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three-phase reclosing scheme for transmission lines in passive network supplied by MMC-HVDC
Electrical Power and Energy Systems 113 (2019) 597–606
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Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes
Adaptive single-phase/three-phase reclosing scheme for transmission lines in passive network supplied by MMC-HVDC
T
⁎
Ting Wanga, , Kazmi Sayed Tassawar Hussaina, Guobing Songa, Wei Hanb, Chao Liub a b
School of Electrical Engineering, Xi’an Jiaotong University, 710049 Xi’an, People’s Republic of China State Grid Henan Electric Power Research Institute, 450052 Zhengzhou, People’s Republic of China
A R T I C LE I N FO
A B S T R A C T
Keywords: AC fault Active injection Fault identification Modular multilevel converter (MMC) Passive network
Modular multilevel converter (MMC) shows prominent advantages on supplying passive networks, which are usually classified by power supply shortage and relatively weak structure. In order to reduce the unnecessary outage time and improve the system stability, an adaptive ac auto-reclosing scheme for passive networks is proposed based on characteristic signal injection. Additional MMC controller is designed to inject the characteristic signals into the healthy line, which in turn induces corresponding signals to the faulty line. Then fault properties are assessed by the travelling wave based fault location method. Finally, an adaptive auto-reclosing scheme is proposed to shorten the reclosing time and avoid the second fault shock to a large extent. The proposed scheme could be applied for both single-circuit and multi-circuit transmission lines. The simulation results obtained from PSCAD/EMTDC verify the effectiveness of the proposed method.
1. Introduction Compared with the line commutated converter (LCC)-high voltage dc (HVDC) transmission, voltage source converter based HVDC (VSCHVDC) is advantageous to supplying power to weak ac systems or even passive networks [1]. The Troll-A project in Norway is the first commercial project in the world to apply VSC-HVDC to power offshore drilling platforms [2]. VSC-HVDC also has wide application in connecting decentralized small power plants (such as wind power generation, solar power generation, etc.) to power grids. Especially in China, numerous wind farms in the west area/offshore wind farms are located far away from load center in the east area, which can better be integrated with main power network through VSC-HVDC [3,4]. The two terminal ± 320 kV VSC-HVDC project has been constructed to supply the Xiamen Island and four-terminal ± 500 kV HVDC grid project to interconnect large scale onshore windfarms in Zhangbei area [5–7]. An ac system can be regarded as a weak system based on two aspects, either high ac system impedance or weak inertia. A typical example of high impedance ac system is the termination of HVDC link at a weak point of large ac system with low short circuit capacity [8]. Lowinertia systems are usually equipped with limited number of rotating machines, or no rotating machine at all. Typical applications of lowinertia systems are island system and windfarm [9]. Converters are
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required to switch from the grid connected mode to the islanded mode under special conditions like tripping of critical ac lines or black start situation. Therefore, passive network can appear which may require certain converters to supply electrical energy independently. Majority of power system failures are transmission line failures. The higher the voltage level, greater the probability of single line-to-ground (SLG) fault [10,11]. Due to the weak structure and lack of power supply, the reliability and stability of passive network is poor and not suitable for its future demand. Therefore, it is critical to improve its reliability and stability, and reduce unnecessary power interruption time. Automatic reclosing is widely applied in the engineering practice [12]. Adaptive auto-reclosing operation, which identifies fault properties before reclosing plays an important role in improving power supply reliability and stability. Single phase/three phase adaptive auto-reclosing (SPAR/TPAR) has attracted wide attention of academia. The current researches mainly focus on SPAR, which is based on recovery voltage, arc characteristics, and the current of shunt reactor. The recovery voltage stage appears from the arc extinction to the reclose operation. The earliest recovery voltage amplitude criterion is proposed in [13]. More methods based on recovery voltage are developed in [11,14] using the phase, beat frequency, fault location, and model recognition etc. Ref. [15] identifies the fault properties by comparing the actual voltage with the theoretical value of instantaneous fault voltage at fault point. The voltage of faulty phase can
Corresponding author. E-mail address: [email protected] (T. Wang).
https://doi.org/10.1016/j.ijepes.2019.06.014 Received 8 November 2018; Received in revised form 28 April 2019; Accepted 6 June 2019 Available online 11 June 2019 0142-0615/ © 2019 Elsevier Ltd. All rights reserved.
Electrical Power and Energy Systems 113 (2019) 597–606
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be deduced from the voltage phasors at both ends of the healthy phases [16]. This method is only suitable for uniformly transposed lines and relies on the communication. Improper transposition due to geographical conditions results in different recovery voltages at different faulty phases. Moreover, in order to reduce the Ferranti Effect, shunt reactors are often installed on high-voltage transmission lines. The recovery voltage in that scenario shows a beat frequency that is close to power frequency [17], which limits the application of SPAR based on recovery voltage amplitude and phase. Therefore, fast reclose based on recovery voltage is difficult to realize. Odd harmonics of arc are higher in the case of temporary SLG faults, whereas arc extinguishes quickly in the case of permanent SLG faults. Therefore, scholars have carried out many researches based on the harmonic characteristics of the arc [18,19], fault current pattern recognition [20] and so on. However, arc is a complicated physical and chemical phenomenon. The strong randomness and instability of secondary arc make such kinds of methods prone to failures. Ref. [21] uses the difference between the actual current and the theoretical current to identify fault properties in the case of shunt reactor installed on the either end of transmission line. The absence of shunt reactor causes quick decrease in electromagnetic energy of the line, which limits the application of methods based on shunt reactor current. Further, since electric quantities are so weak to measure after three phase tripping, satisfying methods are not available for TPAR in the single circuit line configuration. Above-mentioned researches are all based on passive detection methods, which are highly model dependent. The modular multilevel converter (MMC) supplying passive network provides a new way for adaptive auto-reclosing operation due to its fast and flexible control ability. An active detection based adaptive auto-reclosing scheme is proposed in this paper. MMC is used to inject characteristic signals into the healthy line. Mutual coupling exists among transmission lines and therefore the corresponding characteristic electric quantities are induced on the faulty line. The proposed method is suitable for SPAR and TPAR in the case of multi-circuit transmission lines, and also applicable to SPAR in the single-circuit system. Section 2 summarizes the general principles of proposed fault identification scheme, which are line coupling and travelling wave based fault location. MMC controller design to achieve characteristic signal injection is proposed in Section 3. Then adaptive auto-reclosing scheme is put forward in Section 4. Finally, simulation results of temporary faults, permanent faults and fast reclose operation are given in Section 5 to verify the effectiveness of the proposed method.
⎧− ⎪ − ⎨ ⎪− ⎩
∂ua dx ∂x ∂ub dx ∂x ∂uc dx ∂x
∂i
∂i
∂i
∂i
∂i
= L0 dx ∂ta + L m dx ∂tb + L m dx ∂tc ∂i
= L m dx ∂ta + L0 dx ∂tb + L m dx ∂tc ∂i
∂i
∂i
= L m dx ∂ta + L m dx ∂tb + L0 dx ∂tc
(1)
It can be seen from (1) that the voltage and current perturbations on one phase, i.e., SLG faults, will induce corresponding electrical quantities to other phases. MMC could realize independent voltage control of each phase by adjusting upper and lower arm voltages, which is equivalent to a controlled voltage source for the ac system. MMC is utilized to inject characteristic signals to healthy phases. Corresponding electric quantities will be induced in the faulty phase/line, which contain the fault information. Whether the response of the faulty phase/line meets the fault criteria is then checked. The proposed fault identification method by using characteristic signal injection is shown in the right part of Fig. 1. Fig. 1(b) and (c) are respectively the single-circuit configuration and multi-loop configuration, which are two research scenarios of this paper. tf is the injection time, which is known for protection installation. tb is the arrival time of the first reflected wave and ld is the fault distance. The proposed method is also applicable to SPAR in the multiloop scenario, which is not explained to avoid repetition. 2.2. Traveling wave based fault location method The injected characteristic signal is chosen to be voltage pulse signal. Voltage traveling waves propagate nearly at the speed of light on overhead lines (OHLs) and reflect back from fault locations or line boundaries. Therefore, the traveling wave (TW) based fault location method is utilized. Since the injection time (tf) of first forward traveling signal is known, accurate calibration and identification of the first reflected wave is essential to obtain the fault distance. Δts = tb − tf is defined as the time interval of surge reflection and L is the line length. Presence of fault satisfies the fault criteria (2).
ld =
v v Δts = (tb − t f ) ⩽ L 2 2
(2)
Fault location based on pulse detection has a dead zone (several kilometers) in the first and the last segment of the line. No matter how higher is the sampling frequency, complete elimination of dead zone is not possible. Such problem can be resolved by considering the waveform correlation method [22] and the terminal load matching method. Furthermore, the high voltage transmission lines are capable to transmit power to longer distance. Therefore, HVDC systems usually have longer transmission lines (hundreds of kilometers). Shorter lines (several kilometers) are common in the distribution system with lower voltage level and lower sampling rate. Current methodology is proposed for high voltage transmission lines. At the same time, the transient TW contains full band components. The higher the frequency of TW component, faster the propagation speed. TW velocity can be calculated by using the line structural parameters, or can be measured practically [23]. The most reliable approach is to estimate these values from the measurements obtained for the known fault locations, which is adopted in this paper. The maximum deviation of the sampling of relay protection can reach a sampling interval Ts, due to the random sampling time in theory. Moreover, the maximum sampling error caused is obtained as ΔL = v Ts/2 = v /2fs where fs is the sampling frequency. ΔL represents the half distance travelled by the surge during one sampling interval.
2. Fault identification principles Automatic reclosing, especially compromise poles anto-reclosure, is almost used for all types of faults in EHV/UHV systems [12]. The proposed method is mainly based on the line coupling and the control ability of MMC. It could realize fault identification even when the electric quantities of arc disappear.
