y (E i a), he Agency o Ru al A ai s (Ma i), and he Na ional Land Su ey148
o Finland (NLS). The amoun o manu e p oduced pe a m was calcula ed based on149
animal age and species, and he mean amoun s o manu e p oduced pe animal [31].150
The amoun ( esh ma e ; FM) o biowas es was ob ained om he municipali ies and151
ope a o s o municipal was e collec ing se ices. The amoun s ( o al solids; TS) o 152
sewage sludge (municipali ies o Ala us, Äh ä i, and Soini) we e ob ained om he153
En i onmen al P o ec ion da abase [32]. The me hane po en ial o di e en biomasses154
a e p esen ed in Table 2.155
Table 1. Annual amoun s o manu e and biowas e (Mg FM) and sewage sludge (Mg TS)156
gene a ed in he s udy a ea.157
O ganic was e Amoun
Ag icul u al manu e 264,273
Biowas e
- municipal 127
- shops 103
- ou is cen es 306
- oca ional schools 4
Sewage sludge 494
158
Table 2. The me hane po en ial o di e en biomasses used in his s udy.159
Biomass CH4 po en ial Uni Re e ence
Biowas e 107 m3 CH4/Mg FM [33]
Sewage sludge 163 m3 CH4/Mg TS [33]
Ca le manu e 19 m3 CH4/Mg FM [33]
Pig manu e 10 m3 CH4/Mg FM [31]
illus a ed in Fig. 8, whe e he op imal biogas plan loca ion was de ined based on 6259
a ms, o ganic was e om 7 municipal sou ces, 1 ou ism cen e, and 2 g oce y s o es.260
Li es ock manu e was he la ges sou ce o biomass o he po en ial biogas261
plan s. Howe e , in Ala us and Kuo ane, a signi ican inc ease o me hane po en ial262
was achie ed h ough combining manu e wi h biowas e and po en ial RCG cul i a ion263
in cu away pea lands. The la ges me hane ene gy p oduc ion po en ial is in he wes e n264
pa o he egion, whe eas no po en ial loca ions o biogas ins alla ions we e iden i ied265
in he Soini municipali y (Fig. 6). In pa icula , la ge-scale a ms (o e 50 heads o 266
ca le) ha e an impo an ole in u u e biogas p oduc ion in he s udy a ea. Only abou 267
20 % o he dai y a ms ha e o e 50 heads o ca le in Finland and he numbe o small268
a ms is cons an ly dec easing [41]. Fo example, in Denma k, he la ges a ms we e269
also iden i ied, in mos cases, as ele an and i al o u u e biogas p oduc ion; a e age270
a m size in Denma k has inc eased om 131 heads o ca le o 238 heads pe a m in271
en yea s ( om 1999 o 2009 [10]). Ag icul u al esidues, including slu ies and c ops272
p oduced o ene gy, ha e also been ound o be impo an biomass sou ces in o he 273
egional GIS-based biogas analyses, ep esen ing om 50% o o e 90% o o al biogas274
po en ial [13˗14] in s udied u al a eas.275
No ably, he cul i a ion o RCG on p io cu away pea lands was con i med as a276
po en ial eeds ock sou ce o a biogas plan in an a ea o in ensi e pea ex ac ion. In277
Ala us, he e we e wo a eas whe e cul i a ion o RCG on p io cu away pea lands278
could inc ease local biomass esou ces (Fig. 6). Howe e , he cu away pea lands a e279
usually loca ed o e 10 km away om a ms, which can make he logis ic a angemen s280
di icul (Fig. 7). Also, ce ain limi a ions o cu away pea lands mus be add essed, such281
as he di icul y o cul i a ing ag icul u al c ops in hese a eas because o ypical high282
wa e le els [42]. Al e na i ely, o es biomass could be conside ed on emo e cu away283

pea lands, and in ac landowne s gene ally p e e o es y as an a e -use al e na i e284
ins ead o ene gy c op p oduc ion [30].285
The ac ha sludge gene a ed in was ewa e ea men plan s and biowas e286
gene a ed in municipali ies and ou is cen es a e o en loca ed a away om la ge-287
scale a ms complica es he loca ion o he biogas plan . Howe e , in Kuo ane, he288
