Measurement-based solution for low frequency oscillation analysis

doi:10.1007/s40565-016-0200-0

Home > Archive>Volume 4, Issue 3, 2016 >406-413. DOI:10.1007/s40565-016-0200-0

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Measurement-based solution for low frequency oscillation analysis

DOI:

10.1007/s40565-016-0200-0

Author:

Chen SHEN
Chen SHEN
1.Department of Electrical Engineering, Tsinghua University, Beijing, China 2.State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments, Tsinghua University, Beijing, China
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Zhi AN
Zhi AN
1.Department of Electrical Engineering, Tsinghua University, Beijing, China 2.State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments, Tsinghua University, Beijing, China
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Xianzhong DAI
Xianzhong DAI
1.Department of Electrical Engineering, Tsinghua University, Beijing, China 2.State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments, Tsinghua University, Beijing, China
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Wei WEI
Wei WEI
1.Department of Electrical Engineering, Tsinghua University, Beijing, China 2.State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments, Tsinghua University, Beijing, China 3.Electric Power Research Institute of Sichuan Electric Power Company, Chengdu, China
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Lijie DING
Lijie DING
Electric Power Research Institute of Sichuan Electric Power Company, Chengdu, China
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Affiliation:

1. Department of Electrical Engineering, Tsinghua University, Beijing, China 2. State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments, Tsinghua University, Beijing, China 3. Electric Power Research Institute of Sichuan Electric Power Company, Chengdu, China

Fund Project:

National Natural Science Foundation of China (No. 51177079, No. 51321005) and Sichuan Electric Power Company

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Abstract:

This paper presents a measurement-based solution for low frequency oscillation (LFO) analysis in both real time monitoring and off-line case study. An online LFO property discrimination method is developed first, which alternately uses empirical mode decomposition (EMD)/Hilbert transform (HT) and square calculation to process the measurement data. The method magnifies the variation trend of oscillating variables to accurately discriminate the property of the oscillation. Subsequently, an oscillation source locating method for the forced oscillation (FO) and a strongly correlated generator identification method for the weak damping oscillation (WDO) are proposed. Finally, numerical study results on a test system of the isolated Changdu grid in Tibet validate the proposed methods.

Key words:Low frequency oscillation Oscillation property discrimination Oscillation source locationStrongly correlated generator identification

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Online: July 27,2016
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