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Data Modeling and Analysis of Line Loss Management at the Same Time in Distribution Through-Platform Area

Published: 13 March 2023 Publication History

Abstract

The core competitiveness of a power grid enterprise depends on the quality of its services, and the importance of ensuring the reliability of power supply to customers is self-evident to the operation and management of the grid. In recent years, with the continuous deepening of the reform of the power system, users' requirements for power services have become higher and higher, and high-quality power services have gradually become a key concern for grid enterprises. In the process of providing power supply services to users, a more complex task is the management of abnormal data of lost lines in power distribution through the platform area. In this paper, through the application of the results of the data collection of the camp distribution and transfer through, the use of big data statistics and analysis methods, the new ideas and methods of line loss management in the platform area are elaborated, and through the statistical analysis of the line loss in the platform area during the same period, the level of line loss management in the platform area is improved, the full collection rate of the platform area is promoted, a good effect of loss reduction is received, the company's operation and management level is improved, and the quality of the data collection of the camp distribution and transfer through is confirmed, providing direction for the camp distribution and transfer The company's management level was improved and the quality of data collection was confirmed, which provided direction for the quality management of data collection and thus promoted the continuous improvement of data quality.

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  1. Data Modeling and Analysis of Line Loss Management at the Same Time in Distribution Through-Platform Area

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    BDSIC '22: Proceedings of the 2022 4th International Conference on Big-data Service and Intelligent Computation
    November 2022
    87 pages
    ISBN:9781450397070
    DOI:10.1145/3578339
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 13 March 2023

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