inc ease o ene gy po en ial is achie ed om combining he join me hane po en ial o 289
biowas e ( om one ou is cen e, g oce y s o es, and municipal collec ion acili ies)290
and la ge-scale a ms nea he own cen e (Fig. 8). Finally, he GIS ools used in he291
p esen s udy alloca ed biomasses acco ding o easonable anspo a ion dis ances (10292
km) and helped o plan biogas plan s sizing.293
294
Figu e 5. S udied eeds ocks and hei g oss biogas po en ials (MWh) in he s udy295
egion as box-and-whiske s plo s.296
297
Figu e 6. Feeds ock p oduc ion si es and hei di ision in o clus e s (gi en as numbe s)298
o he 13 po en ial a m biogas plan s (la ge ci cles) (>100 kW) and eigh po en ial299
cen alized biogas plan clus e s ( illed wi h colou ) (>300 kW).300
301
302
Figu e 7. Dend og am p esen ing cen alized biogas plan clus e s acco ding o a303
anspo a ion h eshold o 10 km in he s udy egion. Agglome a i e clus e ing based304
on comple e linkage was applied o combine biomass p oduc ion si es as clus e s when305
h eshold dis ance was no exceeded. Rec angles a e used o indica e clus e s, and306
symbols indica e ype o biomass. Biomass poin s (n = 189) and clus e IDs ( o al 43)307
a e indica ed in he bo om le co ne . Me hane po en ials a e gi en in blue.308
309
310
Figu e 8. Example o he sel -p og ammed op imiza ion ool o iden i ying a sui able311
loca ion o a powe plan by minimizing anspo a ion dis ance when biomasses a e312
spa sely dis ibu ed in a po en ial biogas p oduc ion a ea (clus e 19). The model313
minimizes he sum o o al anspo a ion needs. The po en ial plan loca ion is314
illus a ed as an as e isk (ene gy po en ial indica ed below he as e isk in MWh/a). The315
biomass sou ces a e deno ed wi h symbols explained in he legend o Fig. 7.316
3.2 Wood e minal scena io317
The op imal loca ions o wood e minals in he s udy a ea we e de e mined based on318
ke nel densi y analyses along wi h oad ne wo k da a (Fig. 9). The denses wood319
esou ces a e loca ed in no he n pa s o he Soini municipali y and on he bo de o he320
Äh ä i and Ala us municipali ies (Fig. 9). The oad ne wo k co e s he la e a ea qui e321
well, especially conside ing ha a class 1 oad (i.e., a highway) c osses he a ea (Fig. 9).322
In he case o Soini, he wood esou ces a e loca ed nea a oad ne wo k o lowe quali y323
class. Howe e , all he oads in he s udy a ea a e s ill sui able o uck anspo a ion324
o wood biomass.325
Wood e minals in hese p io a eas (Fig. 9) could be conside ed i wood326
p ocessing a in e media e e minals becomes popula , which would imp o e he327
balance o he wood supply and inc ease he need o wood s o age capaci y. The328
calcula ed wood e minal loca ions, howe e , we e no equal o eal exis ing e minals329
(Fig. 9). The e minal loca ions in Ala us, a he Äh ä i (Myllymäki) ailway s a ion,330
and in he cen e o Soini municipali y we e no cong uen wi h eal wood a ailabili y.331
Fu he mo e, exis ing e minals loca e in good logis ical si es (nea ailways and ucks)332
o p omo e la ge-scale wood u iliza ion wi hou conside ing o es esou ces. E en so, i 333
may be a ional o es ablish small-scale e minals o se e mo e local bioene gy plan s334
in he spo s ound in he p esen s udy (e.g., [43]).335
Fu he , in eali y, di e en wood p ocu emen o ganiza ions do conside he336
well-being o he oad ne wo k and en i onmen al limi a ions [45˗46], which he337
applied me hods in his s udy do no au oma ically conside . When linking limi ed338
