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High impedance fault protection in transmission lines using a WPT-based algorithm
Electrical Power and Energy Systems 67 (2015) 537–545
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Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes
High impedance fault protection in transmission lines using a WPT-based algorithm Arash Mahari ⇑, Heresh Seyedi 1 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
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Article history: Received 17 December 2013 Received in revised form 8 November 2014 Accepted 5 December 2014 Available online 26 December 2014 Keywords: High impedance fault Wavelet packet transform Pilot protection Zone discrimination
a b s t r a c t This paper proposes a new algorithm for High Impedance Fault (HIF) protection, in high voltage transmission lines, with the aid of Wavelet Packet Transform (WPT). The new scheme uses the HIF-induced distortion of voltage and current waveforms to detect HIF and discrimination of the fault location, respectively. The algorithm is based on a recursive method, which adds up the absolute values of high frequency signal coefficients, generated over one last cycle. Application of the proposed algorithm to the pilot protection schemes is also discussed. The proposed method is evaluated by Electro Magnetic Transients Program (EMTP) simulation studies. Several simulations, which are performed using an appropriate HIF model, bring about results which assess the proposed technique accuracy in identifying HIF in overhead transmission lines. A comprehensive simulation study shows the efficiency of the proposed protection scheme from the viewpoints of dependability and security. Ó 2014 Elsevier Ltd. All rights reserved.
Introduction A High Impedance Fault, typically, has a low current magnitude, which is often difficult to detect using conventional protection devices. HIF generally occurs when an energized conductor contacts to a surface with high resistance such as tree, dry ground, highly resistive soils or asphalt road. The detection of HIFs is critically important, since it may cause fires and danger to human beings [1]. HIFs on electrical transmission lines include arcing and nonlinear characteristics of fault impedance Therefore, the transients caused by the faults are appropriate features which make HIFs identifiable, using signal processing methods such as Wavelet Transform [2]. The shape of fault induced voltage and current waveforms, include some special features which are used in most of the HIF detection systems [3]. In recent years, several researches have presented many different techniques for detecting HIF, more efficiently. In [1–5], the presented algorithms are based on Discrete Wavelet Transform (DWT). A method is introduced in [6], which uses extra mechanical and electrical devices for HIF detection, thus, it is not proper economically. In [7], an HIF detection method with an appropriate ⇑ Corresponding author. 1
E-mail addresses: [email protected] (A. Mahari), [email protected] (H. Seyedi). Tel.: +98 (411) 339 3712.
http://dx.doi.org/10.1016/j.ijepes.2014.12.022 0142-0615/Ó 2014 Elsevier Ltd. All rights reserved.
arc model for extra high voltage (EHV) lines has been presented. In [8], a technique has been proposed based on wavelet packet transform with an Artificial Neural Network (ANN). This ANNbased method, focuses on HIF detection, rather than protection. In [8], ten cycles of signal is decomposed using WPT, which causes further delay in detection stage. Methods which are based on current asymmetry have been introduced in [9,10]. The main problem with the techniques, based on current asymmetry, is the similarity between normal operation behavior and HIF current waveforms in some cases. Some other algorithms, which have been presented for the HIF protection, are based on the low frequency signal analysis [11–13], ANN [14–17] and intelligent systems [18–21]. The main drawback of low frequency analysis group is their low security. Other system conditions, such as unbalanced load and switching, result in algorithms maloperations. The ANN based method rely on training stage. Improper training results in unreliable protection. Some of other methods are based on signal processing tools. Wavelet is one of the most efficient and high performance tools. WPT is a kind of wavelet, which analyses the signal in restricted frequency spectrum. Limited spectrum characteristic weakens the effect of other conditions (unfaulted) on the decision making. Therefore, it results in the high security of the algorithm. Using wavelet transforms in protection methods impose processing burden. However, nowadays, the digital relays are fast and efficient to handle such calculations.
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In this paper, an HIF detection technique, in transmission lines, is proposed. This technique uses voltage and current waveforms, supplied by voltage and current transformers, respectively. The detection process is executed through signal decomposition using Wavelet Packet Transform (WPT). The obtained WPT coefficients are compared with specified thresholds, during a specific time interval. This procedure forms the basis of a comprehensive decision logic. Due to WPT characteristic, the frequency spectrum is restricted but efficient for HIF protection. The main objective of proposed logic, using WPT, is to decrease the maloperations of HIF detection relays in the transient conditions. Various simulations, using EMTP, were executed to validate the performance of new method. The results, obtained from EMTP simulations, depict that the proposed scheme provides efficient fault detection in transmission lines. The results obviously show that the fault detection algorithm is insensitive to different fault types, fault location, fault current and fault inception angle. The zone discrimination module, clearly, discriminates the zone of fault location. A WPT-based algorithm identifies the fault zone. The proposed zone discrimination algorithm has capability to detect fault zone using local bus measurements. In order to increase protection security and dependability, the proposed algorithm is applied to the pilot protection schemes, such as Direct Underreaching Transfer Trip (DUTT), Permissive Overreaching Transfer Trip (POTT) and Permissive Underreaching Transfer Trip (PUTT). The rest of this paper is organized as follows. In Section ‘High impedance fault model’, high impedance fault model is explained. A brief review of WPT is presented in Section ‘Wavelet packet transform’. Section ‘Pilot protection’ is a brief discussion on the pilot protection. The proposed algorithm is presented in Section ‘The proposed algorithm’. Section ‘Simulation results and analysis’ includes the simulation results and analysis. Section ‘Discussion’ is a brief discussion on the proposed algorithm and obtained results. Finally, Section ‘Conclusion’ provides the conclusion.
High impedance fault model HIF is a very complex phenomenon, which introduces a highly nonlinear behavior. Stochastic nonlinear current has certain attributes in both transient and steady state parts, which makes it identifiable. The HIF current has four most important and significant characteristics, which are known as build-up, shoulder, nonlinearity and asymmetry. Build-up and shoulder characteristics exist only before the steady state, after HIF, while the other two characteristics, nonlinearity and asymmetry exist both before and during the steady state. An HIF current increases until it reaches the steady state value, gradually, which is called build-up. HIF current may stop increasing for a few cycles and then continue to increase again during the build-up stage [22]. Non-linearity features arise from the presence of odd harmonics. DC offset and asymmetric currents, with different magnitudes in the positive and negative half cycles, produce the asymmetry feature of current signal [23]. In other words, in an HIF, the surface which is in contact with the live conductor, shows different behaviors for negative and positive waveforms which is modeled by DC sources, with different values, in the HIF model, as shown in Fig. 1. The model which is used in this paper is presented in [24]. This model includes all HIF signatures, except shoulder, and supports all frequency components. The model simulates first eight cycles of an HIF. In This HIF model, which is based on Emanuel arc model, several arc models are used together to simulate HIF currents and voltage waveforms, similar to the real recorded HIF data from many different experimental tests, on distribution and transmission systems. Fig. 1 shows the applied HIF model [24].
