Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics

Xuemei Chen; Peixuan Wu; Xinran Zhang; Chao Lu; Wenchao Song

doi:10.1109/CPESE59653.2023.10303112

Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics

Xuemei Chen
, Peixuan Wu
, Xinran Zhang
, Chao Lu^*
, Wenchao Song

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Tsinghua University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

To provide a theoretical foundation for dynamic equivalent analysis and partition control in frequency issues of modern power systems, we proposed a co-frequency region partition method based on measured frequency dynamics. First, define the co-frequency region according to the application requirements of frequency dynamic analysis and control. The quantitative co-frequency index of the measured frequency dynamics between buses is proposed with the correlation coefficient. Then, we propose a co-frequency region partition method based on spectral clustering algorithm. The method based on the constructed frequency dynamics similarity graph can effectively extract the information of measured data to realize an appreciate number of clusters for the power system without knowing the system models and parameters. The IEEE 118-bus test system is applied to verify the effectiveness of the proposed method. Finally, the application scenarios of the co-frequency region partition are further illustrated.

Original language	English
Title of host publication	2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	14-19
Number of pages	6
ISBN (Electronic)	9798350327625
DOIs	https://doi.org/10.1109/CPESE59653.2023.10303112
State	Published - 2023
Event	10th International Conference on Power and Energy Systems Engineering, CPESE 2023 - Nagoya, Japan Duration: 8 Sep 2023 → 10 Sep 2023

Publication series

Name	2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023

Conference

Conference	10th International Conference on Power and Energy Systems Engineering, CPESE 2023
Country/Territory	Japan
City	Nagoya
Period	8/09/23 → 10/09/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

frequency dynamic analysis
region partition
spectral clustering
WAMS

Access to Document

10.1109/CPESE59653.2023.10303112

Cite this

Chen, X., Wu, P., Zhang, X., Lu, C., & Song, W. (2023). Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics. In 2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023 (pp. 14-19). (2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CPESE59653.2023.10303112

Chen, Xuemei ; Wu, Peixuan ; Zhang, Xinran et al. / Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics. 2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 14-19 (2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023).

@inproceedings{7fc4aa476e784bdabac9a6e432302405,

title = "Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics",

abstract = "To provide a theoretical foundation for dynamic equivalent analysis and partition control in frequency issues of modern power systems, we proposed a co-frequency region partition method based on measured frequency dynamics. First, define the co-frequency region according to the application requirements of frequency dynamic analysis and control. The quantitative co-frequency index of the measured frequency dynamics between buses is proposed with the correlation coefficient. Then, we propose a co-frequency region partition method based on spectral clustering algorithm. The method based on the constructed frequency dynamics similarity graph can effectively extract the information of measured data to realize an appreciate number of clusters for the power system without knowing the system models and parameters. The IEEE 118-bus test system is applied to verify the effectiveness of the proposed method. Finally, the application scenarios of the co-frequency region partition are further illustrated.",

keywords = "frequency dynamic analysis, region partition, spectral clustering, WAMS",

author = "Xuemei Chen and Peixuan Wu and Xinran Zhang and Chao Lu and Wenchao Song",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 10th International Conference on Power and Energy Systems Engineering, CPESE 2023 ; Conference date: 08-09-2023 Through 10-09-2023",

year = "2023",

doi = "10.1109/CPESE59653.2023.10303112",

language = "英语",

series = "2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "14--19",

booktitle = "2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023",

address = "美国",

}

Chen, X, Wu, P, Zhang, X, Lu, C & Song, W 2023, Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics. in 2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023. 2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023, Institute of Electrical and Electronics Engineers Inc., pp. 14-19, 10th International Conference on Power and Energy Systems Engineering, CPESE 2023, Nagoya, Japan, 8/09/23. https://doi.org/10.1109/CPESE59653.2023.10303112

Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics. / Chen, Xuemei; Wu, Peixuan; Zhang, Xinran et al.
2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 14-19 (2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics

AU - Chen, Xuemei

AU - Wu, Peixuan

AU - Zhang, Xinran

AU - Lu, Chao

AU - Song, Wenchao

PY - 2023

Y1 - 2023

N2 - To provide a theoretical foundation for dynamic equivalent analysis and partition control in frequency issues of modern power systems, we proposed a co-frequency region partition method based on measured frequency dynamics. First, define the co-frequency region according to the application requirements of frequency dynamic analysis and control. The quantitative co-frequency index of the measured frequency dynamics between buses is proposed with the correlation coefficient. Then, we propose a co-frequency region partition method based on spectral clustering algorithm. The method based on the constructed frequency dynamics similarity graph can effectively extract the information of measured data to realize an appreciate number of clusters for the power system without knowing the system models and parameters. The IEEE 118-bus test system is applied to verify the effectiveness of the proposed method. Finally, the application scenarios of the co-frequency region partition are further illustrated.

AB - To provide a theoretical foundation for dynamic equivalent analysis and partition control in frequency issues of modern power systems, we proposed a co-frequency region partition method based on measured frequency dynamics. First, define the co-frequency region according to the application requirements of frequency dynamic analysis and control. The quantitative co-frequency index of the measured frequency dynamics between buses is proposed with the correlation coefficient. Then, we propose a co-frequency region partition method based on spectral clustering algorithm. The method based on the constructed frequency dynamics similarity graph can effectively extract the information of measured data to realize an appreciate number of clusters for the power system without knowing the system models and parameters. The IEEE 118-bus test system is applied to verify the effectiveness of the proposed method. Finally, the application scenarios of the co-frequency region partition are further illustrated.

KW - frequency dynamic analysis

KW - region partition

KW - spectral clustering

KW - WAMS

UR - https://www.scopus.com/pages/publications/85178503233

U2 - 10.1109/CPESE59653.2023.10303112

DO - 10.1109/CPESE59653.2023.10303112

M3 - 会议稿件

AN - SCOPUS:85178503233

T3 - 2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023

SP - 14

EP - 19

BT - 2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th International Conference on Power and Energy Systems Engineering, CPESE 2023

Y2 - 8 September 2023 through 10 September 2023

ER -

Chen X, Wu P, Zhang X, Lu C, Song W. Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics. In 2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 14-19. (2023 10th International Conference on Power and Energy Systems Engineering, CPESE 2023). doi: 10.1109/CPESE59653.2023.10303112

Co-frequency Regional Power System Partition Method Based on Measured Frequency Dynamics

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Keywords

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