An Integrated Entropy-TOPSIS Methodology for Evaluating Green Energy Sources

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).