Field experiment using transient energy method to locate a single-phase to ground fault

Wei Xie1,Xuewen Wang2, 3,Chen Fang4,Hengxu Zhang3,Fang Shi3*,Xiaodong Xing3,Baicong Sun3

1.State Grid Shanghai Municipal Electric Power Company,No.1122 Yuanshen Road,Shanghai 200122,P.R.China

2.State Grid Chongqing Electric Power Research Institute,No.80 Huangshan Road,Chongqing 401123,P.R.China

3.Key Laboratory of Power System Intelligent Dispatch and Control (Ministry of Education),Shandong University,No.17923 Jingshi Road,Jinan 250061,P.R.China

4.State Grid Shanghai Electric Power Research Institute,No.171 Handan Road,Shanghai 200233,P.R.China

Abstract:Distribution networks in China and several other countries are predominantly neutral inefficiently grounding systems (NIGSs),and more than 80% of the faults in distribution networks are single-phase-to-ground (SPG) faults.Because of the weak fault current and imperfect monitoring equipment configurations,methods used to determine the faulty line sections with SPG faults in NIGSs are ineffective.The development and application of distribution-level phasor measurement units (PMUs) provide further comprehensive fault information for fault diagnosis in a distribution network.When an SPG fault occurs,the transient energy of the faulted line section tends to be higher than the sum of the transient energies of other line sections.In this regard,transient energy-based fault location algorithms appear to be a promising resolution.In this study,a field test plan was designed and implemented for a 10 kV distribution network.The test results demonstrate the effectiveness of the transient energy-based SPG location method in practical distribution networks.

Keywords:Single-phase-to-ground fault,Fault location,Neutral inefficiently grounding systems,Distribution network,Distribution-level PMU,Transient energy.

0 Introduction

Several statistics show that single-ph ase-to-ground(SPG) faults constitute 80% of the faults in a distribution network.In China,a large proportion of the distribution networks are neutral inefficiently grounding systems(NIGSs) [1,2].The fault current is the total sum of the ground capacitance currents of all the lines in an entire network.The fault current is weak,and the line voltage of the system remains unchanged.The system can be operated for a certain period to ensure a continuous power supply to the load.However,a long-term over-voltage leads to insulation breakdown.In addition,SPG faults can become phase-to-phase faults,which trip the circuit breaker,thereby causing power interruption and affecting the reliability of the power supply [3,4].Regulations pertaining to current distribution networks demand rapid and accurate identification of faults,determination of fault locations,and isolation of fault areas.However,the available technology for identifying the locations of faulted line sections cannot satisfy the aforementioned requirements.

The existing methods for determining faulty line section can be divided into two types based on the different signals used:active and passive methods.The active methods involve injecting a specific signal into the system or changing the network parameters after a fault.The faulted line section is identified by detecting the distribution of the injected signal in the system,essentially by increasing the faulty current [5-7].However,injecting signals or changing network parameters may aggravate the fault.The passive methods utilize the voltage and current signals generated by the fault to extract the fault characteristics,design the location algorithm,and identify the faulted line section.The passive methods can be further divided into methods that utilize steady-state signals [8,9]and those that utilize transient signals [10,11].

In [12],the steady states prior to and after the fault were analyzed and used for fault detection in the distribution networks with distribution generators (DGs ).In [13,14]the directions of the zero-sequence power and the zerosequence impedance were extracted,respectively,and were used for determining fault locations in an NIGS.The applicability of methods based on steady-state signals is limited to cases involving weak fault signals,and certain methods are unsuitable for resonant grounded systems.In [15],the transient reactive power direction method was proposed to locate faulty sections by comparing the differences in the transient reactive power direction on both sides of each line section.In [16,17],the transient zerosequence current waveform similarities were compared on the two sides of all sections to identify the faulty section.The method based on transient signals requires high sampling frequencies and synchronization of the equipment and has limited applicability.Certain methods based on the traveling wave triggered by a fault also exist;however,these methods require high sampling frequencies,which entail considerable expenses and are impracticable at present[18,19].Moreover,certain methods require expensive phase voltage measurements at each point and are currently unattainable in China.To extract the fault characteristics and improve the fault tolerance of methods for identifying faulted line sections,a series of methods based on artificial intelligence algorithms,such as ant colony algorithm,have been used [20,21].The methods based on artificial intelligence algorithms do not analyze the problem using a physical model,and their effectiveness is limited by the quantity and quality of the training samples.In general,weak fault currents,intense background noise,and imperfect detection device configurations in NIGSs complicate the identification of line sections with SPG faults.

