High impedance faults: from field tests to modeling

DOI 10.1007/s40313-013-0072-8

High Impedance Faults: From Field Tests to Modeling

Núbia Silva Dantas Brito· Flávio Bezerra Costa · Marcelo Renato Cerqueira Paes Jr

Received: 23 April 2012 / Revised: 23 January 2013 / Accepted: 9 August 2013 / Published online: 18 September 2013 © Brazilian Society for Automatics–SBA 2013

Abstract High impedance faults (HIFs) are serious and troubling disturbances on power distribution systems because the main power system protection devices are usually not able to diagnose them accurately due to the low fault current levels. This paper presents the detailing of field experiments and modeling of HIF. A literature review of models of HIF was made and it was proposed to use a model known in the literature with some adjustments. With the model, based on actual records obtained at different contact surfaces, it was possible to obtain a set of simulated records representing the most important features found in most of the HIF.

W. C. dos Santos (

B

PostGraduate Program in Electrical Engineering PPgEE -COPELE, Federal University of Campina Grande (UFCG), Aprígio Veloso Street, 882, Universitário, Campina Grande, Paraíba CEP 58.429-900, Brazil

e-mail: wellincsantos@gmail.com

B. A. de Souza· N. S. D. Brito

Electrical Engineering Department (DEE), Federal University of Campina Grande (UFCG), Aprígio Veloso Street, 882, Universitário, Campina Grande, Paraíba CEP 58.429-900, Brazil e-mail: benemar@dee.ufcg.edu.br

N. S. D. Brito

e-mail: nubia@dee.ufcg.edu.br

F. B. Costa

Federal University of Rio Grande do Norte (UFRN), Campus Universitário Lagoa Nova, Natal, Rio Grande do Norte CEP 59.078-970, Brazil

e-mail: flaviocosta@ect.ufrn.br

M. R. C. Paes Jr

Energisa Paraíba, BR 230, km 25, Cristo Redentor, João Pessoa, Paraíba CEP 58.071-680, Brazil e-mail: mcerqueira@energisa.com.br

Keywords High impedance fault · Electromagnetic transients· Modeling · Field tests

1 Introduction

Conceptually, the power distribution system comprises distri-bution lines and electrical equipment belonging to a distrib-utor in its concession area, including the other distribution and transmission facilities contractually made available to the distributor, but not belonging to the basic grid (ANEEL 2011). According to Article 22 of the Consumer Protection Code (Brazil 1990), distributors are required to provide ade-quate, efficient, and safe service, and the essential services have to be continuous. Within these parameters, the continu-ity of service is considered to be of paramount importance, since it affects the daily lives of people, and causes major disruptions by compromising essential services to the con-sumer.

Continuity refers to the degree of availability of electric power to consumers. The ideal situation is for there not to be interruption in the supply of electricity; if there is, it should be minimal and informed to the consumer in a timely manner, in order to prevent possible losses arising from lack of energy. However, consumers are subject to interruptions in energy supply, due to defects as well as to the execution of preven-tive maintenance services on the network. Among the defects, the most worrisome are the faults that lead to non-scheduled shutdowns of components, caused by problems of electrical, mechanical, or thermal nature, arising from adverse condi-tions to which the system is always subject. In practice, faults are caused by disruptions of cable lines or by equipment fail-ures. Some faults can be avoided by scheduled maintenance of equipment; however, most faults are caused by natural phenomena such as lightning, rain, high winds, etc.

In the case of power distribution systems, a special class of faults called high impedance faults (HIFs) is a constant cause for concern, mainly in aerial distribution networks. Normally, a HIF occurs when there is a failure or contact of an energized conductor of the circuit of the primary network with a highly resistive surface, such as trees, roads, or constructions. As a consequence, a HIF could expose the population to the risk of electric shock, compromising the integrity of the system equipment, causing severe damage to properties and result in a large number of consumers without power supply after the actuation of the protection system. This problem is exac-erbated in rural distribution networks due to predominantly radial topology, with feeders of large extension and that cross long uninhabited stretches.

The problems arising from the HIFs are mainly due to the resulting current levels, which are insufficient to sensi-tize the operation of conventional protective fuses and relays. Because of this characteristic, the HIFs are often confused with oscillatory transients in the network, due to the inser-tion/removal of loads or capacitor bank switching. As a result, the defect may persist.

