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• W3123668911 endingPage "110725" @default.
• W3123668911 startingPage "110725" @default.
• W3123668911 abstract "Researchers have often overlooked the emissions problem during the suitable selection of renewable energy (RE) systems. Therefore, there is a need for an integrated framework that simultaneously considers the economic, technical and environmental criteria for the selection of the appropriate configuration. Firstly, a multi-objective optimization is performed using the ε− constraint method with a simulated annealing algorithm. Then a scenario-based method with a hybrid multi-criterion decision-making approach is used to rank all the available configurations. Five operating strategies are developed to make different configurations, i.e. battery only, pumped hydro storage (PHS), battery–diesel generator (DG), PHS–DG, and hybrid pumped–battery storage. A total of seven scenarios are made based on the weightage given to each main criterion. The study reveals that solar–wind–PHS–DG was the top-ranking alternative under four scenarios, solar–wind–PHS ranked first in two scenarios, and solar–wind–DG–battery got preference under the no-preference scenario; this shows that preferential selection (assigning a weighting to each criterion) significantly affects results. Emissions of all considered RE-based alternatives range from 0.072 to 0.148 kg (CO2 equivalent) per kWh of the served load. Furthermore, sensitivity analysis reveals that technical criteria conflict more with economic criteria than with environmental criteria. The impact of land requirements (an environmental sub-criterion) is visible in this study, indicating the high requirement of land for RE systems. The most appropriate configuration type is selected depending solely on the priorities defined by investors and policy-makers." @default.
• W3123668911 created "2021-02-01" @default.
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• W3123668911 date "2021-04-01" @default.
• W3123668911 modified "2023-10-12" @default.
• W3123668911 title "A hybrid method for scenario-based techno-economic-environmental analysis of off-grid renewable energy systems" @default.
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• W3123668911 doi "https://doi.org/10.1016/j.rser.2021.110725" @default.
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