Managing Wind-based Electricity Generation in the Presence of Storage and Transmission Capacity

Yangfang ZHOU, Singapore Management University
Alan Scheller-Wolf, Carnegie Mellon University
Nicola Secomandi, Carnegie Mellon University
Stephen Smith, Carnegie Mellon University


Managing power generation from wind is conceptually straightforward: generate and sell as much electricity as possible when prices are positive, and do nothing otherwise. However, this leads to curtailment when wind energy exceeds the transmission capacity or when prices are negative, and possible revenue dilution when current prices are low but are expected to increase in the future. Electricity storage is being considered as a means to alleviate these problems, and also enables buying electricity from the market for later resale. But the presence of storage complicates the management of electricity generation from wind, and the value of storage for a wind-based generator is not entirely understood. We demonstrate that for such a combined generation and storage system computing an optimal policy is too time-consuming to be practical, while using overly simple policies can be considerably suboptimal. We thus develop and analyze a triple-threshold policy that we show to be near-optimal and practical to compute on realistic instances. We also find that storage can substantially increase the monetary value of the wind farm: If the transmission capacity is tight, the majority of this value arises from reducing curtailment and time-shifting generation; if the transmission capacity is abundant this value stems primarily from time-shifting generation and arbitrage. In addition, we find that while more storage capacity always increases the average energy sold to the market, it may actually decrease the average wind energy sold when the transmission capacity is abundant.