In the current context of the Brazilian electricity sector, the usual way for concessionaires to detect the occurrence of a HIF happens through the consumer complaints. This process can be time-consuming and depends on the delay until the consumer makes the complaint and then on the speed with which this information is passed on to maintenance crews. In order to reduce the duration of outages and the operat-ing costs caused by HIF, companies have invested in the development of solutions that automate power restoration. For this, it is first necessary to have a detailed description of the event, i.e., to perform a diagnosis. In the context of electric power systems, this translates into the implementa-tion stages of detecimplementa-tion, classificaimplementa-tion, and localizaimplementa-tion of the event. In terms of the state of the art, this is a recent topic and one of growing importance (Chan and Yibin 1998;Lazkano et al. 2000;Moreto 2005;Yang et al. 2007;Souza et al. 2011). In general, the development of diagnostic algorithms requires the construction of a set of computer-simulated stan-dards, which represent the various fault scenarios (Souza et al. 2005). This combination is commonly referred to as a database. In the particular case of HIF, the quality of the diagnosis provided depends mainly on the model used to represent the phenomenon and, consequently, on the quality of the database. The closer the model is to the features found on the real phenomenon, the more reliable the diagnostic algorithms based on them will be.

In assessing the state of the art, it has been observed that there is much to be done in terms of building models for HIF since the models proposed so far fail to fully represent the phenomenon (Yu and Khan 1994;Yibin and Chan 1996; Nak-agomi 2006;Santos 2011). In this sense, this paper presents a literature review of HIF models and uses a model that

com-bines characteristics of existing models with the addition of some innovative features. At the end, a model that represents the most important features found in most HIF was obtained. The implementation of the model was performed on an ATP (Leuven EMTP Center 1987), making use of the language MODELS.

2 Literature Review

2.1 Main Characteristics of a HIF

HIFs have as main feature the low amplitude of the fault cur-rent, which in most cases is of the same order of the currents resulting from other phenomena, such as load energizing/de-energizing and capacitor bank switching (Wester 1998).

Other important features are observed during the process of formation of a HIF. According toNakagomi(2006), when an electrical conductor breaks, it does not initially keep a firm electrical contact when it touches a highly resistive surface. This contact, however, intensifies as the free electrons from the air are accelerated by the electric field formed between the conductor and the surface. When a given threshold of kinetic energy is reached, the neutral molecules in the air are ionized, releasing new free electrons. Then, a process of successive collisions of electrons with neutral molecules initiates in a short time. This process is called avalanche. As a result, the air starts to behave as a conductor, causing electric arcs. During the process of arc formation, the occurrence of scintillations (rapid sequences of the dielectric momentary disruptions) is common.

Electric arcs are widely studied in the specialized litera-ture; however, most of the studies deal with arcs from faults in electric power transmission lines, which typically have the following characteristics: length in the order of meters, the initial current in the range of thousands of amperes, pre-dominantly inductive impedance and homogeneous contact surfaces. In the particular case of HIF, the arcs have: length of approximately centimeters, current below one hundred amps, predominantly resistive impedance, and non-homogeneous contact surfaces (represented by layers of different resistiv-ity). Consequently, in a situation of HIF, vaporizing metal may not occur sufficiently to keep the electric arc steady, which may result in discontinuities in the fault current ( Jeer-ings and Linders 1989).

The presence of electrical arcs on HIF can cause the emer-gence of certain peculiarities in the waveform of the cur-rent, such as asymmetry between half waves, distortion in the waveform, and progressive increase in current (buildup) followed by moments of constancy in amplitude (shoulder), as well as intermittence (Fig.1). According toEmanuel et al. (1990), the fault current from a HIF has asymmetrical char-acteristic and the positive half-wave is greater in amplitude

0 0.1 0.2 0.3 0.4 0.5 0.7 -10 0 10 Time (s) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 -50 0 50 Time (s) (a) (b) 0.6 ) A( t n er r u C ) V k( e g atl o V

Fig. 1 Actual oscillography of a HIF: a voltage, b current

than the negative half-wave. According to the authors, this feature does not depend on the shape of the electrodes, or the material used in their manufacturing. The most influential factors are the porosity and moisture of the surface contact. In particular, the asymmetry can be attributed to silica, a substance which is normally present in the contact surfaces. When heated, the silica forms a kind of cathode spot that absorbs electrons, causing smaller voltage drops when the conductor is subjected to a positive voltage.

