Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method
This letter proposes a reliable transfer learning (RTL) method for pre-fault dynamic security assessment (DSA) in power systems to improve DSA performance in the presence of potentially related unknown faults. It takes individual discrep-ancies into consideration and can handle unknown faults with i...
| প্রধান লেখক: | , , , |
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| অন্যান্য লেখক: | |
| বিন্যাস: | Journal Article |
| ভাষা: | English |
| প্রকাশিত: |
2024
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| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | https://hdl.handle.net/10356/174894 |
| _version_ | 1826125367326277632 |
|---|---|
| author | Ren, Chao Yu, Han Xu, Yan Dong, Zhao Yang |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Ren, Chao Yu, Han Xu, Yan Dong, Zhao Yang |
| author_sort | Ren, Chao |
| collection | NTU |
| description | This letter proposes a reliable transfer learning (RTL) method for pre-fault dynamic security assessment (DSA) in power systems to improve DSA performance in the presence of potentially related unknown faults. It takes individual discrep-ancies into consideration and can handle unknown faults with incomplete data. Extensive experiment results demonstrate high DSA accuracy and computational efficiency of the proposed RTL method. Theoretical analysis shows RTL can guarantee system performance. |
| first_indexed | 2024-10-01T06:35:27Z |
| format | Journal Article |
| id | ntu-10356/174894 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:35:27Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | ntu-10356/1748942024-04-19T15:53:12Z Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method Ren, Chao Yu, Han Xu, Yan Dong, Zhao Yang School of Electrical and Electronic Engineering School of Computer Science and Engineering Engineering Adversarial training Dynamic security assessment This letter proposes a reliable transfer learning (RTL) method for pre-fault dynamic security assessment (DSA) in power systems to improve DSA performance in the presence of potentially related unknown faults. It takes individual discrep-ancies into consideration and can handle unknown faults with incomplete data. Extensive experiment results demonstrate high DSA accuracy and computational efficiency of the proposed RTL method. Theoretical analysis shows RTL can guarantee system performance. Nanyang Technological University National Research Foundation (NRF) Published version This work was supported by the Internal Talent Award (TRACS) with Wallenberg-NTU Presidential Postdoctoral Fellowship 2022; the National Research Foundation, Singapore and DSO National Laboratories under the AI Singapore Program (AISG Award No: AISG2-RP-2020-019); the RIE 2020 Advanced Manufacturing and Engineering (AME) Programmatic Fund (No. A20G8b0102), Singapore; and Future Communications Research & Development Program (FCP-NTU-RG-2021-014). 2024-04-15T08:08:33Z 2024-04-15T08:08:33Z 2024 Journal Article Ren, C., Yu, H., Xu, Y. & Dong, Z. Y. (2024). Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method. CSEE Journal of Power and Energy Systems, 10(1), 427-431. https://dx.doi.org/10.17775/CSEEJPES.2023.00230 2096-0042 https://hdl.handle.net/10356/174894 10.17775/CSEEJPES.2023.00230 2-s2.0-85185201359 1 10 427 431 en AISG2-RP-2020-019 A20G8b0102 FCP-NTU-RG-2021-014 CSEE Journal of Power and Energy Systems © 2023 CSEE. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). application/pdf |
| spellingShingle | Engineering Adversarial training Dynamic security assessment Ren, Chao Yu, Han Xu, Yan Dong, Zhao Yang Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method |
| title | Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method |
| title_full | Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method |
| title_fullStr | Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method |
| title_full_unstemmed | Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method |
| title_short | Understanding discrepancy of power system dynamic security assessment with unknown faults: a reliable transfer learning-based method |
| title_sort | understanding discrepancy of power system dynamic security assessment with unknown faults a reliable transfer learning based method |
| topic | Engineering Adversarial training Dynamic security assessment |
| url | https://hdl.handle.net/10356/174894 |
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