The successful development of the distribution-level PMU (D-PMU) has provided further comprehensive fault information support for fault diagnosis in a distribution network [22].The two primary advantages of the D-PMU are as follows:(i) the D-PMU,which can be installed in a distribution network,has a simple structure and is inexpensive [23],(ii) and the installation location is not limited to power plants and substations.In addition,the D-PMU has a high sampling frequency,and the synchronization waveform and synchronization phasor of each node of the distribution network can be obtained.Thus,the D-PMU has an increasing application potential[24]and can provide more fault information than traditional measurement devices can.

The transient zero-sequence current in the special frequency band (SFB) of a faulted line section is equal to the sum of the transient zero-sequence currents in the SFBs of all healthy line sections [25].Hence,the transient energy of a faulted line section is higher than the sum of the transient energies of the remaining line sections.In this study,a method for determining the locations of faulted line sections based on the transient energy is evaluated in a practical distribution network,and a corresponding verification method is designed.After embedding the algorithm into the distribution automation system,the corresponding interface and procedures are designed.The method is tested and verified in a 10 kV distribution network.Experiments are performed,and the results show that the method can accurately determine fault locations.

The rest of the paper is organized as follow.Section 1 briefly introduces the characteristics of the SPG fault.Section 2 illustrates the basic procedures of the transient energy based fault location method.In Section 3,a filed test experiment is illustrated and the results are given.The conclusions are drawn in Section 4.

1 Analysis of transient zero-sequence current of SPG fault

The designed algorithm is presented herein.Additional details can be found in [26].When analyzing the phasefrequency characteristics of a zero-sequence network in a multiple-line distribution network,the neutral ungrounded system can be regarded as a zero-sequence network composed of multiple open-ended lines in parallel,and the resonant grounded system can be regarded as a zerosequence network formed by connecting a line with an inductive load at the end and multiple open-ended lines in parallel.The upper cut-off frequency of the SFB of the transient zero-sequence current is determined by the longest line in the equivalent zero-sequence network.The lower cut-off frequency is determined using the neutral grounding method.Therefore,

where fk ,L is the upper cut-off frequency,and fs is the fundamental frequency of the ,L is calculated as follows:

where L is the length of the longest line in the equivalent zero-sequence network,and L0 and C0 are the zero-sequence inductance and capacitance per unit length,respectively.

The SFB component of the zero-sequence current flowing into the ground leads the voltage of the corresponding frequency by 90° in a healthy line section and lags the voltage of the corresponding frequency by 90°in a faulted line section [27,28].The SFB component of the zero-sequence current flowing into a faulted line section is the sum of the SFB components of the zero-sequence currents flowing into the ground from all healthy line sections.

Based on this information,considering a multi-branch distribution network with n line sections as an example,when an SPG fault occurs in line section m,the k-th sampling point from the beginning of the fault satisfies the following equation:

where i0i is the SFB component of zero-sequence current in line section i.Based on the amplitude relationship between the SFB components of healthy and faulted line sections shown in (3),the following equations are obtained:

where N is the number of sampling points after the fault. is the largest value when m is the faulty section,and the following expression is obtained:

For convenience,the definition of transient energy is provided herein.Taking line section j as an example,its transient energy is calculated as

where N is often taken as the number of sampling points within four cycles after the fault.

Therefore,the sufficient and necessary condition for an SPG fault in section m is

2 Transient energy-based method for identifying faulted line sections

For a multi-branch distribution network,the identification of a faulted line section based on the transient energy principle involves the following four steps [25]:

1) Designing digital filters:Based on the topology of the network and the neutral grounding method,(1) is used to determine the SFB of the network and design a digital filter.When calculating the cut-off frequency for the SFB,L is taken as the diameter of the zero-sequence network topology.

2) Recording the fault and uploading the waveform:When the criterion for commencing the SPG fault recording is satisfied (for instance,when the amplitude of the zerosequence voltage phasor of the substation is higher than 0.1-0.15 times the rated phase voltage),fault recording is initiated,and the data are uploaded to commence the fault identification procedure.

