Selection of Best Renewable Energy Source by Using VIKOR Method

Transcription

1 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 DOI /s CASE STUDY Selecton o Best Renewable Energy Source by Usng VIKOR Method Mansh Kumar 1 Cheran Samuel 1 Receved: 10 November 2016 / Accepted: 9 Aprl 2017 / Publshed onlne: 19 Aprl 2017 Sprnger Scence+Busness Meda Sngapore 2017 Abstract The ncreasng global demand or the sustanable development o electrcty sectors ncreased the contrbuton o renewable energy sources (RESs). RESs gve the lexblty to nstall generaton unts at demand areas and reduce transmsson and dstrbuton losses. Selecton o approprate RES s more strategc and decsve area. Ths s a complex mult-crtera decson makng (MCDM) problem o havng uncertan and conlctng actors. In ths work, we used the recently developed MCDM technque VIKOR method to choose best approprate RES alternatve or nstallaton at Banaras Hndu Unversty (BHU) campus, Inda. The advantage o VIKOR method s to have a soluton closest to the deal soluton havng an acceptable compromse o conlctng and non-commensurable crtera. For assgnng weghts to the derent crtera, we used analytcal herarchy process (AHP). The mportance o derent crtera has been assgned by decson-makers based on ther preerences. The result shows that the wnd turbne opton s the best choce or the case o BHU campus. Keywords AHP MCDM RESs VIKOR method Dstrbuted generaton Mansh Kumar mkumar.rs.mec13@tbhu.ac.n Cheran Samuel csamuel.mec@tbhu.ac.n 1 Department o Mechancal Engneerng, Indan Insttute o Technology (BHU), Varanas, , Inda Introducton Lmtaton o the conventonal energy sources and ther adverse envronmental eect causes the ncreased demand o RESs n electrcty generaton. Wth small scale generatng capacty o RESs, uses o dstrbuted generaton technologes wth smart grd concept have exponentally ncreased worldwde n the recent past. The uncertanty o power generaton rom the RESs along wth smart mcrogrd needs eectve tools and technques to get optmal utlzaton [1]. RESs plannng eorts nvolve ndng a set o sources and converson devces n the power sector, to meet the electrcty requrement or load demand n an optmal manner. RESs plannng decson also nvolves balancng multple aspects lke techncal, economcal, envronmental, and socal aspects over a perod. For mantanng the ecology and sustanable development, balancng o these actors s crtcally very mportant. The crtcal task o selectng RES becomes a strenuous procedure because the decson maker would have to make a choce between an abundance o alternatves [2, 3]. Mantanng harmony between RESs and grd supply s also a bg challenge [4]. Decson makers or nvestors nterest about the selecton o the sutable RES technology or selecton o the renewable energy projects has been contnuously growng. Optmal utlzaton o small-scale generaton unts o RESs helps us n multple ways lke reducng per unt generaton cost, avod carbon emssons and harness abundant avalable RESs. Based on past lterature n ths area, multple authors agreed on a large number o crtera consdered or makng the selecton o approprate RESs are more complex [5, 6]. For ths, the research communty s dong

2 8 Page 2 o 10 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 research to develop an approprate technque to grab preerences and to dene evaluaton models and algorthms or ths knd o problems [7, 8]. Plannng o RESs projects by usng mult-crtera analyss s beng attracted by the decson makers or the past many years. Wth ncreased utlzaton o RESs n recent tme, t also ncreased the mportance o decson-makng process n the selecton o best-tted RESs technology. Earler, dealng wth the problems o RESs by sngle crteron approaches was amed to denty the most ecent power generaton optons wth mnmum cost. Now a days, growng envronmental awareness moded the above decson-makng ramework. The need or the ntegraton o socal and envronmental consderatons n RESs plannng resulted n the ncreased usage o RESs technologes wth mult-crtera approaches [9]. Identcaton o an approprate alternatve wth the ncreased complexty o the decson-makng process s a very tedous task. At the operatonal level, RESs projects assessments dealng wth the attrbute s dcult to dene. An assessment may cover techncal or economcal areas whose boundares may not be easly dentable, or t may cover regons o the soco-economc, whch could be an eect on varous nterest groups or stakeholders wth ther soco-economc needs or ther demands [10]. Because o these dcultes, VIKOR method could be qute useul n undertakng dcult judgment procedures. The VIKOR method has been ntroduced n the work o Oprcovc and Tzeng [11] n the year 2004, to express the conlctng and ncommensurable attrbutes or crtera and assumng