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Research ArticleA Systematic Evaluation Model for Solar Cell Technologies

Chang-Fu Hsu,1 Rong-Kwei Li,1 He-Yau Kang,2 and Amy H. I. Lee3

Department of Industrial Engineering and Management, National Chiao-ung University, Hsinchu , aiwan Department of Industrial Engineering and Management, National Chin-Yi University of echnology, aichung , aiwan Department of echnology Management, Chung Hua University, No. , Sector , WuFu Road, Hsinchu , aiwan

Correspondence should be addressed to Amy H. I. Lee; [email protected]

Received October ; Revised February ; Accepted February ; Published April

Academic Editor: Ching-er Chang

Copyright Chang-Fu Hsu et al. Tis is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Fossil uels, including coal, petroleum, natural gas, and nuclear energy, are the primary electricity sources currently. However, withdepletion o ossil uels, global warming, nuclear crisis, and increasing environmental consciousness, the demand or renewableenergy resources has skyrocketed. Solar energy is one o the most popular renewable energy resources or meeting global energydemands. Even though there are abundant studies on various solar technology developments, there is a lack o studies on solartechnology evaluation and selection. Tereore, this research develops a model using interpretive structural modeling (ISM),benets, opportunities, costs, and risks concept (BOCR), and uzzy analytic network process (FANP) to aggregate experts opinionsin evaluating current available solar cell technology. A case study in a photovoltaics (PV) rm is used to examine the practicalityo the proposed model in selecting the most suitable technology or the rm in manuacturing new products.

1. Introduction

Energy is an essential element or civilization development omankind and quality improvement o lie. Te use o ossiluels and other natural resources has resulted in detrimentalimpacts on the environment, especially through the damageto the air, climate, water, land, and wildlie []. With increasein both environmental awareness and global demand orenergy, the utilization o clean energy sources is necessary.Although global economic recession has slowed the demandor energy currently, renewable resources energy is still

necessary or the green environment and or the economicgrowth in the long term. Solar energy, one o the promisingand clean renewable energy sources, is becoming a avorableoption o renewable energy source [].

Photovoltaic (PV) solar cells are semiconductor devicesthat transer solar radiation into electricity by convertingthe energy o the sunlight to direct current electricity aferphotovoltaic effect []. Te solar panels that consisted oseveral solar cells made up o photovoltaic material arethe key device to generate the photovoltaic power. Due tothe strong need or renewable energy o solar cells, solarphotovoltaics is now the third most promising renewableenergy source to provide cleaner and abundant energy afer

hydro- and wind power []. However, the major issue o solarcells encountered is still the high energy cost compared toconventional energy sources []. With the improvement intechnology and increase in manuacturing scale, the cost ophotovoltaics solar cells has reduced continuously since therst cells were produced []. Te manuacturing o PV solarcells typically involves similar but simpler methods to thoseapplied in chip abrication. PV solar cells can be categorizedinto two major types: waer-based silicon and thin lm.Currently, cell materials applied to photovoltaic solar cellsinclude crystalline silicon, III-V cells, thin lm chalcogenide,

amorphous/nanocrystalline silicon, and organic thin lm ormodule, with different conversion efficiencies and manuac-turing technology [].

Regardless o the effort in making proper cost-benetsolar cells by using new materials and new technologies,the predominant waer-based silicon technology, or so-calledrst-generation solar cell [], is still expected to maintainits market share at levels o around % []. A lot oresearch continues in the eld o silicon waer-based solarcell to achieve the goal o lower cost and higher conversionefficiencies or obtaining the most possible electricity romthe least amount o silicon []. Tere are two types o thecrystalline solar cells: single crystalline silicon solar cells

Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2014, Article ID 542351, 16 pageshttp://dx.doi.org/10.1155/2014/542351
http://dx.doi.org/10.1155/2014/542351http://dx.doi.org/10.1155/2014/542351

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Mathematical Problems in Engineering

and polycrystalline silicon solar cells. Te rst one usesmonocrystal substrates rom pure homogenous silicon withthe highest efficiency (up to %) []. Te process osingle crystalline is much like those applied to abricatesemiconductor chips; however, they are the most expensiveto manuacture because o the need o a crystalline ingot

o pure silicon []. Polycrystalline (also called multicrys-talline) silicon waers, which are a material consisting omultiple small silicon crystals, are made by melting and thensolidiying silicon. Te modules are made rom an array osilicon waers that have been connected together. With thecharacteristic o large areas manuacturing, polycrystallinesolar cells currently have the largest share o the market, withequivalent module efficiency and lower abricating costs thanthe monocrystalline type.

With the huge growth expectations o thin lm solarcell technologies, the competing market price o crystalline-silicon has slowed the development o thin lm solar cell.Te latter is expected to grow anyway at a lower rate becauseo its potential reduction o production costs, low materialconsumption, lower energy consumption, and a shorterenergy payback time []. Tereore the thin lm solar cellswill stabilize their market share over the next ve years [].Te silicon waers used to make crystalline silicon solar cellsare costly, composed o % o the nal module cost [].In opposite, thin lm solar cells require only a ew micronso thickness o silicon on substrate compared to hundreds omicrons o thickness or a waer-based cell []. Nevertheless,there are some aspects that need to be improved or thethin lm solar cells technology such as better solar radiationconversion efficiency, more product stability or differentabsorption rates o lights with different wavelengths, andlower deterioration capability aferextensivesun exposure orlonger product lietime []. Tere is also a third-generationsolar cell technology, which attempts to improve the conver-sion efficiencies light radiation o thin lm technologies to% while maintaining low production costs []. Someapproaches include multijunction photovoltaic cell (multipleenergy threshold devices), modiying incident spectrum(concentration), using excess thermal generation (by UVlight), and using inrared spectrum [].

