| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6860858 | International Journal of Electrical Power & Energy Systems | 2012 | 9 Pages |
Abstract
⺠The enhanced RCGA presented in this paper is very much faster than the conventional genetic algorithm. ⺠The proposed eRCGA is suitable for on-line load flow solutions of power systems. ⺠The eRCGA can efficiently solve the load flow problem of different ill-conditioned power systems.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hassan Kubba, Hazlie Mokhlis,