Optimizing Household Energy Management Using Fuzzy Logic for Enhanced Electricity Cost Reduction

This paper presents a Fuzzy Logic Controller (FLC)-based Household Energy Management System (HEMS) designed to minimize electricity costs in homes equipped with rooftop photovoltaic panels and battery energy storage systems (BESS). The FLC utilizes intuitive linguistic rules, reducing the need for complex system modeling and relying on readily available data for adaptation. A simplified BESS model, focusing on power and energy metrics, is employed. The proposed HEMS is compared against a typical rule-based controller (RBC) used in commercial products. Simulation results demonstrate that the FLC-based HEMS achieves approximately a 10% reduction in electricity costs compared to the RBC, highlighting the effectiveness of the proposed approach for optimizing energy consumption in residential households. The FLC's adaptability and reduced computational complexity make it a promising solution for enhancing the economic efficiency of hybrid home energy systems.