Optimal scheduling of energy storage under forecast uncertainties

Abstract

Recent studies have concluded that battery energy storage will soon be economically competitive if its cost continues to decline. The authors propose a two-stage look-ahead daily scheduling strategy for distributed energy storage located in distribution networks with a substantial photovoltaic (PV) penetration. They assume that the load serving entity operates this energy storage to harness simultaneously multiple streams of benefits: energy arbitrage, peak shaving, minimising deviations from the load forecast and regulation service. To determine the optimal capacity bid into the day-ahead regulation market and address the price, load, and solar forecast uncertainties, they propose a two-stage optimisation model that bids regulation capacity on the day ahead and determines the storage dispatch schedule in real time. At the day-ahead stage, the load serving entity reserves a portion of the storage capacity for regulation, while the remaining capacity is dispatched for energy arbitrage, peak shaving and minimising the deviations from the forecast. Result suggests that regulation services account for the majority of these benefits. The energy storage is dispatched for peak shaving and forecast-deviation minimisation from around noon to late evening. During the rest of day, storage is dispatched primarily for regulation services.