Intelligent Rule-Based Energy Management and Control of HVAC, Photovoltaic Generation, and Battery Storage Systems in Smart Residential Microgrids

Abstract

The increasing adoption of renewable energy technologies in residential buildings necessitates intelligent energy management strategies capable of improving energy efficiency while maintaining occupant comfort. This study presents a smart home energy management framework integrating a Heating, Ventilation, and Air Conditioning (HVAC) system, rooftop photovoltaic (PV) generation, and a battery energy storage system (BESS) using a computationally efficient rule-based control strategy. The framework was developed and evaluated in MATLAB/Simulink, where HVAC thermal dynamics, household load demand, PV generation, and battery state-of-charge (SOC) behavior were coordinated through hysteresis-based temperature control and SOC-constrained battery management. Simulation results demonstrated that the proposed controller effectively maintained indoor temperature within the prescribed comfort band while enhancing renewable energy utilization. The integrated PV–battery system achieved a PV self-consumption rate of 100%, supplied 90.64% of the total household energy demand from renewable sources, and reduced grid electricity imports from 0.921 kWh to 0.103 kWh, corresponding to an 88.81% reduction in grid dependency. The battery operated safely within an SOC range of 34.18–50.00%, resulting in a utilization swing of 15.82 percentage points. These findings demonstrate that the proposed rule-based framework provides a practical, low-complexity, and reliable solution for improving renewable energy utilization, reducing grid reliance, and supporting sustainable smart residential energy management.