Renewable energy performance evaluation studies using the data envelopment analysis (DEA): A systematic review

This article provides a systematic analysis of renewable energy performance using data envelopment analysis (DEA) to understand the diverging paths of renewable energy development for countries. In this review, 72 quantitative studies were identified using a multi-stage selection process. The review found that the DEA method can be used as an appropriate tool for performance evaluation of renewable energy studies' research. The DEA method can be applied critically for decision making, especially for policymakers in the renewable energy sector. The review also demonstrated that the DEA method, either traditional or advanced, can be comprehensively used to evaluate the performance of renewable energy studies depending on the objective of the research, as well as the complexity and accuracy of data issues. This review revealed that the selection of input and output factors used in DEA is sufficient enough to evaluate renewable energy performance. This review contributed to the current energy literature and filled in the gap with the addition of new knowledge on assessing renewable energy research studies intensively using a formal systematic literature review process. The review revealed that the development of DEA methodologies and applications in renewable energy should be expanded in the future. The results obtained from this review are both beneficial and inspirational for further research regarding the DEA application in renewable energy and provide valuable input for policymakers in decision-making processes.

[1]  Dong-Shang Chang,et al.  Incorporating the learning effect into data envelopment analysis to measure MSW recycling performance , 2013, Eur. J. Oper. Res..

[2]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[3]  Yi Yang,et al.  Data envelopment analysis application in sustainability: The origins, development and future directions , 2018, Eur. J. Oper. Res..

[4]  Luis C. Dias,et al.  Assessing the performance of biogas plants with multi-criteria and data envelopment analysis , 2009, Eur. J. Oper. Res..

[5]  M. Farrell The Measurement of Productive Efficiency , 1957 .

[6]  Hao-En Chueh,et al.  APPLYING DATA ENVELOPMENT ANALYSIS TO EVALUATION OF TAIWANESE SOLAR CELL INDUSTRY OPERATIONAL PERFORMANCE , 2012 .

[7]  C. Barros Efficiency analysis of hydroelectric generating plants : A case study for Portugal , 2008 .

[8]  Ümit Sağlam A two-stage data envelopment analysis model for efficiency assessments of 39 state’s wind power in the United States , 2017 .

[9]  Santosh Ghosh,et al.  Evaluation of relative impact of aerosols on photovoltaic cells through combined Shannon's entropy and Data Envelopment Analysis (DEA) , 2017 .

[10]  Prasanta Kumar Dey,et al.  Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis , 2016, Comput. Oper. Res..

[11]  Jingzheng Ren,et al.  Determining the life cycle energy efficiency of six biofuel systems in China: a Data Envelopment Analysis. , 2014, Bioresource technology.

[12]  R. Balasubramanian,et al.  Optimization of India's power sector strategies using weight-restricted stochastic data envelopment analysis , 2013, Energy Policy.

[13]  Yong Hu,et al.  Efficiency assessment of wind farms in China using two-stage data envelopment analysis , 2016 .

[14]  Changhee Kim,et al.  Do Shifts in Renewable Energy Operation Policy Affect Efficiency: Korea’s Shift from FIT to RPS and Its Results , 2018 .

[15]  Ümit Sağlam,et al.  Assessment of the Productive Efficiency of Large Wind Farms in the United States: An Application of Two-Stage Data Envelopment Analysis , 2017 .

[16]  Toshiyuki Sueyoshi,et al.  Assessment of large commercial rooftop photovoltaic system installations: Evidence from California , 2017 .

[17]  Rui Cunha Marques,et al.  Assessing efficiency drivers in municipal solid waste collection services through a non-parametric method , 2017 .

[18]  Ali Azadeh,et al.  Location optimization of solar plants by an integrated hierarchical DEA PCA approach , 2008 .

[19]  S. Rafiee,et al.  Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach , 2011 .

[20]  Toshiyuki Sueyoshi,et al.  Photovoltaic power stations in Germany and the United States: A comparative study by data envelopment analysis , 2014 .

[21]  Harold O. Fried,et al.  The Measurement of Productive Efficiency and Productivity Growth , 2008 .

[22]  S. M. Asadzadeh,et al.  A flexible neural network-fuzzy data envelopment analysis approach for location optimization of solar plants with uncertainty and complexity , 2011 .

[23]  Hongmei Wang,et al.  A two-stage evaluation and optimization method for renewable energy development based on data envelopment analysis , 2020 .