2.1. The coupling characteristic of transmission line Three phase homogeneous transmission line model is shown in Fig. 1(a). The ac voltages and currents on the left side of dx are uφ and iφ (φ = a, b, c) respectively. dx is the length segment. In addition, ac ∂uφ voltages and currents on the right side of dx are uφ + ∂x dx and
3. Characteristic signal injection
∂i φ
iφ + ∂x dx . The inductance and capacitance of segment dx are L0dx and C0dx respectively. The coupling inductance and capacitance of segment dx among power lines are Lmdx and Cmdx respectively. According to Kirchhoff's Voltage Law (KVL), it could be obtained
Characteristic signal injection method is suitable for ac lines connected to the point of common coupling (PCC). Additional control strategy is proposed to inject characteristic signals upon the fault detection. Duration and amplitude are the two major indices to select the 598
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Fig. 1. The principle of fault identification. (a) Three phase homogeneous transmission line model. (b) Three phase configuration for single circuit transmission. (c) Multi-loop configuration.
Fig. 4. The voltage of faulty phase after an injection.
Fig. 2. MMC-HVDC transmission system topology supplying a passive network.
Fig. 5. Reclosure sequence of temporary faults: (a) Auto-reclosing sequence. (b) Adaptive auto-reclosing sequence.
3.1. Control of MMC supplying to passive network The MMC-HVDC system supplying the passive network is shown in Fig. 2. MMC1 and MMC2 are sending end and receiving end, respectively. The half bridge based MMC (HB-MMC) consists of six bridge arms. Each arm contains hundreds of sub modules (SMs) and a reactor Larm. Every SM contains a capacitor (C0), two IGBTs, and two antiparallel diodes. The capacitor voltage of SM is uc (> 0). usφ and isφ are respectively the ac voltages and currents at PCC. icφ are the ac currents at the converter side. idc is the dc current and udc is the dc voltage. Since the receiving end system is a passive network, MMC2 is responsible for ac frequency and voltage regulation. Thus the coordinated
Fig. 3. Additional control strategy of receiving-end MMC.
injected signals. Specific relay, with travelling wave based fault location, may be required to achieve adaptive auto-reclose operation. Coordination between MMC and relay is also important. In addition, most high voltage lines are equipped with travelling wave protection schemes. Therefore, existing hardware can be utilized with necessary software amendments. 599
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Start
N Fault tripping
Y N
Single-phase tripping? Y Delay 0.3 s
Delay 1.8 s
Injection Y Fault ˛ N Injection
Y
Fault ? N Reclose
N
n>nset ? Y Single-phase tripping?
N
Y Three-phase tripping
Calculating the fault distance
End Fig. 7. Adaptive auto-reclosing scheme. Table 1 Parameters of MMC-HVDC system.
Fig. 6. The fault component and its wavelet transform modulus maxima: (a) A SLG fault with fault impedance 0.01 Ω at the distance of 90 km. (b) A symmetrical fault with fault impedance 50 Ω at the distance of 90 km.
control strategy of MMC-HVDC system is adopted as follows. DC voltage and reactive power control are activated at MMC1, while MMC2 controls ac voltage and frequency. The synchronization phase at PCC cannot be obtained by the phase-locked loop (PLL) when the receiving end network is a passive network. Ideal three phase voltage source is usually introduced as the phase reference for MMC2 controller [24]. In this absolutely stable synchronous reference frame, the ac frequency of MMC2 is limited to be the rated frequency. The normal control strategy of MMC2 is shown in Fig. 3. usd and usq are dq components of ac voltages at PCC. icd and icq are dq components of ac currents at the converter side. usdref and usqref are d-axis and q-axis voltage references, respectively. ω is the angular frequency and θ0 is the ideal synchronous angle. Lc = Ltrans + Larm/2 is equivalent reactance of converter where Ltrans is the transformer reactance. Controller outputs the modulation indices md and mq in dq frame, which are converted to three phase modulation indices mφ after Park transformation. In normal operation, the amplitude of modulation index (m) is maintained at rated value mN. In the case of sudden increase/decrease in m, the ac voltage at converter side will show a surge/sudden drop. The ac bus voltages (usφ) will also have corresponding symmetrical three phase amplitude increase/drop change. The corresponding voltage surge will be coupled with the faulty phase/line from the healthy
Parameters
Values
Rated capacity of MMC AC system voltage Rated voltage of transformer Winding type of transformer Short circuit impedance of transformer (p.u) Number of SMs on per arm Larm SM capacitor SM switching period DC line length AC line length
400 MVA 145 kV 220 kV/145 kV D/Yn 18% 250 116 mH 5 mF 100 μs 200 km 150 km
line, therefore the injection is realized. Thus an additional controller action is suggested as shown red in Fig. 3. When the injection is activated (Injecting signal = 1), the variable m is switched to the constant value m′. The feedback control is temporarily cut off to achieve openloop control. The larger the change of modulation index Δm (=m-m′), more the drop in the amplitude of usφ, and more obvious the characteristic of faulty phase/line voltage. After the removal of proposed controller action, the voltage drop is fed back to the outer loop of MMC2 controller. Modulation index is adjusted to meet the voltage reference. The controller modulates rapidly and the whole recovery process is achieved within several milliseconds. MMC is advantageous to output low modulation ratio, which enables low ac output voltage under certain dc rated voltage. The voltage drop on Larm is usually low which is neglected in this paper. According the KVL, upper and lower arm voltage of phase a could be obtained 600
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Fig. 10. The fault components under different fault impedances with fault distance of 75 km and pre-fault active power of 50 MW.
Fig. 11. The fault components under different pre-fault active power with fault distance of 30 km and fault impedance of 0.01 Ω.
Fig. 8. MMC-HVDC system supplying a passive network: (a) Single circuit configuration. (b) Multi-circuit configuration. (c) Frequency-dependent overhead line model.
⎧ u pa = 0.5udc − ua = 0.5udcN − ua ⎨ ⎩u na = 0.5udc + ua = 0.5udcN + ua
Table 2 Calibration of the traveling wave speed (fc = 1 MHz).
1 2 3 4 5 6
Δ ts (ms)
v (km/ms)
1.001 0.999 1.001 1.000 1.000 1.001
299.700 300.300 299.700 300.000 300.000 299.700
(3)
where udcN is rated dc voltage. During the injection, the output reference modulation wave is nearly zero considering the largest change of modulation index Δm = mN. But the output voltages of upper/lower SMs are approximately equal to udcN/2 [25,26], according to (3), though some perturbations of udc may occur. The dc voltage could be maintained within high level. The lower-level controls of MMC include capacitor voltage balancing [27], circulating current suppression [28] and valve triggering control [29], which have been investigated in many literatures and are not explained to avoid repetition. 3.2. Characteristic signal selection principle Since the proposed scheme is based on pulse detection, its duration (Δt) is very important. In order to avoid influence on transmitted power and sensitive load, Δt should be as short as possible subjected to following two limitations. (1) In order to reliably identify the first reflected surge, subsequent injections should be avoided before the arrival of first reflected TW. The shortest duration Δtmin should be two times the minimum travel time of the TW when the ac line is healthy. Passive network has remote geographical location from main network, with line length ranges from 50 km to 200 km and economically rated voltage ranges from 110 kV to 220 kV [30]. (2) Δt is supposed to be within the detection equipment range. The common sampling frequency of protection devices is 10–50 kHz [31]. Δt should also be much greater than the SM switching period, which is usually 100 μs [32]. The length of ac transmission line in a passive network is usually not too long and Δt = 5 ms is adopted in this paper. The overcurrent capacity of electronics and the voltage requirement of sensitive loads should be taken into account while choosing the amplitude change of modulation index Δm. (1) Larger the Δm, higher the amplitude of injected signal, smaller the impact of dispersion and sampling on the wavefront detection. In addition, the influence of fluctuation, caused by the switching of the SMs, on the singularity detection is weakened. (2) To avoid the large power fluctuation and overcurrent of electronics, Δm should be limited. The inner current loop often sets the limiter. When mN − Δm < 0, the amplitude of modulation index is limited to zero (m − Δm = 0). Therefore Δm < 1.0mN is
Fig. 9. The voltage of faulty phase under temporary faults and its magnified waveform: (a) Voltage on the faulty phase. (b) Magnified fault component. (c) The WTMM result of fault component.
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Fig. 12. The fault components and their WTMM results: (a) 50 MW, 90 km, 100 Ω. (b) 75 MW, 60 km, 10 Ω. (c) 150 MW, 75 km, 50 Ω. Table 3 The fault identification results (P = 50 MW).
Table 4 The fault identification results (P = 75 MW).
ld/km
Rfault/Ω
f1/km
error%
f3/km
error %
ld/km
Rfault/Ω
f1/km
error%
f3/km
error %
20
0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 50.983 50.983 50.983 50.983 59.980 59.980 59.980 62.979 74.975 77.974 77.974 77.974 89.970 92.969 92.969 92.969 98.967 98.967 101.966 101.966 119.960 122.959 122.959 122.959 140.953 143.952 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 1.97 1.97 1.97 1.97 0.03 0.03 0.03 4.97 0.03 3.97 3.97 3.97 0.03 3.30 3.30 3.30 1.03 1.03 1.97 1.97 0.03 2.47 2.47 2.47 0.68 2.82 2.82 2.82
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 50.983 50.983 50.983 50.983 59.980 59.980 59.980 62.979 74.975 74.975 74.975 77.974 89.970 89.970 92.969 92.969 98.967 98.967 101.966 101.966 119.960 119.960 122.959 122.959 140.953 143.952 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 1.97 1.97 1.97 1.97 0.03 0.03 0.03 4.97 0.03 0.03 0.03 3.97 0.03 0.03 3.30 3.30 1.03 1.03 1.97 1.97 0.03 0.03 2.47 2.47 0.68 2.82 2.82 2.82
20
0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 47.984 50.983 50.983 50.983 59.980 59.980 59.980 62.979 74.975 74.975 77.974 77.974 89.970 92.969 92.969 92.969 98.967 98.967 101.966 101.966 119.960 122.959 122.959 122.959 140.953 143.952 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 4.03 1.97 1.97 1.97 0.03 0.03 0.03 4.97 0.03 0.03 3.97 3.97 0.03 3.30 3.30 3.30 1.03 1.03 1.97 1.97 0.03 2.47 2.47 2.47 0.68 2.82 2.82 2.82
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 47.984 50.983 50.983 50.983 59.980 59.980 59.980 59.980 74.975 74.975 77.974 77.974 89.970 89.970 92.969 92.969 98.967 98.967 98.967 101.966 119.960 119.960 122.959 122.959 140.953 140.953 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 4.03 1.97 1.97 1.97 0.03 0.03 0.03 0.03 0.03 0.03 3.97 3.97 0.03 0.03 3.30 3.30 1.03 1.03 1.03 1.97 0.03 0.03 2.47 2.47 0.68 0.68 2.82 2.82
30
50
60
75
90
100
120
140
30
50
60
75
90
100
120
140
in Fig. 4(a). The characteristic of injected surge is very obvious. If Δm is decreased to 0.5p.u, the injected surge on the faulty phase is shown in Fig. 4(b). Comparing with Fig. 4(a) and (b), it is obvious that the amplitude change of the injected signal follows the change of Δm.
set. Moreover, if the amplitude of the injected signal is too large, the regulator requires more time to stabilize the system after the deactivation of additional control. If the MMC2 deviates far from the operating point in this process, the regulator may lose its control ability and cause the system to collapse.
