Wide-area SMES controller design using least-squares support vector machines

This paper presents an adaptive wide-area damping controller of superconducting magnetic energy storage (SMES) using the least squares support vector machine (LS-SVM). The LS-SVM for SMES controllers are trained using wide-area control signal obtained from synchronized phasor measurements considering time delay. The LS-SVM control signals can be adapted by various operating conditions and different disturbances. Simulation results in a two-area four-machine power system demonstrate that the proposed LS-SVM for SMES controller is robust to various disturbances under wide range of operating conditions in comparison to the conventional SMES.