A Collaborative Decision Model for Electric Vehicle to Building Integration

Abstract

The electric vehicle (EV) can be utilized as a dynamically configurable dispersed energy storage in the vehicle-to-building (V2B) operation mode to balance the energy demand. To enable efficient V2B integration, we propose a collaborative decision model to cooperatively operate building and EVs. A commercial building (medium office building) which has thermal and electric storage system, combine cooling, heating, and power system, and photovoltaic (PV) panel is assumed to be interconnected with a EV charging station which has its own PV panel. A multi-objective mixed integer linear programming (MILP) problem is formulated to study the energy exchange between the building and the EV charging station to minimize the operational cost for the building and the EV charging station simultaneously. A set of binary variables are introduced to model the EV's behaviors, such as entering, connecting to, or leaving the charging station. We employ a weighted sum approach to solve the multi-objective MILP to obtain Pareto operation decisions for trade-off analysis between the building and the charging station. Our experimental results demonstrate that the collaborative V2B integration can significantly reduce the operation cost for both the building and the charging station comparing to the non-cooperative strategy where the building and the charging station are operated separately.