Power System Stabilizing Control by SMES Using Fuzzy Concept and Neural Network

Abstract

It has been made clear that a superconducting magnetic energy storage (SMES) is very effective for power system stabilization. The control methods proposed for power system stabilization by SMES are such as the pole assignment, the optimum control and so on, each of which, however, has its drawbacks. The application of fuzzy control is considered in order to overcome these drawbacks.
This paper is concerned with the power system stabilization by fuzzy control of the active and reactive power of SMES. First, the adequate fuzzy control rules of a SMES for the model power system is derived. Then, in order to alleviate the dependence of the fuzzy control on the operating condition and the fault, we propose a method, which adjusts the fuzzy parameter according to the operating condition and the fault using a neural network. The validity of the proposed method is examined by computer simulations.