Abstract
In order to quantitatively analyze the benchmark value of line loss rate in the transformer district, understand the correlation and difference between samples in each transformer district, and improve the dynamic management ability of line loss in the transformer district, a method for calculating the benchmark value of line loss rate in the transformer district based on the portrait of marketing customers is proposed. The high-resolution feature quantity of the data in the transformer district is mined by the feature analysis method of marketing customer portrait, and the electrical parameters of the power grid, the operation mode of the power grid, the power flow distribution, the load and other factors are taken as the index parameters of the benchmark evaluation of the line loss rate in the transformer district, and the different characteristics of different stations are fully mined, and the static data and dynamic data of the transformer district are extracted respectively, and the abnormal data are corrected by the K nearest neighbor complementarity method. Combined with the characteristic differences of marketing customer portraits, the quantitative feature decomposition of the benchmark value of line loss rate in Transformer district is realized. According to the dynamic identification results of the benchmark value of line loss rate in Transformer district, the benchmark value of line loss rate in Transformer district with high-dimensional data is compressed into a low-dimensional space by using the feature space dimension reduction method, and the quantitative calculation of correlation and difference between samples in each Transformer district is realized. The simulation results show that the calculation complexity of this method is low, and the calculation method has a good ability to adjust the learning rate, ensuring a good local optimal solution in the learning process and high calculation accuracy.
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