Title :
Application of neural adaptive power system stabilizer in a multi-machine power system
Author :
Shamsollahi, Payman ; Malik, Om P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
fDate :
9/1/1999 12:00:00 AM
Abstract :
Application of a neural adaptive power system stabilizer (NAPSS) to a five-machine power system is described in this paper. The proposed NAPSS comprises two subnetworks. The adaptive neuro-identifier (ANI) to dynamically identify the nonlinear plant, and the adaptive neuro-controller (ANC) to damp output oscillations. The backpropagation training method is used online to train these subnetworks. The effectiveness of the proposed NAPSS in damping both local and inter-area modes of oscillations and its self-coordination ability are demonstrated
Keywords :
adaptive control; backpropagation; control system analysis; control system synthesis; neurocontrollers; power system control; power system stability; adaptive neuro-controller; adaptive neuro-identifier; backpropagation training method; control design; control simulation; inter-area oscillation modes; local oscillation modes; multimachine power system; neural adaptive power system stabilizer; nonlinear plant identification; output oscillations damping; self-coordination ability; Adaptive control; Adaptive systems; Application software; Neural networks; Power generation; Power system dynamics; Power system reliability; Power system stability; Power system transients; Power systems;
Journal_Title :
Energy Conversion, IEEE Transactions on
