Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power System
The integration of high proportions of renewable energy into power systems to replace traditional synchronous generators has led to continuous weakening of the system inertia support and primary frequency regulation resources. Spatiotemporal dispersion of the system’s frequency response has become i...
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2025-06-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/12/3040 |
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| author | Dongdong Li Zhenfei Yao Yin Yao Bo Xu Fan Yang |
| author_facet | Dongdong Li Zhenfei Yao Yin Yao Bo Xu Fan Yang |
| author_sort | Dongdong Li |
| collection | DOAJ |
| description | The integration of high proportions of renewable energy into power systems to replace traditional synchronous generators has led to continuous weakening of the system inertia support and primary frequency regulation resources. Spatiotemporal dispersion of the system’s frequency response has become increasingly prominent. Historical data from numerous frequency disturbance events show that the unified system’s frequency can no longer accurately represent the variations in the frequency response at each node in the system. To address this issue, a method for frequency measurement point selection and system partitioning in a high-renewable-energy-penetration power system is proposed. Firstly, the frequency regulation influence (FRI) index is defined to quantify the comprehensive ability of nodes to dynamically regulate the spatiotemporal dynamics of the power system’s frequency, identifying key frequency regulation nodes as the regional frequency measurement points. Secondly, a hierarchical clustering method is employed to partition the remaining nodes around the frequency measurement points, and the optimal partitioning result is evaluated using modularity indicators. Finally, the effectiveness of the proposed method is verified using a modified standard 39-node system. The simulation results reveal that the proposed frequency measurement point selection and system partitioning method can effectively enhance the accuracy of regional frequency response measurements, as well as the evaluation accuracy of inertia and primary frequency regulation. |
| format | Article |
| id | doaj-art-9799ff8367a1403d96fa211ded72ea9e |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-9799ff8367a1403d96fa211ded72ea9e2025-08-20T03:24:33ZengMDPI AGEnergies1996-10732025-06-011812304010.3390/en18123040Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power SystemDongdong Li0Zhenfei Yao1Yin Yao2Bo Xu3Fan Yang4College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaThe integration of high proportions of renewable energy into power systems to replace traditional synchronous generators has led to continuous weakening of the system inertia support and primary frequency regulation resources. Spatiotemporal dispersion of the system’s frequency response has become increasingly prominent. Historical data from numerous frequency disturbance events show that the unified system’s frequency can no longer accurately represent the variations in the frequency response at each node in the system. To address this issue, a method for frequency measurement point selection and system partitioning in a high-renewable-energy-penetration power system is proposed. Firstly, the frequency regulation influence (FRI) index is defined to quantify the comprehensive ability of nodes to dynamically regulate the spatiotemporal dynamics of the power system’s frequency, identifying key frequency regulation nodes as the regional frequency measurement points. Secondly, a hierarchical clustering method is employed to partition the remaining nodes around the frequency measurement points, and the optimal partitioning result is evaluated using modularity indicators. Finally, the effectiveness of the proposed method is verified using a modified standard 39-node system. The simulation results reveal that the proposed frequency measurement point selection and system partitioning method can effectively enhance the accuracy of regional frequency response measurements, as well as the evaluation accuracy of inertia and primary frequency regulation.https://www.mdpi.com/1996-1073/18/12/3040frequency dispersionsystem partitioningkey node identificationhierarchical clustering |
| spellingShingle | Dongdong Li Zhenfei Yao Yin Yao Bo Xu Fan Yang Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power System Energies frequency dispersion system partitioning key node identification hierarchical clustering |
| title | Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power System |
| title_full | Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power System |
| title_fullStr | Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power System |
| title_full_unstemmed | Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power System |
| title_short | Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power System |
| title_sort | regional frequency measurement point selection and system partitioning method for high renewable energy penetration power system |
| topic | frequency dispersion system partitioning key node identification hierarchical clustering |
| url | https://www.mdpi.com/1996-1073/18/12/3040 |
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