An integrated Delphi-AHP and Fuzzy TOPSIS approach toward ranking and selection of renewable energy resources in Pakistan

Solangi, Yasir Ahmed and Tan, Qingmei and Mirjat, Nayyar Hussain and Valasai, Das Gordhan and Ali Khan, Muhammad Waris and Ikram, Muhammad (2019) An integrated Delphi-AHP and Fuzzy TOPSIS approach toward ranking and selection of renewable energy resources in Pakistan. Processes, 7 (2). pp. 1-31. ISSN 2227-9717. (Published)

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Pakistan has long relied on fossil fuels for electricity generation. This is despite the fact that the country is blessed with enormous renewable energy (RE) resources, which can significantly diversify the fuel mix for electricity generation. In this study, various renewable resources of Pakistan—solar, hydro, biomass, wind, and geothermal energy—are analyzed by using an integrated Delphi-analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (F-TOPSIS)-based methodology. In the first phase, the Delphi method was employed to define and select the most important criteria for the selection of RE resources. This process identified four main criteria, i.e., economic, environmental, technical, and socio-political aspects, which are further supplemented by 20 sub-criteria. AHP is later used to obtain the weights of each criterion and the sub-criteria of the decision model. The results of this study reveal wind energy as the most feasible RE resource for electricity generation followed by hydropower, solar, biomass, and geothermal energy. The sensitivity analysis of the decision model results shows that the results of this study are significant, reliable, and robust. The study provides important insights related to the prioritizing of RE resources for electricity generation and can be used to undertake policy decisions toward sustainable energy planning in Pakistan.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Delphi; Analytical hierarchy process; Renewable energy (RE) resources; Sustainable energy planning
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Q Science > QA Mathematics > QA76 Computer software
Q Science > QD Chemistry
Faculty/Division: Faculty of Industrial Management
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 13 May 2019 07:48
Last Modified: 13 May 2019 07:48
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