Optimization of Microgrid Energy Management using a Genetic Algorithm

Authors

  • Yamina Nouar Faculty of Technology, Electrical Engineering Department, Electrotechnical Laboratory of Skikda (LES), University of Skikda, Algeria
  • Ahcene Boukadoum Faculty of Technology, Electrical Engineering Department, Electrotechnical Laboratory of Skikda (LES), University of Skikda, Algeria
  • Omar Boudebbouz Faculty of Technology, Electrical Engineering Department, Electrotechnical Laboratory of Skikda (LES), University of Skikda, Algeria
Volume: 15 | Issue: 3 | Pages: 23742-23747 | June 2025 | https://doi.org/10.48084/etasr.10278

Received: 17 January 2025 | Revised: 29 March 2025 | Accepted: 9 April 2025 | Online: 4 June 2025


Corresponding author: Yamina Nouar

Abstract

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.

Keywords:

microgrid, optimization, genetic algorithm, state-space heuristic, energy management, energy storage system, photovoltaic

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[1]
Nouar, Y., Boukadoum, A. and Boudebbouz, O. 2025. Optimization of Microgrid Energy Management using a Genetic Algorithm. Engineering, Technology & Applied Science Research. 15, 3 (Jun. 2025), 23742–23747. DOI:https://doi.org/10.48084/etasr.10278.

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