Distribution network line loss analysis method based on improved clustering algorithm and isolated forest algorithm

The long-term loss of distribution network in the process of distribution network development is caused by the backward management mode of distribution network. The traditional analysis and calculation methods of distribution network loss can not adapt to the current development environment of distr...

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Bibliographic Details
Published in:Scientific reports Vol. 14; no. 1; pp. 19554 - 15
Main Authors: Li, Jian, Li, Shuoyu, Zhao, Wen, Li, Jiajie, Zhang, Ke, Jiang, Zetao
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 22.08.2024
Nature Publishing Group
Nature Portfolio
Subjects:
639/705/1042
639/705/117
639/705/794
Algorithms
Clustering
Coefficient of variation
Data processing
Forest management
Fuzzy C-Means
Humanities and Social Sciences
Isolated forest algorithm
Line loss analysis
Medium voltage distribution networks
multidisciplinary
Science
Science (multidisciplinary)
Fuzzy C-Means
Data processing
Line loss analysis
Medium voltage distribution networks
Isolated forest algorithm
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:The long-term loss of distribution network in the process of distribution network development is caused by the backward management mode of distribution network. The traditional analysis and calculation methods of distribution network loss can not adapt to the current development environment of distribution network. To improve the accuracy of filling missing values in power load data, particle swarm optimization algorithm is proposed to optimize the clustering center of the clustering algorithm. Furthermore, the original isolated forest anomaly recognition algorithm can be used to detect outliers in the load data, and the coefficient of variation of the load data is used to improve the recognition accuracy of the algorithm. Finally, this paper introduces a breadth-first-based method for calculating line loss in the context of big data. An example is provided using the distribution network system of Yuxi City in Yunnan Province, and a simulation experiment is carried out. And the findings revealed that the error of the enhanced fuzzy C-mean clustering algorithm was on average − 6.35, with a standard deviation of 4.015 in the situation of partially missing data. The area under the characteristic curve of the improved isolated forest algorithm subjects in the case of the abnormal sample fuzzy situation was 0.8586, with the smallest decrease, based on the coefficient of variation, and through the refinement of the analysis, it was discovered that the feeder line loss rate is 7.62%. It is confirmed that the suggested technique can carry out distribution network line loss analysis fast and accurately and can serve as a guide for managing distribution network line loss.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-68366-y