Still according toEmanuel et al.(1990), when the arc is started, the distribution of the electrical field in the soil is greatly modified, causing a steep rise in the field between the conductor and the contact surface. Factors such as thermionic emission and high field gradients, and the fact that the con-ductive layer of the soil becomes deeper over time, make the arc advance further into the soil. As a result, the conduction of an electrical current through the contact surface ends up creating fulgurites, which are tubular rock structures result-ing from vitrification of the silica present in the soil. With the penetration of the arc into the contact surface, the area around it begins to lose moisture, forcing its extinction. From this stage on, the moisture of the soil from another area can spread, causing a reigniting of the arc or another point of contact with the ground conductor, and may initiate the for-mation of a new arc. This process occurs in the initial stage of the failure, and is known as intermittency, which results in the emergence of high frequency components of voltages and currents at the point of failure.

In oscillographic records of HIF, it is common to observe growth of the envelope of the fault current. This behavior is known as buildup, a phenomenon resulting from the physical accommodation of the cable, i.e., the time that the cable takes to settle completely into the soil, establishing the last contact resistance of the HIF. Normally, this growth ceases for a

Fig. 2 Model Rfand Lf

Lf

Rf

If

Fault Location

few cycles, originating the characteristic known as shoulder (Nam et al. 2001).

All these characteristics are a function of geometric, spa-tial, environmental, and electrical conditions of the system (Kaufmann and Page 1960). As a consequence, the behav-ior of the electrical quantities involved in HIF has a strong stochastic component, which requires detailed study of the phenomena in order to build realistic models.

2.2 Review of HIF Models

The study of HIF is not an easy task due to the difficulty of obtaining real oscillographic data. Therefore, the use of models consists in a major step in diagnostic tasks of such events. A review of the main models of HIF is presented in this section.

Model 1:Sharaf and Wang(2003)

Model consisting of a variable fault resistance Rfin series with a constant fault inductance Lf(Fig.2).

The values of Rf are calculated as follows:

Rf= Rf0.  1+ α ·  if if0 _β , (1)

in which Rf0is the initial fault resistance,α and β are pre-defined parameters; ifand if0are the present and initial fault currents, respectively. This model simulates only the charac-teristics of nonlinearity and asymmetry of the current.

Model 2:Emanuel et al.(1990)

Model consisting of constant resistance in series with con-stant inductance, combined with two diodes connected in antiparallel, and each diode in series with a source of contin-uous voltage (Fig.3).

The fault current circulates by means of the sources of volt-age VP, during the positive semi-cycle, and VN, during the negative semi-cycle. Since the positive semi-cycle of the fault current is greater than the negative one, VN> VPis used. The occurrence of harmonic contents is controlled by the differ-ence between the sources (V = VN− VP) and by the ratio of the reactance XLand the resistance R (tanθ = XL/R).

Fig. 3 Model of the electrical circuit XL R If Fault Location VN VP

Fig. 4 Model of variable

resistances

R (t)1

If

Fault Location

R (t)2

This model simulates only the characteristics of nonlinearity and asymmetry of the current.

Model 3:Nam et al.(2001)

Model consisting of two resistances in series, which are variant in time and controlled by the Transient Analysis of Control Systems (TACS) routine of the ATP (Fig.4).

The resistance R1simulates the characteristics of nonlin-earity and asymmetry of the HIF, acting in the transitional and permanent regimes. Its value is calculated by using the voltage versus current curve of a cycle, in which significant modifications of the amplitude in relation to the subsequent cycles do not exist. Therefore, it is considered that in the selected cycle there was no influence of the phenomena of buildup and shoulder, which permits the division between the voltage at the fault point and the corresponding current to result in the resistance that simulates the characteristics of asymmetry and nonlinearity of the HIF current.

The resistance R2 simulates the phenomena of buildup (period of elevation of the fault current) and shoulder (peri-ods in which the fault current remains constant before begin-ning to rise). Its value is calculated by dividing the absolute maximum values of the semi-cycles of the voltages by those of the currents. As the steady-state system operation has only the influence of R1, the value in which it was stabilized (R1) is subtracted from the curve obtained beforehand, and the

Feeder TVRs Switch 1 Fault Location Switch 2 R (t)1 R (t)2

...

