Design of an adaptive artificial neural network for online voltage stability assessment

Abstract

Voltage instability has become a major concern in many power systems and blackouts have been reported, where the reason has been voltage instability. Voltage stability is concerned with the ability of a power system to maintain acceptable voltages at all buses in the system under normal condition and after being subjected to a disturbance. It is an important consideration in the design and operation of power system. Voltage stability is also called the load stability. It is a characteristic of a power system, which is required to transmit sufficient power to meet load demand. The objective of this paper is to present the application of artificial neural network (ANN) in on-line assessment of voltage stability. The proposed method is radial basis function (RBF) neural network. This NN is used for estimation of voltage stability margins (VSM). The IEEE-118 test system is considered for application to this method. A comparison between the proposed NN and a multi-layer perceptron (MLP) with standard error back-propagation learning (EBPL) is presented, which indicates efficiency of this NN. Obtained results confirm the validity of the proposed approach.