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±800kV特高压直流输电线路雷击暂态识别 被引量:28

Transient Identification of Lightning Strokes on ±800 kV UHVDC Transmission Lines
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摘要 特高压直流输电线路受到雷击未故障时,极线上电压行波围绕直流分量上下交替变化,与轴线电压相关度趋近于1。此特征可作为识别雷击干扰的判据。雷击故障时,雷电波中有大量高频分量,绝缘闪络后,迅速衰减;接地故障时,短路电压行波由附加电源产生,高频分量少。雷击故障最终呈现接地故障特征,经小波变换后,中低频分量与接地故障相近,故雷击故障高频能量与中低频能量比值较接地故障时大。据此特征可用来识别雷击故障和接地短路故障。利用云广800 kV直流输电模型,采用5 ms时窗,进行了大量的EMTP暂态仿真,验证了该方法的有效性。 When thunderbolt directly strikes on UHVDC transmission line and does not lead to line fault, the voltage traveling wave on polar line alternately fluctuates around the DC component and the correlation degree between the voltage traveling-wave and the direct voltage line is close to 1. Such a feature can be used as the criterion to identify lightning disturbance. When lightning fault occurs, there are lots of high-frequency components in lightning wave, which attenuates quickly after the insulation is broke down; when earth fault occurs, the traveling wave of short-circuit voltage is caused by additional power supply, so there are few high-frequency components in it. The lightning stroke fault finally takes on the feature of earth fault, and after the wavelet transform the medium-and low-frequency components due to lightning stroke are similar to those of earth fault, thus the ratio of high-frequency components caused by lightning stroke to medium-and low-frequency components is larger than that of earth fault, accordingly such a feature can be used to distinguish lightning stroke fault from earth fault. Utilizing the model of ±800 kV UHVDC power transmission project from Yunnan to Guangdong and adopting the time window with the width of 5 ms, a lot of EMTP simulation are performed, and simulation results show that the proposed method is effective.
出处 《电网技术》 EI CSCD 北大核心 2013年第11期3007-3014,共8页 Power System Technology
基金 国家自然科学基金项目(50977039 50847043 90610024 50467002 50347026 51267009 U1202233) 云南省自然科学基金重点项目(2005F0005Z 2008ZC016M 2010Z20)和科技攻关项目(2003GG10)~~
关键词 特高压直流输电 雷击干扰 相关度 小波变换 能量 UHVDC power transmission lightning disturbance correlation degree wavelet transform energy
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