Title :
Optimal control of a hybrid power compensator using an artificial neural network controller
Author :
van Schoor, G. ; van Wyk, J.D. ; Shaw, I.S.
Author_Institution :
Technikon SA, Johannesburg, South Africa
Abstract :
A hybrid power compensator (HPC) consisting of a static VAr compensator (SVC) and a dynamic compensator (DC) needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimising its total cost. The use of an artificial neural network (ANN) to control the HPC amidst a very dynamic environment to achieve the above, is investigated. A state space model of the power distribution network together with the HPC forms the basis of evaluation of the mentioned controller. The model was calibrated against actual in-network measurements. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately
Keywords :
harmonic distortion; load (electric); neurocontrollers; optimal control; power distribution control; power factor; power system harmonics; state-space methods; static VAr compensators; artificial neural network; artificial neural network controller; dynamic compensator; dynamic environment; harmonic distortion; hybrid power compensator; nonlinear loads compensation; optimal control; power distribution network; power factor; state space model; static VAr compensator; total cost minimisation; Africa; Artificial neural networks; Costs; Impedance; Nonlinear control systems; Nonlinear dynamical systems; Optimal control; Power engineering and energy; Power system modeling; Power systems;
Conference_Titel :
Industry Applications Conference, 2000. Conference Record of the 2000 IEEE
Conference_Location :
Rome
Print_ISBN :
0-7803-6401-5
DOI :
10.1109/IAS.2000.881950