Identification of Distribution Network Topology and Line Parameter Based on Smart Meter Measurements
Accurate line parameters are the basis for the optimal control and safety analysis of distribution networks. The lack of real-time monitoring equipment in grids has meant that data-driven identification methods have become the main tool to estimate line parameters. However, frequent network reconfig...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/17/4/830 |
| _version_ | 1797298365885579264 |
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| author | Chong Wang Zheng Lou Ming Li Zhaoyang Zhu Dongsheng Jing |
| author_facet | Chong Wang Zheng Lou Ming Li Zhaoyang Zhu Dongsheng Jing |
| author_sort | Chong Wang |
| collection | DOAJ |
| description | Accurate line parameters are the basis for the optimal control and safety analysis of distribution networks. The lack of real-time monitoring equipment in grids has meant that data-driven identification methods have become the main tool to estimate line parameters. However, frequent network reconfigurations increase the uncertainty of distribution network topologies, creating challenges in the data-driven identification of line parameters. In this paper, a line parameter identification method compatible with an uncertain topology is proposed, which simplifies the model complexity of the joint identification of topology and line parameters by removing the unconnected branches through noise reduction. In order to improve the solving accuracy and efficiency of the identification model, a two-stage identification method is proposed. First, the initial values of the topology and line parameters are quickly obtained using a linear power flow model. Then, the identification results are modified iteratively based on the classical power flow model to achieve a more accurate estimation of the grid topology and line parameters. Finally, a simulation analysis based on IEEE 33- and 118-bus distribution systems demonstrated that the proposed method can effectively realize the estimation of topology and line parameters, and is robust with regard to both measurement errors and grid structures. |
| first_indexed | 2024-03-07T22:34:46Z |
| format | Article |
| id | doaj.art-ab3988bf999048bcba3be1880fa824e4 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-07T22:34:46Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-ab3988bf999048bcba3be1880fa824e42024-02-23T15:15:11ZengMDPI AGEnergies1996-10732024-02-0117483010.3390/en17040830Identification of Distribution Network Topology and Line Parameter Based on Smart Meter MeasurementsChong Wang0Zheng Lou1Ming Li2Zhaoyang Zhu3Dongsheng Jing4Information and Communication Branch, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210024, ChinaInformation and Communication Branch, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210024, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210096, ChinaState Grid Suzhou Power Supply Company, Suzhou 215004, ChinaState Grid Suzhou Power Supply Company, Suzhou 215004, ChinaAccurate line parameters are the basis for the optimal control and safety analysis of distribution networks. The lack of real-time monitoring equipment in grids has meant that data-driven identification methods have become the main tool to estimate line parameters. However, frequent network reconfigurations increase the uncertainty of distribution network topologies, creating challenges in the data-driven identification of line parameters. In this paper, a line parameter identification method compatible with an uncertain topology is proposed, which simplifies the model complexity of the joint identification of topology and line parameters by removing the unconnected branches through noise reduction. In order to improve the solving accuracy and efficiency of the identification model, a two-stage identification method is proposed. First, the initial values of the topology and line parameters are quickly obtained using a linear power flow model. Then, the identification results are modified iteratively based on the classical power flow model to achieve a more accurate estimation of the grid topology and line parameters. Finally, a simulation analysis based on IEEE 33- and 118-bus distribution systems demonstrated that the proposed method can effectively realize the estimation of topology and line parameters, and is robust with regard to both measurement errors and grid structures.https://www.mdpi.com/1996-1073/17/4/830distribution networktopology identificationline parameter identificationlinear power flow model |
| spellingShingle | Chong Wang Zheng Lou Ming Li Zhaoyang Zhu Dongsheng Jing Identification of Distribution Network Topology and Line Parameter Based on Smart Meter Measurements Energies distribution network topology identification line parameter identification linear power flow model |
| title | Identification of Distribution Network Topology and Line Parameter Based on Smart Meter Measurements |
| title_full | Identification of Distribution Network Topology and Line Parameter Based on Smart Meter Measurements |
| title_fullStr | Identification of Distribution Network Topology and Line Parameter Based on Smart Meter Measurements |
| title_full_unstemmed | Identification of Distribution Network Topology and Line Parameter Based on Smart Meter Measurements |
| title_short | Identification of Distribution Network Topology and Line Parameter Based on Smart Meter Measurements |
| title_sort | identification of distribution network topology and line parameter based on smart meter measurements |
| topic | distribution network topology identification line parameter identification linear power flow model |
| url | https://www.mdpi.com/1996-1073/17/4/830 |
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