We study the control of large-scale energy storage operating in a market. Reoptimization of deterministic models is a common pragmatic approach when prices are stochastic. We apply Lagrangian theory to develop such a model and to establish decision and forecast horizons when storage trading affects these prices, an important aspect of some energy markets. The determination of these horizons also provides a simple and efficient algorithm for the determination of the optimal control. The forecast horizons vary between one and 15 days in realistic electricity storage examples. These examples suggest that modeling price impact is important.
ASJC Scopus subject areas
- Computer Science Applications
- Management Science and Operations Research