High-impedancefaultsinpowerdistributionsystemsisalastingproblemwithdecadesofsteadyinves- tigation. Duetothecomplexityoftheproblem,theﬁeldcanalsobechallengingtonavigate. Although there exist surveys of the ﬁeld in the literature, it is not easy to ﬁnd a comprehensive contextualiza- tionofhowandwhentheﬁelddevelopmentsunfolded. Thispaperpresentsthehistoricalnarrativeof the progress and developments based on the most cited papers since the inception of the ﬁeld. The accounts are not limited to archaic and obsolete works. They are all contextualized from the seminal papers to contemporary methods and related technology. Quantitative ﬁgures on the survey of the methods and relevant knowledge gaps are also discussed at the closing of the paper. 1. Introduction Between the short- and open-circuit fault categories ex- istsadisturbancethatblursthelinebetweentheseclassiﬁca- tions—High-ImpedanceFaults(HIFs). Short-circuitfaults are characterised by hazardous large fault currents gener- ated by the alternative low impedance path. They are eas- ily detected due to their substantial eﬀects on the currents of the system by protection devices such as overcurrent or zero sequence relays. If such a conducting path has a high impedance, alternatively, the resulting fault current magni- tude may be relatively small in comparison to the system nominal current. Consequently, as the current magnitude may remain under the maximal nominal values, HIFs di- vergefromtheperceivedcategoryofshort-circuitfaultsbe- causetheydonotposethesamethermalhazardousstresses. However, as they might not interfere with the functionality ofthesystem,HIFsalsodonotﬁttheopen-circuitfaultcate- gory. InHIFoccurrenceswherethereisnoconductorbreak- age,theloadcurrentisnotinterrupted,andnotrivialchanges canbeperceivedinthesignalsatthesubstationlevel. These seemlynon-threateningcharacteristicsofHIFswasprobably the reason why they were neglected until the 70s [1], where evidence of their problems started to stack up. Before the seminal works that highlighted it as a prob- lem worth addressing individually, High-Impedance Faults (HIFs) were just a part of the research ﬁeld investigating earthfaultsinpowerdistributionsystems. Atthetime,HIFs were mainly described by the concerning scenario where a broken conductor falls to the ground, hence their equiva- lencewithearthfaults. Powerengineershadtothereforerely on ground overcurrent protection to address such faults. It wasquicklyrealized,however,thatthesensitivityofground overcurrent relays, which had to tolerate some load unbal- ancing,wasnothighenoughtoadequatelyaddresstheprob- <Corresponding author douglas.uf@gmail.com (D. Gomes); cagil.ozansoy@vu.edu.au (C. Ozansoy) ORCID(s): 0000-0001-7511-2910 (D. Gomes); 0000-0002-9375-9571 (C. Ozansoy)lem. One early work [2], based on technical reports by the Pennsylvania Power & Light Company, drew attention to the underestimation of undetected broken conductor faults. Conductedin1974-75,thisworkfoundthatovercurrentde- vicesfailedtooperatein32%ofthe390stagedfaults. When faults were staged 2-3 miles from the substation, only one of the twenty cases was cleared. They also conducted sur- veyswithmanyutilitypersonnelabouttheclearanceofsuch faults. From the 83 surveys, 61% said they had experience with broken conductors problems. Despite not representing a threat to power equipment, HIFsarestilldangerousdisturbancesduetotheirelusivebe- haviour. They became critical disturbances in power distri- butionsystemswhentheirpotentialtocreatesafetyrisksand ﬁrehazardswasfullyrealised. Forexample,aHIFgivenby an energised conductor that breaks and falls to the ground canbesustainedforanextendedperiodasitgoesundetected by protection devices. An interesting work [3] attested this fact by describing interviews with power line crews. They statedthataroundone-thirdofbrokenconductorfaultswere still energised when the crews reached the fault location. Such an alarming ﬁgure, however, only considers broken conductoroccurrencesthatoftenleadstoservicediscontinu- ityandconsequentreportsfromcostumers. ForHIFsresult- ing from contact with vegetation, service discontinuity may neverhappenas theycanformwithoutconductor breakage, thus likely never being noticed. Accessible work dates back to the late 70s, where the ﬁeldwasprettymuchdominatedbypapersfromTexasA&M University[4,2]andPennsylvaniaPower&LightCompany [5, 6]. They where the ﬁrst to propose practical solutions to the problem, but the ﬁeld turned into a global discussion by the early 90s. Since then, hundreds of papers have been publishedonthesubject. TheﬁeldhasmaturedandtheHIF term is now used to describe a more wide set of problems, encompassingallthefaultsthatarenotdetectedbyovercur- rentprotection. Examplesincludeleaningtreesmakingcon- tact to power lines [7, 8], tree branches that falls between conductors [9], pole and insulation failure [10], and more. DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 1 of 23 High-Impedance Faults in Power Distribution Systems Nomenclature ANNArtiﬁcial Neural Network DTDecision Tree EMDEmpirical Mode Decomposition EMTP Electromagnetic Transient Program FTFourier Transform FFTFast Fourier Transform GEGeneral Electric HHHilbert–Huang PPLPennsylvania Power & Light SELSchweitzer Engineering Laboratories TAMU Texas A&M University HIFHigh-Impedance Fault IPIntellectual Property KNNk-Nearest Neighbour MFMagnetic Field MMMathematical Morphology MRAMulti-Resolution Analysis NERNeutral Earthing Resistor PCAPrincipal Component Analysis PDPartial Discharge PLCPower Line Communication REFCL Rapid Earth Fault Current Limiter RMSRoot Mean Square SVMSupport Vector Machine SWER Single-Wire Earth Return TACSTransient Analysis of Control Systems VHIFVegetation High-Impedance Fault WPAWavelet Packet Analysis WTWavelet Transform Detection and clearance of such faults remains a subject up to this date, but the ﬁeld soon started to encompass other problemslikemodelling[11,12],understandingthefaultbe- haviour[13,14],proposingsignalrepresentationtechniques [15, 16, 17], and HIF location [18, 19]. Thispaperpresentsanarrativeforhowtheﬁeldadvance- ments unfolded through time, contextualizing the novel ideas of the most inﬂuential papers. The inspiration comes primarily from the fact that one might ﬁnd the ﬁeld to be a convoluted and challenging landscape to explore. Since manyclaimtobepresentingadeﬁnitesolutionfortheprob-lem,identifyingthecontributiontoknowledgebetweensim- ilarworksinthevastliteraturecanbeproblematic. Onecan ﬁnd comprehensive reviews in the literature [20, 1], which describe the existing HIF solutions and methods. However, deﬁning techniques of the methods do not necessary gives thereaderthesenseofhowthecoreideasandadvancements unfoldedthroughtime. Thispaperthereforeaimsatguiding thereaderfromthepioneeringeﬀortsontheﬁeldtothecon- temporarystrategiesandcommercialsolutions. Thediscus- sionofsigniﬁcantrecentinnovationsanddisruptivetechnol- ogy