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Optimization of Microgrid Energy Management using a Genetic Algorithm

Article scientifique 2025 Anglais

Résumé

Microgrids (MGs) are used in systems of clean and renewable energy. This research presents an efficient Energy Management System (EMS) for the economic operation of grid-connected integrated solar renewable MGs. The proposed MG consists of a Photovoltaic (PV) generator and a battery storage system and uses a Genetic Algorithm (GA) based on a one-day scheduling timeframe. The main objectives of this study are, achieving the load power requirements at a minimum operating cost, improving the overall efficiency, and protecting the battery from depletion and overcharging. The obtained results were compared with the state-space heuristic optimization technique using two different load profiles to demonstrate the effectiveness of the proposed method. The results show that the total operating cost is reduced by 17.66% and 17.04%, respectively, compared to the state-space heuristic optimization approach.

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Nouar, Y., Boukadoum, A., Boudebbouz, O. (2025). Optimization of Microgrid Energy Management using a Genetic Algorithm. https://doi.org/10.48084/etasr.10278

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Auteur(s)

Yamina Nouar Ahcene Boukadoum Omar Boudebbouz

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