Demand side management verification system for electric vehicles

Large-scale grid integration of plug in Electric Vehicles (EVs) brings in many challenges and opportunities for electric power systems. Considering their relatively high power demand and flexibility in terms of charging time, EVs can offer opportunities for demand side management. In particular, the socalled EV Aggregators or Charge Optimization Systems (COS) can optimize the charging schedule of EVs with respect to a number of factors, such as available renewable generation and electricity market prices. However, the optimized schedules must be validated to assure that they do not lead to violation of any operational constraint of the power system. To this aim, major changes in the charging schedules to be applied by COS must be checked with the system operator. This paper describes an EV schedule verification system based on artificial neural networks. This system verifies if the COS schedules can be directly applied or if some modifications are necessary. The proposed approach is tested on two sample distribution systems.