Abstract
The regulation boundary of reactive power should be a fuzzy boundary which is influenced by voltage state and serves for voltage regulation within a certain range. Therefore, this control of VQC (the Synthetic and Automatic Control of Voltage and Reactive Power in Substation) increases the regulation times of taps and the switching times of capacitor banks and causes voltage fluctuation. On the basis of summarizing several current VQC strategies, this paper puts forward an automatic control algorithm of VQC based on FNN (Fuzzy neural network). Using ANN (artificial neural network) to form the membership function of voltage and reactive power, and according to the control rules summarized in the field, training ANN through BP algorithm to adjust the membership function and control rules, so as to better control the transformer tap changer and capacitor bank to control the VQC power of substation in real time. Use FNN to design a suitable FNN control structure and determine various control parameters. Through simulation calculation, it is proved that the proposed control strategy can better control the voltage of the system and maintain the reactive power balance of the system, thus maintaining the voltage stability of the system more effectively, and at the same time shortening the adjustment time of the on-load tap, shortening the switching time of the capacitor bank and improving the economic benefits of the system.