Line Loss Prediction of Distribution Network Based on BP Neural Network

Abstract

Distribution network line loss calculation refers to the calculation of the electrical energy loss, which is generated by all components in a distribution network system in a given period of time. Distribution network, as the end of the power network, is directly connected with users; there are many equipment on the network; the system has impedance, electric energy in the process of conversion, transmission and distribution with a lot of loss, so the calculation of distribution network line loss has very important economic significance. In addition, with the development of power network construction, the rationality of distribution network topology design and the comparison of practical effects of various measures need the guidance of line loss calculation. Line loss and line loss rate is one of the main criteria to reflect the operation of distribution system. Reducing line loss of distribution system is very important for the effective use of power and economic operation of distribution system. In order to better find the effective reduction method and lay the foundation for the scientific establishment of linear contraction targets. This study uses a line loss calculation method based on BP neural network. The method uses the super matching property of the network to map the complex nonlinear relationship between the line loss and the characteristic variables and stores the evolution of the line loss changes with the changes of the structural and operational variables of the distribution line. On the basis of analyzing the theoretical methods, management methods, and various loss reduction measures of power loss calculation, this study also analyzes the status quo and existing problems of line loss analysis and calculation and collects data from line loss calculation and theoretical line loss calculation methods. This study discusses in detail the method and idea of the application of the improved neural network in the estimation of distribution network line loss, and it is used to predict the line loss in a certain area, and the prediction result is good.