4. Adaptive auto-reclosing scheme 3.3. Electrical characteristics of faulty lines after the injection The sequence of adaptive auto-reclosing operation is given and the method to calibrate the first reflected wave is discussed in this section.
The feasibility of additional control strategy is validated in this part. The length of ac line in the passive network is 150 km and its ac rated voltage is 145 kV. If an SLG fault occurs at 75 km and Δm = 1 p.u, the injected surge on the faulty phase (take phase a as an example) is shown 602
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Table 5 The fault identification results (P = 150 MW). ld/km
Rfault/Ω
f1/km
error%
f3/km
error %
20
0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 50.983 50.983 50.983 50.983 59.980 59.980 59.980 59.980 74.975 77.974 77.974 77.974 89.970 92.969 92.969 92.969 98.967 98.967 101.966 101.966 119.960 119.960 122.959 122.959 140.953 140.953 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 1.97 1.97 1.97 1.97 0.03 0.03 0.03 0.03 0.03 3.97 3.97 3.97 0.03 3.30 3.30 3.30 1.03 1.03 1.97 1.97 0.03 0.03 2.47 2.47 0.68 0.68 2.82 2.82
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 50.983 50.983 50.983 50.983 59.980 59.980 59.980 59.980 74.975 74.975 77.974 77.974 89.970 89.970 92.969 92.969 98.967 98.967 98.967 101.966 119.960 119.960 122.959 122.959 140.953 140.953 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 1.97 1.97 1.97 1.97 0.03 0.03 0.03 0.03 0.03 0.03 3.97 3.97 0.03 0.03 3.30 3.30 1.03 1.03 1.03 1.97 0.03 0.03 2.47 2.47 0.68 0.68 2.82 2.82
30
50
60
75
90
100
120
140
Fig. 14. Simulation results on dc system of adaptive auto-reclosing scheme: (a) DC current. (b) DC voltages on sending and receiving end. (c) The magnified drawing of dc voltages.
Fig. 15. Simulation results of adaptive auto-reclosing scheme for AC systems: (a) AC bus 1 voltages. (b) AC bus 2 currents. (c) AC bus 2 currents. (d) AC bus 2 currents.
activated at the recovery voltage stage. The practical experience of 500 kV HVDC projects in China shows that the arc extinction time is less than 0.2 s with shunt reactor installed [33]. The secondary arc extinction time is highly dependent on voltage level, which implies that lower voltage level results in short arc extinction time. To reliably avoid the influence of arc, the injection is activated after a fixed time delay of 0.3 s for SPAR and 1.8 s for TPAR after the circuit breaker tripping. The proposed adaptive auto-reclosing sequence for temporary faults is shown in Fig. 5(b), which shortens the reclosing time and avoids the second fault shock to a great extent.
Fig. 13. Simulation results of adaptive auto-reclosing scheme: (a) AC current on the faulty line. (b) AC voltage on the faulty line. (c) Active power from MMC2.
4.1. Activation time of injection The conventional auto-reclosing sequence for temporary faults is shown in Fig. 5(a). Circuit breakers reclose after a fixed time delay to restore the power transmission. The fixed time delay should consider different fault types and reclosing manoeuvre, which is generally 500 ms for SPAR and 2 s for TPAR. If the fault still exits, the circuit breakers will be tripped again and the reclosing operation will be ended. The post-fault arc fluctuates unpredictably whereas the post recovery voltage remains relatively stable. In order to avoid the interference of arc on the identification of injected signal, the injection is
4.2. Wavelet transform algorithm The TW based method can be single ended or double ended. Since only one side of passive ac network is connected to the converter, therefore single end method is suitable. Pulse or surge is a non-stationary signal with sudden change and singularity characteristic. Wavelet transform has the advantages over describing every detail of singular signal in both frequency domain and time domain. It is a highly effective mathematical tool for analysing TWs. Quadratic spline 603
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computational burden for dynamic analysis since the simulation steps, usually microsecond level, should be relatively lower than the switching time of the IGBT. Thevenin model of MMC has been widely applied to research works, ranging from fault, and control to stability analysis [34–36], for its fast simulation speed. Therefore, HB-MMC is modelled as Thevenin equivalent model suggested by CIGRE Working Group [37]. The parameters of MMC-HVDC are shown in Table 1. The single circuit configuration is shown in Fig. 8(a) used to study SPAR. The multi-circuit configuration is shown in Fig. 8(b) used to study TPAR. Frequency-dependent OHLs are modelled in PSCAD as shown in Fig. 8(c). The positive/negative sequence impedances of OHL are z1 = z2 = 0.03433 + j0.4188 Ω/km, and zero sequence impedance is z0 = 0.2912 + j1.1566 Ω/km. Velocity calibration of travelling wave, to modify threshold of (2), is done by simulating pulse injection to the healthy line. Results are given in Table 2, where fc is the sampling frequency. The average speed of TW comes out to be v = 299.900 km/ ms.
wavelet is adopted to detect singular points in this paper. The modulus maxima of wavelet transform (WTMM) preforms one-to-one correspondence with the singular points of TWs. The amplitude of WTMM represents the change intensity of the signal, and its polarity indicates the direction of the change. Thus the injected signal singularity analysis is transformed into its WTMM analysis. In data processing, the fault component (Δx) is obtained by subtracting the signals (x[n]) during the injection period from the signals in the previous cycle x[n − T] (T is the power cycle). The injected signals of a SLG (f1) fault, the fault component (Δua), and the WTMM results are shown Fig. 6(a). The simulation result for a symmetrical fault ( f 3 ) is shown in Fig. 6(b). The fault distances for two types of faults are 90 km. The fault impedances are 0.01 Ω and 50 Ω, respectively. As can be seen from both simulation results, the reflected TWs are obvious, even with the increased fault impedance. The quadratic spline wavelet can accurately identify the backward travelling wave. The length of the data window is generally not more than 5 ms, and the detection time is in milliseconds. 4.3. Criteria for adaptive auto-reclosing operation
5.2. Temporary faults An adaptive auto-reclosing scheme for MMC-HVDC system supplying a passive network is proposed as shown in Fig. 7. Before the signal injection, a fixed time delay for arc extinction is required. Otherwise, secondary arc can produce high frequency transients, which result in the inaccuracy of TW based method. After breaker tripping, fixed injection delay of 0.3 s and 1.8 s is set for single phase and three phase tripping, respectively. In order to reduce the impact on power transmission of the healthy pole, the duration of characteristic signal is set to 5 ms. Further, the interval between two injection operations is set to 50 ms to avoid the interaction between consecutive injections. If the fault is present and injection number n is less than the setting number nset, extra pulse signal is injected. The setting number nset is based on the system operation code. Two/three/… more injections could be accepted for the consideration of reliable identification. If the fault is still present and n ≥ nset, fault distance could be calculated and assessment will be ended. In that scenario of permanent single phase tripping in previous assessment, tripolar breaker action will be activated. However, in case of fault removal, an extra assessment with increased pulse amplitude will improve reliability. This operation avoids the random influence of singular points detection when the arc is not disappearing. Increased number of assessments will reduce the chances of misjudgment caused by the disturbances. If the fault is not observed even in an extra assessment, ac breaker will reclose and the assessment will be ended. Otherwise, assessments will continue until permanent opening of circuit breaker. Optimized injection number (nset) of extra injections can be chosen according to the system reliability requirement, which is set to be one in this work.
MMC can still maintain working under SLG faults and the proposed method is applicable to SPAR in the MMC-HVDC system. A temporary SLG fault (at phase a) is initiated 75 km away from MMC2 at t = 0.80 s and ac circuit breakers on both sides of faulty line are tripped at t = 0.82 s. Then characteristic signals are injected to the faulty line as shown in Fig. 9(a). The magnified waveform of fault component during the injection is shown in Fig. 9(b). The injected voltage wave is steep and with sufficient intensity. The WTMM result is shown in Fig. 9(c), which indicates the reflection of forward wave from the line boundary (ac bus). The polarity of reflected wave is the same as that of injected wave. Due to temporary nature, the fault has already disappeared.
5.3. Permanent faults The fault components of faulty phase voltage, under different fault impedances and pre-fault active power, are given in Fig. 10 and Fig. 11, respectively. It is concluded that higher fault impedance and pre-fault power transmission lead to lower wavefront. Reason is that the higher fault impedance reduces the reflection coefficient of TW and lower transmission power decreases the distributed energy stored along the line. Then the fault components of faulty phase voltage and their WTMMs are given in Fig. 12, which are with active powers, fault distances, and fault impedances of (50 MW, 90 km, 100 Ω), (75 MW, 60 km, 10 Ω), and (150 MW, 75 km, 50 Ω). The permanent SLG and symmetrical faults are simulated under the topology shown in Fig. 8(a) and (b), respectively. The backward signal is reflected at the fault location, and its polarity is opposite to the polarity of the forward wave. In case of permanent faults with different distance, impedance Rfault and pre-fault active power, the fault distances identified by quadratic spline wavelet are shown in Table 3–5. f1 and f3 represent fault distances calculated under SLG and symmetrical faults respectively. The maximum error ΔL caused by sampling frequency approximately equals to 3 km with the common sampling frequency of fs = 50 kHz at relay location. According to the calculated results in Table 3–5, the errors of fault location using quadratic spline wavelet are all within one sampling interval (ΔL ). In the case of fault near to remote end, the polarity of backward travelling wave may be opposite to forward wave for a very short time and then backward wave is reflected from the fault point or the remote bus. Therefore, the proposed method is not sufficiently sensitive for the faults near the end of transmission line. However fault sensitivity can be improved to a certain extent by increasing the sampling frequency or the amplitude of injected signal.
