06745063 ground fault and insulation degradation detection and localization in

8/11/2019 06745063 Ground Fault and Insulation Degradation Detection and Localization in

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Ground Fault and Insulation Degradation Detection and Localization in

PV Plants

Mohammed S. Agamy1, Maja Harfman-Todorovic

2, and Ahmed Elasser

2

1School of Engineering, University of British Columbia, Kelowna BC, Canada

2

General Electric Global Research Center, Niskayuna NY, USAAbstract

GroundfaultsareamajorhazardinPVnetworks.Early

detection

as

well

as

location

of

these

ground

faults

can

provide higher plant availability as well as protection forpersonnel

and

equipment.

Since

the

occurrence

of

a

ground

fault

or

even

insulation

degradation

changes

the

equivalent

ac

impedance(RLC)ofthedistributionnetwork,transientanalysisof

the

currents

at

string

or

array

combiners

can

be

used

to

detect

and

locate

the

fault

or

the

beginning

of

insulation

degradation.

In

this

paper,

the

analysis

of

ground

faults

and

insulation

degradation

and

their

effect

on

the

transient

waveforms

is

presented

for

grounded

and

floating

PV

networks.

The

current

spectral

analysis

can

clearly

distinguish,

identify

and

locate

faults

intheplant.

Index

Terms

PV

arrays,

Ground

faults,

Insulation

degradation,

Transient

analysis,

Fast

Fourier

Transform.

I. INTRODUCTION

Ground faults in the dc collection network of a photovoltaic

(PV) array can present significant hazards to both operators

and equipment, and if left undetected can lead to severe fire

damage [1]. Therefore, ground fault protection circuitry is

added on the dc side of the PV inverters to disconnect the

system when ground faults are detected. However most

classical ground fault detection methods rely on directly

measuring ground currents at the central inverter [2, 3], which

can be sufficient to detect the occurrence of the fault, but

cannot determine the location of the fault. Locating the faultposes a significant challenge in large plants that include

thousands of strings, which leads to longer down time of the

plant. With the increasing trend of employing string

combiners that have more monitoring capabilities, current

sensors can be placed to monitor each string current. In this

paper, methods of detecting and locating ground faults as well

as insulation degradation by analyzing the string current are

investigated. The fault/degradation detection is based on

spectral analysis of the string currents, which can be used to

detect network irregularities, due to the change of the

equivalent circuit seen by the string. This approach has been

used for non-intrusive diagnostics of electrical machines [4-6]

and is now being extended to PV arrays. Successfulidentification of fault location allows the isolation of the faulty

line and quickly re-connect the rest of the system, which

increases the overall plant availability and the energy yield.

II. CURRENT RESPONSE DUE TO GROUND FAULTS AND

INSULATION DEGRADATION

Solar power plants are laid out with large numbers of strings

of PV modules connected in parallel to feed a grid tied

inverter through long stretches of cables. Based on equivalent

circuits of PV modules, cables and input of the inverter, the dc

network can be represented by an equivalent resistive,

inductive/capacitive (RLC) network. Ground faults cause

transients in the different current paths based on the equivalent

RLC network seen by each path. Therefore, analyzing current

measurements in the different paths of the dc-network can

indicate the occurrence of a fault as well as determine the

location of the fault based on the measured transient current

signature. In the following sub-sections, the analysis of current

signatures of an example PV plant is presented. Different

combinations of grounding of the inverter and PV array are

studied to investigate the effect on the current signature during

faults and whether it can be used to locate the fault in the dc

network. Furthermore, the current transient at startup is also

studied to detect and locate the degradation in the dc cables.

The cables connecting the PV strings to the inverter are

modeled using their pi- equivalent circuit, with each cable

represented by 10 cascaded pi sections. Cables with 600V

insulation are used for the analysis in this paper. PV module

output capacitance and parasitic capacitances to ground are

also included in the analysis as shown in fig. 1.

The analysis presented in this paper relies on detecting

variations in the differential current to detect ground faults or

insulation degradation rather than directly measuring groundpath current, which simplifies the sensor requirements, as the

string current sensors in smart combiners or current feedback

sensors in systems with distributed power converters can be

used to detect ground fault conditions. Since faults lead to a

change in the equivalent RLC circuit, the equivalent resonant

frequencies in the network change and consequently the

r l

c/2 c/2


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frequency spectrum of the measured differential current leads

to both detecting the occurrence of a fault as well as

determining its location in the solar farm.

Current sensing can be made at either the PV array side or

the inverter side, i.e. either before or after the fault. In both

cases the change in current pattern indicates whether or not a

fault has occurred.

A.

Grounded PV Arrays and Grounded Inverter

In grounded systems, any ground fault will result in creating

two paths for fault current, one from the inverter side of the

cable and the other from the PV string side. Fig. 2 shows the

system layout as well as the harmonic spectrum of the fault

current at different locations of the dc cable (at 10% of the

cable length away from the PV array side and at 50% of the

cable length from the array).