that compromse s acceptable or conlct resoluton, where the decson maker wants a soluton that wll be closest to the deal soluton, and all the alternatves would be evaluated accordng to all the recognzed crtera. VIKOR method ranks the alternatves and nds out the soluton wth compromse and closeness to the deal soluton. Ths shows that the VIKOR method s a mult-crtera decson-makng technque whch has a smple computatonal procedure and that allows smultaneous consderaton o the closeness to the deal and ant-deal alternatves. As per the prevous lterature, there are many authors who have used VIKOR method n ther work n a comparatve manner [7, 11]. The present paper used ths methodology or the decson support to solve the RESs selecton problem. The useulness o ths methodology has been establshed through a case o BHU campus. For whch, decson-makers want to nd and select the approprate RES at BHU campus and wll provde decson support servces on ths bass. Organzaton o the paper s n the ollowng manner: Lterature Revew descrbes lterature revew o the RES selecton process and the related work. Secton Proposed Approach ntroduces the AHP method to weght crtera and use o VIKOR method or rankng the alternatves. In A Case o BHU Campus the proposed method s llustrated by a case o BHU campus. Secton Regonal Importance shows regonal mportance n the selecton o best RES. Fnally, Concluson concludes ths work. Lterature Revew The modern power sector s movng towards adopton o RESs to overcome excessve carbon emssons and lmtatons o ossl uels [2, 12]. In the orm o RESs system, use o small scale renewable energy based power generatng unts s more cost eectve wth multple advantages over the other modes o power generaton systems [3, 10, 13 15]. RESs gves us the lexblty or nstallaton o generatng unts n remote or rural areas, where transmsson and dstrbuton o power would not be easble [16 18]. Kark et al. [19] studed over gettng envronmental benet rom the rural electrcaton n Inda through RESs. Kumar and Ravkumar [20] dented hybrd RESs technology to help needs o the urban buldng n Inda. For the easblty, ncreased penetraton o RESs should mantan the reslence o transmsson and dstrbuton network [21]. On-ste power generaton rom the RESs requres selecton o the sutable energy sources or the nstallaton regon based on multple crtera [5, 6, 22]. In developng countres, selecton o optmal RES n the orm o dstrbuted generaton technology wll gve us the maxmum payo wth the sustanable envronment [23, 24]. In a work o Kumar et al. [25] deployment o the wnd and solar energy n power dstrbuton system to acheve securty o supply, cost compettveness, and envronmental responsblty have been studed. A novel ntellgent energy management system (IEMS) or a DC mcrogrd to connect wth Photovoltac panels, utltes, and storage system, mplemented rom Chauhan et al. [26] or load sharng, reduce power loss and mprove the system relablty. The mpact o Low voltage drect current (LVDC) grd wth dstrbuted generaton n power dstrbuton has been studed by Chauhan et al. [27] to reduce power losses and mprove power qualty, whch manly consdered photovoltac RES or the dstrbuted generaton. RES selecton ntally requres the dentcaton and elaboraton o derent decson crtera that wll gude n the decson-makng process. Derent decson-makng groups may choose derent decson crtera or RES selecton based on some actors whch aect n decsonmakng process lke most aected actors would be the cost actors and envronmental losses. San Crstóbal [22] proposed a model that consders power, nvestment rato, mplementaton perod, operatng hour, useul le, operaton & mantenance costs, tons o CO2 avoded actors or selecton o sutable renewable energy based generatng

3 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 Page 3 o 10 8 unts n Span. In the recent work o Ahmad and Tahar [28], they dvded ther sub-crtera under the major crtera o techncal, economcal, socal, and envronmental. Kahraman et al. [29] dvded ther sub-crtera or the RESs plannng nto our such as technologcal, envronmental, soco-poltcal, and economc crtera. Based on the number o crtera, RESs plannng wll requre the mult-crtera decson-makng analyss. Makng decson s an ntegrated part o human le, whch s comng rom the hstory o the manknd. MCDM technque s the most amous technque or decson makng n the recent world. Authors lke Zmmermann [30] have dvded MCDM nto two categores; one s multobjectve decson makng (MODM), and another one s mult-attrbute decson makng (MADM). However, both are used to represent the same class o MCDM models. The major derence between the two groups o methods s the selecton process o the alternatves. In the MODM method, whch also known as mult-objectve programmng