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In some micro grids, the charging of electric vehicles (EVs) and the generation of wind power may partially cancel each other. This is an effective way to reduce the variation of the wind power to the state grid. Due to the forecasting error, it is of great practical interest to schedule the EV charging demand under the worst-case scenario of the wind power generation. We consider this important robust scheduling problem in this paper and make three major contributions. First, we formulate this robust scheduling problem as a robust stochastic shortest path problem whereby the objective function is a weighted sum of the wind power utilization and the total charging cost. Second, a robust simulation-based policy improvement method is developed to improve the performance of a base policy in the worst case. This improvement is mathematically shown under mild assumptions. Third, the performance of this method is numerically demonstrated based on real wind and EV data.

Robust Scheduling of EV Charging Load With Uncertain Wind Power Integration