Fig. 5 Proposed HIF model

behavior related to the characteristics of buildup and shoul-der (R2) is achieved. At the end, a regression analysis is performed to approximate the points of R2by an equation as a function of the time. Therefore, this model simulates the characteristics of nonlinearity, asymmetry of the current, buildup, and shoulder.

3 Suggested Hif Model

Based on the models discussed in the literature, the HIF model suggested in this paper is shown in Fig.5.

The proposed model simulates the main characteristics of a HIF, such as nonlinearity, asymmetry, buildup, and shoul-der. The model is performed as follows:

• Two time-varying resistances (TVRs), in series, and con-trolled by TACS, such as proposed byNam et al.(2001). – Resistance R1: simulates the characteristics of

nonlinear-ity and asymmetry.

– Resistance R2: simulates the phenomena of buildup and shoulder.

• Two time-controlled switches were added to the model of variable fault resistances:

– Switch 1: connects the resistances to the fault point and initiates the fault.

– Switch 2: connected downstream from the fault point simulating the breaking of the conductor.

Some diagnostic methods of HIF consider the break of the electrical conductor in their algorithms (Malagodi 1997). This break results in a considerable imbalance of voltages, downstream from the fault point. The insertion of switch 2 allows for the consideration of this phenomenon in the wave-forms in the extremities of the feeder.

Figure6shows simulated records of HIF with acquisition of the data at a point downstream from the fault point. Since in Fig. 6a there is not a switch 2, that simulates the break of the conductor, there is not a great imbalance of voltages

0 0.2 0.4 0.6 0.8 1 -20 -10 0 10 20 0 0.2 0.4 0.6 0.8 1 -20 -10 0 10 20 (a) (b) Time (s) Time (s) ) V k( e g atl o V ) V k( e g atl o V

Fig. 6 Records of HIF downstream from the fault point: a without

switch 2, b with switch 2

between the phases. The same does not occur in Fig.6b, where the break of the conductor when it comes into contact with the soil is considered.

The adjustment of the parameters of the model was accom-plished by means of electrical tests performed on seven types of surfaces (grass, cobblestones, gravel, asphalt, sand, local soil, and shrubs), taking into account dry and wet surfaces.

Among the oscillography obtained in the tests, only one in each soil was chosen to be used as reference in the parameter-ization of the model of the contact surface in question. The effective contribution of this model is in the consideration of the different contact surfaces in its parameters by using actual data.

AdoptingNam et al.(2001), the resistance R1was defined as being the ratio between the voltage and the current in a cycle in which the amplitude of the voltage versus current does not present significant modifications in relation to sub-sequent cycles during the HIF. To simplify the implementa-tion of the model in the ATP, only 32 samples of the selected cycle were considered (Fig.7).

The current corresponding to a voltage in the fault interval is calculated byNam et al.(2001):

i(t) =  in+_vin+1−in n+1−vn × v, se vn< v(t) < vn+1 in, sev(t) = vn , (2)

where v(t) is the voltage in the feeder at the fault point;

v = v(t) − vn;vnand inare the voltage and the current of

the characteristic curve in sample n, respectively.

Due to the fact that the characteristic curves show two values of current for each corresponding voltage value, an artifice was used to make a correct choice of the values to be utilized in Eq. (2): the total curve was divided into two parts, one corresponding to the growth of the variables (ascending curve) and the another to the decrease (descending curve).

-1 -0.5 0 0.5 1 -1 -0.5 0 0.5 1 Current (pu) Ascending curve Descending curve (a) -1 -0.5 0 0.5 1 (b) -1 -0.5 0 0.5 1 -1 -0.5 0 0.5 1 Current (pu) (c) -1 -0.5 0 0.5 1 (d) -1 -0.5 0 0.5 1 -1 -0.5 0 0.5 1 Current (pu) (e) -1 -0.5 0 0.5 1 -1 -0.5 0 0.5 1 Current (pu) (f) ) u p( e g atl o V

IBASE=10 A IBASE=10 A IBASE=40 A

IBASE=20 A IBASE=100 A IBASE=100 A

-1 -0.5 0 0.5 1 -1 -0.5 0 0.5 1 Ascending curve Descending curve Ascending curve Descending curve Ascending curve Descending curve Ascending curve Descending curve Ascending curve Descending curve ) u p( e g atl o V ) u p( e g atl o V ) u p( e g atl o V ) u p( e g atl o V ) u p( e g atl o V Current (pu) Current (pu)

