AI APPROACH TO OPTIMAL VAR CONTROL WITH FUZZY REACTIVE LOADS

This paper presents an artificial intelligence (AI) approach to the op timal reactive power (var) control problem. The method incorporates th e reactive load uncertainty in optimizing the overall system performan ce. The artificial neural network (ANN) enhanced by fuzzy sets is used to determine the memberships of control variables corresponding to th e given load values. A power flow solution will determine the correspo nding state of the system. Since the resulting system state may not be feasible in real-time, a heuristic method based on the application of sensitivities in expert system is employed to refine the solution wit h minimum adjustments of control variables. Test cases and numerical r esults demonstrate the applicability of the proposed approach. Simplic ity, processing speed and ability to model load uncertainties make thi s approach a viable option for on-line var control.