Authors: R.C. Bansal
Addresses: School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia Campus, Qld 4072, Australia
Abstract: This paper develops a mathematical modelling of isolated wind-diesel-micro-hydro hybrid power system and presents an artificial neural network (ANN) based approach to tune the parameters of static var compensator (SVC) to meet the reactive power requirement of hybrid system. In the hybrid system considered, a synchronous generator is connected to a diesel-generator (DG) and induction generators connected to the wind and micro-hydro system. The system also has a SVC to provide the required reactive power in addition to the reactive power generated by the synchronous generator. The multi-layer feed-forward ANN with the error back-propagation training is employed to tune the gain of SVC. The dynamic responses presented show that SVC tuned by the ANN can provide optimum dynamic performance of the hybrid power system over a wide range of typical load models.
Keywords: artificial neural networks; ANNs; isolated wind-diesel-micro-hydro power system; hybrid power systems; proportional-integral controller; PID control; static var compensator; SVC; mathematical modelling; wind power; wind energy; micro-hydro; synchronous generators; diesel generators; induction generators; wind turbines.
International Journal of Modelling, Identification and Control, 2009 Vol.6 No.3, pp.196 - 204
Published online: 05 Apr 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article