Incorporating Demand Response with Load Shifting into Stochastic Unit Commitment
51 Pages Posted: 6 Apr 2013
Date Written: April 3, 2013
High costs for fossil fuels and increasing installations of intermittent energy sources are imposing major challenges on power grid management. Uncertainty in generation and demand for electric energy require flexible generation capacity and stochastic optimization of generation schedules. Emerging smart grid technology is one mean to increase efficiency in power generation and to mitigate effects of increasing uncertainty. In this paper, we analyze the potential of demand side resources (DSRs) that can be dispatched to reduce load at peak times. We present a stochastic dynamic programming model for the unit commitment problem in a day ahead market and include dispatch decisions for DSRs. Unlike previous research, we model the stochastic load shifting effect to previous and subsequent periods that must be taken into account when making dispatch decisions. We also present a solution algorithm that combines an approximate dynamic programming algorithm with stochastic progressive hedging to solve the problem. We prove convergence results for our algorithms and derive a lower bound on the optimal solution. Using data from the California Independent System Operator region, we show that our approach can solve real world instances in reasonable time. We conduct an extensive numerical study using real world data to show that substantial savings can be achieved by utilizing DSRs.
Keywords: Demand Response; Stochastic Unit Commitment; Approximate Dynamic Programming; Stochastic Progressive Hedging
Suggested Citation: Suggested Citation