0 0,05 0,10 0,15 0,20 0,25 0 5 10 15 Time (s) 0 10 20 30 Time (s) 0 500 1000 1500 2000 Time (s) R(τ_k) R₁(τ_k) R₂(τ_k) R₂(t) estimated (a) (b) (c) 0,30 0,30 0 0,05 0,10 0,15 0,20 0,25 0 0,05 0,10 0,15 0,20 0,25 0,30 ) m h O( e c n at si s e R Current (A) Voltage(kv)

Fig. 8 Process of calculation of R2on cobblestones: a absolute value

of the voltage referring to HIF, b absolute value of the current referring to HIF, c value of the resistance in relation to time

The algorithm implemented in language MODELS distin-guishes the correct curve by means of the calculus of the derivative of the voltage at the point of application of the fault. If the derivative is positive, the selected curve will be the ascending curve. Otherwise, it will be the descending curve.

Furthermore, according to Fig.7, each type of soil has differences in the characteristics of the curvesvxi and in the values of maximum current amplitude. These differences are a function of specific characteristics of the composition of the contact surfaces, such as porosity, humidity, and density. This consideration is of major importance, since a simulated set of HIF patterns closest to reality can be obtained.

Following the methodology proposed by Nam et al. (2001), the resistance R1was estimated by:

R1(t) = v(t) i(t) = v(t) in+_vin+1−in n+1−vn × (v(t) − vn) . (3)

The procedure shown in Fig.8was accomplished in order to estimate the resistance R2, taking as example the cobble-stone surface.

The currents in the HIF have predominantly resistive char-acteristics. Therefore, the currents are considered as in phase with the voltages (Nam et al. 2001). Thus, the total

resis-tance(R = R1+ R2) can be obtained directly by dividing the values ofv by i.

Since the phenomena of buildup and shoulder are related to the variation of the amplitude of the fault current, the resis-tance R2 was calculated by considering only the absolute maximum values of the voltage and current. For that,τkwas

considered as being the instant in which the voltage and the current reach their maximum values, in the kth semi-cycle.

Assuming that the characteristics of nonlinearity and asymmetry of the fault current are the same in all the cycles,

R1(τk) can be considered approximately constant during all

HIF duration. By doing this, the resistance R2(τk) can be

obtained by subtracting R1(τk) from R(τk).

To guarantee that only the resistance R1 has influence during the HIF, it is assumed that, in this period, the value of the resistance R2is approximately null.

At the end, resistance R2was approximated by a polyno-mial regression, according to Eq. (4):

R2(t) =



an· tn+an−1· tn−1+· · ·+a1· t +a0, set < t

10−5, se t ≥ t (4)

in which n is the function degree, the coefficients ak are

determined via method of least squares, andt is the growing period of HIF current.

To have a parameter of the approximation provided by the equations of R2(t) compared to the measured points R2(τk),

the coefficient of determination R2was chosen. This coef-ficient is normally used in practical situations, such as the ones shown in this case, since it enables more reliable analy-ses than possible visual inspections performed on graphs of resistance (The Mathworks, Inc. 2007).

The coefficient of determination R2 is a measure of the capacity that a model, that is adjusted to a set of parameters, has when representing a determined set of data (Lira 2008). It is defined as being 1 (one) minus the ratio between the sum of the squared errors between calculated and measured signals (SSE) and the sum of the squared errors relative to the mean of the measured signal (SST), according to the following equations (The Mathworks, Inc. 2007;Spiegel et al. 2001):

SSE= m  j=1 rmed( j) − rest( j)2, (5) SST= m  j=1 r_[med( j) − ¯rmed2, (6) R2= 1 −SSE SST, (7)

where rmed( j) and rest( j) are the measured and estimated values of the resistances, respectively; m is the number of samples; and¯rmedis the average value of the measured resis-tances.

