Commutation Failure Detection Based on Temporal Feature of AC Maximum Current on the Valve-Side

doi:10.12141/j.issn.1000-565X.210810

Abstract

Abstract:

Commutation failure (CF) is common for the operation of HVDC transmission system, and it reflects the vulnerability of converter. The existing methods for judging CF are subject to influence of fault factors and control adjustments, resulting in the insufficient sensitivity of the methods. Accurate and reliable detection of CF is extremely important to control and protection. Therefore, the paper proposed a detection scheme for CF based on temporal feature of AC maximum current on the valve-side starting from detecting the valve conduction interval. Firstly, the characteristics of AC maximum current was constructed based on the ratio between the unilaterally polarity current of AC current on the converter terminal and the half of the maximum value of the three-phase AC current. Secondly, to reduce the impact of operating conditions, taking the current intersection of two commutating valves currents as the demarcation point, the virtual conducting state of the valve was constructed by using half of the amplitude of the characteristic quantity of AC maximum current, and the accumulated width was calculated by integrating it in a period to determine whether the virtual conducting state of the valve is abnormal.Then, the interlocking relationship between the lengthened and shortened virtual conduction width was used to determine the commutation failure during the commutation process. According to the analysis of power disturbance, fault transiency and the sampling step, the threshold for commutation failure was derived. The recommended threshold value is 1.3 millisecond. Finally, based on the PSCAD / EMTDC electromagnetic transient simulation and wave recorded data, the results show that the proposed detection method is reliable to detect commutation failure. Compared with the detection method based on differential current, the proposed method for detecting commutation failure is less affected by factors, such as operating conditions of AC and DC system, fault moment, and fault severity under different fault conditions. This proposed method can locate the valve of commutation failure and provides more margin for the adjustment of the control system.

Key words: LCC-HVDC, commutation, valve-side current, valve conducting state, temporal feature

CLC Number:

TM772

LI Xiaohua, YIN Shanshan, LI Jiewen, et al. Commutation Failure Detection Based on Temporal Feature of AC Maximum Current on the Valve-Side[J]. Journal of South China University of Technology(Natural Science Edition), 2022, 50(7): 108-117.

Figures/Tables 14

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Table 1

Influence of fault types on the detection scheme of valve conducting state"

FT	$t c f ? / m s$	$m$	$t c s ? / m s$	$Z H m$	$Δ t Z 1 ? / m s$
单相（a相）接地故障（AG）	5.5	1	16.1	2	0.3
		2	16.0	0
		3	18.7	0
		4	5.8	2
		5	23.1	0
		6	5.8	0
两相（ab两相）接地故障（ABG）	2.2	1	9.2	0	0.3
		2	14.0	0
		3	2.5	2
		4	5.9	2
		5	2.5	0
		6	5.8	0
三相故障（ABC）	2.2	1	9.2	0	0.3
		2	18.0	2
		3	2.5	2
		4	5.9	2
		5	2.5	0
		6	5.8	0
相间（ab两相）故障（AB）	2.1	1	9.2	0	0.4
		2	12.8	0
		3	2.5	2
		4	5.9	2
		5	2.5	0
		6	5.8	0

Table 1

Table 2

Influence of DC power on two detection schemes"

P*（p.u.）	$t c f ? / m s$	$t c s 1 ? / m s$	$t c s 2 ? / m s$	$Δ t Z 1 ? / m s$	$Δ t Z 2 ? / m s$
1.0	5.5	5.8	12.1	0.3	6.6
0.8	5.4	5.8	10.3	0.4	4.9
0.5	5.0	5.4	10.7	0.4	5.7
0.3	4.7	5.0	12.1	0.3	7.4

Table 2

Table 3

Influence of fault resistance on two detection schemes"

$r F ? / Ω$	$t c f ? / m s$	$t c s 1 ? / m s$	$t c s 2 ? / m s$	$Δ t Z 1 ? / m s$	$Δ t Z 2 ? / m s$
0.5	5.5	5.8	12.1	0.3	6.6
1.0	5.5	5.8	12.1	0.3	6.6
3.0	5.7	5.8	11.5	0.1	5.8
5.0	7.3	7.6	11.6	0.3	4.3
8.0	8.4	8.6	11.6	0.2	3.1

Table 3

Table 4

Influence of initial fault angle on two detection schemes"

$A F / (°)$	$t c f ? / m s$	$t c s 1 ? / m s$	$t c s 2 ? / m s$	$Δ t Z 1 ? / m s$	$Δ t Z 2 ? / m s$
0	5.5	5.8	12.1	0.3	6.6
30	3.7	4.1	10.4	0.4	6.7
60	2.1	2.4	4.2	0.3	2.1
90	2.1	2.4	7.9	0.3	5.5
120	8.7	9.2	13.4	0.5	4.7
150	7.0	7.4	11.7	0.4	4.4
180	5.5	5.8	12.1	0.3	6.6

Table 4

Fig.9

Fig.10

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