Home Energy Management combining a welfare calculation and Vehicle-to-house technique for grid stability

Abstract

The increasing adoption of electric vehicles (EVs) poses grid stability challenges. This study explores Home Energy Management (HEM) systems, facilitating bidirectional communication between users and energy providers to address these issues. We review HEM methods, including ZigBee, PLC control, and reinforcement learning, optimizing household energy usage. We investigate the incorporation of welfare calculation, accounting for occupants' well-being, and introduce the potential of Vehicle-to-Home (V2H) technology for enhancing energy resilience. Combining welfare calculation and V2H offers optimized HEM, prioritizing user comfort and decision-making efficiency. This report identifies research gaps and emphasizes the significance of delay-intolerant and delay-tolerant demand considerations. Battery charge-discharge conditions and utility welfare calculation are also discussed as critical facets of HEM. To solve the delay intolerant demand issue, EVs are used as storage devices to mitigate the peak load impacts using vehicle-to-house (V2H) technology. A scaled-down version (1:10^6) of the real UK electricity consumption system is used in the test. Simulation results verify that the proposed V2H system considering the welfare calculation can optimize the welfare level when one 60-kWh Tesla EV is involved in this scaled-down system.