problem, nstead o predetermned alternatves, we have a set o optmzaton objectve unctons subject to constrants. In the MADM method, alternatves are predetermned, and a set o alternatves would be evaluated or the gven set o attrbutes. Selecton o the best alternatve s based on the comparsons between each alternatve on gven crtera or attrbutes [29]. In renewable energy projects lke wnd arm projects, solar projects, geothermal projects or bomass projects, MCDM methods have been wdely used. For decdng the optmum mx o RESs based dstrbuted generaton technology wth varous sectors lke central power generaton system, MODM methods have been used [2, 3, 9, 10]. In the work o Borges and Antunes [31], renewable energy economc plannng s showng the nteractons between techncal and economc parts o the system. Amongst the number o decson-makng technques, Decson Support Systems, MODM, MADM (manly AHP, PROMETHEE, ELECTRE, TOPSIS and Mult-attrbute utlty theory), and Fuzzy programmng s the most appled MCDM technque n renewable energy projects. For an applcaton o the AHP method, the structure o a multple crtera problem s herarchcally and breakng down the problem nto smaller consstent parts [32]. In ths system, the objectve becomes at the top o the herarchy where as crtera and sub-crtera become at the levels, and sub-levels o the herarchy and decson alternatves become at the bottom o the herarchy. Selecton o the sutable alternatve depends on the comparson between the derent alternatves on each crteron. Multple authors used AHP method or the renewable energy plannng projects [13, 28, 29, 33]. Other knds o decson-makng methods used n renewable energy nvestment projects are Fuzzy programmng to evaluate the selecton o renewable energy alternatves [29, 34], Decson Support Systems based on uzzy decson support model or the energy-economy plannng [31, 35], a methodology o Geo-spatal mult-crtera analyss used to set up the wave energy arm [36], and a lnear programmng optmsaton methodology n the orm o energy low optmsaton model (EFOM) s used or the regonal energy plannng wth RESs and envronmental constrants [37]. Takng nto consderaton the decson makers preerences, MAUT (mult-attrbute utlty theory) s developed to help decson-makers allocate utlty values to get outcomes rom the evaluaton o these utlty values regardng multple attrbutes and obtaned the overall utlty measures by combnng these ndvdual assgnments [38]. Jones et al. [39] used ths method n the plannng o RESs or ther respectve work, and Golab et al. [40] used ths theory n the work o solar energy project portolo selecton. For the dscrete nature o crtera n both quanttatve and qualtatve term, the ELECTRE method provdes complete orderng o the alternatves. Ths method chooses a set o alternatves that are preerred or most o the crtera, and that wll not cause an unacceptable level o dscontent or any o the crtera. The ELECTRE method gves graphs or strong and weak relatonshps based on a concordance, dscordance ndces, and ther threshold values. Wth an teratve procedure, we can have a rankng o alternatves rom the graph o strong and weak relatonshps. Beccal et al. [10] and Georgopoulou et al. [41] used ths method n ther renewable energy project. Other MCDM method s PROMETHEE method, whch uses the outrankng prncple to rank the alternatves and combned wth ease o use to reduce the complexty. Wth PROMETHEE method we can perorm a par-wse comparson o alternatves or the rankng o the alternatves on a gven number o crtera. PROMETHEE technque has been used by Goumas et al. [42], Goumas and Lygerou [43], and Haralambopoulos et al. [44] n the work o geothermal project. Pohekar and Ramachandran [45] hasusedprometheemethodorthe utlsaton o parabolc solar cookers n Inda. Mladneo et al. [46] used PROMETHEE technque to select hydro power plant nstallaton area. Another dstance-based MCDM method s the TOPSIS method, whch determnes a soluton o the shortest dstance rom the deal soluton and the arthest dstance rom the negatve-deal soluton, but ts drawback s that t does not gve normaton o the relatve mportance between these two dstances [47, 48]. Kaya and Kahraman [49] used moded uzzy TOPSIS method or the selecton o best energy technology, and Şengül et al. [5] used ths technque or the rankng o renewable energy supply. Comparatve analyss between TOPSIS and VIKOR s shown n the artcle by Oprcovc and Tzeng [11]. Both the VIKOR and TOP- SIS methods were developed as an alternatve to ELECTRE method are based on an aggregatng uncton or closeness