Advanced production technologies can help reduce pro-duction cost, improve product quality, and increase yieldrate, and these technologies can be related to process engi-neering, system integration, production automation, andprocess equipment []. Furthermore, the introduction o

new materials (such as nano- and microcrystalline siliconthin lm solar cell), advanced devices (such as laser scriber),and new methods (such as extremely thin absorber) canalso enhance solar conversion efficiency, decrease productioncosts, and extend product lietime [, ]. Te demand oraw materials increases substantially []. For example, glasssubstrate and silane, the material or making crystallinesilicon, are essential materials or making thin lm solar cellsand modules [].

Even though there are abundant studies on the devel-opment o various solar technologies, there are very ewstudies on solar technology evaluation and selection. osurvive in the global competition, rms need continuously to

develop new products these days. Beore a new technology isintroduced, a rm needs to consider and evaluate availabletechnologies rst and then select the most suitable one inan efficient way. It is a multidisciplinary process to makethe decision in choosing the most appropriate technologyto abricate products since this process needs to integrate

different proessional knowledge, production management,and market trend. Tereore, the decision should not onlyconsider the expected benets a technology can bring inmaking the nal products with specied quality, but alsocover other aspects, such as opportunities, costs, andrisks. Asa result, the technology selection is a sophisticated evaluationprocess which must consider multiple attributes.

echnology selection is not a new researchtopic; however,very little research has examined the interrelationship o thecriteria in the decision making process and considered thepositive and negative aspects o the alternatives simultane-ously. Tus, this paper, based on the model proposed by Leeet al. [], constructed a rened model. Te model appliesinterpretive structural modeling (ISM) to take into accountthe interrelationship o the criteria and adopts benets,opportunities, costs, and risks (BOCR) merits to consider the

various aspects o the alternatives. Fuzzy set theory is appliedto the analytic network process (ANP) model, or so-calledFANP, or the selection o solar cell technologies. By applyingthe uzzy set theory, the model can consider the uncertaintyanduzziness o experts opinions. As a result, a more credibledecision canbe made. In addition, the model can help expertsunderstand the problem comprehensively, so that differentaspects can be examined in evaluating various solar celltechnologies. Te remaining part o this paper is organized asollows.Section studies some recent technology evaluationmodels.Section reviews the works o the solar industry inaiwan.Section develops a systematic model or evaluatingsolar cell technologies. InSection , the model is applied toa solar cell manuacturer in aiwan or technology selection.Te last section contains the conclusions.

2. Review of Technology Evaluation Models

Many approaches on technology evaluation have been pre-sented in previous studies. Internal rate o return (IRR), netpresent value (NPV), return on investment (ROI), and pay-back period (PB) have been traditionally applied to evaluatetechnology alternatives rom nancial viewpoint []. Treebasic types or evaluating a technologys economic value are

cost approach, market approach, and income approach [].Other than the nancial value o technologies, elements, suchas product quality, time to completion, exibility, price, legalprotection, scope o application, and capacity expansion, areofen considered [,].

echnology evaluation problem is a multicriteria deci-sion making (MCDM) problem, and it should involve theopinions o multiple experts and consider uzzy assessments[]. Some o recent works are reviewed as ollows. Hung andseng [] considered our major actors, technology marketactor, legal protection actor, product market actor, andcost dimension actor, and proposed a technology evaluationramework. Hsu et al. [] acquired the critical actors o

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regenerative technologies by adopting uzzy Delphi methodand calculated the importance o each evaluation criterionusing uzzy analytic hierarchy process (FAHP). Lee et al.[] presented an integrated model or evaluating varioustechnologies or new product development or at panelmanuacturing. Te model adopted benets, opportunities,

costs, and risks (BOCR), ISM, and FANP to acilitate theevaluation process. Kang et al. [] proposed a model thatadopted ISM andFANP to assess different available technolo-gies or a at panel manuacturer. Alamian et al. [] aimedto evaluate technologies or harvesting wave energy in theCaspian Sea. Te most important design parameters or waveenergy converter devices were identied rst, and the majoreatures, including power production, sea conditions, deviceinstallation, and electrical system, were listed in a benchmarktable. With assigned weighting or each actor, the synthe-sized scores or each technology were obtained. Bassano etal. [] perormed a modeling and economic evaluation othe integration o carbon capture and storage technologiesintocoal-to-liquid plants. Te system conguration and plantperormance were evaluated rst using Aspen Plus sofware,and the economic analysis, including the IRR, PB, and NPV,was perormed next.

o summarize, even though technology evaluation is aMCDM problem in nature, relatively ew models have beenproposed. Tis study applies and revises the model proposedby Lee et al. [] and constructs a model or evaluating solarcell technologies that should be used in solar cell production.While triangular uzzy numbers are adopted in Lee et al. [],both triangular andtrapezoidal uzzy numbers are adopted inthis work. In addition,-cuts integral approach is applied todeuzzication here, instead o the center o gravity method,which is applied in Lee et al. [].

