Similarity matching method of power distribution system operating data based on neural information retrieval
Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy. Therefore, improvement of the ability of data-driven operation management, intelligent analysis, and mining is urgently requi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2023-02-01
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| Series: | Global Energy Interconnection |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2096511723000117 |
| _version_ | 1811157858651209728 |
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| author | Kai Xiao Daoxing Li Pengtian Guo Xiaohui Wang Yong Chen |
| author_facet | Kai Xiao Daoxing Li Pengtian Guo Xiaohui Wang Yong Chen |
| author_sort | Kai Xiao |
| collection | DOAJ |
| description | Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy. Therefore, improvement of the ability of data-driven operation management, intelligent analysis, and mining is urgently required. To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation, maintenance experience, and knowledge by rule and line, a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology. Based on the processing flow of the operating data of the power distribution system, a technical framework of neural information retrieval is established. Combined with the natural graph characteristics of the power distribution system, a unified graph data structure and a data fusion method of data access, data complement, and multi-source data are constructed. Further, a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed. The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set. The model is verified on the operating section of the power distribution system of a provincial grid area. The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems. |
| first_indexed | 2024-04-10T05:14:33Z |
| format | Article |
| id | doaj.art-1f5540e396b9484ca6c3e3a7a42d6d32 |
| institution | Directory Open Access Journal |
| issn | 2096-5117 |
| language | English |
| last_indexed | 2024-04-10T05:14:33Z |
| publishDate | 2023-02-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Global Energy Interconnection |
| spelling | doaj.art-1f5540e396b9484ca6c3e3a7a42d6d322023-03-09T04:13:20ZengKeAi Communications Co., Ltd.Global Energy Interconnection2096-51172023-02-01611525Similarity matching method of power distribution system operating data based on neural information retrievalKai Xiao0Daoxing Li1Pengtian Guo2Xiaohui Wang3Yong Chen4China Electric Power Research Institute Co. Ltd., Beijing 100192, PR ChinaChina Electric Power Research Institute Co. Ltd., Beijing 100192, PR ChinaChina Electric Power Research Institute Co. Ltd., Beijing 100192, PR ChinaChina Electric Power Research Institute Co. Ltd., Beijing 100192, PR ChinaChina Electric Power Research Institute Co. Ltd., Beijing 100192, PR ChinaOperation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy. Therefore, improvement of the ability of data-driven operation management, intelligent analysis, and mining is urgently required. To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation, maintenance experience, and knowledge by rule and line, a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology. Based on the processing flow of the operating data of the power distribution system, a technical framework of neural information retrieval is established. Combined with the natural graph characteristics of the power distribution system, a unified graph data structure and a data fusion method of data access, data complement, and multi-source data are constructed. Further, a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed. The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set. The model is verified on the operating section of the power distribution system of a provincial grid area. The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.http://www.sciencedirect.com/science/article/pii/S2096511723000117Neural information retrievalPower distributionGraph dataOperating sectionSimilarity matching |
| spellingShingle | Kai Xiao Daoxing Li Pengtian Guo Xiaohui Wang Yong Chen Similarity matching method of power distribution system operating data based on neural information retrieval Global Energy Interconnection Neural information retrieval Power distribution Graph data Operating section Similarity matching |
| title | Similarity matching method of power distribution system operating data based on neural information retrieval |
| title_full | Similarity matching method of power distribution system operating data based on neural information retrieval |
| title_fullStr | Similarity matching method of power distribution system operating data based on neural information retrieval |
| title_full_unstemmed | Similarity matching method of power distribution system operating data based on neural information retrieval |
| title_short | Similarity matching method of power distribution system operating data based on neural information retrieval |
| title_sort | similarity matching method of power distribution system operating data based on neural information retrieval |
| topic | Neural information retrieval Power distribution Graph data Operating section Similarity matching |
| url | http://www.sciencedirect.com/science/article/pii/S2096511723000117 |
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