4 8 Page 4 o 10 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 to the deal, and that orgnates n the compromse programmng method. Both the VIKOR and TOPSIS methods ntroduce derent orms o aggregatng uncton or the rankng o alternatves and perorm derent knds o normalzaton procedure or the elmnaton unts o the crteron uncton [11]. The VIKOR method uses lnear normalzaton technque and the normalzed values, whch do not depend on the assessment unt o each crteron. The TOPSIS method uses vector normalzaton or a partcular crteron, and the value o normalzaton could be derent or a derent evaluaton unt. As regards o the aggregatng uncton, VIKOR method uses an aggregatng uncton that wll represent the dstance rom the deal soluton, wll consder the relatve mportance o all the crtera, and wll have a balance between total and ndvdual satsacton. On the other sde, TOPSIS method uses an aggregatng uncton that wll nclude the dstances rom the deal pont as well as rom the negatve-deal pont wthout havng ther relatve mportance. However, the reerence pont could play a major role n the decson-makng process, and havng the reerence pont near to deal s the justcaton o human choce [11]. Ths paper has shown that the use o the Compromse Rankng Method also known as the VIKOR method n the selecton o the RESs. Along wth VIKOR method, we used AHP technque or assgnng the weghts to have relatve mportance between each attrbute. Smlar approaches can be ound n San Crstóbal [22],whoappledthesame method or the selecton o renewable energy alternatve n Span, or n Kaya and Kahraman [50], who appled the VIKOR method along wth AHP under uzzness or the renewable energy plannng wth a case o Istanbul. In ths work, authors consdered a regon specc problem o BHU campus or gettng the better results. Multple authors suggested that a combnaton o these two wll allow the decson-makers to methodcally allocate the values o relatve mportance to the attrbutes or crtera based on ther preerences. Ths paper assumes that each alternatve s evaluated accordng to all the crtera, and the compromse rankng would be perormed by comparng the computaton o closeness to the deal soluton F*. From the use o Lpmetrc n compromse programmng method, the mert o mult-crtera or compromse rankng has been developed by Yu [51] and Zeleny [52]. In bre, we can say that VIKOR method works on rankng and selecton o the alternatves rom the gven one n the exstence o conlctng crtera. It gves a compromse soluton that wll be accepted by the decson makers because o ts maxmum group utlty or the majorty, and o the mnmum ndvdual regret or the opponent. By the use o lnear normalzaton, ths method representng the closeness to the deal soluton based on aggregatng uncton. Where, n TOPSIS method, use o vector normalzaton and two reerence ponts does not consder the relatve mportance o the dstances. From the group utlty measures, PROMETHEE method ranks the alternatves wth a lnear preerence uncton smlar to the rankng o VIKOR method. Also, ELECTRE II gves smlar value lke VIKOR method rom the lnear surrogate crteron unctons. Proposed Approach Perormance Evaluaton Usng AHP Method Wth the help o AHP method, we can assgn weghts to the relatve mportance o the attrbutes [32]. Based on our objectve uncton we can nd out the relatve mportance o the attrbutes. For that, we should have to construct a par-wse comparson matrx wth a scale o the relatve mportance. Values entered n the par-wse comparson matrx should be based on Saaty s Nne Pont scale. Saaty s Nne pont scale or the AHP s; comparson o an attrbute wth tsel wll always assgn the value o 1, t means the man dagonal entres o the matrx wll have same values 1. For the other cells the numbers 3, 5, 7, and 9 based on experts verbal judgments moderate mportance, strong mportance, very strong mportance, and absolute mportance along wth 2, 4, 6, and 8 or compromse between the prevous values. Suppose we have n number o attrbutes, the par-wse comparson matrx wll develop between the th attrbutes and jth attrbutes whch wll be a square matrx A nxn and aj wll denote the comparatve mportance o th attrbute wth jth the attrbute. In ths par-wse comparson matrx, a j = 1when= janda j = 1/a j. The egenvector or prorty weghts vector w wll be calculated by the summaton o each column o the matrx and then dvde each element o the matrx wth the summaton o ts column. Then, averagng across the rows wll gve us the normalzed egen vector. a 11 a 1n A =..... a n1 a nn We have to know the vector w = [w 1,w 2,.,w n ] whch represents the weght o the each crteron whch s gven n par-wse comparson matrx A. To recover the vector w rom the par-wse comparson matrx A, t wll go or a method o two-step procedure: For each o the A s columns dvde each entry n column o A by the sum o the entres n column. Ths yelds a new matrx, called Anorm (or normalzed) n whch the sum o the entres n each column s 1.