The current spectrum shows differences in amplitude and

frequencies for the two different fault locations, which can be

used to detect and isolate the faulty line

B.

Floated PV Array and Floated Inverter

In case of a floated array and a floated inverter as shown inFig. 3, locating a ground fault becomes more complicated as a

first fault does not provide a dc-current path and classical

methods rely on the occurrence of a second fault to close the

loop and indicate the ground fault problem and shutdown the

plant. The measurement of transients can indicate the

occurrence of the first ground fault, as shown in Fig. 4, which

can be resolved and thus avoiding the occurrence of any

damage as a cause of the second fault.

Furthermore, the occurrence of a second fault can also be

identifiable and its location determined as shown in Fig. 5,

where the current signature is different if the second fault

occurs on the same line or different lines

C.

Floated PV Array and Grounded Inverter

System layout and spectral analysis comparisons for

currents in both normal and faulty lines are shown in fig. 6 for

the architecture with floated strings. The frequency spectra for

faults occurring at different locations along the line are

distinct, which facilitates the isolation of the compromised

zone of the solar farm.

D.

Detection of Insulation Degradation

Another detectable state is the insulation degradation. Since

degradation is more of a steady state condition rather than a

sharp transient, it can be detected by comparison of currents

from healthy and degraded lines during startup transient. Even

if the starting currents in different strings are significantly

different, degradation in a certain zone/cable of the dc-

Fig. 2 (a) Example PV plant with grounded strings and grounded

inverter, (b) Current spectrum of faulted line with the fault at 10%

(Green) and 50% (Blue) of the line length away from the PV array


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network can be located by calculating the differences in

currents from different string combiners. Fig. 7 and fig. 8

show examples of the start-up current transient with different

degrees of dc cable insulation degradation and the associated

frequency response. In fig. 7, the degradation is severe and the

equivalent impedance to ground is modeled as 1k, while in

fig. 8, the degradation is less significant and modeled through

100k impedance to ground. The frequency spectra are still

distinct, which indicates the capability of providing early

warning signals to maintain degrading elements.


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Fault and degradation detection on the dc network depends

only on the transient response of current and/or voltage since

the dc steady state decays to zero as seen in all the time

response waveforms shown in the previous figures. Therefore,

data acquisition and analysis should be performed on a

moving time window. The width of the window depends on

the system layout and components, which determine the time

constants and resonant frequencies of the system. Spectral

analysis is performed for the waveforms in each individual

window.

III.SYSTEM ARCHITECTURE AND FAULT DETECTION

ALGORITHM

In order to locate faults on the dc-network, string current

sensors are required at each string combiner box. The

resolution of the current sensors will determine the types and

severity of faults and/or degradation that can be detected. The

current measurements are then communicated to a central

control unit that analyzes the signals from all combiner boxes

to determine if a fault exists and where it is located based on

the current transients as described in prior sections. Fig. 9

shows an example of such a system, where the communication

can be either hard wired or wireless. The central controller

then performs waveform analysis to determine the type and

location of the fault/degradation. The analysis can be a

spectral analysis as shown in the previous examples or any

other identification and classification method using neural

networks or wavelet analyses.

Since this analysis is based on comparisons between normal

and fault conditions the system should have a saved record of

the expected normal waveforms as a reference. Furthermore,

offline simulations should be made to determine the expected

dominant frequencies that should be monitored since these

frequencies are dependent on type of modules, cables, theircross-section and length and the overall plant layout.

The moving window during which the current waveform is

analyzed is also dependent on the system dominant

frequencies as well as measurement and control bandwidth

and should be specified during the commissioning of the plant.

Fig. 10 shows a basic summary of the proposed fault location

algorithm.

IV.CONCLUSION

A method to locate ground faults in the dc network in large

PV plants is presented. Only the measurement of differential

currents at the string combiners is used. These measurements

are then communicated to a central processor to analyze and

compare the different waveforms to the expected operating

conditions. Since there is an increased interest in smart string

combiners, this method can easily utilize them to provide

better protection, maintenance and diagnostic tools in the PV

plant. The current signatures are distinct for different fault

locations and for different types of faults and from other

transients, which prevents the occurrence of false trips due to

other system transients. The method can be extended to any

dc-distribution system. It should be noted that the type of faultor degradation detected depends on the measurement

resolution and bandwidth.

Fig. 10 A conceptual flowchart of the basic monitoring and fault identification


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REFERENCES

[1] B. Brooks, The Bakersfield Fire, SolarPro, February/March 2011, pp.

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1383.

[3] D. Stellbogen, Use of PV Circuit Simulation for Fault Detection in PV

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[4] U. Orji, Z. Remscrim, C. Laughman, S. Leeb, W. Wichakool, C.

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[6] P. Karlsson & J. Svensson, Fault Detection and Clearance in DC

Distributed Power Systems, Proceedings of Nordic Workshop on

Power and Industrial Electronics, August 2002.

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