The Impacts of Stochastic Programming and Demand Response on Wind Integration

Wind imposes costs on power systems due to uncertainty and variability of real-time resource availability. Stochastic programming and demand response are offered as two possible solutions to mitigate these so-called wind-uncertainty costs. We examine the benefits of these two solutions, and show that although both will reduce wind-uncertainty costs, demand response is significantly more effective. We also examine the impacts of using demand response and stochastic optimization together. We show that most of the value of demand response in reducing wind-uncertainty costs remain if a stochastic optimization is used and that there are subadditive benefits from using the two together.