5 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 Page 5 o 10 8 Estmate W as the average o the entres n row o A norm. w = n n=1 a j nj=1 nj=1 n a j Where n = number o crtera λ max = (Aw) nw CI = (λ max n)/(n 1) CR = CI / RI For gettng the value o CI, we must have the λ max by multplyng each element o the matrx wth the egenvector. The smaller the CI represents the, smaller the devaton rom the consstency. I CI s sucently small, t means the decson-makers comparsons are probably consstent enough and gve useul estmates o the weghts or ther objectve. Perectly consstent decson-maker wll gve the th entry n AW T = n (th entry o W T ). It shows that a perectly consstent decson-maker has CI = 0. Then, nd out the consstency rato (CR) wth dvdng the consstency ndex (CI) rom the random ndex (RI). Fnally, the CR<0.01, then the degree o consstency s satsactory. Otherwse, judgment matrx needs to be readjusted untl satsactory. Use o VIKOR Method When the decson maker s unable to take a decson or doesn t know to express ther preerences at the begnnng stage o the system desgn, the VIKOR method would be an eectve tool or the mult-crtera decson-makng process. For the value o a maxmum group utlty o the majorty (mn S, gven by Eq. 2), and a mnmum ndvdual regret o the opponent (mn R, gven by Eq. 3), obtaned compromse soluton would be accepted by the decson makers. Based on the nvolvement o the decson-makers preerences by weghts o crtera, the compromse solutons would be the bass or negotatons. The result o the VIKOR rankng depends on the deal soluton Q wth values o v, whch wll be only or a gven set o alternatves. Any changes to a gven set o alternatves wll lead to the result o moded VIKOR rankng or the new set o alternatves. The xed deal soluton would be dened by the decson maker based on the best and the worst values, but t could be avoded. Here each alternatve would be evaluated wth each crteron uncton and, the compromse rankng would be perormed wth the comparson o the measure o closeness to deal soluton F*. Compromse soluton F C wll be a easble soluton that wll be the closest to the deal soluton and wll have a compromse establshed by mutual concessons [8]. Wth mult-crtera measure or the compromse rankng o alternatves s developed rom the Lp-metrc by usng an aggregatng uncton rom the compromse programmng method Yu [51], Zeleny [52]: [ n L pj = =1 { w ( j )/( )} ] p 1/ p 1 p, j=1,2,...,j where L 1,j denoted as S j n Eq. 2 and L,j denoted as Rj n Eq. 3, are used to ormulate the rankng measure. For the VIKOR method, the number o j alternatves s denoted as a 1,a 2,..., a j. For any alternatve a j the ratng o the th acet s denoted by j, and ths s the value o the th crteron or the alternatve a j ; where j=1,2,...,m and =1,2,...,n. The compromse rankng algorthm o the VIKOR method s dvded nto the ollowng our steps whch are gven below [11]: Step I: For all the crteron unctons, nd out the best and the worst values, = 1,2,...,n. I the th uncton represents a benet then = j and = j, whereas the th uncton represents a cost = j and = j. Step II. Compute the values o S j and R j,j= 1,2,...,m rom the relatons o S j = n =1 w R j = [ w ( ( j )/( j )/( )] ) Where w denotes the weghts o crtera, whch expresses the decson maker s preerence or the relatve mportance o the crtera. Step III: compute the values o Q j, rom the gven relaton Q j = v ( S j S )/( S S ) +(1 v) ( R j R )/( R R ) (4) Where S = S j ; S = S j ; R = R j ; R = R j and as a weght v has been ntroduced or the strategy o maxmum group utlty, whle (1 - v) s or the weght o the ndvdual regret. The soluton wll be obtaned by S j wth a maxmum group utlty based on majorty rule, where the soluton wll be obtaned by R j wth a mnmum ndvdual regret o the opponent. In general, the value o the v s taken as 0.5, but we can take any value o v n the range o 0 to 1. Step IV: Now rank the alternatves wth the sortng o the results o S, R, and Q n ncreasng order. From ths we wll have three rankng lsts or S, R, and Q. Suppose we have a compromse soluton o the alternatve A 1 best ranked by (1) (2) (3)

