Optimal Setting Method of Anti-time Overcurrent Protection for Transmission Lines in Distribution Network Based on Adaptive Neuron
In order to reduce the excessive dependence of anti-time overcurrent protection setting value on manual experience,al-leviate the problems of low cooperation between protection actions and poor current stability,an optimal set method for anti-time overcurrent protection of distribution network transmission lines based on adaptive neurons is proposed.This paper analy-zes the uncertainty of transmission line operation mode and line failure,and calculates the probability of failure.The actual bearing capacity of the transmission line is determined by exploring the reverse load rate,power supply capacity and harmonic content.The action equation of anti-time overcurrent protection is constructed to determine the three characteristics of anti-time overcurrent protection.With the goal of minimizing the time difference between the main protection and backup protection ac-tions,an objective function is constructed and the constraint conditions are established.A neural network model is constructed with three neurons,each neuron corresponds to a protection feature,a transformation module is introduced to transform the in-put quantity into a state quantity,and output the final overcurrent protection optimal setting result through neuron learning.The comparative experiment results show that under the application of the proposed method,with the increase of fault current,the curves of protection action time do not intersect.The current waveform fluctuates at the beginning of the test,but quickly returns to plateau.The proposed method can make the protection actions cooperate effectively,and the transmission line cur-rent can always be kept in a stable state,which provides a new research idea for the optimization of the protection fixed value.
万方数据
维普
