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Multi-machine power system stabilizers design using chaotic optimization algorithm
DOI:10.1016/j.enconman.2010.02.015.png)
Abstract
En 中文
In this paper, a multiobjective design of the multi-machine power system stabilizers (PSSs) using chaotic optimization algorithm (COA) is proposed. Chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from the local optimum, is a promising tool for the engineering applications. The PSSs parameters tuning problem is converted to an optimization problem which is solved by a chaotic optimization algorithm based on Lozi map. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed chaotic optimization problem introduces chaos mapping using Lozi map chaotic sequences which increases its convergence rate and resulting precision. Two different objective functions are proposed in this study for the PSSs design problem. The first objective function is the eigenvalues based comprising the damping factor, and the damping ratio of the lightly damped electro-mechanical modes, while the second is the time domain-based multi-objective function. The robustness of the proposed COA-based PSSs (COAPSS) is verified on a multi-machine power system under different operating conditions and disturbances. The results of the proposed COAPSS are demonstrated through eigenvalue analysis, nonlinear time-domain simulation and some performance indices. In addition, the potential and superiority of the proposed method over the classical approach and genetic algorithm is demonstrated. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords:
PSS design
Chaotic optimization algorithm
Power system dynamics
Multiobjective optimization
Journal
IF:
10.9
Papers:
2.0W
Citations:
11.3W
Organization
Cited Papers
Design and comparison of adaptive power system stabilizers based on neural fuzzy networks and genetic algorithms
NEUROCOMPUTING
IF6.5

