An Innovative Arc Fault Model and Detection Method for Circuit Breakers in LCC-HVDC AC Filter Banks
被引:7
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作者:
Wang, Bin
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机构:
Tsinghua Univ, Dept Elect Engn, State Key Lab Control & Simulat Power Syst & Gener, Beijing 100084, Peoples R ChinaTsinghua Univ, Dept Elect Engn, State Key Lab Control & Simulat Power Syst & Gener, Beijing 100084, Peoples R China
Wang, Bin
[1
]
Wei, Xiangxiang
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机构:
Tech Univ Berlin, Fac Elect Engn & Comp Sci, D-10623 Berlin, GermanyTsinghua Univ, Dept Elect Engn, State Key Lab Control & Simulat Power Syst & Gener, Beijing 100084, Peoples R China
Wei, Xiangxiang
[2
]
Xia, Yu
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Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R ChinaTsinghua Univ, Dept Elect Engn, State Key Lab Control & Simulat Power Syst & Gener, Beijing 100084, Peoples R China
Xia, Yu
[3
]
机构:
[1] Tsinghua Univ, Dept Elect Engn, State Key Lab Control & Simulat Power Syst & Gener, Beijing 100084, Peoples R China
To maintain reactive power balance, Circuit Breakers (CBs) in AC filter branches of Line Commutated Converter-High Voltage Direct Current (LCC-HVDC) substation need to be switched on and off several times in a day and can easily cause CBs restrike arcs. The restrike arcs lead to insulation breakdown of the arc extinguishing chamber in the CBs and even the explosion of the CBs. Therefore, it is crucial to detect restrike arcs of the CBs in a timely manner. However, due to the intermittent nature and weak fault features of the arc fault events, existing monitoring or protection schemes cannot accomplish this goal. To solve this issue, this article proposes an accurate arc fault model and a novel CBs arc fault detection method based on current variation characteristics. Firstly, an improved arc model is developed to accurately simulate the fast transients of arc current. Then, two fault indexes are derived to construct the detection criterion, one is the average deviation degree, and the other one is the ratio of first and second breakdown currents for the adjacent arc events. Both simulation results and field test results prove the accuracy and reliability of the proposed arc fault detection method.