Optimal Bidding of Li-ion BESS in Regulation Markets Considering Capacity Degradation

The grid deployment of lithium-ion (Li-ion) battery energy storage systems (BESS) has grown fast during recent years. One emerging grid application is using Li-ion BESS in frequency regulation markets for tracking fast-moving frequency regulation signals, such as PJM's RegD signal. However, Liion batteries may encounter fast capacity degradation when tracking these signals. To effectively incorporate the cycling induced degradation cost into the optimal bidding in regulation markets, we develop a statistical feature-based method for capacity degradation estimation. The fractional absolute moment (FAM) of the state-of-charge (SoC) profile is selected as the input feature of a linear regression model that produces an estimate of the capacity degradation as the model's output. Subsequently, the optimal bidding problem is formulated as a convex optimization model to maximize the daily profit of Li-ion BESS in a regulation market. Simulation results show that the proposed model provides, for frequency regulation, cost-effective capacity bidding and 5-min economic basepoints which achieve a tradeoff between regulation credit and battery degradation cost.