5. Simulation In order to verify the validity of proposed method to SPAR and TPAR, simulations are conducted under the single circuit and multicircuit (double circuit) scenario. In addition, fast adaptive auto-reclosing simulation results are presented. 5.1. System model The system model of MMC-HVDC supplying the passive network, as shown in Fig. 2, is simulated in PSCAD/EMTDC. The length of ac transmission line is 150 km. Passive loads are constant power loads of 150 MW. The arc models, utilized in arc extinction based methods, do not change the basic behaviour of TW refraction and reflection, therefore a (constant) fault impedance is adopted when fault location method is studied in this paper. The detailed model of MMC has high 604
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Technology Projects (52170218000 M).
5.4. Fast adaptive auto-reclosing The fast adaptive auto-reclosing scheme is simulated under the topology shown in Fig. 8(a). The simulation results are given in Figs. 13 and 14. A temporary SLG fault occurs at t = 0.8 s and the ac circuit breaker of faulty phase is tripped at t = 0.82 s. Additional control strategy is activated at t = 1.1 s after a fixed delay of 0.3 s. After the fault is assessed to be disappeared, extra injection is conducted to reliably identify the fault property at t = 1.15 s. The interval between the two injections is chosen as 50 ms by considering line length and propagation attenuation of travelling wave. Since the fault is not present any more, the assessment is ended. Then the ac breaker is reclosed and power transmission recovers at t = 1.2 s. The ac voltage (ua) and ac current (ia) on the faulty line are shown Fig. 13(a) and (b), repectively. Secondary arc extinction occurs at t = 0.9 s and then recovery voltage appears. Due to the unbalanced condition, transmitted power (P) of MMC2 and dc current (idc) have second order harmonics as presented in Figs. 13(c) and 14(a). Also, the injection shows negligible influence on dc power flow. The dc voltages on sending end and receiving end (udc1 and udc2) are shown Fig. 14(b) and the magnified drawing during injection is given in Fig. 14(c). The second order harmonic clearly appears on the MMC2. But the injection causes limited disturbances on the udc1 within several milliseconds and no significant impact is observed on udc2. Furthermore, ac bus voltages and currents on both sending and receiving end are given in Fig. 15(a)–(d). As it is shown in Fig. 15, MMC2 can stabilize the system to the normal operating states quickly after the termination of additional control action. Moreover, slight fluctuation for no more than 5 ms occurs on ac bus currents (isabc1 and isabc2). The short adjustment time and the injection duration (milliseconds) do not affect the normal power transmission on the ac side. Compared with the traditional passive detection method, the proposed method could actively increase the intensity of the injected signal and injection frequency to improve the identification reliability.
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Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ijepes.2019.06.014. References [1] Xu J, Zhao C, Zhang B. Control design and operational characteristics comparation for VSC-HVDC supplying active/passive networks. In: 2011 6th IEEE conference on industrial electronics and applications, Beijing; 2011. p. 1381–6. [2] Stendius L, Jones P. Thue challenges of offshore power system construction-bringing power successfully to Troll A, one of the worlds largest oil and gas platform. In: The 8th IEE international conference on AC and DC power transmission, London, UK; 2006. p. 75–8. [3] Zhang L, Ye T, Xin Y, et al. Problems and measures of power grid accommodating large scale wind power. Proc CSEE 2010;30(25):1–9. [in Chinese]. [4] Chi Y, Liu Y, Wang W, et al. Study on impact of wind power integration on power system. Power Syst Technol 2007;21(3):77–81. [in Chinese]. [5] Tang G, He Z, Pang H. Discussion on applying the VSC-HVDC technology in global energy interconnection. IEEE Trans Smart Grid 2016;4(2):116–23. [6] Yang Y, He Z, Zhou Y, et al. Control mode and operating performance of Xiamen ± 320 kV VSC-HVDC Project. IEEE Trans Smart Grid 2016;4(3):229–34. [7] Zhang M, Yuan X, Hu J. Inertia and primary frequency provisions of PLL-synchronized VSC HVDC when attached to islanded AC system. IEEE Trans Power Syst 2018;33(4):4179–88. [8] Guo C, Zhao C. Supply of an entirely passive AC network through a double-infeed HVDC system. IEEE Trans Power Electron 2010;25(11):2835–41. [9] Dhar S, Dash PK. Harmonic profile injection-based hybrid active islanding detection technique for PV-VSC-based microgrid system. IEEE Trans Sustain Energy 2016;7(4):1473–81. [10] Dias O, Tavares MC. Comparison between traditional single-phase auto reclosing and adaptive technique based on harmonic content measurement. IET Gener Transm Distrib 2017;11(4):905–14. [11] Zhalefar F, Dadash Zadeh MR, Sidhu TS. A high-speed adaptive single-phase reclosing technique based on local voltage phasors. IEEE Trans Power Deliv 2017;32(3):1203–11. [12] Zhang B. Protection relay of power system. Beijing, China: China Electric Power Press; 2006. [in Chinese]. [13] Ge YZ, Sui FH, Yiao Y. Prediction methods for preventing single-phase reclosing on permanent fault. IEEE Trans Power Delivery 1989;4(1):114–21. [14] Ning J, He B, Wang Z, et al. Algorithm for adaptive single-phase reclosure on shuntreactor compensated extra high voltage transmission lines considering beat frequency oscillation. IET Gener Transm Distrib 2018;12(13):3193–200. [15] Li B, Li Y. A new adaptive single-pole autoreclosure technique based on calculation of fault point voltage. Autom Elect Power Syst 2013;37(10):86–91. [in Chinese]. [16] Zadeh MRD, Rubeena R. Communication-aided high-speed adaptive single-phase reclosing. IEEE Trans Power Deliv 2013;28(1):499–506. [17] Luo X, Huang C, Jiang Y, et al. Adaptive single-phase reclosure scheme for transmission lines with shunt reactors based on current inner product. IET Gener Transm Distrib 2017;11(7):1770–6. [18] Dias O, Tavares MC. Implementation and performance evaluation of a harmonic filter for use in adaptive single-phase reclosing. IET Gener Transm Distrib 2017;11(9):2261–8. [19] Jamali S, Ghaderi Baayeh A. Detection of secondary arc extinction for adaptive single phase auto-reclosing based on local voltage behaviour. IET Gener Transm Distrib 2017;11(4):952–8. [20] Zahlay FD, Rama Rao KS, Ibrahim TB. A new intelligent autoreclosing scheme using artificial neural network and Taguchi's methodology. IEEE Trans Industry Appl 2011;47(1):306–13. [21] Suonan J, Shao W, Song G, et al. A novel single-phase adaptive reclosure scheme for transmission lines with shunt reactors. IEEE Trans Power Deliv 2009;24(2):545–51. [22] Song G, Wang C, Wang T, et al. A phase selection method for wind power integration system using phase voltage waveform correlation. IEEE Trans Power Deliv 2017;32(2):740–8. [23] Nanayakkara OMKK, Rajapakse AD, Wachal R. Location of DC line faults in conventional HVDC systems with segments of cables and overhead lines using terminal measurements. IEEE Trans Power Deliv 2012;27(1):279–88. [24] Wang W, Shi X, Meng J, et al. Modeling and control of VSC-HVDC supplying passive network. In: 2013 10th IEEE international conference on control and automation (ICCA), Hangzhou; 2013. p. 213–7. [25] Saad H, Peralta J, Dennetière S, et al. Dynamic averaged and simplified models for MMC-based HVDC transmission systems. IEEE Trans Power Deliv 2013;28(3):1723–30. [26] Mehrasa M, Pouresmaeil E, Zabihi S, et al. Dynamic model, control and stability analysis of MMC in HVDC transmission systems. IEEE Trans Power Deliv 2017;32(3):1471–82. [27] Moon J, Kim C, Park J, et al. Circulating current control in MMC under the unbalanced voltage. IEEE Trans Power Deliv 2013;28(3):1952–9. [28] Saad H, Guillaud X, Mahseredjian J, et al. MMC capacitor voltage decoupling and balancing controls. IEEE Trans Power Deliv 2015;30(2):704–12.
6. Conclusion A fault identification method for passive networks supplied by MMC-HVDC is proposed in this paper. It utilizes the control capability of MMC to inject characteristic signal into faulty ac lines. Compared with the passive fault identification methods, the active injection method is independent of recovery voltage, secondary arc, and the current of shunt reactor. Repeated injections and extra independent assessments can be supplemented to prevent misjudgement. The proposed method is not applicable to the TPAR in the single line ac system as electric quantities are hard to measure after three phase trip. In addition, the application of proposed method to active ac systems is suggested as future research work, which is more common in the power network. Lower sampling rate results in a larger error to calibrate the arrival of wavefront. The proposed TW based fault location method is not sufficiently sensitive at near and remote end of transmission line. To solve this problem, increased sampling frequency or the amplitude of injected surge can improve the accuracy of identification method to a certain extent. Furthermore, the characteristics of injected signals on the healthy line are fixed whereas they are indeterminate in the presence of fault. In order to improve the sensitivity at the beginning/end segment, instead of using only WTMM, the waveform correlation is suggested for the future research. Acknowledgments This work was supported by the National Key R&D Program of China under grant 2016YFB0900603 and Technology Projects of State Grid Corporation of China (52094017000 W), and in part by the Study on Fault Coupling Characteristics and New Principle of Relay Protection for AC/DC Hybrid Power Grid (U1766209), and in part by the 605
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[34] Ahmed N, Ängquist L, Mahmood S, et al. Efficient modeling of an MMC-based multiterminal DC system employing hybrid HVDC breakers. IEEE Trans Power Deliv 2015;30(4):1792–801. [35] Xiang W, Lin W, An T, et al. Equivalent electromagnetic transient simulation model and fast recovery control of overhead VSC-HVDC based on SB-MMC. IEEE Trans Power Deliv 2017;32(2):778–88. [36] Yu S, Zhang S, Wei Y, et al. Efficient and accurate hybrid model of modular multilevel converters for large MTDC systems. IET Gener Transm Distrib 2018;12(7):1565–72. [37] Adam G. Continued operation of multi-terminal HVDC networks based on modular multilevel converters. In: Cigré International Symposium; 2014.
