基于离散小波分析与K-means聚类算法的 MMC-HVDC输电线路保护方案

尚学军; 霍现旭; 郑晓冬; 贺杨烊

尚学军,霍现旭,郑晓冬,贺杨烊.基于离散小波分析与K-means聚类算法的 MMC-HVDC输电线路保护方案[J].电测与仪表,2020,57(24):52-57.
Shang Xuejun,Huo Xianxu,Zheng Xiaodong,He Yangyang.MMC-HVDC Transmission Line Protection Scheme Based on discrete wavelet analysis and K-means clustering algorithm[J].Electrical Measurement & Instrumentation,2020,57(24):52-57.

基于离散小波分析与K-means聚类算法的 MMC-HVDC输电线路保护方案

MMC-HVDC Transmission Line Protection Scheme Based on discrete wavelet analysis and K-means clustering algorithm

DOI：10.19753/j.issn1001-1390.2020.24.007

中文关键词: 离散小波分析聚类算法质心阈值 MMC-HVDC 输电线路

英文关键词:Discrete wavelet analysis clustering algorithm centroid threshold modular multilevel converter high voltage direct current transmission line

基金项目:

作者中文名	作者英文名	单位
尚学军	Shang Xuejun	国网天津市电力公司电力科学研究院
霍现旭	Huo Xianxu	国网天津市电力公司电力科学研究院
郑晓冬	Zheng Xiaodong	上海交通大学
贺杨烊	He Yangyang	上海交通大学

摘要点击次数: 1583

中文摘要:

随着以风电、光伏为代表的可再生能源的持续发展，柔性直流输电系统由于能够清洁高效的对其进行远距离大容量输送而得到了大力的发展。快速、准确的识别故障区域并判别故障类型，实现兼具选择性、速动性、灵敏性和可靠性的直流线路保护方案是柔性直流输电系统发展的迫切需要。理论分析表明，MMC-HVDC输电系统直流线路故障时，线路平波电抗器两侧的暂态电压存在明显差异。采用离散小波分析提取线路平波电抗器两侧的暂态电压有效值进行比较，从而对区内、区外故障进行判别。随后采用K-means聚类算法，利用不同故障类型、不同故障位置，直流线路故障发生后较短的时间窗口采集得到的单侧保护单元电压、电流数据，对其进行聚类分析，获取这些数据的质心与阈值，经过训练，确定相应的保护判据，实现故障选极。PSCAD/EMTDC的仿真结果表明，该保护方案不受故障位置、过渡电阻的影响，能够快速准确地检测MMC-HVDC输电线路故障，识别出故障类型。

英文摘要:

With the continuous development of renewable energy represented by wind power and photovoltaic, flexible DC transmission systems have been vigorously developed in recent years due to the ability of clean and efficiently transport of long-distance and large-capacity renewable energy. Fast and accurate identification of fault areas and determination of fault types, achieving DC line protection schemes with selectivity, quickness, sensitivity and reliability are urgent needs for the development of flexible DC (direct current) transmission systems. Theoretical analysis shows that there are significant differences in transient voltage across the line smoothing reactor when the DC line of the MMC-HVDC transmission system fault happens. Discrete wavelet analysis is used to extract the RMS values of the transient voltages on both sides of the line smoothing reactor for comparison, so as to distinguish the faults in and outside the protection area. Then the K-means clustering algorithm is used, the voltage and current data of single-ended protection unit collected in a short time window after DC line faults occur are collected from different fault types, different fault locations. And clustering analysis is carried out to obtain the centroid and threshold of these data. After the process of data training, the corresponding protection criteria are determined to realize the identification of the fault poles. And the simulation results of PSCAD/EMTDC show that the protection scheme is not affected by the fault location and transition resistance, and can quickly and accurately detect the faults of the MMC-HVDC transmission lines and identify fault type.

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