3) Calculating the transient energy:The direction from the bus to the end of a line is specified as the positive direction of the line.The difference between the transient zero-sequence currents measured at the upstream and downstream nodes represents the transient zero-sequence current of each line section.The zero-sequence current of each line section is filtered using a digital filter,and the SFB component of the zero-sequence current of each line section is obtained.Furthermore,the transient energy of each line section is obtained using (7).

4) Identifying the faulted line section:Based on the transient energy of each line section,the largest transient energy is determine,and the corresponding line section is denoted as m.If the transient energy of line section m exceeds the sum of the transient energies of the other line sections,then line section m is the faulted line section.

For a distribution network with multiple lines,after the faulted line is identified,only the transient energy of each line section of the faulted line must be obtained.The faulted line section is assessed in terms of whether RRoE is greater than 1.

3 Field test verification

3.1 Overview

The verification of the faulted line section method was implemented at a 35 kV station including 10 kV lines under its jurisdiction.According to the placement principles [29,30],14 D-PMUs were deployed,and the network was divided into 14 line sections,as shown in Fig.1.A manual SPG fault for the 35 kV neutral resonant grounded system was arranged at the location,which is also shown in Fig.1.

Fig.1 Schematic of the project network

3.2 Test Plans

The artificial fault point is shown in Fig.1,which is located near 4128 electric pole.The electric pole near the fault point is shown in Fig.2.The test plan was prepared,and appropriate safety measures were adopted to ensure a safe and reliable test process.

Fig.2 Field test conditions

The test operator constructed a temporary grounding grid,an artificial grounding platform,and a fuse platform;the wiring was checked by an assigned technician.The overall plan of the experiment is shown in Fig.3.

Fig.3 Experimental layout for artificial SPG fault experiment

After the insulated wire access work was completed,the lead was pulled 45° obliquely,and a safe distance of 2 m was maintained from the surrounding to the wire.The test operator wore insulating gloves,stood on the insulating blanket,and performed the tasks as directed by the supervisor for the experiment.The tester gradually moved the dedicated grounding operating lever close to the live copper bar on the artificial grounding platform until a reliable contact was achieved.The current flowing through the grounding wire during the short-circuit was estimated to be within 30 A.However,the current was higher than 1 A,which is more than the threshold value of the fusing current and less than the setting current value for protective relays.This caused an instant fuse blow,and the fusing time was between 100 ms and 500 ms with no relay trigger.Therefore,the electricity supply was not affected.Based on the data obtained using the D-PMU system,the faulty section wasidentified.The test was repeated by replacing the fuse.Two SPG fault tests were then performed.Fig.4 shows the fault test site and fault conditions.

3.3 Results and discussions

Fig.4 Fault test environment and fault-triggering method

The data recorded during the first fault test are shown in Fig.5.No phase voltage measurement was recorded on the feeder.The three-phase voltage,zero-sequence voltage,three-phase current,and zero-sequence current at the feeder output,along with the three-phase and zero-phase currents at measurement point 3316 are presented.The bus voltage and zero-sequence current in the line changed significantly when the fault occurred.

After the fault had occurred,it was detected based on the zero-sequence voltage,and the faulted line section was identified based on the recorded data for the zero-sequence current in the line.Using the transient zero-sequence current in the SFB,the transient energies of each line section after the fault occurrence were calculated,and the results are listed in Table1.The transient energy in line section 4 was the highest,and RRoE was 3.33.Therefore,line section 4 was determined to be the faulted line section,which was indeed the actual faulted line section.Thus,the proposed method determined the fault location correctly.

Table1 Transient energy of each line section in Test 1

No.1 2 3 4 5 6 7 TE 5.4E-1 2.7E-4 1.0E-3 1.8 7.7E-6 5.4E-6 3.8E-5 No.8 9 10 11 12 13 14 TE 1.1E-4 1.2E-6 5.7E-7 1.1E-6 3.2E-7 7.1E-7 1.1E-6

The recorded data for the second fault test are shown in Fig.6.Measurement signals similar to those in Test 1 were plotted.The bus voltage and zero-sequence current in the line changed after the fault.