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Fig. 1. HIF model based on the Emanuel arc model.
Wavelet packet transform Wavelet Packet Transform (WPT) is the generalized mode of DWT. Wavelet packet offers more complex and flexible analysis. In the DWT, just approximation component is decomposed while in the WPT, detailed components are decomposed, as well. In WPT, a signal is split into two high and low frequency parts, an approximation and a detail, in the first level, similar to the DWT. However, in contrast to the DWT, in upper levels, both details and approximations are decomposed again, in WPT. This approach forms a binary tree, as depicted in Fig. 2. The sampled signal is decomposed into d1 and a1 like DWT, at the first stage. In Fig. 2, nodes number 1 and 2 refer to a1 and d1, respectively. In the second level, decomposition will result in four sub-bands due to the decomposition of both d1 and a1. Four subbands in level two are named (2, 0), (2, 1), (2, 2) and (2, 3) which are designated as nodes 3, 4, 5 and 6, respectively, as shown in Fig. 2 [25,26]. Hence, the DWT is a sub-tree of the WPT tree. The most significant benefit of the WPT, over other types of wavelet transforms, is the accurate and detailed representation of decomposed signals in limited spectrum which makes it useful in signal processing. [8]. The efficiency of WPT, as other WT forms, is highly dependent on the wavelet basis functions, called mother wavelet. Several basis functions, can be selected as a mother wavelet, such as Daubechies (Db), Symlets, Coiflets and Biorthogonals [27]. In this paper, Daubechies-4 (Db4) is selected as the mother wavelet. Daubechies wavelet family is one of the most proper orthogonal wavelets, due to some advantages, such as powerful performance and very easy implementation in digital systems [28]. Pilot protection In the conventional line protection, fast protection from both ends of a transmission line is almost impossible, if the fault is close to end of the line. Pilot relaying systems utilize a communications
Fig. 2. Tree decomposition of the proposed wavelet packet analysis.
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link to transmit signals between two terminals of the line. This method provides more dependability for the protection systems, since information from both ends of the line is available for processing [29,30]. One of the important classes of pilot protection schemes is the transfer trip class. In the transfer trip schemes, the relays at both ends of the line, recognizing a fault within the set protection zones, will send a trip signal to the relay at the remote end of the line. In other words, transfer trip pilot protection is formed to provide high-speed tripping of faults at every point of the line length, and also to provide the benefits of backup protection for adjacent line sections. The design of transfer trip schemes can either be direct or permissive. Direct schemes send a signal from one end to the remote end that indicates a mandatory trip and the trip is initiated without additional checking or delay. Permissive systems oversee the transfer trip signal by monitoring the line condition to see if a fault is detected, even if it is not in the first zone. Direct Underreaching Transfer Trip (DUTT), Permissive Overreaching Transfer Trip (POTT) and Permissive Underreaching Transfer Trip (PUTT) are the transfer trip pilot protection schemes which are utilized in this work [29,30]. The basic concept in DUTT is that, each relay sends a trip signal to the relay at the other end if a zone-1 fault is detected, in addition to sending a trip signal to the local circuit breakers. In POTT, each relay waits for the trip from the far end relay. In this scheme, the protection relays send a trip signal to far end relays, as they detect a fault. However, they do not send trip signal to local breakers, unless they receive trip signal from far end relays. Combining two previous pilot protection schemes, DUTT and POTT, results in a more secure and faster pilot protection which is named PUTT. The zones of the relay devices are similar to those represented in previous one, except that a second set of instantaneous elements are employed. In this pilot protection scheme, as in POTT, the relays in both ends send trip signal to remote end, as they detect a fault in their protection zones. In addition, the relays send trip signal to local breakers, as they detect a fault in first zone. In other words, the relays operate similar to DUTT for zone-1 faults, while they operate similar to POTT for faults in the overreaching protection zone. The proposed algorithm The proposed algorithm includes two parts, fault detection and zone discrimination. This method is based on analyzing voltage and current waveforms, obtained from voltage and current transformers. The sampling frequency is 200 kHz and, as mentioned in last section, the high frequency information of signals is extracted by wavelet packet transform, using the Daubechies-4 wavelet (db4). Figs. 3 and 4 show the algorithm flowchart. The fault detection part uses the high frequency information of voltage waveforms. The most appropriate sub-band (node) for fault detection part is (4, 15) or the 30th node. This node has been selected based on various simulations in different fault conditions. Sa, Sb and Sc are the sum of 30th node coefficients, decomposed using db-4, during the last cycle, for A, B and C phases, respectively. Based on 200 kHz sampling frequency and 50 Hz power frequency each cycle consists of 4000 samples. The coefficient is calculated for each sample and sum is calculated in one cycle intervals. After calculating Sa, Sb and Sc, the absolute values of Sa–Sb, Sb–Sc, Sc–Sa should be calculated and compared with the threshold value, Sth. If any of these absolute values exceed Sth, the situation is recognized as a high impedance fault. In this algorithm, one cycle delay is added to increase protection security. In other words, if the absolute value is greater than the threshold value, for one cycle, the fault detection part raises a flag. In Fig. 3 ‘‘F’’ is the counter that counts samples. The value of ‘‘F’’ increases and as soon as it exceeds
Fig. 3. Flowchart of the proposed fault detection algorithm.
‘‘D’’ (number of samples in one cycle) this part of the algorithm raises a flag which means there is an HIF. In addition to the mentioned part, fault detection part, another section, zone discrimination, is also considered to fulfill a secure protection scheme. Selectivity requires that the protection scheme must be dependable in identifying faults, in its zones of protection. Fig. 4 shows the zone discrimination part of the algorithm. Zone discrimination part of the algorithm uses the current signals information to discriminate between internal and external faults. In this part, WPT coefficients from the (4, 0) elements of Ia, Ib, Ic, i.e. the 15th node, is used for HIF zone discrimination. The 15th node coefficients are selected for zone discrimination part, based on numerous simulation studies in different fault conditions. Averages of the sum values of these
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issued by the relay. The algorithm is also capable to provide an HIF backup protection for the downstream lines.
