Abstract
This paper formulates the renewable power generation sources’ performance evaluation problem as a multicriteria group decision making problem, and presents a new multicriteria group decision making approach for effectively evaluating the performance of renewable power generation sources. The subjectiveness and imprecision of the decision making process is adequately handled by using intuitionistic fuzzy numbers. A multicriteria group decision making approach based on the TOPSIS approach and the degree of similarities are introduced for obtaining the relative degree of closeness value of each alternative on which the final decision can be made. An example is presented for demonstrating the applicability of the approach for dealing with renewable power generation sources’ performance evaluation problem.
Keywords
- Decision makers
- Renewable power generation sources
- Performance evaluation
- Multicriteria
- Subjective assessments
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Luz, T., Moura, P., de Almeida, C.: Multi-objective power generation expansion planning with high penetration of renewables. Renew. Sustain. Energy Rev. 81, 2637–2643 (2018)
Demirbas, A., Sahin-Demirbas, A., Hilal Demirbas, A.: Global energy sources, energy usage, and future developments. Energy Sources 26, 191–204 (2004)
Balat, M., Ayar, G.: Biomass energy in the world, use of biomass and potential trends. Energy Sources 27, 931–940 (2005)
Strantzali, E., Aravossis, K.: Decision making in renewable energy investments: a review”. Renew. Sustain. Energy Rev. 55, 885–898 (2016)
Blenkinsopp, T., Coles, S.R., Kirwan, K.: Renewable energy for rural communities in Maharashtra. India Energy Policy 60, 192–199 (2013)
Ahmad, S., Tahar, R.M.: Selection of renewable energy sources for sustainable development of electricity generation system using analytic hierarchy process: a case of Malaysia. Renew. Energy 63, 458–466 (2014)
Georgopoulou, E., Lalas, D., Papagiannakis, L.: A multicriteria decision aid approach for energy planning problems: the case of renewable energy option. Eur. J. Oper. Res. 103, 38–54 (1997)
Streimikiene, D., Balezentis, T., Krisciukaitiene, I., Balezentis, A.: Prioritizing sustainable electricity production technologies: MCDM approach. Renew. Sustain. Energy Rev. 16, 3302–3311 (2012)
Wibowo, S., Deng, H.: Consensus-based decision support for multicriteria group decision making. Comput. Ind. Eng. 66, 625–633 (2013)
Moura, P.S., de Almeida, A.T.: Multi-objective optimization of a mixed renewable system with demand-side management. Renew. Sustain. Energy Rev. 14, 1461–1468 (2010)
Diakoulaki, D., Karangelis, F.: Multi-criteria decision analysis and cost-benefit analysis of alternative scenarios for the power generation sector in Greece. Renew. Sustain. Energy Rev. 11, 716–727 (2007)
Chatzimouratidis, A.I., Pilavachi, P.A.: Technological, economic and sustainability evaluation of power plants using the analytic hierarchy process. Energy Policy 37, 778–787 (2009)
Cristobal, S., Ramon, J.: Multi-criteria Analysis in the Renewable Energy Industry. Springer, London (2012)
Antunes, C.H., Martins, A.G., Brito, I.S.: A multiple objective mixed integer linear programming model for power generation expansion planning. Energy 29, 613–627 (2004)
Amer, M., Daim, T.U.: Selection of renewable energy technologies for a developing county: a case of Pakistan. Energy. Sustain. Dev. 15, 420–435 (2011)
Wang, J.J., Jing, Y.Y., Zhang, C.F., Zhao, J.H.: Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renew. Sustain. Energy Rev. 13, 2263–2278 (2009)
Stein, E.W.: A comprehensive multi-criteria model to rank electric energy production technologies. Renew. Sustain. Energy Rev. 22, 640–654 (2013)
Brand, B., Missaoui, R.: Multi-criteria analysis of electricity generation mix scenarios in Tunisia. Renew. Sustain. Energy Rev. 39, 251–261 (2014)
Pappas, C., Karakosta, C., Marinakis, V., Psarras, J.: A comparison of electricity production technologies in terms of sustainable development. Energy Convers. Manag. 64, 626–632 (2012)
Troldborg, M., Heslop, S., Hough, R.L.: Assessing the sustainability of renewable energy technologies using multi-criteria analysis: suitability of approach for national-scale assessments and associated uncertainties. Renew. Sustain. Energy Rev. 39, 1173–1184 (2014)
Al Garni, H., Kassem, A., Awasthi, A., Komljenovic, D., Al-Haddad, K.: A multicriteria decision making approach for evaluating renewable power generation sources in Saudi Arabia. Sustain. Energy Technol. Assess. 16, 137–150 (2016)
Wibowo, S., Deng, H.: Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty. Waste Manag. 40, 127–135 (2015)
Wibowo, S., Grandhi, S.: Evaluating the performance of recoverable end-of-life products in the reverse supply chain. Int. J. Netw. Distrib. Comput. 5, 71–79 (2017)
Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20, 87–96 (1986)
Panwar, A.: Evaluation of kernel based Atanassov’s intuitionistic fuzzy clustering for network forensics and intrusion detection. Int. J. Softw. Innov. 4, 1–15 (2016)
Xu, Z.S., Yager, R.R.: Some geometric aggregation operators based on intuitionistic fuzzy sets. Int. J. Gen Syst. 35, 417–433 (2006)
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Wibowo, S., Grandhi, S. (2019). A Multicriteria Group Decision Making Approach for Evaluating Renewable Power Generation Sources. In: Lee, R. (eds) Computer and Information Science. ICIS 2018. Studies in Computational Intelligence, vol 791. Springer, Cham. https://doi.org/10.1007/978-3-319-98693-7_6
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DOI: https://doi.org/10.1007/978-3-319-98693-7_6
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