Hybridizing gaining–sharing knowledge and differential evolution for large-scale power system economic dispatch problems

Authors

Qinghua Liu, Guizhou Key Laboratory of Intelligent Technology in Power System, College of Electrical Engineering, Guizhou University , Guiyang 550025 , China
Guojiang Xiong, Guizhou Key Laboratory of Intelligent Technology in Power System, College of Electrical Engineering, Guizhou University , Guiyang 550025 , China,Institute of Engineering Investigation & Design Co., Ltd., Guizhou University , Guiyang 550025 , China
Xiaofan Fu, Guizhou Key Laboratory of Intelligent Technology in Power System, College of Electrical Engineering, Guizhou University , Guiyang 550025 , China
Ali Wagdy Mohamed, Operations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo University , Giza 12613 , Egypt,Department of Mathematics and Actuarial Science, School of Sciences & Engineering, The American University in Cairo , New Cairo 11835 , Egypt

Fourth Author's Department

Mathematics & Actuarial Science Department

Document Type

Research Article

Publication Title

Journal of Computational Design and Engineering

Publication Date

3-10-2023

doi

10.1093/jcde/qwad008

First Page

615

Last Page

631

Recommended Citation

APA Citation

Liu, Q. Xiong, G. Fu, X. & Mohamed, A. (2023). Hybridizing gaining–sharing knowledge and differential evolution for large-scale power system economic dispatch problems. Journal of Computational Design and Engineering, 10, 615–631. https://doi.org/10.1093/jcde/qwad008

MLA Citation

Liu, Qinghua, et al. "Hybridizing gaining–sharing knowledge and differential evolution for large-scale power system economic dispatch problems." Journal of Computational Design and Engineering, vol. 10, 2023, pp. 615–631.
https://doi.org/10.1093/jcde/qwad008