Adaptive thyristor controlled series capacitor using particle swarm optimization and support vector regression

This paper focuses on the application of support vector regression (SVR) to design of an adaptive thyristor controlled series capacitor (TCSC). A particle swarm optimization (PSO) is used to optimize the SVR parameters based on k-fold cross-validation technique. The SVRs for an adaptive TCSC are trained by the data obtained from a multi-machine power system, and the optimal SVR parameters. The TCSC parameters can be adapted by various operating conditions. Simulation results in a two-area four-machine interconnected power system demonstrate that the proposed SVRs for an adaptive TCSC is much superior to the conventional TCSC with fixed parameters under various operating conditions and severe disturbances. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.