This paper presents an automatic reactive power control of autonomous wind-diesel hybrid power systems (AWDHPS) by artificial neural network (ANN) controller tuned static var compensator (SVC). The real time assessment of such control was carried out using dSPACE R & D controller board. The proposed ANN controller was supported by multilayer perceptron artificial neural network (MPANN). The weights of proposed MPANN were restructured by intensive learning process. The back propagation equations were used to dynamically regulate the weights of proposed MPANN controller. Three models of AWDHPS were considered in the study. The disturbance parameters in the models were the change in reactive power of the load (ΔQL), the change in mechanical power input of the single induction generator (ΔPIW) and the change in mechanical power input of two induction generators (ΔPIW1, ΔPIW2) respectively. The parameters were dynamically varied in control desk of dSPACE Software with DS1104 R & D controller board mounted in personal computer under real time environment. The static and dynamic response curves were depicted. The reactive power deviations realized using the proposed MPANN controller was found to be very less compared to the deviations shown in ANN controller present in literature. The time domain specifications of SVC obtained by the proposed MPANN controller were better than a Proportional plus Integral (PI) controller.
展开▼
