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A novel plug-in electric vehicle (PEV) charging coordination scheme for smart buildings, processed in two separate stages bridged by a load guided signal, is proposed in this study. The goal of the proposed coordination is to minimize the overall energy cost of the building, while satisfying the desired target and operation range of the state of charge (SoC) of each PEV. As the PEV penetration level grows, uncoordinated charging may impact the stability of the building’s energy system by increasing the peak demand and introducing uncertainty. Consequently, the charging decisions on the PEV fleet require considering the uncertainty of the drivers’ behavior and the power demand pattern of the coupled building. In this study, a customized load guided signal is introduced for PEV fleet charging. It formulated and implemented through mixed integer linear programming in two separate stages. The first stage involves the extraction of the electric vehicle supply equipment (EVSE) based guide signal for the benefits and physical constraints of the building’s energy system. The load guided signals are created by jointly investigating the charging/discharging flexibility of the EVSE using load prediction and the PEV fleet to minimize the electricity cost in the time-of-use energy market. In the second stage, the priority weight is exploited for distributing the charging/discharging decisions for individual PEVs. To evaluate the performance of the proposed method, numerical evaluations were conducted at various PEV penetration levels using a pair of energy consumption and vehicle parking datasets for the building. The case study demonstrates that the proposed scheme provides 12% load factor improvement and 13% cost reduction at a 50% PEV penetration level.

Load Guided Signal-Based Two-Stage Charging Coordination of Plug-In Electric Vehicles for Smart Buildings