[24]  Kamaruzzaman Sopian,et al.  Performance evaluation of renewable energy R&D activities in Malaysia , 2021, Renewable Energy.

[25]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement , 2009, BMJ.

[26]  Yi-Tui Chen,et al.  The privatization effect of MSW incineration services by using data envelopment analysis. , 2012, Waste management.

[27]  John S. Liu,et al.  A survey of DEA applications , 2013 .

[28]  Leili Soltanisehat,et al.  Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach , 2020 .

[29]  Adnan Sözen,et al.  Efficiency assessment of the hydro-power plants in Turkey by using Data Envelopment Analysis , 2012 .

[30]  Xiaochuan Ma,et al.  Comprehensive evaluation of renewable energy for power projects based on CA-DEA model , 2015, 2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT).

[31]  Pegah Khoshnevis,et al.  Performance evaluation of R&D active firms , 2018 .

[32]  Corrado lo Storto,et al.  Benchmarking Economical Efficiency of Renewable Energy Power Plants: A Data Envelopment Analysis Approach , 2013 .

[33]  M R Khadivi,et al.  Solid waste facilities location using of analytical network process and data envelopment analysis approaches. , 2012, Waste management.

[34]  Kyung-Taek Kim,et al.  Measuring the efficiency of the investment for renewable energy in Korea using data envelopment analysis , 2015 .

[35]  Meysam Arvan,et al.  A simulation-based Data Envelopment Analysis (DEA) model to evaluate wind plants locations , 2015 .

[36]  Naamsestraat Leuven Economics Evaluating the efficiency of municipalities in collecting and processing municipal solid waste: A shared input DEA-model , 2012 .

[37]  José Ramón San Cristóbal,et al.  A multi criteria data envelopment analysis model to evaluate the efficiency of the Renewable Energy technologies , 2011 .

[38]  Yanghon Chung,et al.  The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries , 2015 .

[39]  Mario Martín-Gamboa,et al.  Environmental benchmarking of wind farms according to their operational performance , 2013 .

[40]  Gonzalo Guillén-Gosálbez,et al.  Methodology for combined use of data envelopment analysis and life cycle assessment applied to food waste management , 2016 .

[41]  Nicky Rogge,et al.  Measuring and explaining the cost efficiency of municipal solid waste collection and processing services , 2013 .

[42]  Mario Martín-Gamboa,et al.  Delving into sensible measures to enhance the environmental performance of biohydrogen: A quantitative approach based on process simulation, life cycle assessment and data envelopment analysis. , 2016, Bioresource technology.

[43]  Yuan Zeng,et al.  Comprehensive evaluation of renewable energy technical plans based on data envelopment analysis , 2019, Energy Procedia.

[44]  B. Rugani,et al.  On the feasibility of using emergy analysis as a source of benchmarking criteria through data envelopment analysis: A case study for wind energy , 2014 .

[45]  Zhaohua Wang,et al.  Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis , 2017 .

[46]  Lu Gan,et al.  Economic Feasibility Analysis for Renewable Energy Project Using an Integrated TFN–AHP–DEA Approach on the Basis of Consumer Utility , 2017 .

[47]  D.K. Jha,et al.  Measuring Efficiency of Hydropower Plants in Nepal Using Data Envelopment Analysis , 2006, IEEE Transactions on Power Systems.

[48]  Nattanin Ueasin,et al.  The Technical Efficiency of Rice Husk Power Generation in Thailand: Comparing Data Envelopment Analysis and Stochastic Frontier Analysis , 2015 .

[49]  Ni-Bin Chang,et al.  Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis. , 2010, Waste management.

[50]  Ângela Carrancho da Silva,et al.  Performance assessment of Alternative Energy Resources in Brazilian power sector using Data Envelopment Analysis , 2012 .

[51]  P. W. Wilson,et al.  Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models , 1998 .

[52]  Peng Zhou,et al.  A survey of data envelopment analysis in energy and environmental studies , 2008, Eur. J. Oper. Res..

[53]  Ali Emrouznejad,et al.  A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016 , 2018 .

[54]  Zongyun Song,et al.  Analysis of wind turbine micrositing efficiency: An application of two-subprocess data envelopment analysis method , 2018 .

[55]  M. Solimanpur,et al.  A framework for performance evaluation of energy supply chain by a compatible Network Data Envelopment Analysis model , 2016 .