Application of proposed algorithm to the pilot protection schemes The zone discrimination part of the algorithm has capability of discrimination between different fault zones. In other words, the algorithm, not only detects the HIF occurrence, but also estimates the fault zone. This feature results in capability of the algorithm, to be applicable to different pilot protection schemes, which causes more security and dependability. The following sections describe the operation and zone sets, in DUTT, POTT and PUTT pilot protection systems. In the following sections, Z1R, Z2R and FR stand for zone-1, zone-2 and Fault detection output for the Remote end relay, respectively. Also, Z1L, Z2L and FL represent zone-1, zone-2 and Fault detection output of proposed relay for the Local relay, respectively. – DUTT scheme In this pilot protection plan, the relays are set to the underreaching zones. The proposed algorithm has the capability to be applied to this pilot protection mode. Fig. 5 shows the operating logic for this scheme. As Fig. 5 depicts, the trip command is sent to the breakers if either the local relay or the far end relay detect an HIF fault in their underreaching zone (zone-1). – POTT scheme In this pilot protection plan, the relays are set to the overreaching zones. In other words, the relays are set similar to zone-2. Fig. 6 shows the operating logic of this pilot protection scheme. In this case, the security is higher than DUTT scheme. In this scheme, only internal faults cause the both relays to operate, while external faults will be seen, only, by one of the relays and therefore the trip command is not initiated. – PUTT scheme Fig. 7 shows the operating logic of the PUTT pilot protection scheme. As mentioned, this plan is a combination of two previous ones. In PUTT, the relays operate for zone-2 faults, provided that they receive trip command from far end, as in POTT. Moreover, there is an extra part, which is the underreaching relay to provide a zone-1, instantaneous and direct tripping function to the local breakers. This scheme has the same security as the POTT scheme. However, dependability of PUTT is higher than POTT, due to the presence of underreaching zones.
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Fig. 4. Flowchart of the proposed zone discrimination algorithm.
coefficients are calculated during the last cycle. These averages are named Aa, Ab and Ac. These coefficients are calculated in both ends of the protected line. These values are compared with predefined threshold values, which separate the protection zones. The zone discrimination part is capable of local protection. In order to increase protection security, this protection algorithm utilizes a communications path to send trip signals from the relaying system, at one end of the line to the other end. Whenever, both fault detection and zone discrimination modules operate, a trip command is
Z1R FR FL Z1L Fig. 5. Pilot HIF protection logic applied to DUTT scheme.
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from the sending end (bus J). The fault type is single phase to ground HIF on phase A. As shown in Fig. 10, the difference value is a function of fault inception angle. In the next sections, the inception angle is considered to be p/12 radians, which produces the lower sum value, according to Fig. 10. If the threshold value is set to be 500, the calculated value will be greater than the threshold value for all fault inception angles with reasonable margin, considering dependability. This threshold value is also appropriate for other internal faults with different distances from the sending end. Effect of fault location
Z2R FR FL Z2L Fig. 6. Pilot HIF protection logic applied to POTT scheme.
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Different fault locations produce different sum values. Fig. 11 depicts the effect of HIF location on the sum values. As shown in the figure, the sum values are functions of fault location. Different fault locations are tested on both protected (JK) and adjacent lines (KL), to find a proper threshold value. Faults on the line JK are considered as internal faults, whereas faults on the line KL are external faults which should be discriminated. In all cases, the fault type is single phase to ground, and the fault inception angle is p/12 radians, which is almost the worst case according to Fig. 10. According to Fig. 11, the threshold value should be set less than 1000, in order to detect all desirable faults. Due to the p/12 radians inception angle, the sum values are greater than the considered threshold value, in other inception angles, with great margin, which is considered to guarantee the dependability. Assuming this threshold value, some out of zone faults may also be detected. This module is supposed to detect an HIF, either internal or external. The algorithm has the capability of operating as backup protection by setting fault detecting threshold value (Sth). Security of the algorithm is attained by the zone discrimination module which will be discussed in the future sections.
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Speed of the algorithm Fig. 7. Pilot HIF protection logic applied to PUTT scheme.
Simulation results and analysis In this section, simulation studies are performed on a simple system, with two transmission lines in series, as depicted in Fig. 8. In this way, capability of the proposed algorithm in discrimination between internal and external faults could be evaluated. JK is the main protected line, while KL is the downstream adjacent line. HIFs are simulated for different fault locations, types and inception angles in EMTP. In all cases, the fault occurs at 60 ms. Fig. 9 shows the voltage, current and node (4, 15) coefficients, respectively. These sample signals are related to a single phase to ground fault at 50% of the line length. In the following subsections, performance of the algorithm is analyzed in different HIF conditions. In this study, effects of fault location, fault inception angle and fault type will be considered. The results demonstrate the efficiency and accuracy of proposed algorithm in HIF protection. Effect of fault inception angle Fig. 10 depicts the difference value of Sa–Sb for different fault inception angles during one cycle. The fault is located at 30 km
Fig. 12 shows the absolute value of Sa–Sb, Sb–Sc, and Sc–Sa before and during the single phase to ground fault. In this case, phase A to ground HIF occurs at 30 (km), of protected line, from the sending end with p/12 radians inception angle. As shown in Fig. 12, the algorithm detects the high impedance fault in less than 0.005 s. This short detection time proves that the proposed scheme is suitable for real time application. However, to increase the security of the protective scheme, a minimum time delay is added to the algorithm. The algorithm raises a flag after detecting HIF and trip command is issued, once the zone discrimination module distinguished the fault as an internal fault. Faulted phase identification Fig. 12 shows the difference values for a single phase (A) to ground fault. As shown in the figure, a significant change is observed in the values of Sa–Sb and Sc–Sa while it is negligible about Sb–Sc. Similarly, for a fault on phase B, the significant change is observed in the values of Sa–Sb and Sb–Sc. Thus, for the single phase to ground HIFs, it is possible to identify the faulted phase by comparing the calculated difference values. In other words, the proposed method has the capability of identifying faulted phase. Therefore, the algorithm is also suitable for the applications where single pole tripping auto reclosing is required. Different fault types
Fig. 8. The simulated system.
