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| Analysis of Influencing Factors on Damping Characteristics of Subsynchronous Oscillation Based on Singular Value Decomposition-Prony and Principal Component Regression |
| Zhang Qian1, Bian Xiaoyan1, Xu Xinyu2, Huang Ruanming3, Li Hanen3 |
1.Shanghai University of Electric Power Shanghai 200090 China;
2. State Grid Shanghai Pudong Electric Power Supply Company Shanghai 200120 China;
3. State Grid Shanghai Electric Power Economic & Technological Institute Shanghai 200223 China |
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Abstract Accurate and effective identification of damping characteristics and its influencing factors of subsynchronous oscillation (SSO) in wind power grid connected system is the premise and key to solve the problem of SSO in actual wind power grid-connected system engineering. To avoid the complex modeling of traditional SSO analysis method, this paper proposes a method to analyze the influencing factors of SSO damping characteristics based on wind farm parameters and operation data. Firstly, singular value decomposition (SVD) based on singular value growth rate spectrum is applied to improve noise resistance performance of Prony and modal information is extracted from oscillation data. Secondly, the influencing factors of oscillation are selected and the correlation and collinearity diagnosis are carried out. Then, principal component regression (PCR) is adopted to reduce the collinearity in the regression analysis, the damping ratio estimation model is established to identify the dominant factors affecting the subsynchronous stability of the wind farm. Finally, the effectiveness and accuracy of the proposed method are verified by power system with DFIG integrated through VSC-HVDC.
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Received: 17 July 2021
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2022, Vol. 37 
