Optimization analysis of energy storage application based on electricity price arbitrage and ancillary services

Abstract

Energy storage is an effective way to facilitate renewable energy (RE) development. Its technical performance and economic performance are key factors for large scale applications. As battery energy storage system (BESS) is one commercially-developed energy storage technology at present, BESS is utilized to connect to RE generation. BESS couple with RE can balance the generation and load, and provide auxiliary services. Thus, the technical and economic performance of this coupling system was investigated. The coupling system generates extra revenue compared to RE-only through arbitrage considering peak-valley electricity price and ancillary services. In order to maximize the net revenues of BESS, a multi-objective three-level model for the optimal configuration of BESS was developed. The outer layer was a model for the optimal configuration of BESS, the middle layer was a multi-objective optimal model for BESS to participate in electricity price arbitrage and reserve ancillary services, and the inner layer was an optimal scheduling model that coordinated wind power, photovoltaic (PV) power and BESS. The multi-objective genetic algorithm (GA) based on the roulette method was employed to solve the optimal model. A case study was conducted, and the annual net revenues of BESS under different BESS capacities were evaluated. When the annual net revenues of BESS reach the maximum, the optimal BESS capacity is obtained. Sensitive analysis was also conducted considering different price difference, environment conditions of irradiance, wind speed. The effective trend and optimization values were calculated. The study presented a solution including methodology and values for how to determine the installation of energy storage to RE.