Locating Type-1 Load Flow Solutions using Hybrid Evolutionary Algorithm

Author

Ting, T.O. ; Wong, K.P. ; Chung, C.Y.

Author_Institution

Dept. of Electr. Eng., Hong Kong Polytech. Univ., Kowloon

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

4093

Lastpage

4098

Abstract

Conventional methods can only locate some of the Type-1 load flow solutions in power systems and the located solutions are inadequate for voltage stability assessment. This paper proposes a hybrid genetic algorithm/particle swarm optimization algorithm for locating all the Type-1 load flow solutions. The characteristics of the Type-1 solutions are described in the paper. The hybrid algorithm is applied to two test systems. The test results obtained are satisfactory and promising for voltage stability monitoring applications

Keywords

genetic algorithms; load flow; particle swarm optimisation; power system stability; Type-1 load flow solutions; genetic algorithm; hybrid GA-PSO algortihm; hybrid evolutionary algorithm; particle swarm optimization; power systems; voltage stability assessment; Bifurcation; Cybernetics; Eigenvalues and eigenfunctions; Equations; Evolutionary computation; Hybrid power systems; Load flow; Load flow analysis; Machine learning; Machine learning algorithms; Particle swarm optimization; Power system stability; System testing; Voltage; Bifurcation; Hybrid evolutionary algorithm; Load flow analysis; Voltage stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258867

Filename

4028788