is also a potential contribution to the interested reader, which may be unfamiliar or newcomer to the ﬁeld. The following narrative describes the ﬁeld progress through decades, with respective highlights in the end of each section, followed by quantitative ﬁgures and commen- tary to illustrate a coarse view of the ﬁeld. The adopted methodology for ﬁltering the papers was purposely direct and simple. It was performed by searching for the term “High-Impedance Fault” on databases like the IEEExplore , ﬁltering the publications by decade, sorting them by num- berofcitations. Ifasigniﬁcantcontributiontotheﬁeldwas identiﬁedafterreadingandanalysingaparticularpaper,the work was integrated and contextualized in the narrative arc proposedhere. Forthecommentarysection,quantitativede- scriptors such as popularity, signal representation, and de- cision methods compared and discussed. These descriptors includepopularity,signalrepresentation,anddecisionmeth- odsofthesurveyedworks. Punctualandbriefcommentson thepossibleknowledgegapsstillpresentintheﬁeldarealso presented. The authors hope that the narrative present here can serve as a historical guide for students, engineers, and man- agers interested in the developments of the ﬁeld. The pio- neeringeﬀortsandthebeginningsoftheﬁeldinthe70sand 80saredescribedinthenextsection. Astheﬁeldpopularity and interest grew, the 90s and 00s have dedicated individ- ualsections. Mostcoresub-ﬁeldslikedecisionsystemsand modelling started in the 90s while the 00s were responsible for signal representation and specialization developments. Their description is followed by a section discussing con- temporary methods (10s) where most recent solutions are discussed,includingnoveltechnology. Thequantitativeﬁg- ures and commentary on the ﬁeld are presented in the ﬁnal section before conclusions. 2. The 70s and 80s — Genesis of the ﬁeld Pioneer researchers at Texas A&M University [4, 2] (TAMU), Pennsylvania Power & Light Company [5, 6, 21] andAmicusEngineeringCompany[22,23]laidthepathfor followingresearcherswithinnovativeapproachestoHIFde- tection. Their ideas still profoundly inspire the works in the recent literature, such as the use of frequency components higher than the fundamental [2], power frequency of har- monics and voltage sequences [23], and the ratio between sequencecurrents[5,6]. Theworkpresentedbyresearchers attheNationalChenKungUniversityinTaiwancanalsobe cited as early work done at concurrent time [24]. DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 2 of 23 High-Impedance Faults in Power Distribution Systems ThePennsylvaniaPower&LightCompany(PP&L)and Westinghouse Electric [21] presented the ﬁrst electrome- chanicalrelayforfallenconductordetection. Theelectrome- chanical relay was an induction disc unit with torque pro- portional to the ratio between the zero-sequence and the positive-sequence currents. It required a substantial imbal- anceforittobeactivated,buttheauthorswereconﬁdentthat it would detect more than 80% of fallen-conductor faults. A few years later, the researchers at PP&L presented an- otherelectro-mechanicalgroundrelaywiththemodellingof a 12.47-kV, four-wire, multi-grounded system. The activa- tion method consisted of measuring the ratio between the phase positive-sequence current and the three-phase zero- sequence current. Such a protection philosophy was based on the premise that the ratio of these currents remains rel- atively constant for a given feeder in the absence of a HIF. Further work from PP&L presented [6] a digital computer implementation to compare the proposed ground ratio relay withtheexistingprotectionschemes. Thisapproachwasfur- thervalidatedandproven[24]tobeeﬀectivewhendetecting currents higher than 15 A in a well-balanced system. TheresearchersatTAMUproposedtheﬁrstdigitalhard- ware prototype to detect staged HIFs [2]. The device com- prised a method utilizing the frequency components from 2-10 kHz as HIF features. It was also the ﬁrst to investigate higher frequencies in HIF detection. The authors felt that frequency components higher than ones close to the funda- mental frequency represented an appropriate approach for detecting “ground arcing faults” from broken conductors. However,theauthorsraisedcautionfornetworkscontaining grounded wye capacitor banks which could increase the at- tenuation of these frequency components. The method was implementedinacomputercapableofdetectingsomeofthe staged faults, attesting for the sophistication of the adopted approach. They were the ﬁrst to conceptualize a top-down approach using data from staged faults to conceptualize a HIF detection detection method. Itmaybeusefultonotethatthereisaparallelﬁeldofre- searchwhichaddressesasubsetofHIFsnamed groundarc- ingfaults [25,26,27,28]. Aspointedbyauthorsearlyinthis ﬁeld [2], the return path of the current is often not fully es- tablishedinabrokenconductorthatfallsintoasolidsurface suchasasphalt. Theairgapbetweensurfacesusuallyresults inarcscreatedwhenthevoltagereachesa breakdownvalue . Therefore, due to the sinusoidal nature of the voltage wave- form, a burst of current conduction can happen near zero- crossingswherethevoltagecrossesthisreigniting-arcbreak- down value. Some works also may use the terms “ground arcing faults” and “high-impedance faults” interchangeably. By the late 80s, TAMU had more than a decade in bro- ken conductor research. This experience gave them the in- sight which is often missing in contemporary works: HIF is too complex to depend on one single detection method. In their work [29, 27], the authors discussed a detection ap- proach where many diﬀerent algorithms calculated distinct featuresfrom the electric signals. They were later fed to a classofprimallearningalgorithmscalled expertsystems . Itintended to leverage the existence of observational data to emulate the decision-making of a human expert. It is not surprising that the authors opted for such an approach since the use of expert systems exploded in popularity in the 80s [30]. Due to its intention, i.e. replication of human intelli- gence to some extent, expert systems were considered to be the ﬁrst successful Artiﬁcial Intelligence agent expert sys- tems. The 70s and 80s found many valuable ﬁndings and in- sights on HIF behaviour. The most relevant insights can be summarized: •Due to the impulsive nature of the fault current, HIFs can increase the energy of a wide band of harmonic, and non-harmonic, frequency components [2, 31]. •HIF current magnitude can vary greatly in between cycles having an intrinsic randomnature [2, 31, 29]. •Arcing often happens in broken conductor faults due to the air gaps between the conductor and high- impedance surface [23, 2]. •The high-frequency bursts in the fault current often happens near zero-crossings of the voltage due to arc reignition phenomenon called voltage breakdown ef- fect [2, 31]. 