Optimal scheduling of microgrid with energy storage system based on improved grey wolf algorithm

Jie Ren; Wenyu Zhang; Zhenyu Song; Zhenhao Zhang; Haixin Zhang; Qiqi Han; Lianbing Li

doi:10.1117/12.2679332

18 July 2023 Optimal scheduling of microgrid with energy storage system based on improved grey wolf algorithm

Jie Ren, Wenyu Zhang, Zhenyu Song, Zhenhao Zhang, Haixin Zhang, Qiqi Han, Lianbing Li

Proceedings Volume 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023); 1272218 (2023) https://doi.org/10.1117/12.2679332
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 2023, Hangzhou, China

Abstract

Energy storage, as a schedulable resource, can be added to the optimal scheduling model of microgrids, which can effectively improve the penetration rate of renewable energy in the grid and improve the reliability and economy of the system. Aiming at grid-connected microgrids, including wind power, photovoltaic, energy storage devices, and micro gas turbines, this paper takes the lowest comprehensive operating cost as the objective function. It takes power balance, distributed power output characteristics, energy storage battery power, and tie line constraints as constraints to establish the optimal configuration model of the microgrid. The Tent chaotic mapping and Cauchy mutation operator method improve the traditional algorithms of the grey wolf, such as the last use of an improved algorithm to solve the model; the simulation results show that the improved grey wolf algorithm has good optimization ability, this model can realize economy optimal micro power grid, the effectiveness of the proposed method was verified.

Citation Download Citation

Jie Ren, Wenyu Zhang, Zhenyu Song, Zhenhao Zhang, Haixin Zhang, Qiqi Han, and Lianbing Li "Optimal scheduling of microgrid with energy storage system based on improved grey wolf algorithm", Proc. SPIE 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 1272218 (18 July 2023); https://doi.org/10.1117/12.2679332

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