3. Studies of the Solar Industry in Taiwan

Te solar industry in aiwan has a great potential in theglobal market due to the technical advantages gained romthe semiconductor industry and the F-LCD industry [].In the past ew years, many PV rms have been developedin the market. Some studies on the solar industry in aiwanare briey reviewed here. Lee [] constructed an industrialportolio analysis model to evaluate the industrial innovationrequirements and national policies thatwerenecessary or thedevelopment o aiwans solar cell industry. Data collectionincluded literature analysis, expert interview, and general sur-

vey, and the relationship between market growth curve andindustrial production chain was analyzed. Lai [] studiedthe localized core competencies o the PV industry in aiwanthrough literature reviews and interviews with experts inthe industry and used Michael Porters diamond model,Andrew Groves six orces analysis, value chain analysis,and SWO analysis to analyze these competencies. Severalcompetitive strategies were then proposed to help establisha unique position in the global PV industry or aiwan.Yue and Wang [] established an evaluation model ordeveloping renewable energy sources, including wind, solar,and biomass energy sources, in Chigu area o southwesternaiwan by analyzing technical, economic, environmental,

and political implications. A GIS is used to assess the localconditions, and actors such as climate conditions, landuses, and ecological environments are considered. Chenet al. [] studied the development o various renewableenergies in aiwan, reviewed the promotional and subsidyprograms implemented by the aiwanese government, and

proposed uture plans achievements. ing [] reviewedthe development o solar cell technology, status o globalindustry, and strategy o major companies and discussed thedynamics and trend o the industry. Te study described theperormance and strategy o the leader companies in aiwanand discussed the competitive advantage and positioningo the companies. Chen [] studied historical data tounderstand the development and current situation o globaland aiwans thin lm PV industry. Te competitiveness othe industries in different countries was analyzed, and arecommendation was proposed to increase the competitiveadvantages o the industry in aiwan. Welling [] analyzedaiwans solar cell process equipment industry based on aninnovative intensive service analysis model by structuring a by matrix, encompassing our customization levels andve innovation levels, in order to study the strategic positionand uture development trend o the industry. Hwang []also reviewed promotional policy o renewable energy inaiwan. Te growth opportunities o individual renewableenergies by considering the technology development, domes-tic conditions, and indigenous industries related to renewableenergy were suggested. Lee et al. [] studied the currentbusiness perormance o PV rms in aiwan and proposeda perormance evaluation model by integrating analytic hier-archy process (AHP) and data envelopment analysis (DEA).Lee et al. [] proposed a two-stage perormance evaluationramework or PV rms. In the rst stage, assurance regions(AR) o the actors were set by the FAHP and the businessperormance o the rms was evaluated by the DEA. In thesecond stage, the changes in efficiency o each rm over timewere assessed by the Malmquist productivity index (MPI).

4. A Systematic Model for Evaluating SolarCell Technologies

A model, based on the model proposed by Saaty [], Saaty[], Lee et al. [], and Kang et al. [], is constructedhere to help evaluate suitable solar cell technologies in a

rm. Te model incorporates ISM, FANP, and BOCR andcontains three phases: the construction o control hierarchyand BOCR-ANP network, the calculation o priority weights,and the ranking o technology alternatives. Te steps are asollows.

Step . Form a committee o experts in a solar rm to denethe solar cell technology evaluation problem.

Phase I: Te Construction of Control Hierarchy and BOCR-ANP Network

Step . Develop a control hierarchy or the solar celltechnology evaluation problem. Te control hierarchy has

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Goal: selection of the most suitable solarcell technology

Strategic criterion1

Opportunities(O)

Costs(C)

Risks(R)

Benets(B)

Strategic criterion2

Strategic criterionS

F : Te control hierarchy or solar cell technology selection.

several strategic criteria and our merits, benets(), oppor-tunities (), costs (), and risks (),asshownin Figure . Tegoal o the control hierarchy is to determine the importanceo the our merits, which are b,o,c, andr, respectively.

Step . Develop a network with BOCR subnetworks. Basedon literature review and interview with the experts, theproblem can be decomposed into a network, as depicted inFigure . o attain the goal o selecting the most appropriatesolar cell technology, we need to consider our merits(,,,and). Tus, a subnetwork is ormed or each merit. Forinstance, the benets()subnetwork contains some criteriathat need to achieve thebenets aspect, andthese criteria maybe interrelated. In addition, technology alternatives are in thelowest level or evaluation.

Step . Develop a relation matrix or the criteria undereach merit. Experts are asked to identiy whether there is arelation between any two criteria and what the direction othe relation is. Ten, a relation matrix D is built to showthe contextual relationship among the criteria or merit.Consider

D

=

1 2...

... ...

12

0 12 121 0 2... d ...... d ...... 0 ...12 0

,

= 1, 2, . . . , ; = 1, 2, . . . , ,

()

whereis the relation between criteriaand. Iisreachable rom,= 1; otherwise,= 0.Step . Construct an initialreachability matrixor each merit.By adding Dwith the unit matrix I, the initial reachability

matrixRis calculated:

R

=D

+I

. ()Step . Calculate the nal reachability matrix R or eachmerit. Convergence o the relationship can be met using theoperators o the Boolean multiplication and addition. Tat is,0 0 = 0, 1 0 = 0 1 = 0, 1 1 = 1, 0 + 0 = 0, 1 + 0 =0 + 1 = 1, and1 + 1 = 1. Te nal reachability matrix Ris

R= R= R+1, > 1

R=

12 1 2... ... ...

