Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data Fusion
As the number of substations continues to increase globally and the market demand continues to rise, the current workload of maintenance and daily operation of substations in power grids cannot meet the current demand if only relying on manual work, and the design and implementation of intelligent s...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10092796/ |
| _version_ | 1797847340981157888 |
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| author | Bo Wu Yifan Hu |
| author_facet | Bo Wu Yifan Hu |
| author_sort | Bo Wu |
| collection | DOAJ |
| description | As the number of substations continues to increase globally and the market demand continues to rise, the current workload of maintenance and daily operation of substations in power grids cannot meet the current demand if only relying on manual work, and the design and implementation of intelligent safety control solutions for substations is imperative. Therefore, this paper proposes a joint safety control system and model analysis for substations based on multi-source heterogeneous data fusion. Firstly, a three-dimensional visualization substation efficient interactive operation platform is realized, which realizes the functions of substation scene roaming, system login, information management, equipment parameters, status viewing and operation ticket pushing; after that, a variety of intelligent hardware devices for data collection, such as multi-dimensional terminal sensors, intelligent wearable devices, intelligent pre-built positioning installation measure rod, and substation intelligent inspection robots are designed to greatly improve the substation inspection efficiency and realize real-time monitoring and data interaction in the inspection process. Finally, we propose an Attention-LSTM-based prediction model for substation multidimensional data, which can predict power equipment spatio-temporal data in the short term, and the prediction results can be combined with intelligent devices for joint diagnosis. The Attention-LSTM prediction model is well-trained in transformer oil temperature experiments, and the experimental results show that this model can provide early warning for the abnormal state of substation power equipment. In summary, this thesis describes a set of complete and practically feasible intelligent safety control methods for substations. The joint safety control system and model analysis of the substation based on multi-source heterogeneous data fusion designed in this paper is mainly oriented to the substation as an electric power workplace, which has quite a vast application prospect for energy equipment. |
| first_indexed | 2024-04-09T18:09:45Z |
| format | Article |
| id | doaj.art-197f30d57316480bb3a445b613149586 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-09T18:09:45Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-197f30d57316480bb3a445b6131495862023-04-13T23:00:45ZengIEEEIEEE Access2169-35362023-01-0111352813529710.1109/ACCESS.2023.326470710092796Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data FusionBo Wu0https://orcid.org/0000-0002-9394-155XYifan Hu1https://orcid.org/0000-0002-5723-5156College of International Education, North China Electric Power University, Baoding, ChinaCollege of International Education, North China Electric Power University, Baoding, ChinaAs the number of substations continues to increase globally and the market demand continues to rise, the current workload of maintenance and daily operation of substations in power grids cannot meet the current demand if only relying on manual work, and the design and implementation of intelligent safety control solutions for substations is imperative. Therefore, this paper proposes a joint safety control system and model analysis for substations based on multi-source heterogeneous data fusion. Firstly, a three-dimensional visualization substation efficient interactive operation platform is realized, which realizes the functions of substation scene roaming, system login, information management, equipment parameters, status viewing and operation ticket pushing; after that, a variety of intelligent hardware devices for data collection, such as multi-dimensional terminal sensors, intelligent wearable devices, intelligent pre-built positioning installation measure rod, and substation intelligent inspection robots are designed to greatly improve the substation inspection efficiency and realize real-time monitoring and data interaction in the inspection process. Finally, we propose an Attention-LSTM-based prediction model for substation multidimensional data, which can predict power equipment spatio-temporal data in the short term, and the prediction results can be combined with intelligent devices for joint diagnosis. The Attention-LSTM prediction model is well-trained in transformer oil temperature experiments, and the experimental results show that this model can provide early warning for the abnormal state of substation power equipment. In summary, this thesis describes a set of complete and practically feasible intelligent safety control methods for substations. The joint safety control system and model analysis of the substation based on multi-source heterogeneous data fusion designed in this paper is mainly oriented to the substation as an electric power workplace, which has quite a vast application prospect for energy equipment.https://ieeexplore.ieee.org/document/10092796/Multi-source heterogeneous data fusionsubstation intelligent safety controlvirtual simulation platformsmart wearable devicessubstation intelligent inspection robotattention-LSTM |
| spellingShingle | Bo Wu Yifan Hu Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data Fusion IEEE Access Multi-source heterogeneous data fusion substation intelligent safety control virtual simulation platform smart wearable devices substation intelligent inspection robot attention-LSTM |
| title | Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data Fusion |
| title_full | Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data Fusion |
| title_fullStr | Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data Fusion |
| title_full_unstemmed | Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data Fusion |
| title_short | Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data Fusion |
| title_sort | analysis of substation joint safety control system and model based on multi source heterogeneous data fusion |
| topic | Multi-source heterogeneous data fusion substation intelligent safety control virtual simulation platform smart wearable devices substation intelligent inspection robot attention-LSTM |
| url | https://ieeexplore.ieee.org/document/10092796/ |
| work_keys_str_mv | AT bowu analysisofsubstationjointsafetycontrolsystemandmodelbasedonmultisourceheterogeneousdatafusion AT yifanhu analysisofsubstationjointsafetycontrolsystemandmodelbasedonmultisourceheterogeneousdatafusion |