Fig. 13 shows Sb–Sc for a phase to phase high impedance fault between phases B and C. The fault occurs at 30(km) from the sending end, and the inception angle is set to p/12 radians. As Fig. 13
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Fig. 11. Effect of fault location.
Fig. 10. Sa–Sb for different fault inception angles.
shows, the proposed algorithm detects the phase to phase fault as fast and accurate as the single phase HIF. Moreover, most of HIFs are single phase to ground. In some rare cases, an HIF occurred between two phases, due to an arc-associated tree bending over the conductors.
Zone discrimination In the zone discrimination part of the proposed algorithm, the coefficients of 15th nodes of the current waveforms should be extracted using WPT. Fig. 14 shows the average of sum values, for the coefficients of current signals, extracted from 15th node. The current signals are obtained from the CTs in bus J. In this figure, single phase to ground faults, with p/12 radians inception angle, is considered, which occur at different locations on both protected
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Fig. 14. Performance of the zone discrimination module (located in bus A).
mented, based on Fig. 7 of Section ‘Application of proposed algorithm to the pilot protection schemes’. Table 1 represents the algorithm output for different fault cases. The numbers in each cell are the algorithm output, and the number in parenthesis shows the corresponding logical output. Logical outputs are utilized in protection decision making stage. As table shows, the algorithm have high performance in protecting HIFs. For instance, case number 5 is a single phase A to ground fault which occurs at 90% of the line length. The parameters, Z1R, Z2R, Z1L, Z2L, FL, FR, and the final relay output are depicted in Fig. 15. As depicted in Fig. 15, although Z1L, the local zone1, is not able to detect this fault, operation of Z2L and Z1R units, initiate the relay output. Discussion
Fig. 12. Performance of the fault detection module for an internal fault (Sa–Sb, Sb– Sc, Sc–Sa).
Fig. 13. Performance of the fault detection module for a phase to phase fault (B–C).
and adjacent lines. As shown, the sum value has a relation with the fault location. The sum value decreases as the distance of fault increases. In order to increase the security of protection scheme, the threshold value of underreaching zone (zone-1) is set to 20% greater than minimum value of internal faults. Overreaching zone is considered to increase accuracy and selectivity of algorithm, which is similar to the zone-2 protection. The threshold value assigned to zone-2 is 30% less than minimum value for internal faults. Considering the mentioned overreaching and underreaching zones cause the algorithm to be applicable to different pilot protection schemes. This capability results in more security and dependability in HIF protection of transmission lines.
Results of PUTT implementation of the proposed algorithm In this section, results of the implementation of new approach, based on the PUTT concept are presented. The algorithm is imple-
This work presents an algorithm for high impedance fault protection on transmission lines. The proposed algorithm is based on the wavelet packet transform. The new WPT-based method has some significant advantage in comparison with previous works. The following important points should be considered about this HIF protection scheme: – The proposed algorithm is based on WPT, which is accurate due to its limited spectrum. While, in previous works, such as [3,7,21], the algorithm was based on DWT which may result in maloperations, due to the wide range of spectrum. The WPT accuracy causes more security and prevents malfunction. – The proposed algorithm is insensitive to fault type, fault location and fault inception angle, while in works as [5,8,16] the protection scheme are based on using Artificial Neural Networks (ANN), which is sensitive to different fault types and fault conditions. – The proposed HIF detection method has capability of detecting internal and external faults, which result in the capability of algorithm in operating as backup protection. While, in most of previous works the algorithms were proposed for fault detection and they were unable to classify internal and external faults [19–21]. As a result of zone discrimination capability, the proposed algorithm has capability of application to different pilot protection schemes. In this work, the pilot protection is employed to increase the security and dependability of new protection scheme. – The HIF detection part is based on HIFs transient and steady state signature of HIF. Therefore, the new algorithm is insensitive to the normal changes in the power flow of the line. – The algorithm has capability of detecting faulted phase, which supports the single pole tripping and auto-reclosing facility, while, most of previous methods [1–8] are not able to detect the faulted phase. – Due to the simplicity of proposed method, which is just based on WPT, without aid by any other technique such as ANN, fuzzy and intelligent systems, the fault detection part of algorithm is fast. HIFs are detected in less than 0.005 s.
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Table 1 Simulation results for different cases. Number
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53(1, 0) 47(1, 0) 42(1, 0) 36(1, 0) 31(0, 1) 25(0, 1) 43(1, 0) 32(0, 1) 25(0, 1)
31(0, 1) 36(1, 0) 42(1, 0) 48(1, 0) 52(1, 1) 0(0, 0) 41(1, 0) 53(1, 1) 0(0, 0)
1 1 1 1 1 0 1 1 0
Fig. 15. Output parameters of proposed algorithm (Z1R, Z2R, Z1L, Z2L, FL, FR, and Trip).
– The algorithm uses Daubechies family (Db4) as basis wavelet function, which is one of the famous wavelets, due to advantages such as easy implementation in digital relays and powerful performance in study of power system transients. Conclusion This paper presents a new HIF protection scheme for transmission lines using WPT. The algorithm uses voltage and current waveforms in fault detection and zone discrimination parts, respectively. The simulations are performed for a sample system with the Emanuel arc model based HIF model. An extensive series of simulations have been carried out to evaluate the performance of the proposed technique in EMTP. The security and dependability of proposed protection scheme are studied in different fault conditions with several simulations. The proposed algorithm is insensitive to fault conditions such as fault type, fault location and fault inception angle. Therefore, dependable and secure protection of the high impedance fault has been attained using WPT-based approach. References [1] Lai TM, Snider LA, Lo E, Sutanto D. High-impedance fault detection using discrete wavelet transform and frequency range and RMS conversion. IEEE Trans Power Deliv 2005;20(1):397–407. [2] Bakar AHA, Ali MS, Tan ChiaKwang, Mokhlis H, Arof H, Illias HA. High impedance fault location in 11 kV underground distribution systems using wavelet transforms. Int J Electr Power Energy Syst 2014;55:723–30. [3] Eldin EST, Aboul-Zahab EM, Saleh SM. Real time evaluation of DWT-based high impedance fault detection in EHV transmission. Electric Power Syst Res 2010;80(8):907–14. [4] Sedighi AR, Haghifam MR, Malik OP, Ghassemian MH. High impedance fault detection based on wavelet transform and statistical pattern recognition. IEEE Trans Power Deliv 2005;20(4):2414–21.
