Optimal Home Energy Management System for a Residential Grid-Connected Microgrid Using Improved Slime Mold Algorithm

The current research introduces a home energy management system (HEMS) utilizing an improved slime mold 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), 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 operational cost of the BSS to minimize overall electricity costs. To achieve the control object, the system incorporates advanced power flow control techniques for the VSI and parallel converter system within the microgrid. The performance of the ISMA-based HEMS is evaluated through experimental validation on a practical microgrid platform. The findings demonstrate that the HEMS using ISMA outperforms conventional rule-based control strategy in terms of electricity cost reduction.