3. The 90s — Experts systems, commercial HIF detection, and modelling ResearchatTAMUcontinuedasoneofthemainleaders theHIFﬁeldinthe90s,despitetheappearanceofnewplay- ersfromotheruniversitiesandcountriessuchasSouthKorea [32], Canada [33], Singapore [15], and Brazil [34]. At the beginning of the decade, TAMU researchers had fully em- braced the idea that no single method could cover all HIFs. They started ﬁrst to publish their ideas on how to address this fact, discussing how environmental parameters such as system unbalance, feeder conﬁguration, load type, and sur- face conditions could aﬀect the fault behaviour [35]. Based on the assumption that each technique will have strengths and weakness giving diﬀerent conditions, they proposed a heuristic to select a detection method based on diﬀerent en- vironmental parameters [35]. The heuristics path by TAMU would become more ev- ident in a further revealing paper [36] where they disclose a product resulted from a collaboration with General Elec- tric (GE) company. The paper described the ﬁrst substation equipment having HIF detection as its primary goal, em- bodied in a case that ﬁtted the panel cut-oﬀ for a GE over- current relay. Following what was previously mentioned as a possibility, this work presented an expert system ap- proachconsistingofmanyindependentalgorithmstodetect HIFs. These algorithms dealt with numerous signal’s fea- tures: energiesonthefrequencyspectrum,randomness,arc- ing (24 algorithms), load analysis and event, and burst pat- terns. Theexpertsystemheuristicconsistedofreceivingthe algorithm’s outputs which were then weighted to arbitrary DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 3 of 23 High-Impedance Faults in Power Distribution Systems values and aggregatedin a detection result. An undertaking so sophisticated at the time that GE had initiated an advi- sorycommitteeofexpertstofacilitatethedeviceacceptance in the market [36]. As yet another signiﬁcant aspect of this work, researchers validated their method using tests staged in a dedicated location called the downed conductor test fa- cility,constructedanddesignedbyTAMUforthesakeofthe experiments. The announced product by GE and TAMU [36] was not arelaybuta DigitalFeederMonitor withbrokenandarcing conductor detection function. The distinction between re- layandmonitorrepresentsanimportantpointhere. Theau- thorsﬁrmlyheldtheopinionthatoneshouldnottripawhole feeder for all HIF positive detections. They were aware that the device was not capable of correctly detecting all HIFs occurrenceswithoutproducingfalse-positives,meaningthat there was a trade-oﬀ between dependability andsecurityto beconsidered. The90swasthestartingpointfordiscussions around these two critical concepts. Dependability refers to thefrequencyoftruepositiveswhentestingaclassiﬁer;itex- presses how good the classiﬁer is at detecting faults. In the HIFdetectionﬁeld,itisrepresentedbytheratiobetweenthe number of fault observations correctly labelled, to the total amount of fault observations tested. Security, on the other hand,referstothefrequencyoftruenegativeswhentestinga classiﬁer;itexpresseshowgoodtheclassiﬁerisatnotdetect- ing faults when they are not occurring. It can be calculated by the number of non-fault observations correctly labelled asnon-fault,dividedbythetotalnumberofnon-faultobser- vations. With the increasing proposal of diﬀerent detection methods, the consequent question of addressing imperfect security and what to do with the detection result had to be addressed. Theauthorsthusmadeuseoftheproductdisclo- suretodiscusspossibleliabilitiesassignedtoutilitieswhich decide not to install such equipment in regards to damages created by undetected HIFs [36]. Comments on how such a method could be used in diﬀerent regions were also made. Theauthorssensiblyarguedthattrippingarelayinaridareas where a downed conductor could ignite wildﬁres in vegeta- tion would make more sense than in a city environment. ResearchesatTAMUcontinuedtobuildontheirworkby proposingadetectionmethodbasedoncurrentRMSfractal analysis[37]andpublishingonpracticalexperiencesgained from the use of their device in real feeders [28]. The au- thors focused on the security discussion defending that ser- vice continuity of clients is far too valuable to be sacriﬁced for a ‘trigger happy’ algorithm. The paper [28] analysed the equivalent of forty-seven unit-months of device opera- tioninﬁvefeederswhereadditionalfaultswerealsostaged. It showed an optimistic view of the device application by stating that faults that were not cleared by overcurrent de- vicesweremostlyalldetectedbythefeedermonitor(88%of staged faults). Furthermore, two more similar papers were publisheddiscussingthedeviceimplementation[38]andits practicality [39]. In the ﬁrst, many issues arising from the use of such technology were discussed. From legal to emo- tionalissues,thepaperincludedaframeworkfortestingandevaluatingaHIFdetectionmethod,theresultofsurveys,and expert opinions. However, none of those subjects was dis- cussedintoobroaddetailbutratherinbriefdiscussions. The secondpaper[39]discloseddetailsontheIPlicensingofthe technology to GE, the balancing of dependability and secu- rity for service continuity, and the functionality of the de- vice. Theresearchundertakenthroughoutmorethanadecade at TAMU has evolved and culminated on the present GE’s Multilin F60 Feeder Protection System [40] which, to present day, still apparently uses expert systems to detect HIFs. Givencurrentknowledgeaboutlearningsystems,and how expert systems were superseded by machine learning techniques, there could be an argument for substantial im- provement. Thisclaimcanbemadebasedsolelyonthefact that the features’ weights used in the expert system method arebasedon aprioriknowledgefromhumanexperts,incon- trary to a top-down empirical approach. Other researchers in 1990 realized possible issues with arbitrarydecisionboundarieswhenproposingtheﬁrstappli- cationofneuralnetworkstodetectHIFs[41]. Theproposed method calculated large amounts of signal features such as the peak of transient current, RMS value, the magnitude of positive sequence, energy of harmonics, and used to learn a multi-layer perceptron feed-forward neural network. It was one of the ﬁrst methods to use simulated HIFs in their vali- dation(anubiquitouspracticeinthefollowingdecades),in- steadofreal,stagedfaultsignals. Despitebeingnovel,there weremanynoticeableissueswiththisapproach. Theneural network had a large number of inputs and nodes compared withtheamountofgenerateddata(possibilityof overﬁtting ). There were no validated HIFs models at the time, making it an excessive unrealistic simulation, and features were still hand-engineered. By “hand-engineered features” is meant that the predictors are created from human knowledge, cal- culated from signal representation techniques; the converse wouldbethefeaturescreatedintheprocessofapplyingdeep