[29] Lin W, Jovcic D, Nguefeu S, et al. Full-bridge MMC converter optimal design to HVDC operational requirements. IEEE Trans Power Delivery 2016;31(3):1342–50. [30] Xia D. Analysis of power system. Beijing, China: China Electric Power Press; 2010. [in Chinese]. [31] Wenig S, Goertz M, Hirsching C, et al. On full-bridge bipolar MMC-HVdc control and protection for transient fault and interaction studies. IEEE Trans Power Deliv 2018;33(6):2864–73. [32] Zhang J, Xiang W, Rao H, et al. Research on DC fault protection scheme of overhead MMC based DC grid with DC circuit breaker. In: Proceedings of the CSEE. p. 1-15 [in Chinese]. [33] Lin D, Wang Q, Wang H, et al. Adaptive reclosure scheme for parallel lines with shunt reactors. Autom Elect Power Syst 2015;39(06):101–6. [in Chinese].
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Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes
Adaptive single-phase/three-phase reclosing scheme for transmission lines in passive network supplied by MMC-HVDC
T
⁎
Ting Wanga, , Kazmi Sayed Tassawar Hussaina, Guobing Songa, Wei Hanb, Chao Liub a b
School of Electrical Engineering, Xi’an Jiaotong University, 710049 Xi’an, People’s Republic of China State Grid Henan Electric Power Research Institute, 450052 Zhengzhou, People’s Republic of China
A R T I C LE I N FO
A B S T R A C T
Keywords: AC fault Active injection Fault identification Modular multilevel converter (MMC) Passive network
Modular multilevel converter (MMC) shows prominent advantages on supplying passive networks, which are usually classified by power supply shortage and relatively weak structure. In order to reduce the unnecessary outage time and improve the system stability, an adaptive ac auto-reclosing scheme for passive networks is proposed based on characteristic signal injection. Additional MMC controller is designed to inject the characteristic signals into the healthy line, which in turn induces corresponding signals to the faulty line. Then fault properties are assessed by the travelling wave based fault location method. Finally, an adaptive auto-reclosing scheme is proposed to shorten the reclosing time and avoid the second fault shock to a large extent. The proposed scheme could be applied for both single-circuit and multi-circuit transmission lines. The simulation results obtained from PSCAD/EMTDC verify the effectiveness of the proposed method.
1. Introduction Compared with the line commutated converter (LCC)-high voltage dc (HVDC) transmission, voltage source converter based HVDC (VSCHVDC) is advantageous to supplying power to weak ac systems or even passive networks [1]. The Troll-A project in Norway is the first commercial project in the world to apply VSC-HVDC to power offshore drilling platforms [2]. VSC-HVDC also has wide application in connecting decentralized small power plants (such as wind power generation, solar power generation, etc.) to power grids. Especially in China, numerous wind farms in the west area/offshore wind farms are located far away from load center in the east area, which can better be integrated with main power network through VSC-HVDC [3,4]. The two terminal ± 320 kV VSC-HVDC project has been constructed to supply the Xiamen Island and four-terminal ± 500 kV HVDC grid project to interconnect large scale onshore windfarms in Zhangbei area [5–7]. An ac system can be regarded as a weak system based on two aspects, either high ac system impedance or weak inertia. A typical example of high impedance ac system is the termination of HVDC link at a weak point of large ac system with low short circuit capacity [8]. Lowinertia systems are usually equipped with limited number of rotating machines, or no rotating machine at all. Typical applications of lowinertia systems are island system and windfarm [9]. Converters are
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required to switch from the grid connected mode to the islanded mode under special conditions like tripping of critical ac lines or black start situation. Therefore, passive network can appear which may require certain converters to supply electrical energy independently. Majority of power system failures are transmission line failures. The higher the voltage level, greater the probability of single line-to-ground (SLG) fault [10,11]. Due to the weak structure and lack of power supply, the reliability and stability of passive network is poor and not suitable for its future demand. Therefore, it is critical to improve its reliability and stability, and reduce unnecessary power interruption time. Automatic reclosing is widely applied in the engineering practice [12]. Adaptive auto-reclosing operation, which identifies fault properties before reclosing plays an important role in improving power supply reliability and stability. Single phase/three phase adaptive auto-reclosing (SPAR/TPAR) has attracted wide attention of academia. The current researches mainly focus on SPAR, which is based on recovery voltage, arc characteristics, and the current of shunt reactor. The recovery voltage stage appears from the arc extinction to the reclose operation. The earliest recovery voltage amplitude criterion is proposed in [13]. More methods based on recovery voltage are developed in [11,14] using the phase, beat frequency, fault location, and model recognition etc. Ref. [15] identifies the fault properties by comparing the actual voltage with the theoretical value of instantaneous fault voltage at fault point. The voltage of faulty phase can
Corresponding author. E-mail address: [email protected] (T. Wang).
https://doi.org/10.1016/j.ijepes.2019.06.014 Received 8 November 2018; Received in revised form 28 April 2019; Accepted 6 June 2019 Available online 11 June 2019 0142-0615/ © 2019 Elsevier Ltd. All rights reserved.
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be deduced from the voltage phasors at both ends of the healthy phases [16]. This method is only suitable for uniformly transposed lines and relies on the communication. Improper transposition due to geographical conditions results in different recovery voltages at different faulty phases. Moreover, in order to reduce the Ferranti Effect, shunt reactors are often installed on high-voltage transmission lines. The recovery voltage in that scenario shows a beat frequency that is close to power frequency [17], which limits the application of SPAR based on recovery voltage amplitude and phase. Therefore, fast reclose based on recovery voltage is difficult to realize. Odd harmonics of arc are higher in the case of temporary SLG faults, whereas arc extinguishes quickly in the case of permanent SLG faults. Therefore, scholars have carried out many researches based on the harmonic characteristics of the arc [18,19], fault current pattern recognition [20] and so on. However, arc is a complicated physical and chemical phenomenon. The strong randomness and instability of secondary arc make such kinds of methods prone to failures. Ref. [21] uses the difference between the actual current and the theoretical current to identify fault properties in the case of shunt reactor installed on the either end of transmission line. The absence of shunt reactor causes quick decrease in electromagnetic energy of the line, which limits the application of methods based on shunt reactor current. Further, since electric quantities are so weak to measure after three phase tripping, satisfying methods are not available for TPAR in the single circuit line configuration. Above-mentioned researches are all based on passive detection methods, which are highly model dependent. The modular multilevel converter (MMC) supplying passive network provides a new way for adaptive auto-reclosing operation due to its fast and flexible control ability. An active detection based adaptive auto-reclosing scheme is proposed in this paper. MMC is used to inject characteristic signals into the healthy line. Mutual coupling exists among transmission lines and therefore the corresponding characteristic electric quantities are induced on the faulty line. The proposed method is suitable for SPAR and TPAR in the case of multi-circuit transmission lines, and also applicable to SPAR in the single-circuit system. Section 2 summarizes the general principles of proposed fault identification scheme, which are line coupling and travelling wave based fault location. MMC controller design to achieve characteristic signal injection is proposed in Section 3. Then adaptive auto-reclosing scheme is put forward in Section 4. Finally, simulation results of temporary faults, permanent faults and fast reclose operation are given in Section 5 to verify the effectiveness of the proposed method.
⎧− ⎪ − ⎨ ⎪− ⎩
∂ua dx ∂x ∂ub dx ∂x ∂uc dx ∂x
∂i
∂i
∂i
∂i
∂i
= L0 dx ∂ta + L m dx ∂tb + L m dx ∂tc ∂i
= L m dx ∂ta + L0 dx ∂tb + L m dx ∂tc ∂i
∂i
∂i
= L m dx ∂ta + L m dx ∂tb + L0 dx ∂tc
(1)
It can be seen from (1) that the voltage and current perturbations on one phase, i.e., SLG faults, will induce corresponding electrical quantities to other phases. MMC could realize independent voltage control of each phase by adjusting upper and lower arm voltages, which is equivalent to a controlled voltage source for the ac system. MMC is utilized to inject characteristic signals to healthy phases. Corresponding electric quantities will be induced in the faulty phase/line, which contain the fault information. Whether the response of the faulty phase/line meets the fault criteria is then checked. The proposed fault identification method by using characteristic signal injection is shown in the right part of Fig. 1. Fig. 1(b) and (c) are respectively the single-circuit configuration and multi-loop configuration, which are two research scenarios of this paper. tf is the injection time, which is known for protection installation. tb is the arrival time of the first reflected wave and ld is the fault distance. The proposed method is also applicable to SPAR in the multiloop scenario, which is not explained to avoid repetition. 2.2. Traveling wave based fault location method The injected characteristic signal is chosen to be voltage pulse signal. Voltage traveling waves propagate nearly at the speed of light on overhead lines (OHLs) and reflect back from fault locations or line boundaries. Therefore, the traveling wave (TW) based fault location method is utilized. Since the injection time (tf) of first forward traveling signal is known, accurate calibration and identification of the first reflected wave is essential to obtain the fault distance. Δts = tb − tf is defined as the time interval of surge reflection and L is the line length. Presence of fault satisfies the fault criteria (2).
ld =
v v Δts = (tb − t f ) ⩽ L 2 2
(2)
Fault location based on pulse detection has a dead zone (several kilometers) in the first and the last segment of the line. No matter how higher is the sampling frequency, complete elimination of dead zone is not possible. Such problem can be resolved by considering the waveform correlation method [22] and the terminal load matching method. Furthermore, the high voltage transmission lines are capable to transmit power to longer distance. Therefore, HVDC systems usually have longer transmission lines (hundreds of kilometers). Shorter lines (several kilometers) are common in the distribution system with lower voltage level and lower sampling rate. Current methodology is proposed for high voltage transmission lines. At the same time, the transient TW contains full band components. The higher the frequency of TW component, faster the propagation speed. TW velocity can be calculated by using the line structural parameters, or can be measured practically [23]. The most reliable approach is to estimate these values from the measurements obtained for the known fault locations, which is adopted in this paper. The maximum deviation of the sampling of relay protection can reach a sampling interval Ts, due to the random sampling time in theory. Moreover, the maximum sampling error caused is obtained as ΔL = v Ts/2 = v /2fs where fs is the sampling frequency. ΔL represents the half distance travelled by the surge during one sampling interval.
