Impact of Vehicle to Home on System Demand Profiles and Available Flexibility

Vehicle to home (V2H) uses bidirectional charging to transfer the energy stored in electric vehicle (EV) batteries for household electricity usage. The usage of energy from EV batteries can lower energy bills by tapping the EV battery during high-cost periods and recharging during low-cost periods. In this work, a V2H optimization model is used to minimize home energy costs considering household electrical and heating demand, EV usage, and generation from rooftop solar under different electricity tariff structures, namely a static three-tier (day/night/peak) and the dynamic tariff structures. The work uses the optimization model to generate 100 representative residential demand profiles assuming V2H usage, which are then used to obtain total aggregate system residential demand assuming widespread use of V2H. The impact of widespread use of V2H on system-level demand profiles under different tariff structures is thus investigated for a case study using data for Ireland. It is shown that the adoption of V2H can give rise to new peaks in residential demand by aligning all charging with hours when electricity costs are low. To mitigate these peaks and flatten the load, nighttime charging constraints can be introduced. Charging constraints that reduce the charging power to 30% of maximum and restrict the minimum EV battery state of charge (SOC) to 50% are shown to be effective in reducing the peak loads by 50%. The impact of adoption of V2H on the availability of up and down flexibility from EV charging is also investigated. It is shown that the use of V2H restricts the available flexibility with down flexibility in particular being largely restricted to nighttime hours. However, the introduction of the load flattening charging constraints results in a better distribution of flexibility over nighttime hours.