learning, which captures layers of features from the data la- tent space. Further work with neural networks (1992) [33] addressed some of these problems. The methodology, in- steadof usinghand-engineered featuresas inputs,consisted of feeding a fundamental frequency cycle of raw current samples to a feed-forward neural network. It was the ﬁrst full top-down, supervised learning approach, used to learn patterns in the current time-domain signals. Although powerful, top-down approaches still present the apparent constraint of requiring data from real, staged faults. Suchexperimentscanbeonerousandexpensive,only tobeperformedbyprominentuniversitiesandlargecompa- nies. Consequently, due to the commercial value of the re- sulting IP, organizations performing such experiments had many incentives to keep the data private. This restriction ledresearcherstoinvesteﬀortsincreatingHIFmodelstobe usedinsimulations,circumventingtheproblemofrequiring experimental data. The complexity of the HIF phenomena and non-converging opinions in the literature clearly make such an attempt ambitious and highly challenging. DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 4 of 23 High-Impedance Faults in Power Distribution Systems i Vp VnXl R Figure 1: Emanuel’s et al. [42] HIF Model (1990). Historically, the ﬁrst relevant and inﬂuential HIF model was proposed in 1990 [42]. The authors represented a HIF as a fault impedance in series with an anti-parallel diode and DC voltage sources branch, as illustrated in Fig. 1. The anti-parallel branch helped to model the previously ex- plained breakdown voltage where conduction only started afteritwashighenoughtobreakthedielectricnatureofthe high-impedance surface. Its main parameters were the fault impedance(XlandR),whichdictatedmostofthefaultcur- rentamplitude,andtheDCvoltagesourcesvalues. TheDC sources(VpandVn)couldassumediﬀerentvaluestoaccount fortheasymmetricnatureofHIFs,whichcanhavediﬀerent breakdownvaluesforpositiveandnegativehalf-cycles. Dur- ing the positive and negative half-cycles, the current ﬂows only through VpandVn, respectively. The second and third harmonic currents (as a percentage of the fundamental) are then deﬁned as functions of the diﬀerence VpandVn(V) andtan.Xl_R/. Notwithstanding, one should mention that this work attempted to model the HIF behaviour of a bro- ken conductor falling to sandy soil. The authors had the main goal of analysing to what extent frequencies from 120 to 180 Hz could be used to detect such HIFs. Any strong claims present in further papers directly inﬂuenced by this workwhichchoosetoignoreordismisstheseenvironmental conditions should be prefaced as hypotheses, speculations, or are just fallacies. The urge for ﬁnding better HIF features, together with developmentsinthesignalandimageprocessingﬁelds[43], was responsible for the introduction of a technique that rev- olutionized signal representation techniques: wavelets. Al- though promising, the application of top-down approaches like neural networks do not provide a phenomena under- standingorcasualframeworkthatbottom-upapproachesdo. When used to decompose signals, the Wavelet Transform (WT) serves as an eﬃcient time-frequency signal represen- tation with fair time localization [44]. Diﬀerent from the dominant and prevalent Fourier Transform (FT), the WT’s decompositionbasisfunctionsaredilatedandtranslatedver- sions of ﬁnite oscillations with constant shape. This diﬀer- ence makes the transformation outputs to be well localized intime,converselytothestationarysinusoidbasisfunctions fromtheFT.Theoscillationsusedinthedecompositionare allowedtohavearbitraryshapes,althoughonewouldprefer (a) Haar. (b) Daubechies. (c) Symlet. (d) Coiﬂet. Figure 2: Examples of commonly used wavelet families. Adapted from [45]. diﬀerentiable, compact, zero-mean, and square-integrable functions for practical reasons. Commonly used wavelets withaspeciﬁcshapenamed‘waveletfamilies’areillustrated inFig. 2: Haar,Daubechies,Symlet,andCoiﬂet. Ingeneral, wavelets are more eﬃcient at representing signals’ discon- tinuities and transients since they have more sparserepre- sentations in the wavelet domain with consequent localized energy. Thiseﬀectbecomesespeciallyevidentifthemother- waveletusedinthedecompositionresemblestheshapeofthe representeddiscontinuity. AnFTofthesamesignal,contrar- ily,willresultinawidebandrepresentationinthefrequency domain with “spreaded” energy. Mostwaveletimplementationsinthisﬁeldareeitherthe traditional Discrete Wavelet Transform (DWT) through the Multi-Resolution Analysis (MRA) or a slight modiﬁcation of it. The DWT has a simple, relatively fast, and non- redundant application as shown in (1). Where, x[k]is the sampled signal, [n]represents the mother wavelet, am ois thedilationcoeﬃcient,and lam oisthetranslationcoeﬃcient. Suchapproachbecomesmorenumericallyeﬃcientwhenthe MRA is used. In this process, the decomposition is given bytheiterativeapplicationofaseriesoflow-passandhigh- pass ﬁlters. The result is time scaled versions of the orig- inal signal which have most of its energy in a well-deﬁned bandwidth. Each time a couple of ﬁlters is applied, the sig- nal is downsampled in a dyadic manner, resulting in fewer samples, thus giving its numeric advantage. The MRA al- gorithm is performed as shown in (2) and (3) by using the h[t]andg[t]asthelow-passandhigh-passimpulseresponse functions, respectively. DWT[x;m;n]=1ùam oÉ lx[k] [n*lam o am o](1) yi d[n]=ØÉ k=*Øyi*1 a[k]h[2n*k] (2) DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 5 of 23 High-Impedance Faults in Power Distribution Systems yi a[n]=ØÉ k=*Øyi*1 a[k]g[2n*k] (3) ItmightbeusefulthecontrasttheDiscreteFourierTrans- form (DFT) since Fourier-based and wavelets and are the maintechniquesforfeatureextractioninHIFdetectionmeth- ods. For a real discrete sequence of length N, the DFT op- erator is given as in (4). Despite eﬀectively used in many applications, applying the DFT for signal representation re- sults in many constraints and issues. As an example, con- sider a 1-second duration signal sampled with at a high rate so frequencies from a wide band can be properly charac- terised. ADFTofsuchsignalwillresultinalongsequence offrequencycomponentssinceithasthesamelengthofthe recorded digital signal. If the exact frequencies of interest are known, there needs to be an adjustment of the length of thesignal,sotheresultedequally-spacedfrequencyindexes have the exact desired value. If the frequencies of interest are not known (usually the case), and one wants to use the whole coeﬃcients, the feature space will comprise a long sequence with high dimension. This is a problem since one usuallywantstolimitthedimensionalityofthefeaturespace as much as possible to not fall prey of the curse of dimen- sionality. Moreover, intermittent and sampling noises can be harmful for frequency estimation, introducing energy in frequency bands that are not originated from the signal of interest. Methods are then prone to use spectrum analysis to leverage existent data that is longer than the amount re- quiredtoattainthedesiredfrequencyresolution. Thedatais usually partitioned so that multiple DFTs can be performed and averaged. This averaging reduces the variances intro- duced by the noise sources, improving the precision of the power estimation of frequency components. As features as real numbers, the power spectrum is often used. Referred toasPowerSpectrumDensity(PSD),itscalculationisbasi- callythesquaredoftheabsolutevaluesgivenbytheDFTof the signal, as shown in 5. DFT^f[n]`=F[k]=N*1É n=0fne*i2kn_N(4) PSD=F^f[t]<f[*t]`=F[!] F<[!]