2. Fault identification principles Automatic reclosing, especially compromise poles anto-reclosure, is almost used for all types of faults in EHV/UHV systems [12]. The proposed method is mainly based on the line coupling and the control ability of MMC. It could realize fault identification even when the electric quantities of arc disappear.
2.1. The coupling characteristic of transmission line Three phase homogeneous transmission line model is shown in Fig. 1(a). The ac voltages and currents on the left side of dx are uφ and iφ (φ = a, b, c) respectively. dx is the length segment. In addition, ac ∂uφ voltages and currents on the right side of dx are uφ + ∂x dx and
3. Characteristic signal injection
∂i φ
iφ + ∂x dx . The inductance and capacitance of segment dx are L0dx and C0dx respectively. The coupling inductance and capacitance of segment dx among power lines are Lmdx and Cmdx respectively. According to Kirchhoff's Voltage Law (KVL), it could be obtained
Characteristic signal injection method is suitable for ac lines connected to the point of common coupling (PCC). Additional control strategy is proposed to inject characteristic signals upon the fault detection. Duration and amplitude are the two major indices to select the 598
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Fig. 1. The principle of fault identification. (a) Three phase homogeneous transmission line model. (b) Three phase configuration for single circuit transmission. (c) Multi-loop configuration.
Fig. 4. The voltage of faulty phase after an injection.
Fig. 2. MMC-HVDC transmission system topology supplying a passive network.
Fig. 5. Reclosure sequence of temporary faults: (a) Auto-reclosing sequence. (b) Adaptive auto-reclosing sequence.
3.1. Control of MMC supplying to passive network The MMC-HVDC system supplying the passive network is shown in Fig. 2. MMC1 and MMC2 are sending end and receiving end, respectively. The half bridge based MMC (HB-MMC) consists of six bridge arms. Each arm contains hundreds of sub modules (SMs) and a reactor Larm. Every SM contains a capacitor (C0), two IGBTs, and two antiparallel diodes. The capacitor voltage of SM is uc (> 0). usφ and isφ are respectively the ac voltages and currents at PCC. icφ are the ac currents at the converter side. idc is the dc current and udc is the dc voltage. Since the receiving end system is a passive network, MMC2 is responsible for ac frequency and voltage regulation. Thus the coordinated
Fig. 3. Additional control strategy of receiving-end MMC.
injected signals. Specific relay, with travelling wave based fault location, may be required to achieve adaptive auto-reclose operation. Coordination between MMC and relay is also important. In addition, most high voltage lines are equipped with travelling wave protection schemes. Therefore, existing hardware can be utilized with necessary software amendments. 599
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Start
N Fault tripping
Y N
Single-phase tripping? Y Delay 0.3 s
Delay 1.8 s
Injection Y Fault ˛ N Injection
Y
Fault ? N Reclose
N
n>nset ? Y Single-phase tripping?
N
Y Three-phase tripping
Calculating the fault distance
End Fig. 7. Adaptive auto-reclosing scheme. Table 1 Parameters of MMC-HVDC system.
Fig. 6. The fault component and its wavelet transform modulus maxima: (a) A SLG fault with fault impedance 0.01 Ω at the distance of 90 km. (b) A symmetrical fault with fault impedance 50 Ω at the distance of 90 km.
control strategy of MMC-HVDC system is adopted as follows. DC voltage and reactive power control are activated at MMC1, while MMC2 controls ac voltage and frequency. The synchronization phase at PCC cannot be obtained by the phase-locked loop (PLL) when the receiving end network is a passive network. Ideal three phase voltage source is usually introduced as the phase reference for MMC2 controller [24]. In this absolutely stable synchronous reference frame, the ac frequency of MMC2 is limited to be the rated frequency. The normal control strategy of MMC2 is shown in Fig. 3. usd and usq are dq components of ac voltages at PCC. icd and icq are dq components of ac currents at the converter side. usdref and usqref are d-axis and q-axis voltage references, respectively. ω is the angular frequency and θ0 is the ideal synchronous angle. Lc = Ltrans + Larm/2 is equivalent reactance of converter where Ltrans is the transformer reactance. Controller outputs the modulation indices md and mq in dq frame, which are converted to three phase modulation indices mφ after Park transformation. In normal operation, the amplitude of modulation index (m) is maintained at rated value mN. In the case of sudden increase/decrease in m, the ac voltage at converter side will show a surge/sudden drop. The ac bus voltages (usφ) will also have corresponding symmetrical three phase amplitude increase/drop change. The corresponding voltage surge will be coupled with the faulty phase/line from the healthy
Parameters
Values
Rated capacity of MMC AC system voltage Rated voltage of transformer Winding type of transformer Short circuit impedance of transformer (p.u) Number of SMs on per arm Larm SM capacitor SM switching period DC line length AC line length
400 MVA 145 kV 220 kV/145 kV D/Yn 18% 250 116 mH 5 mF 100 μs 200 km 150 km
line, therefore the injection is realized. Thus an additional controller action is suggested as shown red in Fig. 3. When the injection is activated (Injecting signal = 1), the variable m is switched to the constant value m′. The feedback control is temporarily cut off to achieve openloop control. The larger the change of modulation index Δm (=m-m′), more the drop in the amplitude of usφ, and more obvious the characteristic of faulty phase/line voltage. After the removal of proposed controller action, the voltage drop is fed back to the outer loop of MMC2 controller. Modulation index is adjusted to meet the voltage reference. The controller modulates rapidly and the whole recovery process is achieved within several milliseconds. MMC is advantageous to output low modulation ratio, which enables low ac output voltage under certain dc rated voltage. The voltage drop on Larm is usually low which is neglected in this paper. According the KVL, upper and lower arm voltage of phase a could be obtained 600
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Fig. 10. The fault components under different fault impedances with fault distance of 75 km and pre-fault active power of 50 MW.
Fig. 11. The fault components under different pre-fault active power with fault distance of 30 km and fault impedance of 0.01 Ω.
Fig. 8. MMC-HVDC system supplying a passive network: (a) Single circuit configuration. (b) Multi-circuit configuration. (c) Frequency-dependent overhead line model.
⎧ u pa = 0.5udc − ua = 0.5udcN − ua ⎨ ⎩u na = 0.5udc + ua = 0.5udcN + ua
Table 2 Calibration of the traveling wave speed (fc = 1 MHz).
1 2 3 4 5 6
Δ ts (ms)
v (km/ms)
1.001 0.999 1.001 1.000 1.000 1.001
299.700 300.300 299.700 300.000 300.000 299.700
(3)
where udcN is rated dc voltage. During the injection, the output reference modulation wave is nearly zero considering the largest change of modulation index Δm = mN. But the output voltages of upper/lower SMs are approximately equal to udcN/2 [25,26], according to (3), though some perturbations of udc may occur. The dc voltage could be maintained within high level. The lower-level controls of MMC include capacitor voltage balancing [27], circulating current suppression [28] and valve triggering control [29], which have been investigated in many literatures and are not explained to avoid repetition. 3.2. Characteristic signal selection principle Since the proposed scheme is based on pulse detection, its duration (Δt) is very important. In order to avoid influence on transmitted power and sensitive load, Δt should be as short as possible subjected to following two limitations. (1) In order to reliably identify the first reflected surge, subsequent injections should be avoided before the arrival of first reflected TW. The shortest duration Δtmin should be two times the minimum travel time of the TW when the ac line is healthy. Passive network has remote geographical location from main network, with line length ranges from 50 km to 200 km and economically rated voltage ranges from 110 kV to 220 kV [30]. (2) Δt is supposed to be within the detection equipment range. The common sampling frequency of protection devices is 10–50 kHz [31]. Δt should also be much greater than the SM switching period, which is usually 100 μs [32]. The length of ac transmission line in a passive network is usually not too long and Δt = 5 ms is adopted in this paper. The overcurrent capacity of electronics and the voltage requirement of sensitive loads should be taken into account while choosing the amplitude change of modulation index Δm. (1) Larger the Δm, higher the amplitude of injected signal, smaller the impact of dispersion and sampling on the wavefront detection. In addition, the influence of fluctuation, caused by the switching of the SMs, on the singularity detection is weakened. (2) To avoid the large power fluctuation and overcurrent of electronics, Δm should be limited. The inner current loop often sets the limiter. When mN − Δm < 0, the amplitude of modulation index is limited to zero (m − Δm = 0). Therefore Δm < 1.0mN is
Fig. 9. The voltage of faulty phase under temporary faults and its magnified waveform: (a) Voltage on the faulty phase. (b) Magnified fault component. (c) The WTMM result of fault component.
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Fig. 12. The fault components and their WTMM results: (a) 50 MW, 90 km, 100 Ω. (b) 75 MW, 60 km, 10 Ω. (c) 150 MW, 75 km, 50 Ω. Table 3 The fault identification results (P = 50 MW).
