Data-driven Localization and Estimation of Disturbance in the Interconnected Power System
Identifying the location of a disturbance and its magnitude is an important component for stable operation of power systems. We study the problem of localizing and estimating a disturbance in the interconnected power system. We take a model-free approach to this problem by using frequency data from...
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers (IEEE)
2020
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| Online Access: | https://hdl.handle.net/1721.1/124723 |
| _version_ | 1826213364784693248 |
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| author | Lee, Hyang-Won Zhang, Jianan Modiano, Eytan H. |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Lee, Hyang-Won Zhang, Jianan Modiano, Eytan H. |
| author_sort | Lee, Hyang-Won |
| collection | MIT |
| description | Identifying the location of a disturbance and its magnitude is an important component for stable operation of power systems. We study the problem of localizing and estimating a disturbance in the interconnected power system. We take a model-free approach to this problem by using frequency data from generators. Specifically, we develop a logistic regression based method for localization and a linear regression based method for estimation of the magnitude of disturbance. Our model-free approach does not require the knowledge of system parameters such as inertia constants and topology, and is shown to achieve highly accurate localization and estimation performance even in the presence of measurement noise and missing data. ©2018 |
| first_indexed | 2024-09-23T15:47:55Z |
| format | Article |
| id | mit-1721.1/124723 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:47:55Z |
| publishDate | 2020 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1247232022-10-02T04:11:33Z Data-driven Localization and Estimation of Disturbance in the Interconnected Power System Lee, Hyang-Won Zhang, Jianan Modiano, Eytan H. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Massachusetts Institute of Technology. Laboratory for Information and Decision Systems Identifying the location of a disturbance and its magnitude is an important component for stable operation of power systems. We study the problem of localizing and estimating a disturbance in the interconnected power system. We take a model-free approach to this problem by using frequency data from generators. Specifically, we develop a logistic regression based method for localization and a linear regression based method for estimation of the magnitude of disturbance. Our model-free approach does not require the knowledge of system parameters such as inertia constants and topology, and is shown to achieve highly accurate localization and estimation performance even in the presence of measurement noise and missing data. ©2018 2020-04-17T15:36:54Z 2020-04-17T15:36:54Z 2018-06 2019-10-30T14:39:41Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/124723 Lee, Hyang-Won, Jianan Zhang, and Eytan Modiano, "Data-driven Localization and Estimation of Disturbance in the Interconnected Power System." 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm 2018), Oct. 29-31, 2018, Aalborg, Denmark (Piscataway, N.J.: IEEE, 2018): p. 1-6 doi 10.1109/SMARTGRIDCOMM.2018.8587509 ©2018 Author(s) en 10.1109/SMARTGRIDCOMM.2018.8587509 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) arXiv |
| spellingShingle | Lee, Hyang-Won Zhang, Jianan Modiano, Eytan H. Data-driven Localization and Estimation of Disturbance in the Interconnected Power System |
| title | Data-driven Localization and Estimation of Disturbance in the Interconnected Power System |
| title_full | Data-driven Localization and Estimation of Disturbance in the Interconnected Power System |
| title_fullStr | Data-driven Localization and Estimation of Disturbance in the Interconnected Power System |
| title_full_unstemmed | Data-driven Localization and Estimation of Disturbance in the Interconnected Power System |
| title_short | Data-driven Localization and Estimation of Disturbance in the Interconnected Power System |
| title_sort | data driven localization and estimation of disturbance in the interconnected power system |
| url | https://hdl.handle.net/1721.1/124723 |
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