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PSO-based learning of support vector machines for adaptive TCSC
Author(s)
Date Issued
June 12, 2012
Type
Conference Paper
Abstract
This paper proposes the design of an adaptive thyristor controlled series capacitor (TCSC) using support vector machines (SVMs) and particle swarm optimization (PSO). The SVMs for an adaptive TCSC are trained by the data obtained from a multi-machine power system. PSO is used to optimize the SVM parameters based on k-fold cross-validation technique. The TCSC parameters produced by SVMs can be adapted by various operating conditions. Simulation results in a two-area four-machine power system demonstrate that the proposed SVMs for an adaptive TCSC is much superior to the conventional TCSC with fixed parameters under various operating conditions.
Citation
Proceedings of the IASTED Asian Conference on Power and Energy Systems Asiapes 2012, 164-169, 2012