An Integrated Entropy-TOPSIS Methodology for Evaluating Green Energy Sources

An Integrated Entropy-TOPSIS Methodology for Evaluating Green Energy Sources

Chiranjib Bhowmik (Faculty of Engineering and Technology, Parul Institute of Engineering and Technology, Parul University, Vadodara, India), Mohamad Amin Kaviani (Department of Electrical and Computer Engineering, KIOS Research and Innovation Center of Excellence, University of Cyprus, Nicosia, Cyprus), Amitava Ray (Jalpaiguri Government Engineering College, India) and Lanndon Ocampo (Cebu Technological University, Philippines)
Copyright: © 2020 |Pages: 27
DOI: 10.4018/IJBAN.2020070104
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Abstract

This research aims to select the optimum green energy sources for sustainable planning from a given set of alternatives. The study presents an integrated multi-criteria decision-making analysis—the entropy-technique for order of preference by similarity to ideal solution (TOPSIS)—to evaluate the energy sources: coal, oil, gas, carbon capture; and storage: nuclear fission/power, large hydro, small hydro, wind, solar photovoltaic, concentrating solar, geothermal, and biomass. Information related to energy parameters are always imprecise; thus, to address the impreciseness of eliciting judgments in the preferences of criteria, the entropy method is used. TOPSIS method is then utilized to select the optimum sources. Results show that solar-photovoltaic is the optimum green energy source having the highest score value, and annual generation is the most prioritized criterion. Sensitivity analysis also demonstrates the robustness of the selection methodology.
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1. Introduction

Green energy sources selection is considered as a crucial issue for any developed as well as developing countries due to its direct impact on society and environment (Çolak and Kaya 2017; Ervural et al. 2018). The process of green energy sources selection is relatively complex due to the diverse influencing criteria that must be taken into consideration (Ren and Lützen 2017; Tsagarakis et al. 2018). Due to the increased utilization of fossil fuels, energy markets today are under tremendous pressure to incorporate environmentally-benign key resources for a sustainable future (Büyüközkan and Güleryüz 2017). The extensive use of fossil fuels in industrial and non-industrial sectors causes numerous environmental problems such as SOx, NOx, CO2 emissions, resource depletion and global warming forcing governments and environmental activists worldwide to consider the use of green resources (Midilli et al. 2006; Wurlod and Noailly 2018). Accordingly, the use of green energy sources is a hot topic of discussion in achieving a greener and more environmentally friendly future (Ren and Lützen 2017; Ng and Zheng 2018). Different green energy sources have different economic, environmental and social importance such that one green energy alternative may perform better than other energy alternatives in at least one aspect but may perform worse in other aspects (Ren and Lützen 2017; Büyüközkan and Güleryüz 2017; Wu et al. 2018). Thus, decision-makers are usually puzzled when choosing an optimum source, at the selection level, with an assessment that may cover various areas which boundaries may not be readily identifiable (Ren and Lützen 2017; Kumar et al. 2017; Kumar and Samuel 2017; Zhao and Chen 2018). The challenge is not only to recognize the role of decision-makers, energy managers or policymakers, but rather to develop a comprehensive framework combining various strategic approaches to address green energy sources selection problem (Qin et al. 2017; Yuan et al. 2018; Ren 2018; Manzella et al. 2018; Aklin et al. 2018).

It is evident from the earlier studies that a dearth of current literature is available with various energy sources selection techniques depending on data availability (Baul et al. 2018; Kardooni et al. 2018; Galvin 2018; Zhao and Chen 2018; Manzella et al. 2018; Aklin et al. 2018; Gao et al. 2018; Liu et al. 2018).

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