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A four-stage intelligent optimization and control algorithm for an electric vehicle (EV) bidirectional charging station equipped with photovoltaic generation and fixed battery energy storage and integrated with a commercial building is proposed in this paper. The proposed algorithm aims at maximally reducing the customer satisfaction-involved operational cost considering the potential uncertainties, while balancing the real-time supply and demand by adjusting the optimally scheduled charging/discharging of EV mobile/local battery storage, grid supply, and deferrable load. The chance-constrained optimization objective has been stated in stages: (1) stage I, optimization of day-ahead energy management schedules; (2) stage II, multitiered EV charging price update and optimization of discharging participation bonus; (3) stage III, optimization of hour-ahead energy management schedules; and (4) stage IV, real-time control. Such algorithm provides more resilience for unpredictable conditions, provides more incentives for EV users to participate, and better coordinates the integrated system including the building load to reliably serve the customers while lessening cost. Case studies are implemented and the comparison analysis is performed in terms of the use and benefit of each design feature of the algorithm. The results indicate that the proposed algorithm can reduce the operational cost and at the same time provide higher tolerability toward uncertainties.
Yan et al. (Mon,) studied this question.
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