model calcula ions and eal wood p ocu emen oge he , expe knowledge and339
consensus solu ions can be used in decision-making (e.g., [46]). Fo example, in la e340
sp ing ime, he e can be weigh limi a ions on local oads, and he d i e- h ough o 341
imbe ucks is o bidden.342

343
Figu e 9. Ke nel densi y map o wood esou ces ( ee s and olume in m3 ha-1) in he344
s udy a ea. Da ke colou s indica e g ea e densi y o wood esou ces ( o es in en o y345
da a [37]; oads [39]; municipal bo de s [38]). Po en ial wood e minal loca ions a e346
loca ed in a eas wi h dense wood esou ces nea he highes oad classes (in da ke 347
blue). Colou ep esen s ela i e densi y and no speci ic uni s.348
349
3.3 Feasibili y o he me hods o de ining he loca ions o bioene gy plan s350
The p esen s udy de eloped and assessed me hods consis ing o ou e op imiza ion,351
hie a chical clus e ing, loca ion op imiza ion, and ke nel densi y es ima ion o 352
iden i ying biomass p ocessing o s o ing loca ions in cases o mul iple eeds ock such353
ha anspo a ion dis ances a e minimized. The me hods op imize biomass354
anspo a ion om he collec ion poin o non-p ede ined powe plan loca ion, which355
shows he p og ess oge he wi h p e ious s udies using di e en GIS on bioene gy356
plan planning as summa ized in Table 3. The goal was o achie e he highes po en ial357
bioene gy p oduc ion and plan size wi h sho anspo a ion dis ances om collec ion358
poin s o all o he loca ions in he oad ne wo k. The esul s show ha hese me hods a e359
sui able o alloca ing biomass o bioene gy in u al a eas and he me hods can be360
conside ed as decision-making ools o help plan powe plan size.361
The op imiza ion me hods applied in his s udy p omo e he use o GIS ools in362
bioene gy planning. The same kind o R analyses ha e no p e iously been used in363
biogas plan planning while e.g. ke nel densi y analyses we e used in loca ion biogas364
plan s in Sou he n Finland (e.g., [14]).365
In u al a eas, i is impo an o include in he model he oad ne wo k and no 366
only Euclidean dis ance because geog aphic obs acles such as lakes and moun ains can367
a ec he s uc u e o he oad ne wo k in many cases. Fo example, in he p esen 368
s udy, he oad ne wo k conside ed he lakes, which o ms app oxima ely 7% o he369
o al s udy a ea, and only a ew o hem can be c ossed by using b idges [35].370
Consequen ly, he s uc u e o a oad ne wo k has an essen ial ole in anspo a ion371
cos s.372
Table 3. Selec ed GIS based decision suppo models s udied o di e en bioene gy373
applica ions.374
GIS me hod The me hod can be used o Re e ence
Ma ko chain model Fo ecas ing he spa ial dis ibu ion o
Danish li es ock in ensi y and u u e biogas
plan s [10]
Mixed in ege linea p og amming model Bio e ining plan
loca ion op imiza ion
by
emo e sensing and oad ne wo k [16]
GIS – Analy ical Hie a chy P ocess –
Fuzzy Weigh ed O e lap Dominance
(GAF) model
Decision suppo on sui able loca ions o
biogas plan s [12]
Ke nel densi y and p-median p oblem
Pinpoin ing a eas wi h high biome hane
concen a ion (Ke nel densi y). Whe eas p-
median p oblem is applied by choosing
acili ies such ha he o al sum o weigh ed
dis ances alloca ed o a acili y is minimized
[14]
Modi ied p-median p oblem E alua ing
biomass supply ca chmen s
(an
ex ension o he p-median model) [9]
Modi ied Dijks a algo i hm
A sys emic app oach o op imizing animal
manu e supply om mul iple small scale
a ms o a bioene gy gene a ion complex
including concep ual modelling,
ma hema ical o mula ion, and analy ical
solu ion.
