Graphical Modular Power Technology of Distribution Network Based on Machine Learning Statistical Mathematical Equation
The distribution network structure is complex, the equipment is numerous, and the frequency of pattern and mode changes is high. These characteristics lead to certain difficulties in power distribution automation operation and maintenance graph management. This paper adopts the mathematical statisti...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2023-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2022.2.0186 |
| _version_ | 1797688740818190336 |
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| author | Yuan Jie Ji Yuan Yang Yuman Qian Junfeng Alshalabi Riyad |
| author_facet | Yuan Jie Ji Yuan Yang Yuman Qian Junfeng Alshalabi Riyad |
| author_sort | Yuan Jie |
| collection | DOAJ |
| description | The distribution network structure is complex, the equipment is numerous, and the frequency of pattern and mode changes is high. These characteristics lead to certain difficulties in power distribution automation operation and maintenance graph management. This paper adopts the mathematical statistics method of machine learning to analyze the multi-version hierarchical subscription mechanism of the distribution network graph. We conduct a breadth search on the distribution network graph to realize the automatic topology of the network. This paper implements a dynamic display system of distribution network monitoring information. The research results show that the graph-digital-analog integrated system has practical significance for data integration, application integration, and interoperability between systems. |
| first_indexed | 2024-03-12T01:35:03Z |
| format | Article |
| id | doaj.art-6230d844ccc444f2a6d310be34ed1fdc |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-12T01:35:03Z |
| publishDate | 2023-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-6230d844ccc444f2a6d310be34ed1fdc2023-09-11T07:01:10ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562023-01-01811027103610.2478/amns.2022.2.0186Graphical Modular Power Technology of Distribution Network Based on Machine Learning Statistical Mathematical EquationYuan Jie0Ji Yuan1Yang Yuman2Qian Junfeng3Alshalabi Riyad41Information Center of Guizhou Power Grid Co., Ltd., Guiyang, 550002, China1Information Center of Guizhou Power Grid Co., Ltd., Guiyang, 550002, China1Information Center of Guizhou Power Grid Co., Ltd., Guiyang, 550002, China1Information Center of Guizhou Power Grid Co., Ltd., Guiyang, 550002, China2College of Administrative Sciences, Applied Science University, BahrainThe distribution network structure is complex, the equipment is numerous, and the frequency of pattern and mode changes is high. These characteristics lead to certain difficulties in power distribution automation operation and maintenance graph management. This paper adopts the mathematical statistics method of machine learning to analyze the multi-version hierarchical subscription mechanism of the distribution network graph. We conduct a breadth search on the distribution network graph to realize the automatic topology of the network. This paper implements a dynamic display system of distribution network monitoring information. The research results show that the graph-digital-analog integrated system has practical significance for data integration, application integration, and interoperability between systems.https://doi.org/10.2478/amns.2022.2.0186machine learningmathematical and statistical methodspower systemgraph-to-mode conversionensemble97e60 |
| spellingShingle | Yuan Jie Ji Yuan Yang Yuman Qian Junfeng Alshalabi Riyad Graphical Modular Power Technology of Distribution Network Based on Machine Learning Statistical Mathematical Equation Applied Mathematics and Nonlinear Sciences machine learning mathematical and statistical methods power system graph-to-mode conversion ensemble 97e60 |
| title | Graphical Modular Power Technology of Distribution Network Based on Machine Learning Statistical Mathematical Equation |
| title_full | Graphical Modular Power Technology of Distribution Network Based on Machine Learning Statistical Mathematical Equation |
| title_fullStr | Graphical Modular Power Technology of Distribution Network Based on Machine Learning Statistical Mathematical Equation |
| title_full_unstemmed | Graphical Modular Power Technology of Distribution Network Based on Machine Learning Statistical Mathematical Equation |
| title_short | Graphical Modular Power Technology of Distribution Network Based on Machine Learning Statistical Mathematical Equation |
| title_sort | graphical modular power technology of distribution network based on machine learning statistical mathematical equation |
| topic | machine learning mathematical and statistical methods power system graph-to-mode conversion ensemble 97e60 |
| url | https://doi.org/10.2478/amns.2022.2.0186 |
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