Data-driven Static Equivalence with Physics-informed Koopman Operators
With deployment of measurement units, fitting static equivalent models of distribution networks (DNs) by linear regression has been recognized as an effective method in power flow analysis of a transmission network. Increasing volatility of measurements caused by variable distributed renewable energ...
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| Format: | Article |
| Language: | English |
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China electric power research institute
2024-01-01
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| Series: | CSEE Journal of Power and Energy Systems |
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| Online Access: | https://ieeexplore.ieee.org/document/10106204/ |
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| author | Wei Lin Changhong Zhao Maosheng Gao C. Y. Chung |
| author_facet | Wei Lin Changhong Zhao Maosheng Gao C. Y. Chung |
| author_sort | Wei Lin |
| collection | DOAJ |
| description | With deployment of measurement units, fitting static equivalent models of distribution networks (DNs) by linear regression has been recognized as an effective method in power flow analysis of a transmission network. Increasing volatility of measurements caused by variable distributed renewable energy sources makes it more difficult to accurately fit such equivalent models. To tackle this challenge, this letter proposes a novel data-driven method to improve equivalency accuracy of DNs with distributed energy resources. This letter provides a new perspective that an equivalent model can be regarded as a mapping from internal conditions and border voltages to border power injections. Such mapping can be established through 1) Koopman operator theory, and 2) physical features of power flow equations at the root node of a DN. Performance of the proposed method is demonstrated on the IEEE 33-bus and IEEE 136-bus test systems connected to a 661-bus utility system. |
| format | Article |
| id | doaj-art-6c1cc0ba4208456d865cae2d4abcc0a8 |
| institution | OA Journals |
| issn | 2096-0042 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | China electric power research institute |
| record_format | Article |
| series | CSEE Journal of Power and Energy Systems |
| spelling | doaj-art-6c1cc0ba4208456d865cae2d4abcc0a82025-08-20T01:51:39ZengChina electric power research instituteCSEE Journal of Power and Energy Systems2096-00422024-01-0110143243810.17775/CSEEJPES.2022.0875010106204Data-driven Static Equivalence with Physics-informed Koopman OperatorsWei Lin0Changhong Zhao1Maosheng Gao2C. Y. Chung3The Hong Kong Polytechnic University,Department of Electrical Engineering,Hong Kong SAR,ChinaThe Chinese University of Hong Kong,Department of Information Engineering,Hong Kong SAR,ChinaSchool of Electrical Engineering, Chongqing University,Chongqing,China,400044The Hong Kong Polytechnic University,Department of Electrical Engineering,Hong Kong SAR,ChinaWith deployment of measurement units, fitting static equivalent models of distribution networks (DNs) by linear regression has been recognized as an effective method in power flow analysis of a transmission network. Increasing volatility of measurements caused by variable distributed renewable energy sources makes it more difficult to accurately fit such equivalent models. To tackle this challenge, this letter proposes a novel data-driven method to improve equivalency accuracy of DNs with distributed energy resources. This letter provides a new perspective that an equivalent model can be regarded as a mapping from internal conditions and border voltages to border power injections. Such mapping can be established through 1) Koopman operator theory, and 2) physical features of power flow equations at the root node of a DN. Performance of the proposed method is demonstrated on the IEEE 33-bus and IEEE 136-bus test systems connected to a 661-bus utility system.https://ieeexplore.ieee.org/document/10106204/Data-drivendistribution networkKoopman operator theorystatic equivalent model |
| spellingShingle | Wei Lin Changhong Zhao Maosheng Gao C. Y. Chung Data-driven Static Equivalence with Physics-informed Koopman Operators CSEE Journal of Power and Energy Systems Data-driven distribution network Koopman operator theory static equivalent model |
| title | Data-driven Static Equivalence with Physics-informed Koopman Operators |
| title_full | Data-driven Static Equivalence with Physics-informed Koopman Operators |
| title_fullStr | Data-driven Static Equivalence with Physics-informed Koopman Operators |
| title_full_unstemmed | Data-driven Static Equivalence with Physics-informed Koopman Operators |
| title_short | Data-driven Static Equivalence with Physics-informed Koopman Operators |
| title_sort | data driven static equivalence with physics informed koopman operators |
| topic | Data-driven distribution network Koopman operator theory static equivalent model |
| url | https://ieeexplore.ieee.org/document/10106204/ |
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