Optimal battery management in PV + WT micro-grid using MSMA on fuzzy-PID controller: a real-time study

Abstract In modern energy systems, managing energy within a microgrid (MG) poses significant challenges due to the unpredictable nature of renewable energy sources. This article introduces a novel approach for optimal battery management in a photovoltaic–wind microgrid using a Modified Slime Mould Algorithm (MSMA) combined with a fuzzy-PID controller. The microgrid comprises a wind turbine (WT) generator, solar photovoltaic (PV) generator, and a battery energy storage system (BESS). The BESS plays a crucial role in meeting high power demand during outages, while the fuzzy-PID controller ensures accurate prediction of the battery’s state of charge (SOC). The proposed method’s performance is evaluated by comparing the MSMA-based fuzzy-PID controller with a PSO-based fuzzy-PID controller to establish its effectiveness. The optimal energy management of the BESS in the microgrid is achieved by fine-tuning the fuzzy-PID controller using the MSMA algorithm. Simulation results demonstrate that the battery management system (BMS) effectively optimizes charging and discharging based on renewable energy availability and load demand. The fuzzy-PID controller adjusts battery operation by minimizing the error between the desired and actual battery voltage. Performance validation has been conducted in RTS-lab using five distinct load scenarios—45 kW, 35 kW, 75 kW, 4.5 kW, and 12.5 kW, which confirming the effectiveness of the proposed control strategy for energy management.