Coordinated Management of Residential Batteries and Vehicle-to-Grid Resources Under Dynamic Electricity Pricing in a Smart Community Microgrid

Abstract

The increasing integration of photovoltaic (PV) systems, battery energy storage systems (BESSs), and electric vehicles (EVs) is transforming residential electricity networks into flexible community microgrids. However, intermittent renewable generation and mismatches between generation and demand require effective energy management strategies for reliable and economical operation. This paper presents a dynamic pricing-based Energy Management System (EMS) for a residential PV microgrid comprising 19 households with a total rooftop PV capacity of 76 kW, distributed battery storage rated at 9.6 kWh per household, and 19 Vehicle-to-Grid (V2G)-enabled EVs with 50 kWh battery capacity each. The proposed EMS integrates PV generation data obtained from PVsyst, residential load profiles, dynamic electricity pricing, and coordinated control of household batteries, EV charging/discharging, V2G operation, and grid interactions. A rule-based scheduling framework is employed to improve renewable energy utilization, reduce electricity procurement costs, and enhance overall microgrid performance under predefined operational and price-based decision rules. Hourly-resolution simulations were conducted over an extended operating period to evaluate the effectiveness of the proposed strategy. The results achieved a PV self-consumption rate of 86.9%, community energy self-sufficiency of 63.6%, and PV energy coverage of 87.9%. The coordinated storage operation resulted in 34,732 kWh of battery charging energy and 30,018 kWh of discharged energy, with an average battery efficiency of 86.4%. Grid imports and exports were 27,671 kWh and 10,015 kWh, respectively, yielding an export-to-import ratio of 0.36. Transformer loading was maintained at 12.8% of its rated capacity, indicating secure transformer operation with loading well below the rated capacity. Overall, the proposed rule-based EMS improves renewable energy utilization, grid flexibility, and operational performance, providing a practical approach for managing distributed energy resources in residential community microgrids.