1112 12122 2... d ...... d ...... d ...12

,

= 1, 2, . . . , ; = 1, 2, . . . , ,

()

whereis the impact o criterionxi to criterionxjundermeritM.

Step . Develop a subnetwork or the criteria under each

merit based onR

or the merit.

Phase II: Te Calculation of Priority Weights

Step . Prepare a questionnaire based on Figures and and the subnetworks developed inStep . Based onFigure ,the questionnaire contains the pairwise comparison o theimportance o the strategic criteria and the rating o theimportance o each merit(, ,, and) with respect toeach strategic criterion. Based onFigure and the subnet-works developed in Step , the questionnaire contains thepairwise comparison o the importance o the criteria undereach merit, the pairwise comparison o the interdependence

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Opportunities

Costs

(C)

Risks(R)

Benets(B)

Goal

echnology AT

Criterion b1

Criterion b2

Criterion o1

Criterion o2

Criterion c1

Criterion c2

Criterion r1

Criterion r2

Benets (B) subnetwork

(O)

echnology A1

echnology A2

echnology A3

.

.

.

.

.

.

.

.

.

...

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

Goal Merits Criteria Alternatives

F : Te BOCR-ANP network or solar cell technology selection.

1 98765432

0

1

Extremelyhigh

VeryhighHighhigh

Moderatelyhigh

LittlehighEqual

Relatively

F : Fuzzy numbers or relative importance/perormance.

among the criteria under each merit, and the pairwisecomparison o the expected perormance o the technologiesunder each criterion. Te experts in the rm are asked to llout the questionnaire.

Step . Based on the control hierarchy, two kinds o inor-mation are collected through the questionnaire. First, experts

1

0

VerygoodGood

Verypoor Poor poor Fair good

0.1 0.90.80.70.60.50.40.30.2

Relatively Relatively

F : Fuzzy numbers or ranking.

are asked to pairwise compare the importance o the strategiccriteria with seven linguistic terms, as shown in Figure .UsingFigure , the linguistic variables are transormed intotrapezoid uzzy numbers. Second, the importance o each

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Goal: selection of the most suitable solarcell technology

Manufacturing

Opportunities(O)

Costs(C)

Risks(R)

Benets(B)

Market demand SocialFinancialcapability (S1) (S2) responsibility (S4)performance (S3)

F : Te control hierarchy or solar cell technology selection.

merit(,,, and) on each strategic criterion is deter-mined by the experts also using a seven-step scale, as shown

inFigure .

Step . Calculate the importance o the strategic criteria.Aggregate experts responses by employing geometric averageapproach, and a synthetic trapezoid uzzy number is calcu-lated as ollows:

= 12 1/, ()whereis the pairwise comparison value between strategiccriteriaanddetermined by expert.

Deuzziy uzzy numberinto a crisp numberusingYager [] ranking method, and the-cuts o the uzzynumbers are listed inable :

= 1012

+ d. ()

Afer deuzzication, the aggregated pairwise comparisonmatrix is

W=

1 12 1112 1 2

...... 1

......

... 1 ... ... ... 1 1 1 11

12 1

. ()

Priority vector or the aggregated comparison matrix isderived:

W = max , ()where W is the aggregated comparison matrix, is theeigenvector,and

maxis the largest eigenvalue oW.

Step . Check the consistency o the aggregated comparisonmatrix. Te consistency index (CI) and consistency ratio

(CR) are [,]

CI=max 1 ,CR= CI

RI,

()

where is the number o items being compared in the matrixand RI is random index [].

Te experts are asked to revise the part o the question-naire i there is an inconsistency, and the calculations inStep are done again. Once the consistency test is passed,the priorities o the strategic criteria are determined.

Step . Calculate the importance o each merit(,,,and)with respect to each strategic criterion. Based on theinormation collected inStep , aggregate experts responsesusing the geometric average approach. Yager ranking method[] is used to deuzziy each uzzy number into a crispnumber.

Step . Calculate the priorities o the merits. Te priority o amerit is obtained by multiplying the importance o the merit

on eachstrategic criterionrom Step with thepriorityo therespective strategic criterion romStep and summing upthe calculated values or the merit. Te priorities o benets,opportunities, costs, and risks, that is, b, o, c, and r, arecalculated by normalizing the calculated values o the ourmerits.

Step . Calculate the relevant priorities on the BOCR-ANPnetwork in Figure andthe subnetworks developed in Step .A similar procedure as in Steps and is adopted tocalculate the relative importance weights o the criteria withrespect to the same upper-level merit, the interdependence othe criteria with respect to the same upper-level merit, and

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:-Cuts o uzzy numbers. () ()=(7.5,8.5,9,9)L-R = 7.5 + = 9=(6.5,7.5,7.5,8.5)L-R = 6.5 + = 8.5

=(5,5.75,6.75,7.5)L-R

= 5 + 0.75

= 7.5 0.75=(4,5,5,6)L-R = 4 + = 6 =(2.5,3.25,4.25,5)L-R = 2.5 + 0.75 = 5 0.75=(1.5,2.5,2.5,3.5)L-R = 1.5 + = 3.5 =(1,1,1.5,2.5)L-R = 1 = 2.5

AlternativesMerits Criteria

Material usage reduction (b3)

Mass production technology (b1)

Conversion efficiency (b4)- -Benets (B)

Opportunities(O)

Costs (C)

Risks (R)

Equipment technology (o2)

Policy/regulation requirement (o3)