6 8 Page 6 o 10 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 the mnmum value o the measure Q, then t should satsy the gven condtons. Propose as a compromse soluton the alternatve A 1, whch s the best ranked by the measure Q(mnmum), the ollowng two condtons are satsed: a. Frst one s the acceptable advantage. Q ( A 2) Q ( A 1) DQ, wheredq= 1/ (J - 1) and A 2 s the alternatve wth the second poston on the rankng lst by Q; b. The second one s the acceptable stablty n decsonmakng. The alternatve A 1 should also be the best ranked by S or/and R. Ths compromse soluton should be stable or a decson-makng process, that could be the strategy o maxmum group utlty (when v >0.5 s needed), or by consensus (v 0.5), or wth veto (v <0.5). I one o the above condtons s not satsed, then we wll have to propose a set o compromse solutons, whch wll consst o: c. Alternatve A 1 and A 2 when the condton b s not satsed, or d. Alternatves A 1, A 2,..., A M when the condton a s not satsed and, A M s determned by the relaton Q ( A M) Q ( A 1) <DQor maxmum value n means the postons o these alternatves are n closeness. A Case o BHU Campus One o the characterstcs o the BHU power consumpton system s ts hgh degree o dependence on ossl uel based central power generaton system. Lmtatons o conventonal energy sources and ther economc mpact wth envronmental concern are the motvaton towards the adopton o RESs. Wth small scale generatng capacty and lexblty o onste power generaton ncreased the demand or RESs based dstrbuted generaton technology and helps to reduce the load o grd supply. In our case, we are proposng a set o alternatves whch could be geographcally easble or onste power generaton at BHU campus. Wth the overall am o makng t possble and havng ten-megawatt capacty nstallaton lmtaton, we have to select the best RES alternatve and prortze them or dstrbuted generaton at BHU campus. To do so, we have set more ambtous goals n renewable energy area that s developng rapdly and has establshed new measures to support energy sector that has not yet been managed to take o. From the derent areas covered by the overall renewable energy Project, we have selected as an example or mult-crtera decson-makng, only the easble alternatves or the electrc generaton at BHU campus. These are shown n Table 1, whch are photovoltac (PV), concentrated Table 1 Lst o renewable energy alternatves proposed n a case o BHU campus, Inda Alternatves A1 A2 A3 A4 A5 PV CSP WT BM GT solar power (CSP), wnd turbne (WT), bomass (BM) and geothermal (GT). We have to prortze alternatves based on selected crtera, whch aect n decson makng. We consdered regon specc crtera or BHU campus to have better smulaton and manageral decson. The desgned model evaluated wth these crtera are shown n Table 2. Consultaton wth experts and department o Electrc and Water Supply Servce (EWSS) BHU, we consdered the crtera specc or case o BHU: Investment Cost (Crores), Operaton and Mantenance Cost (INR/KWh), Implementaton Perod (Year), Power Generaton (MW), Annual Operatng Hours, Envronmental Loss (gco2eq/kwh), Useul Le (Year), Area Acquston (square meter). Consderaton o the regonal actors o BHU regon s helpul n selecton o the best alternatve. Values o each crteron or derent alternatves have been gven n Table 3. Investment Cost crteron shows ndvdual nvestment cost o derent alternatves n BHU campus. Expected uture Operaton and Mantenance Cost, and Implementaton Perod data or derent technologes are gven by the EWSS, BHU. A Power Generaton crteron s derved wth geographcal data lke hourly wnd speed and solar rradaton o BHU regon. Hourly wnd speed and solar rradaton data have been taken rom the Natonal Renewable Energy Laboratory webste or BHU regon wth N to Nand E to E[53]. Annual Operatng Hours crteron s showng a number o hours or power generaton n a year. Table 2 Lst o crtera or the selecton o sutable RES Crtera C1 C2 C3 C4 C5 C6 C7 C8 Investment Cost Operaton and Mantenance Cost Implementaton Perod Power Generaton Annual Operatng Hours Envronmental Loss Useul Le Area Acquston

