An Efficient Energy Management and Control Strategy for a Hybrid Microgrid System

Majlesi Journal of Electrical Engineering

مقاله 4، دوره 19، شماره 2، شهریور 2025، صفحه 1-10   

نوع مقاله: Reseach Article

شناسه دیجیتال (DOI): 10.57647/j.mjee.2025.1902.27

نویسنده

Aymen Kadhim Mohaisen^*

Department of Electrical Power, Amara Technical Institute, Southern Technical University, Missan, Iraq.

چکیده

Areas with high or unstable electricity costs implement microgrids (MGs), making them economically viable. They also provide backup power during grid outages, reducing peak demand charges and promoting grid independence. Lowering electricity costs within an MG can lead to increased economic activity and improved quality of life. MGs improve power quality and play an important role in renewable energy (RE) systems. MGs can help reduce carbon emissions by integrating renewable energy sources into the electrical grid and eliminating the need for fossil fuel electricity generation. Therefore, minimizing electricity prices in an MG is essential for ensuring affordability, sustainability, and reliability, as well as promoting the widespread adoption of MG technology. This paper uses the linear programming optimization (LPO) method as an energy management system (EMS) to manage the energy and power sharing between the MG components, which are solar photovoltaic (PV), battery energy storage system (BESS), and load. Moreover, we tested the
proposed system PV/BESS under real solar irradiance and residential load profiles using MATLAB/Simulink software. We subjected the MGs to tests under different weather conditions, specifically clear and cloudy days, to evaluate the proposed system. The results show that the proposed technique provides the lowest price of electricity on clear and cloudy days when compared to the base case. The LPO-based EMS reduced the daily grid cost from 904.1$ to 580$, and it provides a cost savings of 45% when the grid usage is 3400 kWh. Finally, the suggested EMS reduces the grid’s cost from 700$ to 370$ under cloudy day conditions, saving 80% of the cost.

کلیدواژه‌ها

Microgrid؛ Linear programming optimization؛ Energy management system؛ Solar battery energy storage

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