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IJSGCE 2023 Vol.12(4): 118-123
DOI: 10.12720/sgce.12.4.118-123

Improved Multi-objective Lion Swarm Algorithm Based on Scheduling Model for Wind Power Systems

Manuscript submitted May 25, 2023; revised July 19, 2023; accepted August 10, 2023; published October 8, 2023.

Qi Zhang, Mingyan Jiang*, Keqin Jiang

School of Information Science and Engineering, Shandong University, Qingdao, 266237, China
*Correspondence: jiangmingyan@sdu.edu.cn (M.Y.J.)
International Journal of Smart Grid and Clean Energy, vol. 12, no. 4, 2023: pp. 118-123
Submitted May 25, 2023; revised July 19, 2023; accepted August 10, 2023; published October 9, 2023.
Full Paper.pdf

The multi-objective model is established to minimize the cost of power generation and optimize the energy and environmental benefits, and the improved lion swarm optimization algorithm is adopted in the solution method, i.e. the idea and mechanism of coati optimization is introduced into the lion swarm algorithm. The method enhances the high-dimensional search capability of the population and verifies the effectiveness, scientificity, and advancement of the improved algorithm. Experimental analysis is carried out with the micro-wind power grid-connected generation example to verify that the proposed model considers the cost of micro-grid from various aspects and helps to improve the reliability of the system. The objective of optimizing the cost of wind and solar energy penalties is to achieve the full utilization of wind and solar energy, which helps to solve the problem of "wind" and "solar" abandonment.

wind, water and fire power generation scheduling, multi-objective optimization, lion swarm algorithm

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.