Optimal User-Side Energy Arbitrage Strategy in Electricity Market With Accurate Battery Model Using Benders Decomposition

Abstract

In this paper, the optimal operation and arbitrage strategies for user-side energy storage systems are studied considering an accurate battery model to capture the charging and discharging features. Meanwhile, the proposed method uses Benders decomposition to help solve the consequential decision-making problems of energy arbitrage in electricity market with dynamic price signal and continuous iteration of charging cycling counting and battery life costs. Empirical analysis and simulation based on different scenarios of Chinese provisional electricity markets demonstrate the variability of such energy arbitrage strategies in realistic applications, which mainly depends on the trade-off between the physical operation features of the energy storage systems and the market pricing scheme. The main findings and results confirm the advantages of involving such user-side energy storage system resources that can participate in the deregulated electricity market, ultimately benefiting the energy end-users at the distribution level, as well as the upper-level market or system operation. It is believed that further study of a more accurate battery model and a more precise battery cycling life cost can also contribute to improving the reasonable market mechanism design.