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A. Mahari, H. Seyedi / Electrical Power and Energy Systems 67 (2015) 537–545 [20] Sheng Y, Rovnyak SM. Decision tree-based methodology for high impedance fault detection. IEEE Trans Power Deliv 2004;19(2):533–6. [21] Etemadi AH, Sanaye-Pasand M. High-impedance fault detection using multiresolution signal decomposition and adaptive neural fuzzy inference system. IET Gener Trans Distrib 2008;2(1):110–8. [22] Nam SR, Park JK, Kang YC, Kim TH. A modeling method of a high impedance fault in a distribution system using two series time-varying resistances in EMTP. In: Power engineering society summer meeting, 2001, vol. 2. IEEE; 2001. p. 1175–80. [23] Aboul-Zahab EM, Eldin ES, Ibrahim DK, Saleh SM. High impedance fault detection in mutually coupled double-ended transmission lines using high frequency disturbances. In: Power system conference, 2008. MEPCON 2008. 12th IEEE international middle-east; March 2008. p. 412–9. [24] Sedighi AR, Haghifam MR. Simulation of high impedance ground fault In electrical power distribution systems. In: Power system technology (POWERCON). 2010 IEEE international conference; October 2010. p. 1–7.
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Contents lists available at ScienceDirect
Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes
High impedance fault protection in transmission lines using a WPT-based algorithm Arash Mahari ⇑, Heresh Seyedi 1 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
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Article history: Received 17 December 2013 Received in revised form 8 November 2014 Accepted 5 December 2014 Available online 26 December 2014 Keywords: High impedance fault Wavelet packet transform Pilot protection Zone discrimination
a b s t r a c t This paper proposes a new algorithm for High Impedance Fault (HIF) protection, in high voltage transmission lines, with the aid of Wavelet Packet Transform (WPT). The new scheme uses the HIF-induced distortion of voltage and current waveforms to detect HIF and discrimination of the fault location, respectively. The algorithm is based on a recursive method, which adds up the absolute values of high frequency signal coefficients, generated over one last cycle. Application of the proposed algorithm to the pilot protection schemes is also discussed. The proposed method is evaluated by Electro Magnetic Transients Program (EMTP) simulation studies. Several simulations, which are performed using an appropriate HIF model, bring about results which assess the proposed technique accuracy in identifying HIF in overhead transmission lines. A comprehensive simulation study shows the efficiency of the proposed protection scheme from the viewpoints of dependability and security. Ó 2014 Elsevier Ltd. All rights reserved.
Introduction A High Impedance Fault, typically, has a low current magnitude, which is often difficult to detect using conventional protection devices. HIF generally occurs when an energized conductor contacts to a surface with high resistance such as tree, dry ground, highly resistive soils or asphalt road. The detection of HIFs is critically important, since it may cause fires and danger to human beings [1]. HIFs on electrical transmission lines include arcing and nonlinear characteristics of fault impedance Therefore, the transients caused by the faults are appropriate features which make HIFs identifiable, using signal processing methods such as Wavelet Transform [2]. The shape of fault induced voltage and current waveforms, include some special features which are used in most of the HIF detection systems [3]. In recent years, several researches have presented many different techniques for detecting HIF, more efficiently. In [1–5], the presented algorithms are based on Discrete Wavelet Transform (DWT). A method is introduced in [6], which uses extra mechanical and electrical devices for HIF detection, thus, it is not proper economically. In [7], an HIF detection method with an appropriate ⇑ Corresponding author. 1
E-mail addresses: [email protected] (A. Mahari), [email protected] (H. Seyedi). Tel.: +98 (411) 339 3712.
http://dx.doi.org/10.1016/j.ijepes.2014.12.022 0142-0615/Ó 2014 Elsevier Ltd. All rights reserved.
arc model for extra high voltage (EHV) lines has been presented. In [8], a technique has been proposed based on wavelet packet transform with an Artificial Neural Network (ANN). This ANNbased method, focuses on HIF detection, rather than protection. In [8], ten cycles of signal is decomposed using WPT, which causes further delay in detection stage. Methods which are based on current asymmetry have been introduced in [9,10]. The main problem with the techniques, based on current asymmetry, is the similarity between normal operation behavior and HIF current waveforms in some cases. Some other algorithms, which have been presented for the HIF protection, are based on the low frequency signal analysis [11–13], ANN [14–17] and intelligent systems [18–21]. The main drawback of low frequency analysis group is their low security. Other system conditions, such as unbalanced load and switching, result in algorithms maloperations. The ANN based method rely on training stage. Improper training results in unreliable protection. Some of other methods are based on signal processing tools. Wavelet is one of the most efficient and high performance tools. WPT is a kind of wavelet, which analyses the signal in restricted frequency spectrum. Limited spectrum characteristic weakens the effect of other conditions (unfaulted) on the decision making. Therefore, it results in the high security of the algorithm. Using wavelet transforms in protection methods impose processing burden. However, nowadays, the digital relays are fast and efficient to handle such calculations.
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In this paper, an HIF detection technique, in transmission lines, is proposed. This technique uses voltage and current waveforms, supplied by voltage and current transformers, respectively. The detection process is executed through signal decomposition using Wavelet Packet Transform (WPT). The obtained WPT coefficients are compared with specified thresholds, during a specific time interval. This procedure forms the basis of a comprehensive decision logic. Due to WPT characteristic, the frequency spectrum is restricted but efficient for HIF protection. The main objective of proposed logic, using WPT, is to decrease the maloperations of HIF detection relays in the transient conditions. Various simulations, using EMTP, were executed to validate the performance of new method. The results, obtained from EMTP simulations, depict that the proposed scheme provides efficient fault detection in transmission lines. The results obviously show that the fault detection algorithm is insensitive to different fault types, fault location, fault current and fault inception angle. The zone discrimination module, clearly, discriminates the zone of fault location. A WPT-based algorithm identifies the fault zone. The proposed zone discrimination algorithm has capability to detect fault zone using local bus measurements. In order to increase protection security and dependability, the proposed algorithm is applied to the pilot protection schemes, such as Direct Underreaching Transfer Trip (DUTT), Permissive Overreaching Transfer Trip (POTT) and Permissive Underreaching Transfer Trip (PUTT). The rest of this paper is organized as follows. In Section ‘High impedance fault model’, high impedance fault model is explained. A brief review of WPT is presented in Section ‘Wavelet packet transform’. Section ‘Pilot protection’ is a brief discussion on the pilot protection. The proposed algorithm is presented in Section ‘The proposed algorithm’. Section ‘Simulation results and analysis’ includes the simulation results and analysis. Section ‘Discussion’ is a brief discussion on the proposed algorithm and obtained results. Finally, Section ‘Conclusion’ provides the conclusion.
