Comparative Evaluation of Fuzzy and Rule-Based Energy Management Strategies for Photovoltaic–Battery Microgrids

Abstract

Renewable energy–based microgrids have emerged as an effective solution for integrating distributed energy resources such as photovoltaic (PV) generation and battery energy storage systems (BESS). However, the intermittent nature of renewable energy sources and variations in load demand present significant challenges for maintaining power balance and system stability. This paper presents a comparative evaluation of rule-based and fuzzy logic energy management strategies for a photovoltaic–battery microgrid using a MATLAB/Simulink-based digital twin. The proposed model integrates photovoltaic generation, battery storage, and load demand to simulate realistic operating conditions. Both control strategies are evaluated under varying solar irradiance and load scenarios based on voltage stability, battery state-of-charge dynamics, and energy utilization efficiency. Simulation results indicate that the fuzzy logic controller provides smoother battery operation, improved adaptability, and enhanced system stability compared with the conventional rule-based approach. The proposed framework provides an effective platform for evaluating advanced energy management strategies and supports future implementation in PLC-based microgrid control systems.