Yield rate (o1)

Tin lm cell (A4)

Goal

Dye sensitized solar cell (DSSC) (A1)

Crystalline silicon cell (A2)

Organic cell (A5)

Concentrating cell (GaAs) (A3)

Goal:se

lectiono

fthemostsuita

bleso

larce

lltec

hnolo

gy

Power generation stability (o4)

R and D capability and speed (o5)

Market scale and growth (o6)

Material cost (c4)

Investment cost (c2)

Product quality and reliability (c3)

Environmental pollution of production (r3)

Financial capability (r1)

Material source (r4)

Fossil fuels price (r2)

Production cost (c1)

Price of other renewable energy sources (r5)

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

Delivery-on-time rate (b2)

F : Te BOCR-ANP network or solar cell technology selection.

the expected relative perormance o technologies withrespect to each criterion.

Phase III: Te Ranking of echnology Alternatives

Step . Prepare an unweighted supermatrix or each meritusing the priorities obtained rom Step , as depicted in

the ollowing matrix, where is a vector that showsthe impact o merit Mon the criteria, W represents theinterdependency o the criteria, Wis a matrix that indicatesthe impact o criteria on each alternative, and I is the identitymatrix.

Unweighted supermatrix or merit[] is

Merit Criteria AlternativesMerit

Criteria

Alternatives

I

.

.

....

... W

...

... W

... I

.

.

....

.

()

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Mass production ConversionMaterial usage

technology (b1)

Delivery-on-time

rate (b2) efficiency (b4)reduction (b3)

F : Subnetwork or the criteria under the benets merit.

Step . Obtain the weighted supermatrix or each meritsubnetwork. One approachis to determine the relativeimpor-tance o the clusters in the supermatrix with the columncluster (block) as the controlling component []. Anotherpopular approach is to assign equal weights to the blocks inthe same column and to make each column sum to unity [].

Step . Obtain the priorities o technology alternatives under

each merit subnetwork. Calculate the limit supermatrix oreach merit subnetwork by raising the weighted supermatrixto powers. Te priorities o the technology alternatives undereach merit are ound in the alternative-to-goal column o thelimit supermatrix o the merit.

Step . Obtain overall priorities o the technology alterna-tives by synthesizing the priorities o each alternative undereach merit romStep with the corresponding normalizedweightsb,o,c, andrromStep . Five popular ways can beused to calculate the overall priority o each alternative [].

Additive. Consider

= + + 1Normalized + 1Normalized , ()where, , , and represent the synthesized results oalternative t under merits,, , and, respectively, and,,, andare normalized weights o merits, , , and,respectively.

Probabilistic Additive.Consider

= + + 1 + 1 . ()Subtractive. Consider

= + . ()Multiplicative Priority Powers.Consider

= 1Normalized1Normalized

. ()Multiplicative.Consider

= . ()Step . Perorm sensitivity analysis to examine the robust-ness o the outcomes. By changing the priorities o the merits,Steps are perormed again to check whether the rankingo alternatives changes and at what priority the rankingchanges.

5. Case Study

Te proposed model is applied to an anonymous solar cellmanuacturer in aiwan to select the most suitable solarcell technology. A comprehensive literature review is donerst, and some experts in the solar cell technology eld areinterviewed. A controlhierarchy and an ANP-BOCR networkare developed by the authors and veried by the experts, as

shown in Figuresand, respectively. Four strategic criteriaare named: manuacturing capability, market demand, nan-cial perormance, and social responsibility. Te our meritsare benets(), opportunities(), costs(), and risks(),under each o which there are a number o criteria. Forinstance, the benets that may be acquired rom adoptinga solar cell technology include mass production technology(1), delivery-on-time rate(2), material usage reduction(3), and conversion efficiency(4). Te most probabletechnologies in making solar cells are dye sensitized solar cell(DSSC)(1), crystalline silicon cell(2), concentrating cell(GaAs)(3), thin lm cell(4), and organic cell(5).

Te interrelationship among the criteria under the sameupper-level merit is determined through the ISM. Expertsconsensus is obtained through the Delphi method, and arelation matrix under each merit is prepared. Te relationmatrix among the criteria under benets, D, is

D=1 2 3 41234

0111

1000

0001

0010. ()

UsingStep , we can obtain the initial reachability matrixRor the criteria under benets:

R= D+I =

0 1 0 01 0 0 01 0 0 11 0 1 0

+

1 0 0 00 1 0 00 0 1 0

0 0 0 1

=

1 1 0 01 1 0 01 0 1 1

1 0 1 1

.()

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Afer the calculation, the nal reachability matrix Rorthe criteria under benetsis

R= R2=

1 1 0 01 1 0 0

1 1 1 11 1 1 1

. ()

Based on R, we can determine the interrelationshipamong the our criteria under benets, as shown in Figure .Te direction o an arrow shows the dependence, and a two-way arrow means that the two criteria are interdependent.Using the same procedure, the interrelationships among thecriteria under the other three merits are determined, asshown in Figures,, and, respectively.

