TY - JOUR
T1 - New ANN method for multi-terminal HVDC protection relaying
AU - Yang, Qingqing
AU - Le Blond, Simon
AU - Aggarwal, Raj
AU - Wang, Yawei
AU - Li, Jianwei
PY - 2017/7/1
Y1 - 2017/7/1
N2 - 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.
AB - 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.
KW - Artificial neural network
KW - Fault current signal
KW - Fault detection
KW - Fault location
KW - Transmission line
KW - VSC-HVDC system
UR - http://www.scopus.com/inward/record.url?scp=85017103892&partnerID=8YFLogxK
UR - https://doi.org/10.1016/j.epsr.2017.03.024
U2 - 10.1016/j.epsr.2017.03.024
DO - 10.1016/j.epsr.2017.03.024
M3 - Article
AN - SCOPUS:85017103892
SN - 0378-7796
VL - 148
SP - 192
EP - 201
JO - Electric Power Systems Research
JF - Electric Power Systems Research
ER -