Table 1 Parameters of the polynomial functions of R2and the quality of its approximation

Surface a8 a7 a6 a5 a4 a3 a2 a1 a0 R2

Sand 6.91e+11 −5.77e+11 2.01e+11 −3.79e+10 4.14e+9 −2.65e+8 9.45e+6 −1.74e+5 1.73e+3 0.978 Asphalt 3.05e+12 −2.86e+12 1.12e+12 −2.27e+11 2.92e+10 −2.11e+9 8.49e+7 −1.71e+6 1.41e+4 0.946 Gravel 7.08e+7 −1.71e+8 1.70e+8 −9.12e+7 2.84e+7 −5.25e+6 5.65e+5 −3.35e+4 1.05e+3 0.944 Cobblestones 4.75e+9 −7.95e+9 5.30e+9 −1.84e+9 3.63e+8 −4.06e+7 2.47e+6 −7.75e+4 1.34e+3 0.963 Grass 3.63e+10 −3.34e+10 1.28e+10 −2.61e+9 3.09e+8 −2.13e+7 8.27e+5 −1.72e+4 2.12e+2 0.954

Local soil 0 0 0 −3.17e+6 2.75e+6 −8.32e+5 1.05e+5 −6.89e+3 5.13e+2 0.977

0 0.05 0.10 0.15 0 500 1000 1500 2000 Time (s) R₂(τ_k) R₂(t) estimated (a) 0 0.05 0.10 0.15 0.20 0 5000 10000 15000 R₂(τ_k) R₂(t) estimated (b) 0 0.1 0.2 0 500 1000 1500 R₂(τ_k) R₂(t) estimated (d) 0 0.05 0.10 0.15 0.20 0 50 100 150 200 250 R₂(τ_k) R₂(t) estimated (e) 0 0.1 0.2 0.3 0 200 400 600 R₂(τ_k) R₂(t) estimated (f) 0 0.2 0.4 0 500 1000 1500 R₂(τ_k) R₂(t) estimated 0.1 0.3 0.5 0.3 0.20 (c) Time (s) Time (s) Time (s) Time (s) Time (s) ) m h O( e c n at si s e R ) m h O( e c n at si s e R ) m h O( e c n at si s e R ) m h O( e c n at si s e R ) m h O( e c n at si s e R ) m h O( e c n at si s e R

Fig. 9 Curve corresponding to the estimated polynomial function for resistance R2: a sand, b asphalt, c gravel, d cobblestones, e grass, f local

soil

To obtain a good adjustment, it is necessary SSE be low, i.e., the estimated values be close to the measured values. In such cases, the coefficient of determination will be close to 1 (one) (Lira 2008).

Table1 shows the parameters of the polynomial func-tions (evaluated until the eighth degree) that should estimate the values of the measured resistances for each type of soil. Besides the parameters, the coefficient of determination R2 is shown to enable the verification of the quality of the per-formed adjustments. The curves obtained from the polyno-mial functions for each type of contact surface are shown in Fig.9.

At the stage of testing and modeling, not all the desirable contact surfaces were addressed due to operational problems. The ideal experiment would be to consider the largest pos-sible number of soils where HIF may occur in the region. However, the methodology proposed may perfectly be uti-lized to determine the parameters of the model in other HIF situations.

Fig. 10 Structure set up for the performance of the tests

All the modeling process was performed for the six types of surfaces, which had actual data obtained from the field tests (grass, cobblestones, asphalt, sand, gravel, and local soil).

Table 2 Number of HIF tests performed

Contact surface Number of tests

Remote point (1 km) Remote point (11 km)

Grass Dry 5 5 Wet 5 5 Cobblestones Dry 5 5 Wet 5 8 Gravel Dry 5 5 Wet 5 5 Asphalt Dry 5 5 Wet 5 7 Sand Dry 4 6 Wet 5 4 Local soil Dry 5 9 Wet 5 6

Table 3 Levels of the fault currents

Contact surface Current (A)

Grass Dry < 60 Wet < 90 Cobblestones Dry < 10 Wet < 20 Gravel Dry – Wet < 50 Asphalt Dry – Wet < 20 Sand Dry < 10 Wet < 50 Local soil Dry – Wet < 60

The characteristics of buildup, shoulder, nonlinearity, and asymmetry of the HIF current were considered in the simu-lations. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -10 0 10 Time (s) (a) -1 0 1 Time (s) (b) -0,5 0 0,5 Time (s) (c) -5 0 5 Time (s) (d) -50 0 50 Time (s) (e) -0,5 0 0,5 Time (s) (f) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C

