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Modern smart grid, as a typical cyber-physical system (CPS), allows plug-in hybrid electric vehicles (PHEVs) to be a promising candidate for grid services. In this paper, by following the CPS design approach, we propose a novel framework for the local aggregator to estimate the charging status and solve for the charging control signals for PHEVs. The physical battery charging is executed by charging stalls, where charging information is processed in the embedded system and only the generated index information is transmitted to the aggregator via Internet. An aggregation model is developed for the entire cyberspace to inherently guarantee heterogeneous charging requirements, i.e., deadlines for charging. Furthermore, we develop a nonlinear model-predictive control (NMPC) scheme for the overnight valley-filling service. Both the aggregation model and control strategy are designed based on the PHEV population migration probabilities. From the CPS perspective, both the cyber and physical loads of this novel framework are extremely low. As part of this paper, we present a case study to verify the proposed approaches.
Liu et al. (Thu,) studied this question.