Cost-Benefit Evaluation for Battery Energy Storage Considering Degradation and Data Clustering in Performance-Based Frequency Regulation Service

With the development of Battery Energy Storage System (BESS), it is of great importance to evaluate the benefit of BESS more accurately and effectively. This paper provides a cost-benefit evaluation model for BESS considering battery’s degradation and performance-based regulation (PBR) in power markets. Meanwhile, the benefit is estimated and maximized through battery behaviors’ optimization in the expected lifespan. The case data is derived from the historical data of the PJM market, and the k-means clustering method is applied to obtain data set of the typical scenes, so that the computation burden in cost-benefit evaluation can be eased. Different cases with and without considering degradation and data clustering are then studied and compared. The results show that more profits can be made by considering internal degradation and the calculation efficiency can be greatly improved by k-means clustering without losing too much accuracy.