=ðF[!]ð2(5) The use of wavelets for HIF feature extraction started at the end of the decade. The ﬁrst inﬂuential work [15] used wavelets to detect the transients generated by the faults, fol- lowed by a heuristic to diﬀerentiate them from other distur- bances. It was not only novel in its wavelet application but alsobuiltonthepreviouslymentionedmodel[42]topropose a more intricate HIF model based on arc theory. Claiming thatitspredecessordidnotrepresenttheuniversalbehaviour of HIFs, the authors proposed a model that was supposedly better at representing the non-linearity of a HIF impedance. An illustration of the proposed model [15] is shown in Fig. T ACS Switch SignalT a ∆tvDistribution f eeder S wi tch 1 S wi tch 2 R D1 D2 S1 S2Figure 3: David and Xia’s [15] HIF Model (1998). 3,whereSwitch2isconnectedtoaTransientAnalysisCon- trolSystem(TACS)modelsettorepresentthearcre-ignition and extinction. Its operation is dependent on a comparison ofTa,thetimefromtheappliedvoltagezero-crossingtoarc re-ignition point, and t, the time of arc conduction in one half-cycle. The TACS model inputs are the arc re-ignition voltageVr, peak value of the applied voltage Vm, and arc voltageVa,withrelationshipdeﬁnedbyEq. 6and7. Diﬀer- entlyfromtheinspiredwork,thevoltagesourcesintheanti- parallel branch (S1 and S2) are time-varying, not restricted to DC values. They were chosen to have a sawtooth wave functionwithincreasinganddecreasinglinearitytosuppos- edly represent the arc v-i characteristic better. The variable resistanceRis mainly responsible for the value of the fault current magnitude, which was in the order of tens of amps in the paper [15]. Such work was also one of the ﬁrst pa- perstopresentafullsimulation-basedmethodologyinstead ofrelyingonexperimentaldata. Asecondwavelet-basedin- ﬂuentialwork[46]soonfolloweditbyproposingtheuseofa diﬀerentwaveletfamilyasitsonlymaincontribution. Asyet anovelidea,wavelet-basedworksbecamewidelypopularin thenextdecades,ﬁercelycompetingwithFourier-basedap- proaches. Ta=1 !sin*1Vr Vm(6) t=Vr+2t V2 m*V2 r !.Va+Vr/(7) Nevertheless, Fourier/Harmonic analysis was still the prevalent feature extraction method in the majority of de- DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 6 of 23 High-Impedance Faults in Power Distribution Systems tection methodologies. Most methods were based on ﬁnd- ings made in the 80s around the HIFs eﬀects on the har- monicsignatureofphaseandneutralcurrents. Onepioneer- ing work [47] presented a Kalman ﬁltering approach as an on-line recursive estimator of harmonics that accounted for time-varying nature of the signals. The advantage of this approach was that it did not need to assume the signal to be stationary (like the conventional FT). The method was cen- tred on calculating a randomness value from estimated har- monics, in four to six fundamental cycles, and detecting a faultifitincreasedhigherthannormallyobservedvalues. A followingwork[48]arguedfortheuniqueharmoniccharac- teristics of HIFs. It stated that such faults would have high third harmonic components with characteristic phase shifts that could be used for detection. Similarly, a creative ap- proach using the ratio of odd and even harmonics to detect HIFoccurrenceswasproposed[32]. Itwasbasedonthehy- pothesesthatHIFshaveaparticularharmonicsignaturedue to their half-cycle asymmetry, which could introduce even harmonics to the system. The unbalanced current and en- ergy of harmonics were also used to conceptualize another method [49] that was validated with staged tests. Such an approach seemed to work reasonably well for fault currents higher than 5 A. Thesecitedworkshavetheadvantageofbeingvalidated with data from real, staged tests, usually in multi-grounded systems, mimicking a downed conductor scenario. Their weakness, however, relates to the consensus that harmonic content alone is not a reliable parameter to attest for a fault occurrences [34, 16, 50, 51, 52, 53, 54]. It is often stated thatsimilarharmonicconditionscouldappearinnormalop- eration states of the system, mostly from switching events and the contemporary diversity of non-linear loads. A sig- niﬁcant number of VHIFs do not produce harmonics in the ﬁrstsecondsofconductionatthefaultlocation,meaningthat they would be even more attenuated for measurements far away from the fault point. Nonetheless, it was not a widely sharedopinionatthetimethesemethodswereproposedbut itchangedparticularlyduetotheever-increasingpenetration of non-linear loads and novel signal representation tools. Two other inﬂuential and valuable works from this decade are also worth commenting. The ﬁrst is the highly innovativemethod[34]presentingtheﬁrstactivemethodto detect HIFs. It consisted of injecting periodical impulses to the network and measuring its response, which would pre- sumablychangeinthepresenceofafault. Themethodology wastailoredtoBraziliannetworks,whichhavemanysingle- andtwo-phasesbranches,thusbeingheavilyunbalanced. Its mostsubstantialconstraintsweretheneedfornetworkdata, fullknowledgeofitstopology,andhigh-speeddataacquisi- tion systems. After injection, the electric signals were sam- pled, processed via FFT, and used as inputs in a fuzzy rea- soning system. The fuzzy rules, as in other approaches in this era, also used a prioriknowledge and rules of thumb from human experts. In the second work, a paper by a GE engineer [55] reviewed and discussed some of the current technologies to detect HIF. This paper was the ﬁrst inﬂuen-tial work in the literature to discuss mechanical methods to detect HIFs. The author explains that such a device would be mounted, in a cross arm or pole, under each phase wire and connected to the ground. In this manner, a conductor breakage would realize contact between phase and device, creating a ground fault that could be easily detected by ex- isting overcurrent devices. He also then quickly dismisses the usage of such a method claiming that installation and maintenance costs would be too high to be feasible. Nev- ertheless,theauthorstillrecommendeditsinstallationclose to critical areas such as churches, schools, or hospitals. The rest of the paper could be seen as a call to action to utilities