A VARIABLE-STRUCTURE ADAPTIVE NEURAL-NETWORK STATIC VAR CONTROLLER

A variable structure adaptive neural network power system static VAR s tabilizer is developed. The static VAR compensator (SVC) controlled by the above proposed controller is used for voltage regulation and enha ncing power system stability. The artificial neural network (ANN) is t rained off-line using the variable structure control system Benchmark data at different operating conditions and external disturbances. More over, the trained ANN parameters (weights and biases) are tuned and up dated on-line using the synchronous machine speed deviation state as t he ANN output error to increasingly improve the power system performan ce. A sample digital simulation result of the power system speed devia tion state responses when reference voltage, speed deviation state and input power disturbances take place are obtained. The digital simulat ion results prove the effectiveness and robustness of the present adap tive neural network in terms of a high performance power system. (C) 1 998 Published by Elsevier Science S.A. All rights reserved.