http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Fu Xiaofan (검색결과 1 건)
- 무료
- 기관 내 무료
- 유료
-
Liu Qinghua,Xiong Guojiang,Fu Xiaofan,Mohamed Ali Wagdy,Zhang Jing,Al-Betar Mohammed Azmi,Chen Hao,Chen Jun,Xu Sheng 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.2
Economic dispatch (ED) of thermal power units is significant for optimal generation operation efficiency of power systems. It is a typical nonconvex and nonlinear optimization problem with many local extrema when considering the valve-point effects, especially for large-scale systems. Considering that differential evolution (DE) is efficient in locating global optimal region, while gain-sharing knowledge-based algorithm (GSK) is effective in refining local solutions, this study presents a new hybrid method, namely GSK-DE, to integrate the advantages of both algorithms for solving large-scale ED problems. We design a dual-population evolution framework in which the population is randomly divided into two equal subpopulations in each iteration. One subpopulation performs GSK, while the other executes DE. Then, the updated individuals of these two subpopulations are combined to generate a new population. In such a manner, the exploration and the exploitation are harmonized well to improve the searching efficiency. The proposed GSK-DE is applied to six ED cases, including 15, 38, 40, 110, 120, and 330 units. Simulation results demonstrate that GSK-DE gives full play to the superiorities of GSK and DE effectively. It possesses a quicker global convergence rate to obtain higher quality dispatch schemes with greater robustness. Moreover, the effect of population size is also examined.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