installthepreviouslymentionedfeedermonitorconceptual- izedbyTAMU.Commentsontheuseofthedetectionresult and the need for HIF detection devices were made based on the possible million-dollar liabilities companies could face for damages created by HIFs. One can see the 90s as the golden era of HIF detection engagementandinnovation,wherethemostinﬂuentialideas were proposed. The core of insights and innovations of the decade can be summarized: •First commercial protection device targeting HIFs [36]. •First full top-down application of neural networks in HIF detection [33]. •FirstHIFmodeltocircumventtheneedforexperimen- tal data [42]. •First use of wavelets in HIF detection [15]. •Firstactivedetectionmethodbasedonthenetworkim- pulse response [34]. •Emphasis on HIF detection based on the harmonic content of current signals [49, 48, 32, 47]. •Deeper discussions on the trade-oﬀ between depend- abilityandsecuritygivenbypossibleactionstoaHIF detection and utility liabilities [36, 28, 38, 39, 55]. •Despite exceptions, methods still heavily relied on a priorihuman expert knowledge. 4. The 00s — Wavelets, machine learning, and specializations Although falling short in terms of ground-breaking in- novations, the 00s were responsible for important incre- mentalcontributionstopreviouslyproposedtechniquesand sub-ﬁeldspecializations. Manyfeatureextractionvariations wereproposedasnovelcontributions,formingacompetitive scenarioinsignalrepresentationapproachessuchaswavelet andFourier. Beingmostlyhand-engineeredandrelyingon a prioriknowledge, the new proposed features can be mainly classiﬁed as bottom-up approaches to HIF representation. Detection methods using such features, however, started to DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 7 of 23 High-Impedance Faults in Power Distribution Systems increasingly have their decision boundaries deﬁned by ma- chinelearningtechniques( aposteriori ),insteadofarbitrary thresholds. Forthemostpart,mostofthecontributionvalue from this era probably came from sub-ﬁeld specializations such as in speciﬁc conduction surface, network grounding types, and sensor-based sampling technologies. Wavelet-basedmethodssurgedinnumbersandpopular- itywithmanyfeatureextractionvariationsproposedasnovel contributions. Oneoftheﬁrstworksofthisdecade[56]isan exampleofsuchanapproach. ItproposesadiﬀerentWTde- composition where the frequency bands are linearly spaced in the frequency domain, named wavelet Packet Analysis (WPA).InadditiontobeingtheﬁrsttoapplyWPAtoHIFde- tection, the authors also took into consideration the wavelet components phase distribution w.r.t. the current fundamen- tal cycle. Such phase distribution becomes relevant when considering the previously mentioned voltage “breakdown value”, which will lead to more discontinuities near zero crossings of the fundamental voltage signals. Its downside, not surprisingly, is that not all HIFs present evident break- down phenomena (further explained). A feature variation on the coeﬃcients of the WT, now in its traditional Multi-Resolution Analysis (MRA), is also presented in [57]. The work calculates the RMS conversion on the detail coeﬃcients extracted from current signals as featuresandusesittoestablishdecisionboundariesforfault detection. Thefeaturesarefedtotheclassicalmachinelearn- ing technique named Nearest Neighbours Rule (NNR). In a similarwaytoitsmoreknownversion,K-NearestNeighbors (KNN),thistechniqueisasimplenon-parametricclassiﬁca- tion method that established decision boundaries based on votes from the nearest data points in the feature space. This work’s [57] specialization factor, however, comes from its consideration of distributed generation in the power system simulations. As in many other works further discussed, its solelymodellingapproachissomewhatsimplisticinregards tothecomplexityofthephenomena,whichmakesithardto defend as a conclusive ﬁnding. Further papers [58, 59] proposed a diﬀerent heuristic for classiﬁcation and an important specialization consider- ation: network neutral earthing type. The feature extrac- tion is performed by the application of the WT on the neu- tral/residual voltage and current signals. The detection is done by a heuristic on a measure of phase displacement be- tweencurrentandvoltagecoeﬃcients[58]andaperceptron- basedclassiﬁer[59]. Initspurelysimulation-basedanalysis, the authors conclude that the most challenging faults to be detectedweretheonessimulatedinacompensatednetwork (resonant grounding type) due to the signiﬁcantly reduced ground fault current. Stillinwavelets,someauthorssuchas[60,61]proposed variationsonthetransformapplicationintwosimilarpapers. BothuseWTforfeatureextractionbutdiﬀerentapproaches infaultdetection: (1)Geneticalgorithmforfeatureselection and a Naive Bayes classiﬁer for classiﬁcation, and (2) Prin- cipal Component Analysis (PCA) for feature selection and ANN for classiﬁcation. The works are relevant due to theiruse of real, staged tests, intricate machine learning algo- rithms, and optimization methods. However, the relatively small number of HIF staged tests opens the work for criti- cismwhen ANNisappliedforclassiﬁcation. Thecomplex- ity of the method in relation to the number of used features makestheapproachproneto overﬁtthedataset,andpossibly less generalizable to new HIF data. Adding this to the fact thatnon-faultexamplescamefromsimulationsmakesithard to evaluate the real eﬀectiveness of the approach, even with the application of intricate, powerful tools. Other worth- while mentioning works presenting wavelet variations are papers proposing adaptive neural fuzzy inference [62] and Support Vector Machines (SVM) [63] as classiﬁers. In the ﬁrst[62],theauthorsusedsixfeatures: fourderivedfromthe wavelet coeﬃcients energies from current signals and two from third harmonic and signal mean value. In the second [63],theenergyofthedetailswasextractedasfeatures,hav- ingtheirdimensionreducedbyPCA,andthenfedtoanSVM classiﬁer. Various Fourier-based approaches shared the theme of feature extraction variation and specialization. Early in the decade, a paper [50] describing the use of harmonics ener- gies from residual currents and voltages was presented. As some of the recently cited papers, its strength was mainly correlated to being a specialization approach. In this case, it was related to a hardware prototype implementation of an ANN-based classiﬁer, which was indeed novel for the time. Afollowinginterestingapproach[64]usingharmonics and its phases to draw ‘Harmonic Patterns/Phase Portraits’ was soon after introduced. By making use of the third and ﬁfth harmonic, phase portraits were drawn and used as pat- terns that could discriminate a fault occurrence from nom- inal system operation. Although interesting, it was a con- voluted heuristic that did not get much attention after pro- posed. Later,asimpleandeﬀectiveapproachusingFT[65] andlearningalgorithmsbecameveryinﬂuential. Itconsisted of merely doing the FT of the