BESS Optimal Sizing and Scheduling for Energy Arbitrage and Frequency Containment Reserve via Dual-Loop Optimization

Abstract

This paper proposes optimal sizing and scheduling of battery energy storage system (BESS) installed in fast charging station (FCS), which considers the energy arbitrage (EA), frequency containment reserve (FCR) services, and battery degradation. To minimize the capital cost and lifetime operating expenditures, the BESS could actively participate in the grid services, such as EA and FCR. Therefore, the optimal size of BESS should be estimated. The dual-loop strategy, consisting of inner and outer-loop optimizations, is designed to determine the optimal scheduling and sizing of BESS. The inner-loop optimization computes one year data of day ahead spot and frequency containment reserve normal (FCR-N) prices, frequency, and FCS demand data. To reduce the computational burden, the hierarchical clustering via auto-encoder is realized to classify the type of the days based on the input data profiles. The autoencoder is implemented to reduce data dimensionality. Furthermore, the outer-loop optimization, based on differential evolution algorithm, is performed to determine optimal BESS capacity and power ratings. The simulation results show that the proposed method is able to determine optimal size of BESS, thereby maximizing profit. Furthermore, the optimal scheduling of BESS power, which minimizes the penalty cost, is also obtained.