Fig. 11 Currents of HIF on dry surfaces: a sand, b asphalt, c gravel, d

cobblestones, e grass, f local soil

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -100 0 100 Time (s) (a) -5 0 5 Time (s) (b) -50 0 50 Time (s) (c) -20 0 20 Time (s) (d) -100 0 100 Time (s) (e) -50 0 50 Time (s) (f) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C

Fig. 12 Currents of HIF on wet surfaces: a sand, b asphalt, c gravel, d cobblestones, e grass, f local soil

Fig. 13 Single line diagram of

the modeled feeder

57 53 51 41 39 Recloser Substation 2 3 4 5 6 10 11 17 18 24 25 29 30 7 8 9 12 13 14 15 16 19 20 21 22 23 28 27 26 37 36 31 35 32 33 34 50 52 ₅₅54 56 46 45 47 48 49 38 42 44 43 40 83 82 81 84 80 85 90 86 87 88 89 79 78 65 64 62 63 59 58 60 61 66 67 68 69 72 70 71 73 74 ₇₅ 76 77 1

Currently, there is no established detection method of HIF, mainly due to the weak influence of this fault on voltages and currents monitored by protection equipment (Costa et al. 2011). The greater the extent of the characteristics of simulated models compared to the phenomena occurring in the electrical system, the greater the reliability of the diag-nostic algorithms based on these simulations will be. The model presented here examines the main characteristics of HIF, showing great potential in the aid of future research dealing with the detection and localizing of this type of fault.

4 Experimental Tests of HIF

The tests were performed on a farm localized about 15 km from the substation of the town of Boa Vista, in the state of Paraíba (Santos et al. 2011). The choice of the locality and of the feeder was made aiming to minimize the occur-rence of accidents and guarantee enough space to set up the experiment and house the team with safety.

With the aid of a management program belonging to the local power company, it was possible to obtain the levels of short circuits in the region where the tests were performed, which would be of about 475, 410, and 404 amps for three-phase, two-three-phase, and single-phase short circuits, respec-tively.

The structure shown in Fig. 10 was used for the per-formance of the tests, and it is described succinctly as follows:

• Seven types of contact surfaces (dry and wet), consisting of small areas displayed parallel to each other and covered

with grass, cobblestones, gravel, asphalt, sand, local soil, and shrubs.

• A transitional pole with two meters of height installed near the contact surfaces, aiming to diminish the mechan-ical stress to the conductor coming from the conventional pole already existing on the property. A potential trans-former (TP) and a current transtrans-former (TC) were installed on this pole to capture the signals of voltage and current produced by the HIF, respectively.

• Ladder and hot stick for the installation and replacement of possible fuse links damaged during the tests.

• An energized cable in 13, 8/√3 kV coming from the conventional pole and connected to one of the isolators fixed on the transitional pole. The extremity of the cable was connected to a serial isolator with a hot stick, to be operated by a live line technician from the company. • An isolating platform (scaffold) for the technician to

han-dle the energized cable.

• A fuse link of 1H installed on the conventional pole where the phase submitted to the short came from, aiming to protect the electrical system connected to the extension. • Three points of measurement: the first at the place of the fault; the second and third about one and eleven kilome-ters of distance from the fault, respectively. The usage of more than one point of measurement had the objective of relieving the level of disturbance caused by a HIF along the feeder.

• Two digital fault recorders (DFR) for the execution of the measuring: a DFR at the place of the fault (Fig.9) and the other at the points away from the place of the fault. At the end, each test was read simultaneously at two different places. Manual triggering of the DFR was adopted, with 30 s of monitoring, because normally the HIF does not sensitize the parameters monitored by the DFR.

The tests were performed between the 27th and 29th days of May, 2010, following the procedure shown below:

1. Isolation and signaling of the test area with tapes and cones, aiming to prevent the circulation of people and animals at the moment of the HIF.

2. Installation and configuration of the DFR. 3. Choice of the contact surface.

4. Preparation of the scaffold and of the live line technician. 5. Announcing among the teams of the launching of the

test.

6. Shutdown of the protection fuse link. 7. Triggering of the local DFR.

8. Approximation and contact of the energized conductor with a surface.

9. Permanence of 20 s of HIF. 10. Elevation of the conductor.

11. Communication among the members of the team about the end of the test.

12. Superficial analysis of the oscillographic recording. 13. Replacement of the fuse link, if necessary.

14. Repetition of steps 6–13 at least four times for each sur-face.

15. Repetition of steps 3–14 for all the surfaces.

Each surface was tested in dry and wet conditions, resulting in a total of 129 tests, according to results shown in Tables2 and3. Due to operational difficulties, the tests on the shrub surface were not performed.

