Optimal Home Energy Management System for a Residential Grid-Connected Microgrid using Improved Slime Mould Algorithm

This study presents a home energy management system (HEMS) utilizing an improved slime mould algorithm (ISMA) for the efficient energy management of a residential grid-connected microgrid. The studied microgrid comprises a photovoltaic system (PVS), a battery storage system (BSS), two DC-DC converters, a DC-AC voltage source inverter (VSI), a Y-Y three-phase transformer, and varying electricity loads. The proposed ISMA-based HEMS optimizes the power flow ratio among the PVS, BSS, and the utility grid, taking into account factors including load demand, battery's state of charge (SOC), PVS power, time-of-use (TOU) electricity rates, feed-in tariffs, and the electricity costs of both battery and utility grid to minimize overall electricity costs. To achieve the control object, the system incorporates advanced power flow control (PFC) techniques for the voltage source inverter (VSI) and parallel converter system (PCS) within the microgrid. The performance of the ISMA-based HEMS is evaluated through experimental validation on a practical microgrid platform. Results indicate that the ISMA-based HEMS significantly reduces electricity costs compared to rule-based control strategy.