Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics
Abstract State estimation plays an important role in the monitoring and control of integrated electric–gas systems (IEGSs), but it faces limitations due to insufficient measurement configurations and low data redundancy in these systems; additional measurement configurations are needed to increase t...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-12-01
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| Series: | IET Energy Systems Integration |
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| Online Access: | https://doi.org/10.1049/esi2.12176 |
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| author | Zeming Chen Zhigang Li Huajian Li Jiahui Zhang Yixuan Li Jiehui Zheng |
| author_facet | Zeming Chen Zhigang Li Huajian Li Jiahui Zhang Yixuan Li Jiehui Zheng |
| author_sort | Zeming Chen |
| collection | DOAJ |
| description | Abstract State estimation plays an important role in the monitoring and control of integrated electric–gas systems (IEGSs), but it faces limitations due to insufficient measurement configurations and low data redundancy in these systems; additional measurement configurations are needed to increase the overall system observability. Owing to the lack of suitable observability analysis methods, optimal measurement configurations for IEGSs remain underexplored. This paper presents an IEGS observability analysis method that incorporates gas flow dynamics via the Lie derivative. This method incorporates the complex topological structure of the gas network and the dynamic process of gas flow into the IEGS observability analysis. Furthermore, the measurement configuration problem for IEGSs considering gas flow dynamics is formulated as a rank‐constrained optimization problem. To handle the rank constraints effectively, an iterative cutting method is developed with convergence guarantees. Finally, the efficacy and practicality of the proposed methods are validated through case studies of varying scales. The proposed optimal measurement configuration model reduces measurement configuration costs while maintaining system observability. |
| format | Article |
| id | doaj-art-14786e683fc046f291c621acb5b09878 |
| institution | Kabale University |
| issn | 2516-8401 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Energy Systems Integration |
| spelling | doaj-art-14786e683fc046f291c621acb5b098782025-01-29T05:18:54ZengWileyIET Energy Systems Integration2516-84012024-12-016S189190210.1049/esi2.12176Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamicsZeming Chen0Zhigang Li1Huajian Li2Jiahui Zhang3Yixuan Li4Jiehui Zheng5School of Electric Power Engineering South China University of Technology Guangzhou ChinaSchool of Science and Engineering The Chinese University of Hong Kong ‐ Shenzhen Shenzhen ChinaShanxi Energy Internet Research Institute Taiyuan ChinaShanxi Energy Internet Research Institute Taiyuan ChinaShanxi Energy Internet Research Institute Taiyuan ChinaSchool of Electric Power Engineering South China University of Technology Guangzhou ChinaAbstract State estimation plays an important role in the monitoring and control of integrated electric–gas systems (IEGSs), but it faces limitations due to insufficient measurement configurations and low data redundancy in these systems; additional measurement configurations are needed to increase the overall system observability. Owing to the lack of suitable observability analysis methods, optimal measurement configurations for IEGSs remain underexplored. This paper presents an IEGS observability analysis method that incorporates gas flow dynamics via the Lie derivative. This method incorporates the complex topological structure of the gas network and the dynamic process of gas flow into the IEGS observability analysis. Furthermore, the measurement configuration problem for IEGSs considering gas flow dynamics is formulated as a rank‐constrained optimization problem. To handle the rank constraints effectively, an iterative cutting method is developed with convergence guarantees. Finally, the efficacy and practicality of the proposed methods are validated through case studies of varying scales. The proposed optimal measurement configuration model reduces measurement configuration costs while maintaining system observability.https://doi.org/10.1049/esi2.12176natural gas technologypower gridspower system measurement |
| spellingShingle | Zeming Chen Zhigang Li Huajian Li Jiahui Zhang Yixuan Li Jiehui Zheng Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics IET Energy Systems Integration natural gas technology power grids power system measurement |
| title | Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics |
| title_full | Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics |
| title_fullStr | Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics |
| title_full_unstemmed | Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics |
| title_short | Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics |
| title_sort | measurement configuration for integrated electric gas systems via observability analysis considering gas flow dynamics |
| topic | natural gas technology power grids power system measurement |
| url | https://doi.org/10.1049/esi2.12176 |
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