Based on the network inFigure and the interrelation-ship among the criteria under the our merits in Figure to Figure , a questionnaire is prepared. Nine experts,

including one project manager, one engineering manager,one production manager, two senior R and D engineers, twoquality managers, and two marketing managers, in the rmare asked to ll out the questionnaire. For example, the ourstrategic criteria are pairwise compared using seven different

linguistic terms shown inFigure . An aggregated pairwisecomparison matrix is prepared next to synthesize expertsopinions. For example, the pairwise comparisons betweenmanuacturing capability(1) and market demand(2) bythe experts are little high, equal, equal, little high,equal, little high, equal, little high, and little high. Te

uzzy numbers are (., ., ., .), (, , ., .), (, , .,.), (., ., ., .), (, , ., .), (., ., ., .), (, , .,.), (., ., ., .), and (., ., ., .). By applying (),the aggregated trapezoid uzzy number is

(1.25,1.66,1.99,3.01)= (1.5 1 1 1.5 1 1.5 1 1.5 1.5)1/9,

(2.5 1 1 2.5 1 2.5 1 2.5 2.5)1/9,(2.5 1.5 1.5 2.5 1.5 2.5 1.5 2.5 2.5)1/9(3.5 2.5 2.5 3.5 2.5

3.5 2.5 3.5 3.5)1/9

. ()Te uzzy aggregated pairwise comparison matrix or the

strategic criteria is

w=1 2 3 4

1234

(1,1,1,1)(1.25,1.66,1.99,3.01)1(1.27,1.55,2.00,3.02)1(1.64,2.07,2.67,3.67)1(1.25,1.66,1.99,3.01)(1,1,1,1)(2.02,2.69,3.36,4.28)1(3.68,4.54,5.23,6.08)1

(1.27,1.55,2.00,3.02)(2.02,2.69,3.36,4.28)(1,1,1,1)(1.33,1.71,2.11,3.14)1(1.64,2.07,2.67,3.67)(3.68,4.54,5.23,6.08)(1.33,1.71,2.11,3.14)(1,1,1,1)

. ()

A deuzzied comparison matrix is prepared by the Yager

[] ranking method using (). For example, the synthetictrapezoid uzzy number or the comparison between1and2 is ., ., ., and .. Te deuzzied comparisonbetween1and2 is .. Tus, the deuzzied aggregatedpairwise comparison matrix is

W=1 2 3 41234

10.5050.5110.398

1.98110.3240.205

1.9583.08710.483

2.5124.8852.0721. ()

Ten, the priority vector, that is,, andmaxoWarecalculated using ():

= 12340.3810.3580.1650.096

,

max= 4.218. ()

By applyingStep , we can check the consistency o thedeuzzied aggregated pairwise comparison matrix. Con-sider

CI=max 1 =4.218 4

4 1 = 0.073CR= CI

RI=0.0730.9 = 0.081.

()

Because CR is less than ., the consistency test is passed.

In the opinions o the experts, manuacturing capability(1)is the most important strategic criterion with a priority o., ollowed by market demand(2) with a priority o..

Next, the importance o each merit to each strategiccriterion is determined. A seven-level linguistic scale is usedto collect the experts opinions in the questionnaire, and eachlinguistic scale is assigned a trapezoid uzzy number. Te out-comes rom the experts are aggregated using the geometricaverage method, and the uzzy numbers are deuzzied bythe Yager [] ranking method.able shows the integrateduzzy weights o the our merits on strategic criteria. Teoverall priorities o the our merits can then be calculated

based on the priorities o strategic criteria and the deuzziedweights o the our merits. Te results are shown inable .Te normalized priorities o the our merits are listed in thelast column oable : benets (), .; opportunities (),.; costs (), .; and risks (), ..

Based on the opinions o the experts collected romthe questionnaire, we can urther calculate the priorities othe criteria with respect to each merit, the interrelationshipamong thecriteria under each merit,and the expected relativeperormance o the technologies under each criterion. Tatis, the collected data are synthesized into aggregated pairwisecomparison matrices using the geometric average methodrst, and the Yager [] ranking method is adopted next

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Equipment Power generation Market scale andPolicy/regulation R and D capabilityYield rate (o1)

technology (o2) requirement (o3) stability (o4) and speed (o5) growth (o6)

F : Subnetwork or the criteria under the opportunities merit.

Production cost Investment cost Product quality

(c1) (c2)Material cost (c4)

and reliability (c3)

F : Subnetwork or the criteria under the costs merit.

Price of other

renewable energyFinancial Fossil fuels price Material source

Environmental

pollution of

sources (r5)

capability (r1) (r2) (r4)

production (r3)

F : Subnetwork or the criteria under the risks merit.

: Integrated uzzy weights o the merits on strategic criteria.

Manuacturing capability (1) Market demand (2) Financial perormance (3) Social responsibility (4)Benets (., ., ., .) (., ., ., .) (., ., ., .) (., ., ., .)

Opportunities (., ., ., .) (., ., ., .) (., ., ., .) (., ., ., .)Costs (., ., ., .) (., ., ., .) (., ., ., .) (., ., ., .)

Risks (., ., ., .) (., ., ., .) (., ., ., .) (., ., ., .)

: Priorities o the merits(, ,,).1 2 3 4

Overall priorities Normalized priorities(.) (.) (.) (.)

Benets . . . . . .

Opportunities . . . . . .

Costs . . . . . .

Risks . . . . . .

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: Unweighted supermatrix or the benets merit.

G 1 2 3 4 1 2 3 4 5G

1 . . . . . 2 . . . . . 3 . . . 4 . . . 1 . . . . 2 . . . . 3 . . . . 4 . . . . 5 . . . .

: Weighted supermatrix or the benets merit.

G 1 2 3 4 1 2 3 4 5G .

