This study presents the design and implementation of a fuzzy logic-based energy management system for optimizing power distribution and managing renewable energy sources within Malaysian microgrids.
The research involves creating and testing a fuzzy logic controller (FLC) to improve energy scheduling and management within microgrids, particularly focusing on the integration of photovoltaic (PV) systems and battery storage.
The study is conducted by researchers M. Nur-E-Alam, T. Abedin, N.A. Samsudin, and others involved with their respective institutions.
The findings are published in 2025.
The study focuses on Malaysia's energy management systems and microgrid setups.
The research aims to address issues related to energy supply and demand within microgrids, particularly concerning the efficient use of renewable resources and the prevention of battery overcharging or discharging.
The fuzzy logic controller is implemented and assessed using MATLAB/Simulink simulations along with various comparative analyses against Proportional-Integral Controllers (PIC).
The study emphasizes the importance of total harmonic distortion (THD) analysis to compare system performances and maintain IEEE standards.
FLC offers a flexible solution to energy scheduling effectively assessed by MATLAB/Simulink simulations.
FLC provides superior SOC control in a system comprising PV, battery, grid, and load.
The findings demonstrate the output current is zero when the SOC is higher than 80% or lower than 20%.
The results show the PI controller design reduces THD in the current signal, whereas FLC does not reduce THD of the grid current.
Start with the growing need for efficient energy management systems (EMS) due to increased renewable energy usage. Engage the reader by highlighting potential benefits of fuzzy logic controllers (FLC) over traditional methods.
Discuss the significance of microgrids and renewable energy within Malaysia's energy policy, introducing concepts like Operational Models, Energy Storage Systems, and current challenges facing traditional EMS frameworks.
Explain the design of the fuzzy logic controller (FLC) and the integration with MATLAB/Simulink, focusing on the technical aspects of the controller and simulation parameters.
Present key results, including the comparison of FLC and PI performance, and how FLC reduces the risk of overcharging/discharging batteries, alongside THD analysis and compliance with IEEE standards.
Summarize the main outcomes, the innovative approach of FLC, and potential future research avenues to build on this work for enhancing energy management systems using fuzzy logic.