1.School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;2.College of Smart Energy, Shanghai Jiao Tong University, Shanghai 200240, China;3.Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education (Northeast Electric Power University), Jilin 132012, China

To improve the operation efficiency and investment effectiveness of the user-side energy storage, an optimal configuration method of shared energy storage (SES) in the industrial park considering full-cycle economic benefits in the market environment is proposed. On the one hand, the method could reduce energy storage capacity requirements by coordinating differentiated adjustment needs among different users. On the other hand, it could expand profit channels by integrating the flexible adjustment capabilities of users and SES to participate in the demand response market, and the full-operation-cycle economic benefits calculation of the SES is considered to reduce the investment risks. Firstly, based on the trading rules of the electricity market, a park SES operation mode with multiple industrial users forming cooperative alliances is proposed. Secondly, with the goal of minimizing the total cost of the alliance during the operation cycle, an SES bi-level optimal configuration model is established. The upper-level model aims to form an SES planning scheme that maximizes investment effectiveness, while the lower-level model comprehensively considers some factors such as time-of-use electricity prices and demand response default risks to form the optimal bidding and scheduling mode for energy storage, and accurately quantifies the operation benefits of SES throughout the full operation cycle based on time-series evolution laws of market, correcting the upper-level results. Then, the model is converted into a single-level model by using the approximate Karush-Kuhn-Tucker (KKT) condition for solution. Combining the rain flow counting method and the iterative method, the impact of SES capacity decay on its configuration scheme is quantified, and the investment cost of each industrial user is apportioned by using the bilateral Shapley value method. Finally, numerical simulations are conducted to validate the effectiveness of the proposed method and analyze the impact of some factors such as energy storage profit mode, SES capacity decay, and demand response default risk on the economic benefits of SES investment.

This work is supported by the Open Fund of Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education (No. MPSS2023-10).