Early Warning Analysis of Grid Ferromagnetic Resonance Overvoltage Risk Based on Multi-source Data

Authors

  • Gou Yu College of Electrical Engineering & New Energy at China Three Gorges University, Yichang Hubei 443002, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.3863

Keywords:

Distribution network, ferromagnetic resonance overvoltage, multi-source data, risk warning

Abstract

In the impartial factor ungrounded system, ferromagnetic resonance overvoltage is a frequent fault that lasts for a lengthy time and is hazardous to the grid. In this paper, the mechanism of grid ferromagnetic resonance overvoltage is first explored in depth. The precept of impartial voltage shift and ferromagnetic resonance brought about through PT saturation is analyzed with the aid of graphical and mathematical analysis. Then, the characteristics of fault current information are extracted by wavelet transform, and indicators such as wavelet fault degree, wavelet singularity and wavelet energy measurement are obtained respectively. D-S evidence theory is used to fuse multi-source information of electrical volume and switching quantity, so as to obtain comprehensive fault results of power grid more accurately. Finally, based on the time series risk assessment, the distribution network time series risk index is calculated, the risk level and risk area of each period are determined, and the early warning results are issued. Finally, an example is given to verify the effectiveness of the proposed method.

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Author Biography

Gou Yu, College of Electrical Engineering & New Energy at China Three Gorges University, Yichang Hubei 443002, China

Gou Yu graduated from the College of Electrical Engineering & New Energy at China Three Gorges University, majoring in intelligent electrical information engineering. She has received the Special Scholarship from China Three Gorges University and the Yangtze River Power Scholarship. She won the first prize in the 2022 Hubei iCAN International Innovation China Qualification Competition. Silver Award in the Hubei Province “Challenge Cup Entrepreneurship Competition”. Her team won first prize in the 9th National Securities Investment Simulation Training Competition. The main research direction is power system optimization.

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Published

2023-08-29

How to Cite

Yu, G. . (2023). Early Warning Analysis of Grid Ferromagnetic Resonance Overvoltage Risk Based on Multi-source Data. Distributed Generation &Amp; Alternative Energy Journal, 38(06), 1763–1790. https://doi.org/10.13052/dgaej2156-3306.3863

Issue

Section

Renewable Power & Energy Systems