Briefly, the applied HIF had the following characteristics: • The dry asphalt, gravel, and local soil surfaces produced imperceptible arcs, so that the recording time limit of the DFR was achieved without breaking the fuse link. • The dry sand and cobblestone surfaces produced weak

electrical arcs.

• The dry grass surface produced strong electrical arcs, which resulted in the operation of the fuse link.

• The wet local soil and grass surfaces produced strong electrical arcs, which resulted in the triggering of the fuse link.

• The wet sand and gravel surfaces produced perceptible electrical arcs, so that in some cases, the protection fuse link broke.

• The wet asphalt and cobblestone surfaces produced weak electrical arcs in a few cases, without breaking the fuse element.

Illustrations of the oscillographic records of the HIF currents are shown in Figs.11and12.

0 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 -15 -10 -5 0 5 10 15 Time (s) Measured Current Simulated Current (a) 0 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 -3 -2 -1 0 1 2 3 (b) 0 0.1 0.2 0.3 0.4 0.5 -40 -20 0 20 40 -30 -20 -10 0 10 20 30 0 0.05 0.10 0.15 0.20 0.25 0.30 -100 -50 0 50 100 (f) 0 0.05 0.10 0.15 0.20 0.25 (d) 0 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 -100 -50 0 50 100 (e) (c) 0.22 0.35 R =0,94392 R =0,96322 R =0,98842 R =0,92272 R =0,82792 R =0,97972 0.30 0.6 0.22 0.20 ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C ) A( t n er r u C Time (s) Time (s) Time (s) Time (s) Time (s) Measured Current Simulated Current Measured Current Simulated Current Measured Current Simulated Current Measured Current Simulated Current Measured Current Simulated Current

Fig. 14 Simulated currents versus measurements: a sand, b asphalt, c

5 The Modeled Feeder

To finish the model utilized in this article, the distribution feeder used in the electrical tests was implemented in the ATP. The modeling was performed, considering:

• Non-transposed three-phase lines at distributed and con-stant parameters with the frequency.

• Stretches consisting of only one type of cable: cable 4 American Wire Gauge (AWG).

• Loads of near points along the feeder, grouped on an only bus, resulting in a feeder with 90 buses (Fig.13). • Skin effect factor of 0.33 for the cables.

• Resistivity of the ground (350 m). • Model of constant impedance for the loads.

• Loads modeled as parallel RL circuits connected between each phase of each bus and the ground.

• Average power factor of 0.955.

6 Validation of the Simulated Records

In practice, the evaluation of the precision of the model is made by considering only the current signals (EPRI 1982). For this, the coefficient of determination R2between the mea-sured and simulated current signals for the chosen contact surfaces were calculated, and are shown in Fig.14.

During the tests, the presence of high frequency noise was observed, but fortunately it did not hamper the mea-suring, with exception to the tests on the asphalt. This fact was confirmed when evaluating the value of R2(the lowest value obtained among the evaluated surfaces). At the end, the great precision between the signals generated by the utilized model and the signals measured in the electrical tests was confirmed.

7 Conclusions

The procedure shown in this paper permits other research teams to have a guide of the steps to form a set of simulated HIF records based on real data.

The use of information coming from actual oscillography and from different contact surfaces resulted in the construc-tion of simulated records which can satisfactorily represent the various facets of the real phenomenon. At the end, a set of simulations that contemplates the main characteristics of a HIF was obtained.

The performed electrical tests were very valuable, since they gave the involved researchers and engineers a better understanding of the phenomenon. At the end, the results obtained and the difficulties faced in the performance of the

tests assisted the researchers in the development of more elaborate test measuring and procedure techniques.

From the simulated records, it is possible to create a data-base of the simulations that will permit the development and validation of HIF detection and localization methods with more reliability.

Acknowledgments The authors thank the Coordination of Perfecting Higher Level Personnel [Coordenação of Aperfeiçoamento of Pessoal of Level Superior (CAPES)] for the concession of scholarships for study and the Energisa Group (Grupo Energisa), for technical and financial support.

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