1 . . . . . 2 . . . . . 3 . . . 4 . . . 1 . . . . 2 . . . . 3 . . . . 4 . . . . 5 . . . .

: Limit supermatrix or the benets merit.

G 1 2 3 4 1 2 3 4 5G

1 2 3 4 1 . . . . . 2 . . . . . 3 . . . . . 4 . . . . . 5 . . . . .

to calculate deuzzied comparison matrices. Based on thedeuzzied aggregated comparison matrices, we can calculatethe priority vectors. Ten, the priority vectors are enteredinto the designated places in an unweighted supermatrix.Te unweighted supermatrix or the benets merit is asshown inable . A weighted supermatrix is ormed to makethe matrix stochastic, as shown in able . By taking theweighted supermatrix to a large power, a limit supermatrixis calculated, as shown inable . Te (,) block o the limitsupermatrix shows the priorities o the solar cell technologyalternatives. Under the benets merit, the priorities or1,

2,3,4, and5are ., ., ., ., and .,respectively.

Te relative perormances o solar cell technology alter-natives under each merit are shown in able . Under thebenets merit, crystalline silicon cell(2)perorms the bestwith a priority o ., ollowed by dye sensitized solar

cell(1) with . and concentrating cell (GaAs)(3)with .. Under the opportunities merit, dye sensitizedsolar cell (DSSC)(1) perorms the best with a priority o., ollowed by organic cell(5) with .. Under thecosts merit, concentrating cell (GaAs)(3)is the least costlywith a normalized reciprocal priority o ., ollowed bycrystalline silicon cell(2)with .. Under the risks merit,the least risky alternative is crystalline silicon cell(2)with anormalized reciprocal priority o ., ollowed by thin lmcell(4)with . and concentrating cell (GaAs)(3)with.. Te results show that crystalline silicon cell(2)ranksthe rst under the benets and risks merits, dye sensitizedsolar cell (DSSC) (1) ranks the rst under the opportunitiesmerit, and concentrating cell (GaAs)(3) ranks the rstunder the costs merit. Because the perormances o thealternatives under each merit are different, the nal rankingo the ve alternatives is not clear.

By aggregating the scores o each alternative under,,, and, the nal ranking o the alternatives can be calcu-lated. Tere are ve methods or accomplishing the task, thatis, additive, probabilistic additive, subtractive, multiplicativepriority powers, and multiplicative. able shows the results.Te priority o dye sensitized solar cell (DSSC)(1) usingeach o the ve methods is calculated as ollows.

Additive.Consider

0.295 0.243 + 0.216 0.236 + 0.266 0.221+ 0.223 0.159 = 0.2171. ()Probabilistic Additive.Consider

0.295 0.243 + 0.216 0.236 + 0.266(1 0.173)+ 0.223 (1 0.235)= 0.5133. ()

Subtractive. Consider

0.295 0.243 + 0.216 0.236 0.266 0.173

0.223 0.235 = 0.0240. ()

Multiplicative Priority Powers.Consider

0.2430.295 0.2360.216 0.2210.266 0.1590.223 = 0.2144.()

Multiplicative.Consider

0.243 0.236(0.173 0.235)= 1.4070. ()

No matter which aggregation method is used, crystallinesilicon cell (2) alwaysranks the rst, dye sensitized solar cell

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: Perormance o alternatives under the our merits.

Merits Benets Opportunities Costs Risks

Priorities . . . .

Alternatives Normalized Normalized Normalized Reciprocal Normalized

Normalized Reciprocal Normalized

Reciprocal Reciprocal

Dye sensitized solar cell(DSSC) (1) . . . . . . . .Crystalline silicon cell (2) . . . . . . . .Concentrating cell (GaAs)(3) . . . . . . . .Tin lm cell (4) . . . . . . . .Organic cell (5) . . . . . . . .

: Final priorities o alternatives.

Methods Additive Probabilistic additive Subtractive Multiplicative priority powers Multiplicative

Alternatives Priorities Ranking Priorities Ranking Priorities Ranking Priorities Ranking Priorities Ranking

Dye sensitized solarcell (DSSC) (1) . . . . . Crystalline silicon cell(2) . . . . . Concentrating cell(GaAs) (3) . . . . . Tin lm cell (4) . . 0.0100 . . Organic cell (5) . . 0.0473 . .

: Importance o criteria.

Merits Criteria Criterion priorities Integrated priorities

in the network Integrated ranking

Benets(.)

(1) Mass production technology . . (2) Delivery-on-time rate . . (3) Material usage reduction . . (4) Conversion efficiency . .

Opportunities(.)

(1) Yield rate . . (2) Equipment technology . . (3) Policy/regulation requirement . . (4) Power generation stability . . (

5) R and D capability and speed . .

(6) Market scale and growth . . Costs(.)

(1) Production cost . . (2) Investment cost . . (3) Product quality and reliability . . (4) Material cost . .

Risks(.)

(1) Financial capability . . (2) Fossil uels price . . (3) Environmental pollution o production . . (4) Material source . . (5) Price o other renewable energy sources . .

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(1) Changes in the priority of benets (2) Changes in the priority of opportunities

(3) Changes in the priority of costs (4) Changes in the priority of risks

F : Sensitivity analysis when applying the additive method.

