Analytical study on optimized configuration strategy of electrochemical energy storage system under multiple scenarios
Author:
Li Tou1, Zhang Wei2, Zhang Xuan2
Affiliation:
1. School of Electrical Engineering, Nanjing Institute of Technology , Nanjing , Jiangsu, , China . 2. Nanjing Weilixuan Information Technology Co., Ltd , Nanjing , Jiangsu, , China .
Abstract
Abstract
This paper models the electrochemical energy storage system and proposes a control method for three aspects, such as battery life, to generate a multiobjective function for optimizing the capacity allocation of electrochemical energy storage under multiple scenarios, with conditional constraints on the system, storage, and progression aspects. The improved whale optimization algorithm is used to solve the multi-objective function to find the most reasonable electrochemical energy storage system capacity optimization allocation scheme. Using the model constructed in this paper under multi-scenario conditions, it is found after solving that the optimal allocation scheme purchases power from the grid at around 25MW during the highest peak hours in summer and 5MW in winter, which ensures the economic benefits. Meanwhile, the maximum power fluctuation of the electrochemical energy storage system at point A of the optimization strategy provided by the model is only 2.16%, which is much lower than the preset 4.32%, so the optimal allocation strategy reaches the optimum. Comparing the performance of configured energy storage in different scenarios, the peak-valley power difference of the model proposed in this paper decreases from 11.6 MW to 8.9 MW, which is a better performance than that of the control group, which is 10.8 MW-9.1 MW, and the effect of peak shaving and valley filling is obvious.
Publisher
Walter de Gruyter GmbH
Reference27 articles.
1. Arutyunov, V. S., & Lisichkin, G. V. (2017). Energy resources of the 21st century: problems and forecasts. Can renewable energy sources replace fossil fuels. Russian Chemical Reviews, 86(8), 777. 2. Wang, H., Asif Amjad, M., Arshed, N., Mohamed, A., Ali, S., Haider Jafri, M. A., & Khan, Y. A. (2022). RETRACTED: Fossil Energy Demand and Economic Development in BRICS Countries. Frontiers in Energy Research, 10, 842793. 3. Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities. Journal of Cleaner Production, 289, 125834. 4. Zhou, J., & Wang, B. (2017). Emerging crystalline porous materials as a multifunctional platform for electrochemical energy storage. Chemical Society Reviews, 46(22), 6927-6945. 5. Cheng, X., Pan, J., Zhao, Y., Liao, M., & Peng, H. (2018). Gel polymer electrolytes for electrochemical energy storage. Advanced Energy Materials, 8(7), 1702184.
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