Event-Based Optimization for Stochastic Matching EV Charging Load with Uncertain Renewable Energy

It is of great importance to control the elastic demand to follow the renewable energy supply in order to reduce its fluctuation on the grid. Electrical vehicle (EV) is a promising form of the elastic demand. Considering the random nature of the EV charging load, it would be ideal if the charging load of the EVs can be controlled to match the wind energy supply for improving wind power utilization. We consider this important problem in this paper and make the following major contributions. First, we formulate the stochastic matching problem as a Markov decision process (MDP), which is then solved approximately by event-based optimization (EBO) to overcome the curse of dimensionality. Second, simulation-based policy improvement is used to enhance a given heuristic-based policy for EV charging. Third, we numerically demonstrate the performance of our method by comparing with the dynamic programming method.