Power Marketing Risk Prevention and Control Management of Power Supply Enterprises Based on Big Data Analysis Technology

Abstract

AbstractIn order to improve the efficiency and accuracy of distribution network risk warning, this paper adopts the Relief algorithm. Relief algorithm is a widely used feature selection algorithm. The main point of the algorithm is to evaluate the importance of features based on their ability to distinguish short-range samples. Sex. In this experiment, the electric power big data system through GIS automatically calculates the line loss according to the topological relationship of the analysis object, and achieves the automatic statistics of line loss division, voltage division, line division, and station division, and proposes analysis and treatment methods for abnormal problems. Experimental data shows that, taking a local 4 stations as an example, the line loss operation system of the power supply system linkage of the GIS-based power big data platform enables the line loss rate to be effectively controlled. The experimental results show that, for the line loss in the sub-station area, select a certain local station area as an example, the line loss rate of the station area in 2020 compared with the same period in 2019 is reduced by 0.21, 1.77, and 4 respectively. 1.94, 1.19. Therefore, the power big data platform based on GIS is very convenient and efficient to calculate the line loss, which can save a lot of manpower and material resources, and play the greatest role for the power enterprises to specify targeted loss reduction technologies and management measures in the energy saving and consumption reduction work.KeywordsBig data analysis technologyPower supply enterprise powerPower marketing risk prevention and control management