New ANN method for multi-terminal HVDC protection relaying

Qingqing Yang, Simon Le Blond, Raj Aggarwal, Yawei Wang, Jianwei Li*

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

135 引用 (Scopus)

摘要

This paper proposes a comprehensive novel multi-terminal HVDC protection scheme based on artificial neural network (ANN) and high frequency components detected from fault current signals only. The method is shown to accurately detect, classify and locate overhead line faults. Unlike existing travelling wave based methods which must capture the initial wavefront and require high sampling rates, the new approach is more robust since it gives accurate fault detection and fault location over a range of windowed post-fault signals. Furthermore, the proposed method is fault resistance independent meaning even a very high fault impedance has no effect on accurate fault location. A three-terminal VSC-HVDC system is modelled in PSCAD/EMTDC, which is used for obtaining the fault current data for transmission line terminals. The method is verified by studying different cases with a range of fault resistances in various fault locations, and in addition, external faults. The results show that the proposed method gives fast (<5 ms) and reliable (100%) fault detection and classification and accurate location (<1.16%) for DC line faults.

源语言英语
页(从-至)192-201
页数10
期刊Electric Power Systems Research
148
DOI
出版状态已出版 - 1 7月 2017
已对外发布

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