High impedance fault model HIF is a very complex phenomenon, which introduces a highly nonlinear behavior. Stochastic nonlinear current has certain attributes in both transient and steady state parts, which makes it identifiable. The HIF current has four most important and significant characteristics, which are known as build-up, shoulder, nonlinearity and asymmetry. Build-up and shoulder characteristics exist only before the steady state, after HIF, while the other two characteristics, nonlinearity and asymmetry exist both before and during the steady state. An HIF current increases until it reaches the steady state value, gradually, which is called build-up. HIF current may stop increasing for a few cycles and then continue to increase again during the build-up stage [22]. Non-linearity features arise from the presence of odd harmonics. DC offset and asymmetric currents, with different magnitudes in the positive and negative half cycles, produce the asymmetry feature of current signal [23]. In other words, in an HIF, the surface which is in contact with the live conductor, shows different behaviors for negative and positive waveforms which is modeled by DC sources, with different values, in the HIF model, as shown in Fig. 1. The model which is used in this paper is presented in [24]. This model includes all HIF signatures, except shoulder, and supports all frequency components. The model simulates first eight cycles of an HIF. In This HIF model, which is based on Emanuel arc model, several arc models are used together to simulate HIF currents and voltage waveforms, similar to the real recorded HIF data from many different experimental tests, on distribution and transmission systems. Fig. 1 shows the applied HIF model [24].
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Fig. 1. HIF model based on the Emanuel arc model.
Wavelet packet transform Wavelet Packet Transform (WPT) is the generalized mode of DWT. Wavelet packet offers more complex and flexible analysis. In the DWT, just approximation component is decomposed while in the WPT, detailed components are decomposed, as well. In WPT, a signal is split into two high and low frequency parts, an approximation and a detail, in the first level, similar to the DWT. However, in contrast to the DWT, in upper levels, both details and approximations are decomposed again, in WPT. This approach forms a binary tree, as depicted in Fig. 2. The sampled signal is decomposed into d1 and a1 like DWT, at the first stage. In Fig. 2, nodes number 1 and 2 refer to a1 and d1, respectively. In the second level, decomposition will result in four sub-bands due to the decomposition of both d1 and a1. Four subbands in level two are named (2, 0), (2, 1), (2, 2) and (2, 3) which are designated as nodes 3, 4, 5 and 6, respectively, as shown in Fig. 2 [25,26]. Hence, the DWT is a sub-tree of the WPT tree. The most significant benefit of the WPT, over other types of wavelet transforms, is the accurate and detailed representation of decomposed signals in limited spectrum which makes it useful in signal processing. [8]. The efficiency of WPT, as other WT forms, is highly dependent on the wavelet basis functions, called mother wavelet. Several basis functions, can be selected as a mother wavelet, such as Daubechies (Db), Symlets, Coiflets and Biorthogonals [27]. In this paper, Daubechies-4 (Db4) is selected as the mother wavelet. Daubechies wavelet family is one of the most proper orthogonal wavelets, due to some advantages, such as powerful performance and very easy implementation in digital systems [28]. Pilot protection In the conventional line protection, fast protection from both ends of a transmission line is almost impossible, if the fault is close to end of the line. Pilot relaying systems utilize a communications
Fig. 2. Tree decomposition of the proposed wavelet packet analysis.
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link to transmit signals between two terminals of the line. This method provides more dependability for the protection systems, since information from both ends of the line is available for processing [29,30]. One of the important classes of pilot protection schemes is the transfer trip class. In the transfer trip schemes, the relays at both ends of the line, recognizing a fault within the set protection zones, will send a trip signal to the relay at the remote end of the line. In other words, transfer trip pilot protection is formed to provide high-speed tripping of faults at every point of the line length, and also to provide the benefits of backup protection for adjacent line sections. The design of transfer trip schemes can either be direct or permissive. Direct schemes send a signal from one end to the remote end that indicates a mandatory trip and the trip is initiated without additional checking or delay. Permissive systems oversee the transfer trip signal by monitoring the line condition to see if a fault is detected, even if it is not in the first zone. Direct Underreaching Transfer Trip (DUTT), Permissive Overreaching Transfer Trip (POTT) and Permissive Underreaching Transfer Trip (PUTT) are the transfer trip pilot protection schemes which are utilized in this work [29,30]. The basic concept in DUTT is that, each relay sends a trip signal to the relay at the other end if a zone-1 fault is detected, in addition to sending a trip signal to the local circuit breakers. In POTT, each relay waits for the trip from the far end relay. In this scheme, the protection relays send a trip signal to far end relays, as they detect a fault. However, they do not send trip signal to local breakers, unless they receive trip signal from far end relays. Combining two previous pilot protection schemes, DUTT and POTT, results in a more secure and faster pilot protection which is named PUTT. The zones of the relay devices are similar to those represented in previous one, except that a second set of instantaneous elements are employed. In this pilot protection scheme, as in POTT, the relays in both ends send trip signal to remote end, as they detect a fault in their protection zones. In addition, the relays send trip signal to local breakers, as they detect a fault in first zone. In other words, the relays operate similar to DUTT for zone-1 faults, while they operate similar to POTT for faults in the overreaching protection zone. The proposed algorithm The proposed algorithm includes two parts, fault detection and zone discrimination. This method is based on analyzing voltage and current waveforms, obtained from voltage and current transformers. The sampling frequency is 200 kHz and, as mentioned in last section, the high frequency information of signals is extracted by wavelet packet transform, using the Daubechies-4 wavelet (db4). Figs. 3 and 4 show the algorithm flowchart. The fault detection part uses the high frequency information of voltage waveforms. The most appropriate sub-band (node) for fault detection part is (4, 15) or the 30th node. This node has been selected based on various simulations in different fault conditions. Sa, Sb and Sc are the sum of 30th node coefficients, decomposed using db-4, during the last cycle, for A, B and C phases, respectively. Based on 200 kHz sampling frequency and 50 Hz power frequency each cycle consists of 4000 samples. The coefficient is calculated for each sample and sum is calculated in one cycle intervals. After calculating Sa, Sb and Sc, the absolute values of Sa–Sb, Sb–Sc, Sc–Sa should be calculated and compared with the threshold value, Sth. If any of these absolute values exceed Sth, the situation is recognized as a high impedance fault. In this algorithm, one cycle delay is added to increase protection security. In other words, if the absolute value is greater than the threshold value, for one cycle, the fault detection part raises a flag. In Fig. 3 ‘‘F’’ is the counter that counts samples. The value of ‘‘F’’ increases and as soon as it exceeds
Fig. 3. Flowchart of the proposed fault detection algorithm.
