Fast-tracking method of inertial constant based on system identification
Aiming at the problem of quantitative inertia evaluation of a new energy electric power system, the system inertia constant tracking method based on system identification is studied. The method is divided into two categories: non-recursive algorithm and recursive algorithm. The non-recursive algorit...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2024-01-01
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| Series: | Science and Technology for Energy Transition |
| Subjects: | |
| Online Access: | https://www.stet-review.org/articles/stet/full_html/2024/01/stet20230141/stet20230141.html |
| _version_ | 1797343576602968064 |
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| author | Hu Xuekai Zeng Siming Meng Liang Li Tiecheng Zhang Qian |
| author_facet | Hu Xuekai Zeng Siming Meng Liang Li Tiecheng Zhang Qian |
| author_sort | Hu Xuekai |
| collection | DOAJ |
| description | Aiming at the problem of quantitative inertia evaluation of a new energy electric power system, the system inertia constant tracking method based on system identification is studied. The method is divided into two categories: non-recursive algorithm and recursive algorithm. The non-recursive algorithm uses a batch of data for batch processing to obtain the estimated value of the identification model parameters. The recursive algorithm is based on the estimated value of the model parameter at the previous moment and corrects the estimated value based on the new data currently obtained. From the perspective of the identification principle, the difference and internal relationship between the two in terms of calculation storage and identification speed are analyzed. The IEEE typical system is used to compare and verify the experimental examples. Theoretical analysis and experimental results show that the recursive algorithm has high identification accuracy, stable identification results and fast identification speed. It is suitable for the identification of objects with large numbers of nodes and complex structures, which is conducive to real-time monitoring and fast perception of the inertia constant of the new energy power system. |
| first_indexed | 2024-03-08T10:49:46Z |
| format | Article |
| id | doaj.art-d89ab8f4d3ba4749822bde3df70cbeed |
| institution | Directory Open Access Journal |
| issn | 2804-7699 |
| language | English |
| last_indexed | 2024-03-08T10:49:46Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Science and Technology for Energy Transition |
| spelling | doaj.art-d89ab8f4d3ba4749822bde3df70cbeed2024-01-26T16:50:39ZengEDP SciencesScience and Technology for Energy Transition2804-76992024-01-0179410.2516/stet/2023045stet20230141Fast-tracking method of inertial constant based on system identificationHu Xuekai0Zeng Siming1Meng Liang2Li Tiecheng3Zhang Qian4State Grid Hebei Electric Power Research InstituteState Grid Hebei Electric Power Research InstituteState Grid Hebei Electric Power Research InstituteState Grid Hebei Electric Power Research InstituteState Grid Hebei Electric Power Research InstituteAiming at the problem of quantitative inertia evaluation of a new energy electric power system, the system inertia constant tracking method based on system identification is studied. The method is divided into two categories: non-recursive algorithm and recursive algorithm. The non-recursive algorithm uses a batch of data for batch processing to obtain the estimated value of the identification model parameters. The recursive algorithm is based on the estimated value of the model parameter at the previous moment and corrects the estimated value based on the new data currently obtained. From the perspective of the identification principle, the difference and internal relationship between the two in terms of calculation storage and identification speed are analyzed. The IEEE typical system is used to compare and verify the experimental examples. Theoretical analysis and experimental results show that the recursive algorithm has high identification accuracy, stable identification results and fast identification speed. It is suitable for the identification of objects with large numbers of nodes and complex structures, which is conducive to real-time monitoring and fast perception of the inertia constant of the new energy power system.https://www.stet-review.org/articles/stet/full_html/2024/01/stet20230141/stet20230141.htmlelectric power systemsinertia constantsystem identificationquantitative evaluationnon-recursive algorithmrecursive algorithm |
| spellingShingle | Hu Xuekai Zeng Siming Meng Liang Li Tiecheng Zhang Qian Fast-tracking method of inertial constant based on system identification Science and Technology for Energy Transition electric power systems inertia constant system identification quantitative evaluation non-recursive algorithm recursive algorithm |
| title | Fast-tracking method of inertial constant based on system identification |
| title_full | Fast-tracking method of inertial constant based on system identification |
| title_fullStr | Fast-tracking method of inertial constant based on system identification |
| title_full_unstemmed | Fast-tracking method of inertial constant based on system identification |
| title_short | Fast-tracking method of inertial constant based on system identification |
| title_sort | fast tracking method of inertial constant based on system identification |
| topic | electric power systems inertia constant system identification quantitative evaluation non-recursive algorithm recursive algorithm |
| url | https://www.stet-review.org/articles/stet/full_html/2024/01/stet20230141/stet20230141.html |
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