Article ID Journal Published Year Pages File Type
410117 Neurocomputing 2013 12 Pages PDF
Abstract

Due to having such features as easy implementation, short running time and robust mechanisms to escape local minimums, the Lozi map-based Chaotic Optimization Algorithm (LCOA) has attracted researchers' attention as a new stochastic search algorithm. Using a modified version of Lozi map, an Improved Lozi map-based Chaotic Optimization Algorithm (ILCOA) with such features as higher stability, better escaping from the local minima, more robustness to search space size, and finer performance in comparison to the LCOA is proposed in this work. Further, the proposed ILCOA is tested; it is employed to solve a single-machine Power System Stabilizer (PSS) design problem and its promising features in comparison with LCOA are highlighted. Later on, the coordinated design problem of PSS and Static Synchronous Series Compensator (SSSC) damping controllers in a four-machine two-area benchmark system is formulated as an optimization problem with the time domain-based objective function which is solved by both the LCOA and the ILCOA. The results show that the proposed controllers can effectively improve the power system dynamic stability. The superiority of the ILCOA over the LCOA and PSO is also demonstrated.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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