‘‘D’’ (number of samples in one cycle) this part of the algorithm raises a flag which means there is an HIF. In addition to the mentioned part, fault detection part, another section, zone discrimination, is also considered to fulfill a secure protection scheme. Selectivity requires that the protection scheme must be dependable in identifying faults, in its zones of protection. Fig. 4 shows the zone discrimination part of the algorithm. Zone discrimination part of the algorithm uses the current signals information to discriminate between internal and external faults. In this part, WPT coefficients from the (4, 0) elements of Ia, Ib, Ic, i.e. the 15th node, is used for HIF zone discrimination. The 15th node coefficients are selected for zone discrimination part, based on numerous simulation studies in different fault conditions. Averages of the sum values of these
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issued by the relay. The algorithm is also capable to provide an HIF backup protection for the downstream lines.
Application of proposed algorithm to the pilot protection schemes The zone discrimination part of the algorithm has capability of discrimination between different fault zones. In other words, the algorithm, not only detects the HIF occurrence, but also estimates the fault zone. This feature results in capability of the algorithm, to be applicable to different pilot protection schemes, which causes more security and dependability. The following sections describe the operation and zone sets, in DUTT, POTT and PUTT pilot protection systems. In the following sections, Z1R, Z2R and FR stand for zone-1, zone-2 and Fault detection output for the Remote end relay, respectively. Also, Z1L, Z2L and FL represent zone-1, zone-2 and Fault detection output of proposed relay for the Local relay, respectively. – DUTT scheme In this pilot protection plan, the relays are set to the underreaching zones. The proposed algorithm has the capability to be applied to this pilot protection mode. Fig. 5 shows the operating logic for this scheme. As Fig. 5 depicts, the trip command is sent to the breakers if either the local relay or the far end relay detect an HIF fault in their underreaching zone (zone-1). – POTT scheme In this pilot protection plan, the relays are set to the overreaching zones. In other words, the relays are set similar to zone-2. Fig. 6 shows the operating logic of this pilot protection scheme. In this case, the security is higher than DUTT scheme. In this scheme, only internal faults cause the both relays to operate, while external faults will be seen, only, by one of the relays and therefore the trip command is not initiated. – PUTT scheme Fig. 7 shows the operating logic of the PUTT pilot protection scheme. As mentioned, this plan is a combination of two previous ones. In PUTT, the relays operate for zone-2 faults, provided that they receive trip command from far end, as in POTT. Moreover, there is an extra part, which is the underreaching relay to provide a zone-1, instantaneous and direct tripping function to the local breakers. This scheme has the same security as the POTT scheme. However, dependability of PUTT is higher than POTT, due to the presence of underreaching zones.
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Fig. 4. Flowchart of the proposed zone discrimination algorithm.
coefficients are calculated during the last cycle. These averages are named Aa, Ab and Ac. These coefficients are calculated in both ends of the protected line. These values are compared with predefined threshold values, which separate the protection zones. The zone discrimination part is capable of local protection. In order to increase protection security, this protection algorithm utilizes a communications path to send trip signals from the relaying system, at one end of the line to the other end. Whenever, both fault detection and zone discrimination modules operate, a trip command is
Z1R FR FL Z1L Fig. 5. Pilot HIF protection logic applied to DUTT scheme.
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from the sending end (bus J). The fault type is single phase to ground HIF on phase A. As shown in Fig. 10, the difference value is a function of fault inception angle. In the next sections, the inception angle is considered to be p/12 radians, which produces the lower sum value, according to Fig. 10. If the threshold value is set to be 500, the calculated value will be greater than the threshold value for all fault inception angles with reasonable margin, considering dependability. This threshold value is also appropriate for other internal faults with different distances from the sending end. Effect of fault location
Z2R FR FL Z2L Fig. 6. Pilot HIF protection logic applied to POTT scheme.
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Different fault locations produce different sum values. Fig. 11 depicts the effect of HIF location on the sum values. As shown in the figure, the sum values are functions of fault location. Different fault locations are tested on both protected (JK) and adjacent lines (KL), to find a proper threshold value. Faults on the line JK are considered as internal faults, whereas faults on the line KL are external faults which should be discriminated. In all cases, the fault type is single phase to ground, and the fault inception angle is p/12 radians, which is almost the worst case according to Fig. 10. According to Fig. 11, the threshold value should be set less than 1000, in order to detect all desirable faults. Due to the p/12 radians inception angle, the sum values are greater than the considered threshold value, in other inception angles, with great margin, which is considered to guarantee the dependability. Assuming this threshold value, some out of zone faults may also be detected. This module is supposed to detect an HIF, either internal or external. The algorithm has the capability of operating as backup protection by setting fault detecting threshold value (Sth). Security of the algorithm is attained by the zone discrimination module which will be discussed in the future sections.
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Speed of the algorithm Fig. 7. Pilot HIF protection logic applied to PUTT scheme.
