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Area inertia estimation of power system containing wind power considering dispersion of frequency response based on measured area frequency

Area inertia estimation of power system containing wind power considering dispersion of frequency... With the rapid increase of the penetration rate of renewable energy sources in power system, the decrease of system inertia will threaten the frequency stability, and the dispersion of frequency response cannot be ignored. This paper proposes a method to estimate area inertia of power system containing wind power considering dispersion of frequency response. Firstly, the impact of inertia distribution between areas on the frequency stability and the inter‐area oscillation are analysed. Secondly, the system is divided based on the spectral clustering algorithm and the frequency similarity index is defined according to the Pearson correlation coefficient to determine the measurement locations for area frequency. Thirdly, the measured tie‐line power and frequency deviation are used to estimate the area inertia based on the numerical integration method. Finally, the case study is conducted based on the modified IEEE 39‐bus system. The simulation results revealed that the proposed method is accurate and reliable in different scenarios. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png "IET Generation, Transmission & Distribution" Wiley

Area inertia estimation of power system containing wind power considering dispersion of frequency response based on measured area frequency

Area inertia estimation of power system containing wind power considering dispersion of frequency response based on measured area frequency

"IET Generation, Transmission & Distribution" , Volume 16 (22) – Nov 1, 2022

Abstract

With the rapid increase of the penetration rate of renewable energy sources in power system, the decrease of system inertia will threaten the frequency stability, and the dispersion of frequency response cannot be ignored. This paper proposes a method to estimate area inertia of power system containing wind power considering dispersion of frequency response. Firstly, the impact of inertia distribution between areas on the frequency stability and the inter‐area oscillation are analysed. Secondly, the system is divided based on the spectral clustering algorithm and the frequency similarity index is defined according to the Pearson correlation coefficient to determine the measurement locations for area frequency. Thirdly, the measured tie‐line power and frequency deviation are used to estimate the area inertia based on the numerical integration method. Finally, the case study is conducted based on the modified IEEE 39‐bus system. The simulation results revealed that the proposed method is accurate and reliable in different scenarios.

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Publisher
Wiley
Copyright
© 2022 The Institution of Engineering and Technology.
eISSN
1751-8695
DOI
10.1049/gtd2.12628
Publisher site
See Article on Publisher Site

Abstract

With the rapid increase of the penetration rate of renewable energy sources in power system, the decrease of system inertia will threaten the frequency stability, and the dispersion of frequency response cannot be ignored. This paper proposes a method to estimate area inertia of power system containing wind power considering dispersion of frequency response. Firstly, the impact of inertia distribution between areas on the frequency stability and the inter‐area oscillation are analysed. Secondly, the system is divided based on the spectral clustering algorithm and the frequency similarity index is defined according to the Pearson correlation coefficient to determine the measurement locations for area frequency. Thirdly, the measured tie‐line power and frequency deviation are used to estimate the area inertia based on the numerical integration method. Finally, the case study is conducted based on the modified IEEE 39‐bus system. The simulation results revealed that the proposed method is accurate and reliable in different scenarios.

Journal

"IET Generation, Transmission & Distribution"Wiley

Published: Nov 1, 2022

References