Stochastic-programming-based bidding strategy for V2G services

Vehicle-to-grid (V2G) is an effective technique for the integration of electric vehicles (EVs) into the grid. Aggregation of large numbers of EVs under a single entity to participate in electricity markets is necessary for its implementation. However, trading in the day-ahead energy or regulation market is risky due to uncertain prices, load demand, and deployment signals. In this work, an optimal bidding algorithm for unidirectional V2G is developed while considering the uncertainties associated with regulation up/down prices and deployment signals. Stochastic programming is used to formulate this optimization with the objective to maximize total profit of an EV aggregator participating in the regulation market. Simulation results demonstrate the benefits of the proposed stochastic approach in comparison with a deterministic one.