current signals and using the components to learn a machine learning algorithm, named ‘Decision Trees’ (DT). As yet another purely simulation- based work, the authors granted in their conclusions that wavelets could have helped enhance the performance of the classiﬁcationresults. Ifencompassedintheclassiﬁcationof Fourier-based approaches, proposed Kalman ﬁltering tech- niques [66, 67] for features extraction should also be men- tioned. The authors of these two similar papers studied the use of the estimated harmonics with an ANN [66] and an SVM classiﬁer [67]. After discussing some of the most inﬂuential wavelets- andFourier-basedworks,acoupleofimportantremarksre- garding their adoption and HIF modelling should be made. The ﬁrst concerns the increasing use of wavelets to repre- sent fault signals. Since the ﬁrst impactful work in 1998 [15], wavelet-based methods went from a fringe idea to a prevalent approach in the surveyed works. One could argue that such an eﬀect, and the ever-present use of wavelets, is evidence of its superiority in representing HIF signals over Fourier-based approaches. The second remark concerns the DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 8 of 23 High-Impedance Faults in Power Distribution Systems overwhelmingnumberofproposedmethodsbasedsolelyon HIFmodelsimulations. AlltheFourier-basedmethodsmen- tioned in this section exclusively rely on models rather than data from real experiments. From wavelet-based methods, more than half rely on models when conceptualizing their approach. On the one hand, this practice is not surprising given the fact that experiments are so onerous and simula- tions are so accessible. On the other hand, it is also not sur- prising that commercial methods do not use most of these variations, and they are not regarded as robust and defensi- bleevidence. Thisassertionisespeciallytrueifoneaccepts the presupposition that HIF behaviours are not fully repre- sented in current HIF models. Despite the challenging nature of the problem, essen- tial works regarding HIF modelling were presented in this period. The authors of the ﬁrst paper [68] argued that the modelspreviouslypresenteddidnotrepresentimportantHIF behaviours such as Build-up andShoulder. Build-up is de- ﬁned by the period where fault current grows to its maxi- mum local value, which last approximately tens of cycles, according to the authors. The shoulder is the period where thebuild-uptemporarilyceaseforafewcyclesuntilitstarts growing again towards its maximum global value. The au- thorsintendedtoproposeasimplerandmorerealisticmodel incorporating such features that did not have as many com- ponents as previous ones. It was conceptualized by just two seriestime-varyingresistancescontrolledbyTACSinElec- tromagneticTransientsProgram(EMTP).IllustratedinFig. 4, this model was inspired by thirty-two tests performed by a Korean power company, sampled at 10 kHz. It attempted toaccountfortheproposedfeaturesbymodelling R1asthe time-varying resistance with periodical changes (shoulder), whileR2monotonicallydecreasesfromitslargeinitialvalue (build-up). As it was set to represent the non-linearity and asymmetry,R1hasthesamecharacteristicateverycyclein steady state. R2modulates the build-up and shoulder char- acteristics, which are predominantly present before steady state, according to the authors. Both elements are then con- trolledbyaTACSelementthatﬁtthetotalresistancetofol- low a certain v-i characteristic through time. Despite im- pactful,itisnothardtoﬁndissueswiththisapproach. Some examplesarethenumberoftestsused,theabsenceofinfor- mation around the fault surface, and more importantly, how it was validated. The authors seemed satisﬁed with the fact that the current curves from simulated and real data closely overlapped visually and had close harmonic content. A fur- ther work [69] also used the same two-resistor scheme to propose a HIF model based on arc theory. The authors at- tempted to propose, in a full bottom-up approach, a model thatwouldmimicsurveyedHIFfeaturesdescribedinthelit- erature and their arc-like characteristics. Notwithstanding, it is hard to defend such a methodology since there was no veriﬁcation with real data. An important contribution proposed in works from this decade was the specialization on diﬀerent types of neu- tral grounding. In multi-grounded or solidly grounded sys- tems, a ground-fault current is limited by the series line R1(t) R2(t)Controlled by TACSF aul t pointFigure 4: Nam et al. [68] HIF Model (2001). impedance. In an ‘Ungrounded’ system, the limiting factor is the stray system capacitance. The diﬀerence in the cir- cuit diagrams is illustrated in Fig. 5. As these capacitances are the only current return paths in ground faults, they are solely responsible for the existence of fault currents in un- grounded systems. This fact makes such a conﬁguration to have major beneﬁts: lower ground-fault current, better per- sonnel safety, and more reliable service [70]. The latter is achievedbythefactthatagroundfaultwillnotaltervoltage between phases; two- and three-phase loads can then sim- ply ride through them. Any signiﬁcant fault impedance on such a system would result in current levels similar to HIFs ingroundedsystems. Itdoesmakefaultslessdangerousbut does not solve all the problems. Single-digit fault currents, which can ignite ﬁre in surfaces like vegetation, are still not easily identiﬁed. Moreover, another considerable downside is the increased voltage level in the other two phases cre- ated by the shift of the neutral point in an occurrence of a fault. The practical application of neutral grounding types inrealsystemsis,nevertheless,notsopolarizing. ANeutral Earth Resistance (NER) can be placed between the neutral andearth,makingitahigh-impedanceneutralearthingsys- tem. Evenmoresophisticated,alternatively,avariablehigh- impedancereactorconnectedtotheneutralpointcanbead- justed to compensate the stray system capacitance. Such a reactor, illustrated in Fig. 6, is known as Peterson Coil, arc- suppression coil, or ground-fault neutralizer. Three-phase networkswiththistypeofgroundingareoftenreferredtoas resonant-grounded or compensated systems. Ground fault currents in this type of systems can be reduced to about 3 to 10 per cent of that for an ungrounded system. They can be found in Northern and Eastern Europe, especially in Nordic countries [71, 18], China [72], and Israel [73]. In Australia, legislation has been enforcing and mandating utilitiestoinstallresonantgroundingwithRapidEarthFault CurrentLimiters(REFCLs)[74]duetopastseverewildﬁres ignitedbypowerlinesinthecountry. Ifinterested,thereader can ﬁnd more information on ground fault protection meth- odsfordiﬀerentneutralgroundingsystemsinadetailedand DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 9 of 23 High-Impedance Faults in Power Distribution Systems N R esidual Curr entA B C GNGr ound F