Résumé

This paper introduces an energy management strategy that enhances the utilization of renewable energy sources through the use of battery energy storage, with the goal of promoting sustainable energy use in a microgrid. The optimization problem is formulated to boost the efficiency of energy distribution while reducing costs and environmental impacts, ensuring a reliable energy utilization to meet the variable demand power that occur during the day. The proposed algorithm determines the ideal power output for each component of the microgrid, including the charging power of electric vehicles, while considering grid limitations, variable electricity tariffs, and user needs. The developed algorithms are solved using heuristic algorithms and mixed-integer linear programming, with outcomes compared against two baseline scenarios where energy management strategies depend solely on rule-based calculations. Simulations are executed daily over a year with a one-hour time resolution to ensure a fair comparison among the implemented methods with annual results. The performance of rule-based methods is benchmarked against optimization techniques including Mixed-Integer Linear Programming (MILP), Particle Swarm Optimization (PSO), Differential Evolution (DE), and a hybrid PSO-DE strategy. Simulation results show that when only BESS flexibility is leveraged, cost reductions range from 1.97% to 2.13%. When EV flexibility is also incorporated, cost savings increase substantially—up to 13.22% with MILP. MILP achieves the best performance with minimal computational effort, while hybrid PSO-DE provides a practical compromise between optimization quality and time requirements. The findings reveal a notable improvement in both cost efficiency and environmental advantages when applying the proposed energy management algorithm, underscoring its potential to improve the overall functionality of microgrid systems.