Forward thresholds for operation of pumped-storage stations in the real-time energy market

Pumped-storage hydroelectric plants are very valuable assets on the electric grid and in electric markets as they are able to pump and store water for generation, thus allowing for grid-level storage. Within the realm of short-term energy markets, we present a model for determining forward-looking thresholds for making generation and pumping decisions at such plants. A multistage stochastic programming framework is developed to optimize the thresholds with uncertain system prices over the next three days. Tractability issues are discussed and a novel method based on an implementation of the scatter search algorithm is proposed. Given the size of the multistage stochastic programming formulation, we argue that this novel method is a more accurate representation of the decision process. We demonstrate model stability and quality, and show that the forward thresholds obtained using a stochastic programming framework outperform the forward thresholds from a deterministic model, and thus can lead to efficiency gains for both the generation unit owner and the overall system in the real-time market.