Effects of V2H Integration on Optimal Sizing of Renewable Resources in Smart Home Based on Monte Carlo Simulations

This paper investigates optimal sizing of rooftop PV, wind turbine (WT), and battery storage system (BSS) in smart home (SH) with a plug-in electric vehicle (PEV) considering vehicle-to-home (V2H) and home-to-grid operations. The proposed idea is to use a rule-based home energy management system (HEMS) along with the Monte Carlo simulations and particle swarm optimization to find the optimal sizes of renewable resources and BSS by minimizing the annual cost of household electricity. The probabilistic behaviors of wind speed, irradiance, temperature, load and electricity rate, as well as the availability of PEV are considered for the input data generation. Detailed simulations and sensitivity analyses are performed to investigate the impacts of shiftable loads, V2H integration, battery charge/discharge rates, designated maximum daily export energy and maximum PV, and WT and battery capacity limits on the annual and levelized costs of electricity. Our analyses reveal the possibility of eliminating BSS altogether in SH with PEV with some reduction in annual electricity cost.