Optimization of off-grid hybrid renewable energy systems for cost-effective and reliable power supply in Gaita Selassie Ethiopia
Status PubMed-not-MEDLINE Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články
PubMed
38740883
PubMed Central
PMC11636871
DOI
10.1038/s41598-024-61783-z
PII: 10.1038/s41598-024-61783-z
Knihovny.cz E-zdroje
- Klíčová slova
- Cost-effective energy solutions, Hybrid energy systems, Optimization algorithms, Renewable energy systems, Rural electrification,
- Publikační typ
- časopisecké články MeSH
This paper explores scenarios for powering rural areas in Gaita Selassie with renewable energy plants, aiming to reduce system costs by optimizing component numbers to meet energy demands. Various scenarios, such as combining solar photovoltaic (PV) with pumped hydro-energy storage (PHES), utilizing wind energy with PHES, and integrating a hybrid system of PV, wind, and PHES, have been evaluated based on diverse criteria, encompassing financial aspects and reliability. To achieve the results, meta-heuristics such as the Multiobjective Gray wolf optimization algorithm (MOGWO) and Multiobjective Grasshopper optimization algorithm (MOGOA) were applied using MATLAB software. Moreover, optimal component sizing has been investigated utilizing real-time assessment data and meteorological data from Gaita Sillasie, Ethiopia. Metaheuristic optimization techniques were employed to pinpoint the most favorable loss of power supply probability (LPSP) with the least cost of energy (COE) and total life cycle cost (TLCC) for the hybrid system, all while meeting operational requirements in various scenarios. The Multi-Objective Grey Wolf Optimization (MOGWO) technique outperformed the Multi-Objective Grasshopper Optimization Algorithm (MOGOA) in optimizing the problem, as suggested by the results. Furthermore, based on MOGWO findings, the hybrid solar PV-Wind-PHES system demonstrated the lowest COE (0.126€/kWh) and TLCC (€6,897,300), along with optimal satisfaction of the village's energy demand and LPSP value. In the PV-Wind-PHSS scenario, the TLCC and COE are 38%, 18%, 2%, and 1.5% lower than those for the Wind-PHS and PV-PHSS scenarios at LPSP 0%, according to MOGWO results. Overall, this research contributes valuable insights into the design and implementation of sustainable energy solutions for remote communities, paving the way for enhanced energy access and environmental sustainability.
Department of Electrical and Computer Engineering Debre Markos University Debre Markos Ethiopia
Department of Electrical and Computer Engineering Hawassa University Hawassa Ethiopia
Department of Electrical Engineering Graphic Era Dehradun 248002 India
Graphic Era Hill University Dehradun 248002 India
Hourani Center for Applied Scientific Research Al Ahliyya Amman University Amman Jordan
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