Comparative Analysis of MCDM Methods for the Evaluation of Optimum Green Energy Sources: A Case Study

Comparative Analysis of MCDM Methods for the Evaluation of Optimum Green Energy Sources: A Case Study

Chiranjib Bhowmik (Faculty of Engineering and Technology, Parul Institute of Engineering and Technology, Parul University, Vadodara, Gujarat, India), Sreerupa Dhar (Haldia Institute of Technology, India) and Amitava Ray (Jalpaiguri Government Engineering College, Jalpaiguri, India)
Copyright: © 2019 |Pages: 28
DOI: 10.4018/IJDSST.2019100101
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The aim of this article is to select the optimum green energy sources for sustainable planning from a given set of energy alternatives. This study examines the combined behavior of multi-criteria decision-making approaches-TOPSIS, MOOSRA and COPRAS are used to evaluate the green energy sources–solar, hydro, biogas and biomass and to identify the optimum source by appraising its functioning features based on entropy probability technique. An illustrative case study is presented in order to demonstrate the application feasibility of the combined approaches for the ranking of optimum green energy sources. The analyzed results show that biogas is the optimum green energy source having the highest score value obtained by combined approaches. The sensitivity analysis shows the robustness of the combined approaches with the highest effectiveness. The study not only considers the various cost criteria but other actors like power generation, implementation period and useful life are also considered to select the optimum green energy sources for future project investment.
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1. Introduction

Energy is considered one of the crucial elements in modern life for sustainable development. Globalization leads the modern society towards green energy resources (Bhowmik et al., 2017). Green energy sources are the sources of cleaner form of energy including solar, wind, hydro, biomass, geothermal and wave energy. In today’s life, high demand of energy can also boost the economy of the nation through implementation of green energy technologies (Bhowmik et al., 2017; Tsagarakis et al., 2018). In recent trends, a newly adopted concept is flying in the mind of researcher’s milieu which is defined as Green Energy Engineering, primarily aiming at combining the fossil and green era towards the implementation of clean and sustainable future (Tsagarakis et al., 2018). Due to the crisis in energy supply from green resources, various researchers are attracted to investigate or select the optimum sources of energies to secure the environment and promote those sources for regional development (Mardani et al., 2015). Research also shows that green energy entrepreneurship and green energy programs are better implemented when they are supported by the government policies (Wu et al., 2018). Policies also plays an important role for the nation in the promotion of green energy business towards energy sustainability (Mardani et al., 2015; Wu et al., 2018; Buyukozkan & Guleryuz, 2017). The green energy technologies for energy production are different, encompassing solar, wind, hydro, biogas, biomass, geothermal etc. Since each and every technology captures different earth resources in different ways, the environmental, economic, social, political and market impacts also vary compared to each technology (Moula et al., 2013). Thus, technology changes play a significant role in energy source evaluation dilemma. Green energy sources evaluation is fundamental for sustainable development in context with various conflicting criterion such as environmental, social, economic, technical, risk, security issues (Ervural et al., 2017; Colak & Kaya, 2017; Baul et al., 2018). Therefore, the need for green energy sources evaluation techniques with multi-criteria decision-making (MCDM) approaches is quite obvious for optimal evaluation (Dutta et al., 2011; Ozcan et al., 2011). There is a vast evidence of MCDM techniques used in different real-life engineering problems such as energy sources selection, material selection, supplier selection, location selection, management applications and so on for sustainable planning (Nigim et al., 2004). Some of the relevant studies by past researchers are highlighted below.

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