[56]  László Szabó,et al.  Cost-efficiency benchmarking of European renewable electricity support schemes , 2018, Renewable and Sustainable Energy Reviews.

[57]  Beyzanur Cayir Ervural,et al.  Energy Efficiency Evaluation of Provinces in Turkey Using Data Envelopment Analysis , 2016 .

[58]  William W. Cooper,et al.  Handbook on data envelopment analysis , 2011 .

[59]  Nikolaus Ederer Evaluating capital and operating cost efficiency of offshore wind farms: A DEA approach , 2015 .

[60]  Jiang Wu,et al.  Identification of key energy efficiency drivers through global city benchmarking: A data driven approach , 2017 .

[61]  Mohammad Sadegh Pakkar Using DEA and AHP for Hierarchical Structures of Data , 2016 .

[62]  Agnese Rapposelli,et al.  Evaluating joint environmental and cost performance in municipal waste management systems through data envelopment analysis: Scale effects and policy implications , 2017 .

[63]  Nickolaos G. Tzeremes,et al.  Analyzing the Greek renewable energy sector: A Data Envelopment Analysis approach , 2012 .

[64]  Toshiyuki Sueyoshi,et al.  World trend in energy: an extension to DEA applied to energy and environment , 2017 .

[65]  Deok-Joo Lee,et al.  Measuring the Efficiency of Investment in the Deployment and Technology Development of Renewable Energy in Korea Using the DEA , 2014 .

[66]  Gento Mogi,et al.  A fuzzy analytic hierarchy process (AHP)/data envelopment analysis (DEA) hybrid model for efficiently allocating energy R&D resources: In the case of energy technologies against high oil prices , 2013 .

[67]  Prasanta Kumar Dey,et al.  Analysing Efficiency of Waste to Energy Systems: Using Data Envelopment Analysis in Municipal Solid Waste Management , 2016 .

[68]  Ali Emrouznejad,et al.  Recent developments on the use of DEA in the public sector , 2018 .

[69]  Haitao Li,et al.  Two-stage network DEA: Who is the leader? , 2018 .

[70]  Jin-Li Hu,et al.  Renewable energy and macroeconomic efficiency of OECD and non-OECD economies , 2007 .

[71]  Angeliki N. Menegaki,et al.  Growth and renewable energy in Europe: Benchmarking with data envelopment analysis , 2013 .

[72]  John S. Liu,et al.  Research fronts in data envelopment analysis , 2016 .

[73]  Gonzalo Guillén-Gosálbez,et al.  Enhanced data envelopment analysis for sustainability assessment: A novel methodology and application to electricity technologies , 2016, Comput. Chem. Eng..

[74]  H. J. Vermeulen,et al.  Sector performance monitoring in utility-scale solar farms using data envelopment analysis , 2017, 2017 IEEE PES PowerAfrica.

[75]  Abdorrahman Haeri,et al.  Evaluation and comparison of crystalline silicon and thin-film photovoltaic solar cells technologies using data envelopment analysis , 2017, Journal of Materials Science: Materials in Electronics.

[76]  Ali Azadeh,et al.  Location optimization of wind plants in Iran by an integrated hierarchical Data Envelopment Analysis , 2011 .

[77]  Qingyou Yan,et al.  Economic and Technical Efficiency of the Biomass Industry in China: A Network Data Envelopment Analysis Model Involving Externalities , 2017 .

[78]  Federica Cucchiella,et al.  Data Envelopment Analysis to Compare Renewable Energy Efficiency in the Italian Regions , 2014 .

[79]  Finn R. Førsund,et al.  Economic interpretations of DEA , 2018 .

[80]  D. Štreimikienė,et al.  A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency , 2017 .

[81]  R Ramanathan,et al.  Comparative Risk Assessment of Energy Supply Technologies: a Data Envelopment Analysis Approach , 2001 .

[82]  S. Mohtasebi,et al.  Energy efficiency improvement and input cost saving in kiwifruit production using Data Envelopment Analysis approach , 2011 .

[83]  Romualdas Bausys,et al.  An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies , 2020, Sustainability.

[84]  K. Boubaker Renewable energy in upper North Africa: Present versus 2025-horizon perspectives optimization using a Data Envelopment Analysis (DEA) framework , 2012 .

[85]  Marta Meleddu,et al.  Public spending on renewable energy in Italian regions , 2018 .

[86]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .