DocumentCode :
1299191
Title :
Non-dominated sorting genetic algorithm-II for robust multi-objective optimal reactive power dispatch
Author :
Zhihuan, L. ; Yinhong, L. ; Xianzhong, Duan
Author_Institution :
Hubei Electr. Power Security & High Efficiency Key Lab., Huazhong Univ. of Sci. & Technol. (HUST), Wuhan, China
Volume :
4
Issue :
9
fYear :
2010
fDate :
9/1/2010 12:00:00 AM
Firstpage :
1000
Lastpage :
1008
Abstract :
The concept of robust optimal solution is incorporated into multi-objective optimal reactive power dispatch (MORPD) for the consideration of uncertain load perturbations during system operations. Robust MORPD searches for solutions that are immune to parameter drifts and load changes. It uses information of load-increase directions to promote the stability of optimal solutions in the presence of load perturbations. Non-dominated sorting genetic algorithm-II (NSGA-II) is adopted to search for the robust Pareto solutions on a standard IEEE 118-bus system. The simulation validated the effectiveness of NSGA-II for robust MORPD. NSGA-II obtained Pareto solutions over the trade-off surface. The experimental results also indicated that the robust Pareto solutions are comparatively less sensitive to load perturbations in their neighbourhoods and can maintain their objective values against uncertain load perturbations. Robust MORPD can provide optimal solutions with a higher degree of stability in the face of perturbations and can be more practical in reactive power optimisation of the real-time operation systems.
Keywords :
Pareto optimisation; genetic algorithms; power generation dispatch; power system security; reactive power; sorting; IEEE 118-bus system; NSGA-II; nondominated sorting genetic algorithm-II; reactive power optimisation; robust Pareto solutions; robust multiobjective optimal reactive power dispatch; uncertain load perturbations;
fLanguage :
English
Journal_Title :
Generation, Transmission & Distribution, IET
Publisher :
iet
ISSN :
1751-8687
Type :
jour
DOI :
10.1049/iet-gtd.2010.0105
Filename :
5551065
Link To Document :
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