Application Study On Adaptive Single Automatic Reclosing Based On Intelligent Control

With the power system becoming more and more complicated, and the voltage scale becoming higher, System problems are more likely to happen than before. As the most important one in all kinds of security measures, power system' s personnel have concerned relay protection widely. As one of important components of relay protection, automotive reclosing device plays an important role in guaranteeing security, stability and economical running, etc.Adaptive single-phase reclosing based on intelligent control is a new sort of protection principle, which develops with the advancement of power system technology and the progress of intelligent control theory. It is presented to satisfy the higher request for power system relay protection.The thesis systematically and deeply studied in faults identifying of automatic reclosing and on-line obtaining the optimal reclosing time of transient faults based on wavelet transform and artificial neural network.Conventional automatic reclosing' s shortcoming is that it acts blindly entirely before reclosing and cannot distinguish instantaneous fault from permanent fault. Though microprocessor-based adaptive single-phase reclosing scenario can distinguish instantaneous fault from permanent fault definitely and avoid the blindness of traditional automatic reclosing, in some cases, adaptive reclosing can confound instantaneous fault with permanent fault. So it has defects too. At present, reclosing devices are mostly reclosed by a fixed time , or called periodic time. In order to effectively enhance system transient stability, research on how to set reclosing time based-on shortest periodic time is always followed with interest. Automatic reclosing exits an optimal reclosing time, but the operation manner and wiring manner changein(Lfrequently so that optimal reclosing time changes accordingly. How to obtain the optimal reclosing time of transient faults is a worthy topic.This thesis referred to the applications of neural network and wavelet transform theory in power system, used the function of mode identification and mode classification of ANN and the function of signal extraction of wavelet transform, and established the model of single-phase reclosing based on wavelet neural network. Through simulating a line model, the paper approved its feasibility. In these bases, and using the gathered local signal, the paper obtained the optical reclosing time of transient faults by a new intelligent on-line method. The feasibility is verified by simulation also.The major creative idea of the thesis is that it draws wavelet neural network into automatic reclosing firstly. The choice of input eigenvalue contains all kinds of electric parameters more completely and more perfectly. A new intelligent on-line method for obtaining the optimal reclosing time of transient faults is presented and verified and satisfies the need of real-time.