7 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 Page 7 o 10 8 Table 3 Numercal values o each crteron or each alternatve Crtera PV CSP WT BM GT Investment Cost (mn) Operaton and Mantenance Cost (mn) Implementaton Perod (mn) Power Generaton (max) Annual Operatng Hours (max) Envronmental Loss (mn) Useul Le (max) Area Acquston (mn) Envronmental Loss s consdered as gram equvalent o carbon emtted rom derent technologes per kwh o power generaton. Le span o the derent alternatves s consdered as Useul Le crteron. Area requred or nstallaton o derent technologes s consdered as Area Acquston / /9 1/ /4 1/2 1/3 A = 1/8 1/4 1/2 1 31/5 1/3 1/5 1/9 1/7 1/2 1/3 11/7 1 1/5 1/ /7 1/ /3 1 1/2 1/3 1/ /5 2 1 W1=0.36, W2=0.19, W3=0.04, W4=0.04, W5=0.03, W6=0.18, W7=0.05, W8=0.10 λ max = 8.88 CI = CR = CR<0.1 Table 4 s havng the benet and cost values o each crteron. It represents the maxmum values or the benet and mnmum values or cost crtera. Table 5 represent the rankng o gven alternatves wth ther S and R values. Values Table 4 Benet and cost values o each crteron Crtera Investment Cost (mn) Operaton and Mantenance Cost (mn) Implementaton Perod (mn) 1 2 Power Generaton (max) Annual Operatng Hours (max) Envronmental Loss (mn) Useul Le (max) Area Acquston (mn) Table 5 Rankng o alternatves based on ther majorty S and opponent R values PV CSP WT BM GT S j R j o Q rom the value o S and R or each alternatve wth derent values o v n between 0 and 1 have been shown n Table 6. Rankng the proposed alternatves by the VIKOR method that we have proposed as a compromse soluton and or all the consdered values o v, the alternatve wnd turbne s the best one. The alternatve o a wnd turbne wth the capacty o ten megawatts s the best ranked rom the values o Q. As ths alternatve s also the best ranked by S and R, condtons IV-a and IV-b are satsed. Regonal Importance As a developng country, wth ts ast-growng populaton and economy, Inda s acng ncreasng demand or energy due to technologcal penetraton n human le. Lmted avalablty o conventonal energy sources and ts negatve envronmental eects restrcts Inda to ulll ts energy demand. Inda s a major energy-mportng country and tryng to reduce the country s dependence on mported conventonal energy sources. An nsucent quantty o domestc conventonal energy resources, commtment to reduce carbon emsson levels, has orced the country to change ts energy supply to renewable and sustanable resources. Inda has abundant reserves o RESs that can be used as a major part o the decentralzed power generaton system to meet the total energy demand. The government o Inda has set Table 6 Values o deal soluton Q or derent values o v v PV CSP WT BM GT

8 8 Page 8 o 10 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 an ambtous target o 175,000 MW o renewable power by In the rst quarter o the year 2017, the percentage contrbuton o RESs has reached to 15.9 percent o total power capacty n Inda [54]. Current nstalled capacty and the capacty under constructon would be able to meet Inda s power demand tll about 2026, and no new nvestments are lkely to be made n coal-based power generaton, sad a report released by The Energy and Resources Insttute (TERI). The report also estmates that beyond , new power generaton capacty could be all renewable, based on cost compettveness o renewable as well as the ablty o the grd to absorb large amounts o renewable energy together wth battery-based balancng power [55]. Regonal dstrbutons o the RESs vary wth geographcal changes. The harnessng o RESs needs case-specc analyss to get the sutable mode o RES or the nstallaton. In ths work, we consdered a case o BHU campus or nstallaton o sutable RES based dstrbuted generaton unts to help n reducng carbon emsson levels and a load o grd supply. Ths wll also help to acheve the vson o government o Inda to develop sustanable power generaton system. BHU s located n the north Inda between N lattude and E longtude. It s one o the largest unverstes regardng land mass n Inda; BHU campus s a mnature representaton o resdental regons n the country spread over 1300 acres wth approxmate resdents. In ths work, the ve RESs that could be easble to generate electrcty at BHU campus have been taken nto consderaton. These RESs are photovoltac, concentrated solar power, wnd turbne, bomass and geothermal. Determnaton o the most approprate RES s carred out usng the steps descrbed n the methodology secton. Followng steps are gven n methodology secton, rst, determnes a score va a par-wse comparson or the regon specc crtera to weght them. The lsted crtera n preerence rankng o RESs at BHU campus s the Investment Cost, ollowed by the Operaton and Mantenance