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Sustainable development goal-driven MCDM for HRES configuration selection: Prioritizing hydrogen production from excess electricity via integrated objective and subjective weighting methods

Samal SyrlybekkyzyFaculty of Engineering, Yesenov University, Aktau, 130002, KazakhstanAkhmetov Berik BakytzhanovichFaculty of Engineering, Yesenov University, Aktau, 130002, KazakhstanBaimbetov DinmukhambetFaculty of Engineering, Yesenov University, Aktau, 130002, KazakhstanAskar SeidaliyevFaculty of Engineering, Yesenov University, Aktau, 130002, KazakhstanMohammad Hossein AhmadiFaculty of Mechanical Engineering, Shahrood University of Technology, Shahrood, IranHabib Forootan FardInstitute of Research and Development, Duy Tan University, Da Nang, Viet NamOtabek MukhitdinovDepartment of Mechanical Engineering, Kimyo International University in Tashkent, Shota Rustaveli Str. 156, Tashkent, 100121, UzbekistanDilshod RaupovThe Department of Technology of mechanical engineering, Tashkent State Technical University, University street 2, Tashkent, 100095, Uzbekistan

2026en

Ochiq kirish: yoʻq

ABI

Annotatsiya

This study focuses on the selection of the best hybrid renewable energy system (HRES) configuration based on technical, economic, environmental, and sustainable development indices, considering how excess electricity (EE) is best utilized for hydrogen production, water desalination, grid sales, storage, or dumping. The integration of sustainable development goals (SDGs) into configuration selection and decision-making regarding EE utilization has not been considered. A primary residential load demand of 1000 kWh/day for a case study in Astana, Kazakhstan, is considered to be supplied through an HRES. Results show that the PV/WT/Gen/Bat configuration and the use of EE for hydrogen production, with an energy cost of 0.128 $/kWh and a renewable fraction (RF) of 90%, fulfill all considered aspects with the highest TOPSIS score, where weights are generated using DEMATEL-ANP, the Best Worst Method (BWM), and CRITIC. Sensitivity analyses of resource, technical, and economic parameters generalize the results for other conditions.

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Identifikatorlar

DOI: 10.1016/j.ijhydene.2026.157704

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