Energy Storage Arbitrage and Peak Shaving in Distribution Grids Under Uncertainty

Energy storage systems can provide peak shaving services in distribution grids to enable an increased penetration of renewable energy sources and load demand growth. Moreover, storage owners can make profits through energy arbitrage in electricity markets by buying energy when the price is low and selling when the price is high. This work considers the energy scheduling of a storage system integrated in a transformer substation to minimize the transformer power limit violations and maximize the arbitrage profits. However, uncertainty on the electricity price and net-load demand of the distribution grid may cause a mismatch between scheduled and actual operation, causing transformer power violations and reduced arbitrage profits. Towards this direction, a scenario-based stochastic optimization scheme to make uncertainty-aware decisions is developed, considering both net-load and price uncertainty. The corresponding scheme is formulated as a linear program that can be solved efficiently even under a large number of scenarios. The performance of the proposed scheme is evaluated and compared to the corresponding deterministic scheme using net-load profiles from a real distribution grid and price data from the Spanish day ahead electricity market. The developed scheme can be used for enhancing both the bidding and operating strategy of a storage system.