Title :
Coordination of multiple PSSs using multi-objective genetic algorithm
Author :
Zhang, P.X. ; Cao, Y.J. ; Cheng, S.J.
Author_Institution :
Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
A multi-objective genetic algorithm (MOCA) used for the coordination of power system stabilizers to deal with the damping of multi-mode oscillations in large-scale power systems is presented in this paper. The selection of the PSS parameters for large power system is formulated as a multiobjective optimization problem, in which the system response is optimized by minimizing several system-behavior measure criterions. Design of the multi-objective optimization aims to find out the Pareto optimal solution, which is a set of possible optimal solutions for parameters of the PSSs. The simulation results show that the proposed MOGA method is effective. It enables the PSSs to provide effective damping for power system multi-mode oscillations and satisfactory control performance can be obtained.
Keywords :
Pareto optimisation; damping; genetic algorithms; oscillations; power system dynamic stability; Pareto optimal solution; coordinative control; large-scale power systems; multimode oscillations; multiobjective genetic algorithm; power system stabilizers; Damping; Design optimization; Genetic algorithms; Large-scale systems; Pareto optimization; Power measurement; Power system control; Power system measurements; Power system simulation; Power systems;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1343677