(DSSC)

(1)the second, and concentrating cell (GaAs)

(3)the third.A sensitivity analysis is perormed next to examine therobustness o the outcomes. Te sofware Super Decisions[] is applied to ulll the task. Te priorities o the meritsare changed to observe whether the ranking o alternativeschanges. Figures(1),(2),(3), and(4) show the sensi-tivity analysis graphs under the additive method when thepriority o benets, opportunities, costs, and risks changes,respectively. Te best technology may change when thepriorities o the merits change. For example, the originalpriority o benets () is ., andthe best alternative overallis2. However, when increases rom . to ., thebest alternative shifs rom2 to1. Te original priority

o opportunities (

) is .. Whenoincreases rom . to

., the best alternative changes rom2 to1. Te originalpriority o costs () is .. Whenincreases rom . to., the best alternative shifs rom2to3. Te originalpriority o risks (r) is .. Whendecreases rom . to., the best alternative changes rom2to1. Since it isunlikely that the priorities o the our merits will have suchbig changes, the current solution is rather robust.

Te management needs to understand the importance othe criteria when making the solar cell technology selectiondecision, and such inormation can be obtained rom thecalculation results. Te importance o the criteria under eacho the our merits is shown in able . Te most importantcriterion under the benets merit is conversion efficiency(4),

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: Perormance o alternatives with respect to each criterion.

Criteria Alternatives

1 2 3 4 5(1) Mass production technology . . . . .(2) Delivery-on-time rate . . . . .(3) Material usage reduction .

. . . .

(4) Conversion efficiency . . . . .(1) Yield rate . . . . .(2) Equipment technology . . . . .(3) Policy/regulation requirement . . . . .(4) Power generation stability . . . . .(5) R and D capability and speed . . . . .(6) Market scale and growth . . . . .(1) Production cost . . . . .(2) Investment cost . . . . .(3) Product quality and reliability . . . . .(4) Material cost . . . . .(1) Financial capability

. . . . .

(2) Fossil uels price . . . . .(3) Environmental pollution o production . . . . .(4) Material source . . . . .

with a priority o .. Tis indicates that the major benetconsidered when selecting a technology is the efficiency orconversing solar power to electricity. Te second and thirdcriteria are material usage reduction (3) (.) and delivery-on-time rate(2) (.). Under the opportunities merit, RandD capability and speed(5)(.) is the most importantcriterion, andpower generation stability

(4)(.) ranks the

second. Under the costs merit,product quality and reliability(3)(.) is the major concern, ollowed bymaterial cost(4) (.). Under the risks merit, fossil fuels price(2)(.) is what the rm concerns the most since it may affectthe demand o renewable energy.Material source(4)(.)ranks the second. Te integrated priorities o criteria andtheir respective rankings are also shown inable . Amongall the criteria,conversion efficiency(4), with an integratedpriority o . in the network, is the most importantconcern in selecting a technology. Other important criteriainclude product quality and reliability(3), material usagereduction(3),material cost(4), andinvestment cost(2).

In the case study, the expected perormance o alter-

natives with respect to each criterion can be learned. Teperormance results are ound in the (,) block o the limitsupermatrix. For instance, the relative perormances o1to5 under mass production technology(1) are shown inthe rst column o the (,) block o the limit supermatrixor the benets merit in able , and they are ., .,., ., and ., respectively. Te perormances o thealternatives under various criteria are shown inable . Tebest perormance o an alternative under each criterion isshown in bold. Undermass production technology(1), both1and2perorm the best.1perorms the best under criteria.2,4, and5perorm the best under , , and criteria, respectively. Even though1 perorms the best in

more criteria than2 does, crystalline silicone cell (2), withthe consideration o different criterion importance weights,has the most outstanding perormance ovserall.

In conclusion, the criteria o solar technology can belogically identied, organized, reviewed, and concluded bythis model to avoid the rank bias and halo effect [] in groupdiscussion. In addition, the quality o nal decision can be

more consistent through this systematic process.

6. Conclusions

With natural resource scarcity and environmental protection,renewable energy sources have been recognized as the lastresort or uture economic development, and solar energy isone o the most promising renewable energy sources romthe perspective o environmental sustainability. However, thePV market is acing a rather volatile market cycle in responseto the global economic condition. A PV rm must have a

solid oundation in its technology in order to survive andto lead the market in the uture. Tereore, good evaluationand selection o the most appropriate technology become acomplicated decision that a rm ofen encounters.

Tis research constructed an integrated model, whichincorporates interpretivestructural modeling (ISM), benets,opportunities, costs, and risks concept (BOCR), and uzzyanalytic network process (FANP), or acilitating the evalu-ation o technologies. Te model consists o three phases. Inthe rst phase, a control hierarchy anda BOCR-ANP networkare constructed. In the second phase, the relevant priorityweights in the control hierarchy and the BOCR-ANP networkare calculated. In the last phase, the technology alternatives

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are ranked. Te proposed model is implementedin a solar cellrm to help select the most suitable solar cell technologies.

Tis evaluation model is constructed under known tech-nology o solar cell or technology selection or mass produc-tion. By applying the proposed model, experts can under-stand the expected perormance o technology alternatives

based on different criteria and merits. Te overall ranking othe technologies can be calculated as a result. Further studiescan be conducted or the conceptualized or developing stageo solar cell technology to acilitate decision making on newtechnology development to ensurethe success o new productintroduction. In addition,based on thespecial needs o a rm,the proposed model can be adjusted as required by the rmin the PV industry or in another industry to help select themost suitable technology.

Conflict of Interests

Te authors declare that there is no conict o interests

regarding the publication o this paper.

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