Design and Implementation of a Fuzzy-Based Microgrid Energy Management System

Renewable Energy Sources (RES) have recently gained an increase in popularity and adoption driven by their sustainable energy generation. Despite these benefits, the high costs and intermittent nature of RES pose significant challenges for efficient and reliable utilization. Microgrids (MGs) have emerged as a promising solution to address these challenges, offering improved energy management and enhanced economic benefits. However, the variability of RES, such as solar and wind power, can lead to power supply fluctuations that jeopardize the stability and reliability of MGs. To address these issues and optimize economic benefits and reliability, this paper proposes the design, implementation, and testing of an Energy Management System (EMS) for MGs. The EMS utilizes a Fuzzy Inference System (FIS) to optimize power flow and regulate MG frequency. The system was developed using MATLAB/Simulink and its performance was validated through simulations and real-world lab experiments on a MG testbed. The results demonstrate that the implemented EMS effectively optimizes power flow, stabilizes frequency, and enhances overall system reliability and efficiency. The developed EMS has the potential to significantly advance the deployment of efficient, reliable, and sustainable RES-integrated MGs for both off-grid and on-grid applications.