An integrated decision-making approach with golden cut and bipolar q-ROFSs to renewable energy storage investments

Abstract

A new hybrid fuzzy decision-making model is created in this study to evaluate significant factors of renewable energy storage investments and select the appropriate energy types. The factors are analyzed with golden cut-oriented bipolar q-rung orthopair fuzzy (q-ROF) multi-stepwise weight assessment ratio analysis (M-SWARA). Moreover, alternatives are examined by golden cut-oriented bipolar q-ROF elimination and choice translating reality (ELECTRE). The calculations are also made with IFSs and PFSs to measure the reliability. This study gives a novel approach to selection problem of renewable energy storage investments with golden cut, bipolar, and q-ROFSs. It is identified that capacity protection has the greatest weight with respect to the storage investments. Additionally, regarding the ranking results, solar is the best clean energy alternative for the energy storage. Hence, investors should give priorities avoiding the delays with the full capacity of renewable energy production. Minimizing the energy loss in the energy storage process will contribute to the increase in performance. In this way, it will be possible to ensure sustainability by increasing the profitability of the projects. It would be the right decision for investors to prioritize solar energy projects to increase their energy storage efficiency. Especially in recent years, very important technological developments have occurred for energy storage process in solar energy projects. Therefore, by prioritizing the solar energy for this purpose, the sustainability of the energy projects can be provided.