Procedures similar to those employed in Test 1 were followed in Test 2,and the results are listed in Table2.The results were identical to those of Test 1,which verified the effectiveness of the proposed method.

Table2 Transient energy of each line section in Test 2

No.1 2 3 4 5 6 7 TE 5.5E-1 3.1E-4 1.0E-3 1.81 7.8E-6 5.5E-6 4.0E-5 No.8 9 10 11 12 13 14 TE 1.1E-4 2.1E-6 8.4E-7 2.4E-6 5.1E-7 7.4E-7 1.0E-6

After determining the faulted line section,the D-PMU surrounding the faulted section on the monitoring interface changed from green to red,as shown in 7 The transient energy- based SPG location method operated normally and met the design requirements.

For the two experiments,the waveforms of the zerosequence current were different.For the first fault,there was only one surge in the current.However,multiple surges were observed in the second experiment.This was because in the first experiment,a quick touch triggered the fault seamlessly.Thus,the current surged as the fault occurred and then disappears as the fuse broke.In the second experiment,the lever quivered during the touch,producing three successive touches,which produced multiple current surges.

Fig.5 Recorded waveforms in first experiment

Fig.6 Recorded waveforms in second experiment

4 Conclusions

In this study,a method for identification of faulted line sections based on transient energy was developed and embedded in a distribution automation system.To test the effectiveness of the method,a field testing experiment was designed.An artificial SPG fault was triggered in an actual 10-kV network.The results proved the feasibility and effectiveness of the designed experiment.

Fig.7 Identified fault location in the fault diagnosis software

Only the SPG fault is designed and performed in the experiment.And the fault is trigger manually.In the future,the experiment for the high resistance arcing fault should be designed and tested.The automatic devices for triggering the faults are also need to be invented.


National Key R&D Program of China (2017YFB0902800)and Science and Technology Project of State Grid Corporation of China (52094017003D) supported this work.

Declaration of Competing Interest

We declare that we have no conflict of interest.


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Received:2 June 2020/Accepted:16 July 2020/Published:25 December 2020

Fang Shi

Wei Xie

Xuewen Wang

Chen Fang

Hengxu Zhang

Xiaodong Xing

Baicong Sun

2096-5117/© 2020 Global Energy Interconnection Development and Cooperation Organization.Production and hosting by Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.This is an open access article under the CC BY-NC-ND license (


Wei Xie received the from Shanghai Jiaotong University in 1990.He is currently the Chief Engineer with the State Grid Shanghai Municipal Electric Power Company.His current research interests include renewable energy integration of smart grid and power storage technology and management of the power supply company.

Xuewen Wang received the B.E.and in electrical engineering from Shandong University in 2017 and 2020.He is currently working for State Grid Chongqing Electric Power Research Institute.His research interest includes fault location for distribution networks and power system simulation.

Chen Fang received the B.Sc.and Ph.D.degrees from the Department of Electrical Engineering,Tsinghua University,Beijing,China,in 2006 and 2011,respectively.He is currently an Electrical Engineer with the Electric Power Research Institute,State Grid Shanghai Municipal Electric Power Company,Shanghai,China.His current research interests include renewable energy integration of smart grid and power storage technology.

Hengxu Zhang received his in electrical engineering from Shandong University of Technology,in 1998,and his M.S.and electrical engineering from Shandong University,in 2000 and 2003,respectively.He is now a professor with the Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education (Shandong University),P.R.China.His main research interests are power system security and stability assessment,power system monitoring and numerical simulation.

Fang Shi received the from Shanghai Jiao Tong University,Shanghai,China,2014.

He is currently a associate professor in the Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education (Shandong University),P.R.China.His research interests include theory and applications of D-PMU,and power system stability and control.

Xiaodong Xing received the bachelor and master degrees at Shandong University,Jinan,in 2017 and 2020,respectively.He is working in Yunnan Power Grid Co.,Ltd.,Kunming.His research interests include fault detection and diagnosis of distribution network.Baicong Sun received the bachelor and master degrees at Shandong University,Jinan,in 2018 and 2020,respectively.He is working in Shenzhen Power Supply Bureau Co.,Ltd.,Shenzhen.His research interests include fault detection and diagnosis of power system.

(Editor Yanbo Wang)