Alleviating Energy Poverty through Renewable Energy Technology: An Investigation Using a Best-Worst Method-Based Quality Function Deployment Approach with Interval-Valued Intuitionistic Fuzzy Numbers

Renewable energy technology is suitable for reducing consumption and emissions, the corresponding impact on poverty has aroused tremendous attention. This paper proposed best-worst method- (BWM-) based quality function deployment (QFD) approach within interval-valued intuitionistic fuzzy number (IVIFN) to select appropriate renewable alleviation. QFD firstly used explore relationship between reduction requirements (CRs), selection criteria (TRs), correlation among TRs. Interval-valued (IVIF) BWM then applied obtaining CRs. After that, IVIF-QFD method attain weight of TRs, which are evaluate alternatives through IVIF-VIKOR approach. The six representative technologies, including wind energy, solar biomass (direct combustion, combined heat power, gasification), hydropower have been selected in decision model, result shows that large-scale could be as best choice reduce issues, whose interval numbers [0, 0.2925]. Except prioritization findings this also contribute developing sustainable policies roadmaps.