Optimal configuration of energy storage capacity in microgrid based on improved grey wolf optimizer algorithm

Xin Dai; Yixin Su; Danhong Zhang; Fangzheng Jia; Junyi Hao

doi:10.1117/12.3030184

5 June 2024 Optimal configuration of energy storage capacity in microgrid based on improved grey wolf optimizer algorithm

Xin Dai, Yixin Su, Danhong Zhang, Fangzheng Jia, Junyi Hao

Author Affiliations +

Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 131634W (2024) https://doi.org/10.1117/12.3030184
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China

Abstract

In order to improve the voltage quality of microgrid, and lower the configuration cost of energy storage system, a method based on Improved Grey Wolf Optimizer (IGWO) for the optimal configuration of the energy storage capacity in microgrid is proposed. The IGWO algorithm generates the initial population by introducing Tent chaotic mapping to enhances the diversity of the population; by linearly decreasing inertia weight, better balance local search and global search capabilities; by randomly adjusting the control parameter, the optimization performance of the algorithm is greatly improved. The simulation results verify the superiority of IGWO algorithm in solving the energy storage capacity allocation problem of microgrid, which provides a new solution to improve the operation economy of microgrid system.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xin Dai, Yixin Su, Danhong Zhang, Fangzheng Jia, and Junyi Hao "Optimal configuration of energy storage capacity in microgrid based on improved grey wolf optimizer algorithm", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 131634W (5 June 2024); https://doi.org/10.1117/12.3030184

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