Abstract:
At present,it has become more and more difficult for the traditional methods to detect various covert power theft behaviors,not only due to low accuracy rate,but also due to high time cost.Therefore,as an application of machine learning theory,this paper presents a detection method of power theft behavior on distribution network based on RBF neural network.Through the analysis on the current common power theft behavior,this paper picks up divergence among three-phase voltage,divergence among three-phase current and divergence among power factor as three important features and build a power theft detection model based on RBF neural network with the historical data containing three important features mentioned above.The experimental result shows that the accuracy rate of this method on distinguishing the current common power theft behavior is up to 94.1%,which means this method could be used on suspecting power consumers who are probably stealing power effectively.This method not only meets the precision requirements of practical application,but also makes the power anti-theft technology more intelligent and thus the power supply enterprises can take the initiative.