Simulation results and analysis In this section, simulation studies are performed on a simple system, with two transmission lines in series, as depicted in Fig. 8. In this way, capability of the proposed algorithm in discrimination between internal and external faults could be evaluated. JK is the main protected line, while KL is the downstream adjacent line. HIFs are simulated for different fault locations, types and inception angles in EMTP. In all cases, the fault occurs at 60 ms. Fig. 9 shows the voltage, current and node (4, 15) coefficients, respectively. These sample signals are related to a single phase to ground fault at 50% of the line length. In the following subsections, performance of the algorithm is analyzed in different HIF conditions. In this study, effects of fault location, fault inception angle and fault type will be considered. The results demonstrate the efficiency and accuracy of proposed algorithm in HIF protection. Effect of fault inception angle Fig. 10 depicts the difference value of Sa–Sb for different fault inception angles during one cycle. The fault is located at 30 km
Fig. 12 shows the absolute value of Sa–Sb, Sb–Sc, and Sc–Sa before and during the single phase to ground fault. In this case, phase A to ground HIF occurs at 30 (km), of protected line, from the sending end with p/12 radians inception angle. As shown in Fig. 12, the algorithm detects the high impedance fault in less than 0.005 s. This short detection time proves that the proposed scheme is suitable for real time application. However, to increase the security of the protective scheme, a minimum time delay is added to the algorithm. The algorithm raises a flag after detecting HIF and trip command is issued, once the zone discrimination module distinguished the fault as an internal fault. Faulted phase identification Fig. 12 shows the difference values for a single phase (A) to ground fault. As shown in the figure, a significant change is observed in the values of Sa–Sb and Sc–Sa while it is negligible about Sb–Sc. Similarly, for a fault on phase B, the significant change is observed in the values of Sa–Sb and Sb–Sc. Thus, for the single phase to ground HIFs, it is possible to identify the faulted phase by comparing the calculated difference values. In other words, the proposed method has the capability of identifying faulted phase. Therefore, the algorithm is also suitable for the applications where single pole tripping auto reclosing is required. Different fault types
Fig. 8. The simulated system.
Fig. 13 shows Sb–Sc for a phase to phase high impedance fault between phases B and C. The fault occurs at 30(km) from the sending end, and the inception angle is set to p/12 radians. As Fig. 13
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shows, the proposed algorithm detects the phase to phase fault as fast and accurate as the single phase HIF. Moreover, most of HIFs are single phase to ground. In some rare cases, an HIF occurred between two phases, due to an arc-associated tree bending over the conductors.
Zone discrimination In the zone discrimination part of the proposed algorithm, the coefficients of 15th nodes of the current waveforms should be extracted using WPT. Fig. 14 shows the average of sum values, for the coefficients of current signals, extracted from 15th node. The current signals are obtained from the CTs in bus J. In this figure, single phase to ground faults, with p/12 radians inception angle, is considered, which occur at different locations on both protected
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Fig. 14. Performance of the zone discrimination module (located in bus A).
mented, based on Fig. 7 of Section ‘Application of proposed algorithm to the pilot protection schemes’. Table 1 represents the algorithm output for different fault cases. The numbers in each cell are the algorithm output, and the number in parenthesis shows the corresponding logical output. Logical outputs are utilized in protection decision making stage. As table shows, the algorithm have high performance in protecting HIFs. For instance, case number 5 is a single phase A to ground fault which occurs at 90% of the line length. The parameters, Z1R, Z2R, Z1L, Z2L, FL, FR, and the final relay output are depicted in Fig. 15. As depicted in Fig. 15, although Z1L, the local zone1, is not able to detect this fault, operation of Z2L and Z1R units, initiate the relay output. Discussion
Fig. 12. Performance of the fault detection module for an internal fault (Sa–Sb, Sb– Sc, Sc–Sa).
Fig. 13. Performance of the fault detection module for a phase to phase fault (B–C).
and adjacent lines. As shown, the sum value has a relation with the fault location. The sum value decreases as the distance of fault increases. In order to increase the security of protection scheme, the threshold value of underreaching zone (zone-1) is set to 20% greater than minimum value of internal faults. Overreaching zone is considered to increase accuracy and selectivity of algorithm, which is similar to the zone-2 protection. The threshold value assigned to zone-2 is 30% less than minimum value for internal faults. Considering the mentioned overreaching and underreaching zones cause the algorithm to be applicable to different pilot protection schemes. This capability results in more security and dependability in HIF protection of transmission lines.
Results of PUTT implementation of the proposed algorithm In this section, results of the implementation of new approach, based on the PUTT concept are presented. The algorithm is imple-
This work presents an algorithm for high impedance fault protection on transmission lines. The proposed algorithm is based on the wavelet packet transform. The new WPT-based method has some significant advantage in comparison with previous works. The following important points should be considered about this HIF protection scheme: – The proposed algorithm is based on WPT, which is accurate due to its limited spectrum. While, in previous works, such as [3,7,21], the algorithm was based on DWT which may result in maloperations, due to the wide range of spectrum. The WPT accuracy causes more security and prevents malfunction. – The proposed algorithm is insensitive to fault type, fault location and fault inception angle, while in works as [5,8,16] the protection scheme are based on using Artificial Neural Networks (ANN), which is sensitive to different fault types and fault conditions. – The proposed HIF detection method has capability of detecting internal and external faults, which result in the capability of algorithm in operating as backup protection. While, in most of previous works the algorithms were proposed for fault detection and they were unable to classify internal and external faults [19–21]. As a result of zone discrimination capability, the proposed algorithm has capability of application to different pilot protection schemes. In this work, the pilot protection is employed to increase the security and dependability of new protection scheme. – The HIF detection part is based on HIFs transient and steady state signature of HIF. Therefore, the new algorithm is insensitive to the normal changes in the power flow of the line. – The algorithm has capability of detecting faulted phase, which supports the single pole tripping and auto-reclosing facility, while, most of previous methods [1–8] are not able to detect the faulted phase. – Due to the simplicity of proposed method, which is just based on WPT, without aid by any other technique such as ANN, fuzzy and intelligent systems, the fault detection part of algorithm is fast. HIFs are detected in less than 0.005 s.
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Table 1 Simulation results for different cases. Number
Fault type
Distance
Local fault detection output (FL)
Remote fault detection output (FR)
Local zone discrimination output ⁄ 103 (Z1L, Z2L)
Remote zone discrimination output ⁄ 103 (Z1R, Z2R)
Trip
1 2 3 4 5 6 7 8 9
AG AG AG AG AG AG BC BC BC
10 30 50 70 90 120 50 90 120
4500(1) 2540(1) 1330(1) 1390(1) 1170(1) 600(1) 2490(1) 2055(1) 890(1)
1210(1) 1405(1) 1390(1) 2620(1) 4440(1) 3250(1) 2580(1) 7540(1) 6780(1)
53(1, 0) 47(1, 0) 42(1, 0) 36(1, 0) 31(0, 1) 25(0, 1) 43(1, 0) 32(0, 1) 25(0, 1)
31(0, 1) 36(1, 0) 42(1, 0) 48(1, 0) 52(1, 1) 0(0, 0) 41(1, 0) 53(1, 1) 0(0, 0)
1 1 1 1 1 0 1 1 0
Fig. 15. Output parameters of proposed algorithm (Z1R, Z2R, Z1L, Z2L, FL, FR, and Trip).
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