An optimal scheduling for aggregators in smart grids

This paper proposes a stochastic optimization method that produces bidding curves to be submitted by an aggregator to the day ahead wholesale markets taking into account the possible imbalance costs as well as the uncertainty of the forecasts (market price, demand and renewable generation for the next day). A formulation is proposed, which yields a linear optimization problem of moderate dimension with short computation times. The result of applying this technique is an increase in revenues of the aggregator from the trading of the resources that it represents. The benefits are assessed, by comparing it with a standard deterministic optimization technique.