Table 4 The fault identification results (P = 75 MW).
ld/km
Rfault/Ω
f1/km
error%
f3/km
error %
ld/km
Rfault/Ω
f1/km
error%
f3/km
error %
20
0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 50.983 50.983 50.983 50.983 59.980 59.980 59.980 62.979 74.975 77.974 77.974 77.974 89.970 92.969 92.969 92.969 98.967 98.967 101.966 101.966 119.960 122.959 122.959 122.959 140.953 143.952 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 1.97 1.97 1.97 1.97 0.03 0.03 0.03 4.97 0.03 3.97 3.97 3.97 0.03 3.30 3.30 3.30 1.03 1.03 1.97 1.97 0.03 2.47 2.47 2.47 0.68 2.82 2.82 2.82
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 50.983 50.983 50.983 50.983 59.980 59.980 59.980 62.979 74.975 74.975 74.975 77.974 89.970 89.970 92.969 92.969 98.967 98.967 101.966 101.966 119.960 119.960 122.959 122.959 140.953 143.952 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 1.97 1.97 1.97 1.97 0.03 0.03 0.03 4.97 0.03 0.03 0.03 3.97 0.03 0.03 3.30 3.30 1.03 1.03 1.97 1.97 0.03 0.03 2.47 2.47 0.68 2.82 2.82 2.82
20
0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 47.984 50.983 50.983 50.983 59.980 59.980 59.980 62.979 74.975 74.975 77.974 77.974 89.970 92.969 92.969 92.969 98.967 98.967 101.966 101.966 119.960 122.959 122.959 122.959 140.953 143.952 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 4.03 1.97 1.97 1.97 0.03 0.03 0.03 4.97 0.03 0.03 3.97 3.97 0.03 3.30 3.30 3.30 1.03 1.03 1.97 1.97 0.03 2.47 2.47 2.47 0.68 2.82 2.82 2.82
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 47.984 50.983 50.983 50.983 59.980 59.980 59.980 59.980 74.975 74.975 77.974 77.974 89.970 89.970 92.969 92.969 98.967 98.967 98.967 101.966 119.960 119.960 122.959 122.959 140.953 140.953 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 4.03 1.97 1.97 1.97 0.03 0.03 0.03 0.03 0.03 0.03 3.97 3.97 0.03 0.03 3.30 3.30 1.03 1.03 1.03 1.97 0.03 0.03 2.47 2.47 0.68 0.68 2.82 2.82
30
50
60
75
90
100
120
140
30
50
60
75
90
100
120
140
in Fig. 4(a). The characteristic of injected surge is very obvious. If Δm is decreased to 0.5p.u, the injected surge on the faulty phase is shown in Fig. 4(b). Comparing with Fig. 4(a) and (b), it is obvious that the amplitude change of the injected signal follows the change of Δm.
set. Moreover, if the amplitude of the injected signal is too large, the regulator requires more time to stabilize the system after the deactivation of additional control. If the MMC2 deviates far from the operating point in this process, the regulator may lose its control ability and cause the system to collapse.
4. Adaptive auto-reclosing scheme 3.3. Electrical characteristics of faulty lines after the injection The sequence of adaptive auto-reclosing operation is given and the method to calibrate the first reflected wave is discussed in this section.
The feasibility of additional control strategy is validated in this part. The length of ac line in the passive network is 150 km and its ac rated voltage is 145 kV. If an SLG fault occurs at 75 km and Δm = 1 p.u, the injected surge on the faulty phase (take phase a as an example) is shown 602
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Table 5 The fault identification results (P = 150 MW). ld/km
Rfault/Ω
f1/km
error%
f3/km
error %
20
0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100 0.01 10 50 100
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 50.983 50.983 50.983 50.983 59.980 59.980 59.980 59.980 74.975 77.974 77.974 77.974 89.970 92.969 92.969 92.969 98.967 98.967 101.966 101.966 119.960 119.960 122.959 122.959 140.953 140.953 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 1.97 1.97 1.97 1.97 0.03 0.03 0.03 0.03 0.03 3.97 3.97 3.97 0.03 3.30 3.30 3.30 1.03 1.03 1.97 1.97 0.03 0.03 2.47 2.47 0.68 0.68 2.82 2.82
20.993 20.993 20.993 20.993 29.990 29.990 29.990 29.990 50.983 50.983 50.983 50.983 59.980 59.980 59.980 59.980 74.975 74.975 77.974 77.974 89.970 89.970 92.969 92.969 98.967 98.967 98.967 101.966 119.960 119.960 122.959 122.959 140.953 140.953 143.952 143.952
4.97 4.97 4.97 4.97 0.00 0.00 0.00 0.00 1.97 1.97 1.97 1.97 0.03 0.03 0.03 0.03 0.03 0.03 3.97 3.97 0.03 0.03 3.30 3.30 1.03 1.03 1.03 1.97 0.03 0.03 2.47 2.47 0.68 0.68 2.82 2.82
30
50
60
75
90
100
120
140
Fig. 14. Simulation results on dc system of adaptive auto-reclosing scheme: (a) DC current. (b) DC voltages on sending and receiving end. (c) The magnified drawing of dc voltages.
Fig. 15. Simulation results of adaptive auto-reclosing scheme for AC systems: (a) AC bus 1 voltages. (b) AC bus 2 currents. (c) AC bus 2 currents. (d) AC bus 2 currents.
activated at the recovery voltage stage. The practical experience of 500 kV HVDC projects in China shows that the arc extinction time is less than 0.2 s with shunt reactor installed [33]. The secondary arc extinction time is highly dependent on voltage level, which implies that lower voltage level results in short arc extinction time. To reliably avoid the influence of arc, the injection is activated after a fixed time delay of 0.3 s for SPAR and 1.8 s for TPAR after the circuit breaker tripping. The proposed adaptive auto-reclosing sequence for temporary faults is shown in Fig. 5(b), which shortens the reclosing time and avoids the second fault shock to a great extent.
Fig. 13. Simulation results of adaptive auto-reclosing scheme: (a) AC current on the faulty line. (b) AC voltage on the faulty line. (c) Active power from MMC2.
4.1. Activation time of injection The conventional auto-reclosing sequence for temporary faults is shown in Fig. 5(a). Circuit breakers reclose after a fixed time delay to restore the power transmission. The fixed time delay should consider different fault types and reclosing manoeuvre, which is generally 500 ms for SPAR and 2 s for TPAR. If the fault still exits, the circuit breakers will be tripped again and the reclosing operation will be ended. The post-fault arc fluctuates unpredictably whereas the post recovery voltage remains relatively stable. In order to avoid the interference of arc on the identification of injected signal, the injection is
4.2. Wavelet transform algorithm The TW based method can be single ended or double ended. Since only one side of passive ac network is connected to the converter, therefore single end method is suitable. Pulse or surge is a non-stationary signal with sudden change and singularity characteristic. Wavelet transform has the advantages over describing every detail of singular signal in both frequency domain and time domain. It is a highly effective mathematical tool for analysing TWs. Quadratic spline 603
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computational burden for dynamic analysis since the simulation steps, usually microsecond level, should be relatively lower than the switching time of the IGBT. Thevenin model of MMC has been widely applied to research works, ranging from fault, and control to stability analysis [34–36], for its fast simulation speed. Therefore, HB-MMC is modelled as Thevenin equivalent model suggested by CIGRE Working Group [37]. The parameters of MMC-HVDC are shown in Table 1. The single circuit configuration is shown in Fig. 8(a) used to study SPAR. The multi-circuit configuration is shown in Fig. 8(b) used to study TPAR. Frequency-dependent OHLs are modelled in PSCAD as shown in Fig. 8(c). The positive/negative sequence impedances of OHL are z1 = z2 = 0.03433 + j0.4188 Ω/km, and zero sequence impedance is z0 = 0.2912 + j1.1566 Ω/km. Velocity calibration of travelling wave, to modify threshold of (2), is done by simulating pulse injection to the healthy line. Results are given in Table 2, where fc is the sampling frequency. The average speed of TW comes out to be v = 299.900 km/ ms.
wavelet is adopted to detect singular points in this paper. The modulus maxima of wavelet transform (WTMM) preforms one-to-one correspondence with the singular points of TWs. The amplitude of WTMM represents the change intensity of the signal, and its polarity indicates the direction of the change. Thus the injected signal singularity analysis is transformed into its WTMM analysis. In data processing, the fault component (Δx) is obtained by subtracting the signals (x[n]) during the injection period from the signals in the previous cycle x[n − T] (T is the power cycle). The injected signals of a SLG (f1) fault, the fault component (Δua), and the WTMM results are shown Fig. 6(a). The simulation result for a symmetrical fault ( f 3 ) is shown in Fig. 6(b). The fault distances for two types of faults are 90 km. The fault impedances are 0.01 Ω and 50 Ω, respectively. As can be seen from both simulation results, the reflected TWs are obvious, even with the increased fault impedance. The quadratic spline wavelet can accurately identify the backward travelling wave. The length of the data window is generally not more than 5 ms, and the detection time is in milliseconds. 4.3. Criteria for adaptive auto-reclosing operation
5.2. Temporary faults An adaptive auto-reclosing scheme for MMC-HVDC system supplying a passive network is proposed as shown in Fig. 7. Before the signal injection, a fixed time delay for arc extinction is required. Otherwise, secondary arc can produce high frequency transients, which result in the inaccuracy of TW based method. After breaker tripping, fixed injection delay of 0.3 s and 1.8 s is set for single phase and three phase tripping, respectively. In order to reduce the impact on power transmission of the healthy pole, the duration of characteristic signal is set to 5 ms. Further, the interval between two injection operations is set to 50 ms to avoid the interaction between consecutive injections. If the fault is present and injection number n is less than the setting number nset, extra pulse signal is injected. The setting number nset is based on the system operation code. Two/three/… more injections could be accepted for the consideration of reliable identification. If the fault is still present and n ≥ nset, fault distance could be calculated and assessment will be ended. In that scenario of permanent single phase tripping in previous assessment, tripolar breaker action will be activated. However, in case of fault removal, an extra assessment with increased pulse amplitude will improve reliability. This operation avoids the random influence of singular points detection when the arc is not disappearing. Increased number of assessments will reduce the chances of misjudgment caused by the disturbances. If the fault is not observed even in an extra assessment, ac breaker will reclose and the assessment will be ended. Otherwise, assessments will continue until permanent opening of circuit breaker. Optimized injection number (nset) of extra injections can be chosen according to the system reliability requirement, which is set to be one in this work.