Cost, Implementaton Perod, Power Generaton, Annual Operatng Hours, Envronmental Loss, Useul Le, and Area Acquston. Accordng to these results, the prmary necessary condtons or the selecton o RES at BHU campus s the cost actors and envronmental loss. In recent years some authors have made mportant contrbutons n the area o selecton o RESs n ther research works. In multple studes by derent authors, major works have been done n a generalzed way to plannng renewable energy or the natonal level. Generalzaton o renewable energy plannng devates rom ts regonal actors and lmtatons to get best sutable regon specc alternatves n dstrbuted generaton system. Avalablty o RESs s hgh dependent on geographcal dversons and clmatc condtons. Kabak and Dağdevren [56] consdered actors aectng n the selecton o RESs or the plannng o renewable energy n Turkey. Tasr and Suslawat [57] dented that hydro power source s rch source or the naton Indonesa, whch may gve derent results or derent locaton o the country. Dakoulak and Karangels [58] studed or the country Greece to denty the best alternatve o RES. Şengül et al. [5] dented that hydro power source s the best source or the country Turkey, dependng on regonal potental and mportance hydro power ecency may vary wth locatons or some other alternatve can be perect n derent locaton. Ahmad and Tahar [28] consdered a lst o alternatves o RESs to select the best alternatve o RES or the country Malaysa. Kahraman et al. [29] dented that wnd energy source s a perect source o energy n Turkey whch wll der n nstallaton regons and ther local manageral challenges. Work o Kaya and Kahraman [9] shows regonal mportance n ther work and dented best-tted alternatve n a specc regon, whch gves wnd energy s the most approprate renewable energy opton, and Çatalca dstrct s the best area among the alternatves or establshng wnd turbnes n Istanbul. The present study supports the decson taken by the planner to utlze optmum avalable RESs or the BHU campus. Thus the mult-crtera decson makng analyss showed that the wnd turbne s determned to be the most approprate renewable energy supply system or BHU campus. Addtonally, the photovoltac s determned to be the second one. The planner o ths project should nvest, n order o prorty n these systems. The planner should also evaluate the projects whch are related to these RESs. Thus, nvestment prortes can be planned accordng to the rankng. The benets o expandng these energy sources would be enormous; RESs would reduce BHU s dependency on grd supply and elevate the envronmental hazards by dependng almost completely on ndgenous resources. The cost o electrcty, whch s droppng rapdly, when drawn rom RESs, opens up the competton to many conventonal technologes. Renewable technologes have mnmal uel costs, and they cannot be exhausted easly. In ths context, ths study proposes a scentc model to prortze alternatve RESs or a regon specc wth ther geographcal actors. Evoluton o smart grd technology promotes decentralzed power generaton wth optmal utlzaton o regonal RESs. Concluson Selectng the best RES rom a set o renewable energy nvestment projects requres derent groups o decsonmakers nvolvement n the decson-makng process. It s well known that the number o actors consdered n the

9 Technol Econ Smart Grds Sustan Energy (2017) 2: 8 Page 9 o 10 8 decson-makng process makes ths more complex. In ths work, we have taken eght actors or rankng o the ve alternatves n the decson-makng process or the selecton o sutable RES at BHU campus. For ths knd o problem, tradtonal sngle-crteron decson-makng process s unable to handle anymore. The polcy ormulaton or the use o RESs under rapdly growng renewable energy markets should be addressed n a mult-crtera context. For gettng the soluton, we have used the VIKOR method n ths work, whch gves the mult-crtera rankng ndex wth the partcular measure o closeness to the deal soluton. Weghtng the mportance o the derent crtera or rankng o the gven alternatves, we used AHP technque wth VIKOR method that allows the decson-maker or assgnng the values o relatve mportance to the attrbutes wth ther preerences. The results have shown that the wnd turbne alternatve s the best choce, ollowed by the photovoltac alternatve. 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