Artificial neural network power system stabilizers in multi-machine power system environment

Abstract

The effectiveness of an artificial neural network (ANN), functioning as a power system stabilizer (PSS), in damping multi-mode oscillations in a five-machine power system environment is investigated in this paper. Accelerating power of the generating unit is used as the input to the ANN PSS. The proposed ANN PSS using a multilayer neural network with error-backpropagation training method was trained over the full working range of the generating unit with a large variety of disturbances. The ANN was trained to memorize the reverse input/output mapping of the synchronous machine. Results show that the proposed ANN PSS can provide good damping for both local and inter-area modes of oscillations. >