MMC can still maintain working under SLG faults and the proposed method is applicable to SPAR in the MMC-HVDC system. A temporary SLG fault (at phase a) is initiated 75 km away from MMC2 at t = 0.80 s and ac circuit breakers on both sides of faulty line are tripped at t = 0.82 s. Then characteristic signals are injected to the faulty line as shown in Fig. 9(a). The magnified waveform of fault component during the injection is shown in Fig. 9(b). The injected voltage wave is steep and with sufficient intensity. The WTMM result is shown in Fig. 9(c), which indicates the reflection of forward wave from the line boundary (ac bus). The polarity of reflected wave is the same as that of injected wave. Due to temporary nature, the fault has already disappeared.
5.3. Permanent faults The fault components of faulty phase voltage, under different fault impedances and pre-fault active power, are given in Fig. 10 and Fig. 11, respectively. It is concluded that higher fault impedance and pre-fault power transmission lead to lower wavefront. Reason is that the higher fault impedance reduces the reflection coefficient of TW and lower transmission power decreases the distributed energy stored along the line. Then the fault components of faulty phase voltage and their WTMMs are given in Fig. 12, which are with active powers, fault distances, and fault impedances of (50 MW, 90 km, 100 Ω), (75 MW, 60 km, 10 Ω), and (150 MW, 75 km, 50 Ω). The permanent SLG and symmetrical faults are simulated under the topology shown in Fig. 8(a) and (b), respectively. The backward signal is reflected at the fault location, and its polarity is opposite to the polarity of the forward wave. In case of permanent faults with different distance, impedance Rfault and pre-fault active power, the fault distances identified by quadratic spline wavelet are shown in Table 3–5. f1 and f3 represent fault distances calculated under SLG and symmetrical faults respectively. The maximum error ΔL caused by sampling frequency approximately equals to 3 km with the common sampling frequency of fs = 50 kHz at relay location. According to the calculated results in Table 3–5, the errors of fault location using quadratic spline wavelet are all within one sampling interval (ΔL ). In the case of fault near to remote end, the polarity of backward travelling wave may be opposite to forward wave for a very short time and then backward wave is reflected from the fault point or the remote bus. Therefore, the proposed method is not sufficiently sensitive for the faults near the end of transmission line. However fault sensitivity can be improved to a certain extent by increasing the sampling frequency or the amplitude of injected signal.
5. Simulation In order to verify the validity of proposed method to SPAR and TPAR, simulations are conducted under the single circuit and multicircuit (double circuit) scenario. In addition, fast adaptive auto-reclosing simulation results are presented. 5.1. System model The system model of MMC-HVDC supplying the passive network, as shown in Fig. 2, is simulated in PSCAD/EMTDC. The length of ac transmission line is 150 km. Passive loads are constant power loads of 150 MW. The arc models, utilized in arc extinction based methods, do not change the basic behaviour of TW refraction and reflection, therefore a (constant) fault impedance is adopted when fault location method is studied in this paper. The detailed model of MMC has high 604
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Technology Projects (52170218000 M).
5.4. Fast adaptive auto-reclosing The fast adaptive auto-reclosing scheme is simulated under the topology shown in Fig. 8(a). The simulation results are given in Figs. 13 and 14. A temporary SLG fault occurs at t = 0.8 s and the ac circuit breaker of faulty phase is tripped at t = 0.82 s. Additional control strategy is activated at t = 1.1 s after a fixed delay of 0.3 s. After the fault is assessed to be disappeared, extra injection is conducted to reliably identify the fault property at t = 1.15 s. The interval between the two injections is chosen as 50 ms by considering line length and propagation attenuation of travelling wave. Since the fault is not present any more, the assessment is ended. Then the ac breaker is reclosed and power transmission recovers at t = 1.2 s. The ac voltage (ua) and ac current (ia) on the faulty line are shown Fig. 13(a) and (b), repectively. Secondary arc extinction occurs at t = 0.9 s and then recovery voltage appears. Due to the unbalanced condition, transmitted power (P) of MMC2 and dc current (idc) have second order harmonics as presented in Figs. 13(c) and 14(a). Also, the injection shows negligible influence on dc power flow. The dc voltages on sending end and receiving end (udc1 and udc2) are shown Fig. 14(b) and the magnified drawing during injection is given in Fig. 14(c). The second order harmonic clearly appears on the MMC2. But the injection causes limited disturbances on the udc1 within several milliseconds and no significant impact is observed on udc2. Furthermore, ac bus voltages and currents on both sending and receiving end are given in Fig. 15(a)–(d). As it is shown in Fig. 15, MMC2 can stabilize the system to the normal operating states quickly after the termination of additional control action. Moreover, slight fluctuation for no more than 5 ms occurs on ac bus currents (isabc1 and isabc2). The short adjustment time and the injection duration (milliseconds) do not affect the normal power transmission on the ac side. Compared with the traditional passive detection method, the proposed method could actively increase the intensity of the injected signal and injection frequency to improve the identification reliability.
of
State
Grid
Corporation
of
China
Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ijepes.2019.06.014. References [1] Xu J, Zhao C, Zhang B. Control design and operational characteristics comparation for VSC-HVDC supplying active/passive networks. In: 2011 6th IEEE conference on industrial electronics and applications, Beijing; 2011. p. 1381–6. [2] Stendius L, Jones P. Thue challenges of offshore power system construction-bringing power successfully to Troll A, one of the worlds largest oil and gas platform. In: The 8th IEE international conference on AC and DC power transmission, London, UK; 2006. p. 75–8. [3] Zhang L, Ye T, Xin Y, et al. Problems and measures of power grid accommodating large scale wind power. Proc CSEE 2010;30(25):1–9. [in Chinese]. [4] Chi Y, Liu Y, Wang W, et al. Study on impact of wind power integration on power system. Power Syst Technol 2007;21(3):77–81. [in Chinese]. [5] Tang G, He Z, Pang H. Discussion on applying the VSC-HVDC technology in global energy interconnection. IEEE Trans Smart Grid 2016;4(2):116–23. [6] Yang Y, He Z, Zhou Y, et al. Control mode and operating performance of Xiamen ± 320 kV VSC-HVDC Project. IEEE Trans Smart Grid 2016;4(3):229–34. [7] Zhang M, Yuan X, Hu J. Inertia and primary frequency provisions of PLL-synchronized VSC HVDC when attached to islanded AC system. IEEE Trans Power Syst 2018;33(4):4179–88. [8] Guo C, Zhao C. Supply of an entirely passive AC network through a double-infeed HVDC system. IEEE Trans Power Electron 2010;25(11):2835–41. [9] Dhar S, Dash PK. Harmonic profile injection-based hybrid active islanding detection technique for PV-VSC-based microgrid system. IEEE Trans Sustain Energy 2016;7(4):1473–81. [10] Dias O, Tavares MC. Comparison between traditional single-phase auto reclosing and adaptive technique based on harmonic content measurement. IET Gener Transm Distrib 2017;11(4):905–14. [11] Zhalefar F, Dadash Zadeh MR, Sidhu TS. A high-speed adaptive single-phase reclosing technique based on local voltage phasors. IEEE Trans Power Deliv 2017;32(3):1203–11. [12] Zhang B. Protection relay of power system. Beijing, China: China Electric Power Press; 2006. [in Chinese]. [13] Ge YZ, Sui FH, Yiao Y. Prediction methods for preventing single-phase reclosing on permanent fault. IEEE Trans Power Delivery 1989;4(1):114–21. [14] Ning J, He B, Wang Z, et al. Algorithm for adaptive single-phase reclosure on shuntreactor compensated extra high voltage transmission lines considering beat frequency oscillation. IET Gener Transm Distrib 2018;12(13):3193–200. [15] Li B, Li Y. A new adaptive single-pole autoreclosure technique based on calculation of fault point voltage. Autom Elect Power Syst 2013;37(10):86–91. [in Chinese]. [16] Zadeh MRD, Rubeena R. Communication-aided high-speed adaptive single-phase reclosing. IEEE Trans Power Deliv 2013;28(1):499–506. [17] Luo X, Huang C, Jiang Y, et al. Adaptive single-phase reclosure scheme for transmission lines with shunt reactors based on current inner product. IET Gener Transm Distrib 2017;11(7):1770–6. [18] Dias O, Tavares MC. Implementation and performance evaluation of a harmonic filter for use in adaptive single-phase reclosing. IET Gener Transm Distrib 2017;11(9):2261–8. [19] Jamali S, Ghaderi Baayeh A. Detection of secondary arc extinction for adaptive single phase auto-reclosing based on local voltage behaviour. IET Gener Transm Distrib 2017;11(4):952–8. [20] Zahlay FD, Rama Rao KS, Ibrahim TB. A new intelligent autoreclosing scheme using artificial neural network and Taguchi's methodology. IEEE Trans Industry Appl 2011;47(1):306–13. [21] Suonan J, Shao W, Song G, et al. A novel single-phase adaptive reclosure scheme for transmission lines with shunt reactors. IEEE Trans Power Deliv 2009;24(2):545–51. [22] Song G, Wang C, Wang T, et al. 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6. Conclusion A fault identification method for passive networks supplied by MMC-HVDC is proposed in this paper. It utilizes the control capability of MMC to inject characteristic signal into faulty ac lines. Compared with the passive fault identification methods, the active injection method is independent of recovery voltage, secondary arc, and the current of shunt reactor. Repeated injections and extra independent assessments can be supplemented to prevent misjudgement. The proposed method is not applicable to the TPAR in the single line ac system as electric quantities are hard to measure after three phase trip. In addition, the application of proposed method to active ac systems is suggested as future research work, which is more common in the power network. Lower sampling rate results in a larger error to calibrate the arrival of wavefront. The proposed TW based fault location method is not sufficiently sensitive at near and remote end of transmission line. To solve this problem, increased sampling frequency or the amplitude of injected surge can improve the accuracy of identification method to a certain extent. Furthermore, the characteristics of injected signals on the healthy line are fixed whereas they are indeterminate in the presence of fault. In order to improve the sensitivity at the beginning/end segment, instead of using only WTMM, the waveform correlation is suggested for the future research. Acknowledgments This work was supported by the National Key R&D Program of China under grant 2016YFB0900603 and Technology Projects of State Grid Corporation of China (52094017000 W), and in part by the Study on Fault Coupling Characteristics and New Principle of Relay Protection for AC/DC Hybrid Power Grid (U1766209), and in part by the 605
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