Location and capacity planning method of distribution network energy storage based on improved grey wolf algorithm

Bo Jiao; Kai Huang; Shibiao Zhang; Hongliang Liu; Guodong Lu

doi:10.1117/12.2673145

25 April 2023 Location and capacity planning method of distribution network energy storage based on improved grey wolf algorithm

Bo Jiao, Kai Huang, Shibiao Zhang, Hongliang Liu, Guodong Lu

Author Affiliations +

Proceedings Volume 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022); 125981E (2023) https://doi.org/10.1117/12.2673145
Event: Eighth International Conference on Energy Materials and Electrical Engineering (ICMEE 2022), 2022, Guangzhou, China

Abstract

In view of the problem that the existing distribution network energy storage location and capacity planning method is easy to cause the distribution network load risk coefficient to be too high, this paper carries out the research on the distribution network energy storage location and capacity planning method based on the improved gray wolf algorithm. The improved gray wolf algorithm is used to establish the planning objective function; the uncertain scenario of distribution network planning is considered, and the constraints of energy storage location and capacity planning are set. The scenario analysis is used to solve the location and capacity of energy storage. By comparing the proposed planning method with the heuristic-based planning method, it is concluded that the load risk coefficient is significantly reduced after the proposed planning method is used to complete the energy storage location and capacity planning of the distribution network, which is superior to the comparison method and promotes the safety and stability of distribution network operation.

Citation Download Citation

Bo Jiao, Kai Huang, Shibiao Zhang, Hongliang Liu, and Guodong Lu "Location and capacity planning method of distribution network energy storage based on improved grey wolf algorithm", Proc. SPIE 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022), 125981E (25 April 2023); https://doi.org/10.1117/12.2673145

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