Optimal control of a hybrid power compensator using an artificial neural network controller

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator 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 minimizing its total cost. The use of an artificial neural network (ANN) to control the HPC amid 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.