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一种适用于双馈风电场群的短路电流计算与故障分析新方法。

A New Short-Circuit Current Calculation and Fault Analysis Method Suitable for Doubly Fed Wind Farm Groups.

作者信息

Yin Jun, Qian Weichen, Huang Xiaobo

机构信息

School of Electrical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China.

出版信息

Sensors (Basel). 2023 Oct 10;23(20):8372. doi: 10.3390/s23208372.

DOI:10.3390/s23208372
PMID:37896465
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10610826/
Abstract

The transient characteristics of wind farms in groups are quite different; in addition, there is a strong coupling between the wind farms and the grid, and these factors make the fault analysis of the grid with wind farm groups complicated. In order to solve this problem, a mathematical model of the converter is established based on the input-output external characteristics of the converter, and a transient model of a doubly fed wind turbine (DFIG) is presented considering the influence of the low-voltage ride-through control (LVRT) of the converter, and the effect mechanism of the LVRT strategy on the short-circuit current is analyzed. Finally, a short-circuit current calculation model of a doubly fed wind turbine with low-voltage crossing control is established. The interaction mechanism between wind farms during the fault is analyzed, and a short-circuit current calculation method of doubly fed wind farm groups is proposed. RTDS is used to verify the accuracy of the proposed short-circuit current calculation method for doubly fed field groups. On this basis, a method of power grid fault analysis after doubly fed field group access is discussed and analyzed.

摘要

风电场群的暂态特性差异较大;此外,风电场与电网之间存在较强的耦合,这些因素使得含风电场群的电网故障分析变得复杂。为解决这一问题,基于变流器的输入输出外特性建立了变流器的数学模型,提出了考虑变流器低电压穿越控制(LVRT)影响的双馈风力发电机(DFIG)暂态模型,并分析了LVRT策略对短路电流的作用机理。最后,建立了具有低电压穿越控制的双馈风力发电机短路电流计算模型。分析了故障期间风电场群之间的相互作用机理,提出了双馈风电场群短路电流计算方法。利用RTDS验证了所提出的双馈风电场群短路电流计算方法的准确性。在此基础上,对双馈风电场群接入后电网故障分析方法进行了探讨和分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/d85c805c07e1/sensors-23-08372-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/b004747266d8/sensors-23-08372-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/93b1bb1fc10d/sensors-23-08372-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/76f8b0865d18/sensors-23-08372-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/4dda735f4056/sensors-23-08372-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/d85c805c07e1/sensors-23-08372-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/b004747266d8/sensors-23-08372-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/05aa9f4583dc/sensors-23-08372-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/3567047db051/sensors-23-08372-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/8db63795a61f/sensors-23-08372-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/93b1bb1fc10d/sensors-23-08372-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/76f8b0865d18/sensors-23-08372-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/4dda735f4056/sensors-23-08372-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0d6/10610826/d85c805c07e1/sensors-23-08372-g010.jpg

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