In order to better explore effective loss reduction methods and provide a basis for formulating scientific line loss indicators, this paper aims to study the distribution network (DN) line damage calculation relying on BP neural network. This paper makes an in-depth analysis of the existing non-destructive testing methods, and compares the advantages and disadvantages of various non-destructive testing methods in the home DN, such as low practicability, complex component distribution, and difficulty in collecting raw data. In addition, based on the analysis of the scientific method, management and various loss reduction measures of energy loss measurement, the current situation and existing problems of line loss measurement are analyzed from the perspective of line loss measurement data acquisition. In addition to bias methods and other aspects, this paper analyzes and summarizes research, especially bias measures, and provides many valuable insights from both technical and managerial perspectives. Experiments show that the simulation error is less than 1%. Compared with the traditional BP network, the learning rate of the algorithm in this paper is higher.

Shabnam Hassan. Damage Calculation of Distribution Network Lines Relying on BP Neural Network. International Journal of Neural Network (2020), Vol. 1, Issue 3: 35-42. https://doi.org/10.38007/NN.2020.010305.

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