[15]
A Mul ic i e ia Spa ial Decision Suppo
Sys em in eg a ed wi h GIS/ELECTRE
TRI
me hodology
Add essing eal-wo ld p oblems and ac ual
in o ma ion (e.g. soil ype, slope,
in as uc u es) in biogas plan s si e
selec ion.
[11]
The analy ical hie a chical p ocess (AHP)
Decision suppo p ocess, which cap u es
quali a i e and quan i a i e aspec s o
in o ma ion (such as en i onmen and
economy) in o GIS en i onmen o he
si ing o anae obic co-diges ion plan s
[13]
375
The me hod desc ibed in he p esen pape can be use ul o municipal-le el376
business de elope s and o p omo ing business ac i i y in u al a eas. The me hod377
helps o ecognize ene gy po en ials by clus e ing he eeds ocks and by inding378
ho spo s wi h ke nel densi y analysis. In pa icula , he biogas plan op imiza ion379
scena io was use ul o iden i ying po en ial a eas o bioene gy p oduc ion gi en380
mul iple po en ial eeds ocks. Fu he , he sel -p og ammed ool can help o op imize381
biogas plan loca ions by minimizing anspo a ion cos s, especially in si ua ions when382
candida e biogas plan loca ions ha e no been de ined in ad ance. Many GIS ools,383
such as e.g. Closes Facili y and Loca ion-Alloca ion in A cGIS, equi e such candida e384
poin s. One clea ad an age o his me hod is also ha he con igu a ion o biomass385
sou ces can be easily changed and he analysis can be e- un i some a ms decide o386
lea e ou om p oposed coope a i es.387
The assessed op imiza ion model can make loca ion de e mina ion easy when388
cen alized biogas plan s a e planned. Di e en ne wo k analyses and adjus ing he389
anspo a ion h eshold limi (10 km) lowe o highe could p o ide di e en 390
alloca ions o logis ical solu ions o biogas plan loca ion. Fo example, by adjus ing391
he h eshold limi o 12 and 15 km, he numbe o po en ial clus e s inc eases o 9 and392
11, espec i ely. The biogas plan s a e o en placed nea he spa ial mean o biomass393
sou ces, because in many cases he e a e se e al a he la ge biomass sou ces. In hese394
cases, he anspo a ion dis ances would s ill be less han 10 km, because he dis ances395
om biomass sou ces o he cen ally loca ed plan a e usually smalle han he396
maximum dis ance be ween he biomass sou ces. Also, i is possible o balance397
biomasses be ween clus e s a e wa ds o each an e en mo e e en dis ibu ion o 398
loca ions conside ing biogas po en ial among all clus e s.399
Acco ding o he applied biogas plan loca ion op imiza ion me hod, he simples 400
anspo a ion si ua ion is in hose la ge a ms (a leas 4,500 Mg o cow manu e pe 401
yea ) which a e conside ing he cons uc ion o a m biogas plan (>100 kW o g oss402
powe capaci y). In p ac ice, his means app oxima ely 200 dai y cows o abou 300403
bulls a a m. In hese cases, i may be easy o b ing addi ional eeds ock om smalle 404
a ms, because he manu e quan i ies in hem a e smalle and he eby anspo needs405
along he oads a e minimized. Acco ding o he op imiza ion model, he biogas plan 406
localisa ion si ua ion is pa icula ly demanding i he e a e 2-3 equal size a ms wi hin407
he po en ial clus e , and he a m’s own p oduc ion o manu e is no high enough o a408
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