aul t (a) MultiGroundedSystem N R esidual Curr entA B CGr ound F aul t C a C b C c (b) UngroundedSystem Figure 5: Types of neutral earthing. Image based on [51]. NA B C Gr ound F aul tC a C b C cP eterson coi lC bcC ab C ac Figure 6: Diagram of a compensated system. Image based on [73] professionaldescriptionby SchweitzerEngineeringLabora- tories(SEL) [73]. One of the advantages of having the high-impedance connected between the neutral and ground point of a three- phasesystemistheresultingsmallerearth-faultcurrent. The operation of the system beneﬁts from the fact that, since the loads have all to be connected between phases, zero- sequence measurements are freeto be used for earth fault detection. The REFCL, labelled ‘Ground fault neutralizer’[75] by its pioneering company, Swedish neutral , presents itself as an enhanced suppression coil. Its main advantage liesonspeed,beingabletocompensateneutralresidualcur- rentsinunderthreepowercycles(150ms). Suchcapabilities makeREFCLsaneﬀectivesolutionforearthfaultsinterms ofﬁresafety. However,asmostengineeringsolutions,there are trade-oﬀs and limitations in their application. The ﬁrst REFCLapplicabilityconstraintisthefactthatitcanonlybe implemented in resonant-grounded systems. As their func- tionality is primarily dependent on the residual earth cur- rent, REFCLs are not suitable to systems that intentionally rely on the earth path for their standard operation like most Australian networks. This incompatibility represents a con- siderable constraint since, in places like Victoria, Australia, SWERlinesare28,000ofthe88,000kmofthedistribution overhead power lines [76]. The installation of REFCLs can be expensive and have exceptionaladdedcosts. Thesecostsemergefromtheintrin- sic behaviour of ungrounded systems in fault occurrences. As in all other conﬁgurations, if a conductor comes in con- tactwiththeearth,theybothassumethesameelectricalpo- tential. However, phase-to-phase voltages magnitudes will notchangeinungroundedsystems. Instead,ashiftingofthe neutralpointhappens,changingitsvaluetoapointwhereall the voltages between phases remain the same as before the fault. This intrinsic characteristic of ungrounded systems gives it the ability to ride-through earth faults without any servicedisruptions(loadsareallconnectedbetweenphases). However, if the fault happens in the phase C, for example, thevoltagesofphaseAandBtogroundwillincreasetoval- ueshigherthannominal,assumingpreviousphase-to-phase values. This overvoltage event on the remaining phases is oneofthesidesfromthetrade-oﬀassociatedwiththeadop- tion of ungrounded systems; it adds more stress to power equipment insulation. Therefore, power companies have to take precautions with vulnerable equipment in the network before installing such equipment. Discussions of HIF detection in non-eﬀectively grounded systems in the literature started in the middle of thedecadewiththeaforementionedwavelet-baseddetection work [58]. The authors propose a detection method on the phase displacement between the zero-sequence voltage and current, arguing that it would be more challenging to detect HIFs in such systems due to their smaller fault currents. However, a later analysis [70] by a SEL engineer argued the case that, in such systems, HIF could be more deterministic and accurate by just having highly-sensitive measurements on the ground residual current (see Fig. 5b for residual current representation). With detailed circuit theory, the authors proposed faulted feeder and faulted phase identiﬁcation with residual voltage and current phasor analysis. Nevertheless, researches from Finland and Egypt were convinced that current resonant systems’ technologytodetecttree-relatedHIFsneededimprovement. Given that ﬁres can be ignited by faults with single- digit amperes in vegetation [9], it is not surprising that the important specialization regarding tree/vegetation faults DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 10 of 23 High-Impedance Faults in Power Distribution Systems came from works discussing non-eﬀectively grounded sys- tems. Thediscussionstartedinaseriesofthreepublications [71, 8, 77], where authors focus on this particular type of fault. In their ﬁrst paper [71], laboratory experiments were set-up to conceptualize a leaning-tree HIF model. The out- comes included an arc theory-based model and a wavelet- based HIF detection method. Features were extracted from residualvoltageandcurrentsignals,andHIFoccurrencewas detectedbyasimplewavelet-coeﬃcientsummation. Theau- thors were satisﬁed with the resulted model, which closely approximated the V-I characteristic curve of a small num- ber of experiments. The method scheme, with validating simulations,wasfurtherpresentedintheirsecondpaper[8]. Oneoftheirconclusionwasthatthefaultbehaviourwasalso dependent on the network characteristics, making the tran- sients used in the detection less sensible for faults distant from the measuring point. Therefore, they also had to in- clude and advocate for wireless sensors that would be dis- tributedthroughoutthenetwork. Suchwide-areamonitoring throughsensorswasoneoftheinnovativeideasthatgottrac- tioninthe00s;itwasalsopresentedintheirthirdpaper[77], which used new data from a few tree HIF tests staged on a realfeedertovalidatetheirpreviouslyproposedmethod. De- spitediﬀerentfromthemethodologyproposedin[70],both authors pointed to the consensus of using residual current andvoltagestodetectHIFsinnon-eﬀectivelygroundedsys- tems. A pioneering work focusing on the electrical charac- terisationofvegetationfaults[14]isalsoworth-mentioning. Itpresentedimportantevidencetotheimportanceofdealing withthesespeciﬁctypesoffaultssuchasthelinearityofthe fault current in the ﬁrst cycles of conduction. Regardingtheuseofwirelesssamplingtechnologies,an increasing number of works started to propose and discuss the idea of using distributed sensors to aid in HIF detec- tion. In one of the ﬁrst inﬂuential works from this decade, researchersfromBrazil[78]proposedaninnovativesensor- based approach. It described a sensor to be placed in power poles such that it would be sensitized by the electric ﬁelds produced by the conductors on the primary feeder. With strategic placement, this single sensor was able to detect three-phase voltages unbalances that would indicate the oc- currence of a broken conductor. In addition to the presen- tation of the detecting device, the authors also suggested a methodology based on powerline carrier communication for signal transmission. The cost could be pointed out as a constraining aspect of the presented scheme. The au- thorsexplainedthatalthoughtherestofthedevicewasrela- tivelylow-cost,thecapacitorusedinthetransmittercoupling costed around thirty-ﬁve thousand dollars. Moreover, a dif- ferent sensor approach targeting covered conductors in Fin- land’s systems was proposed [10]. The sensor based on the Rogowskicoil —anair-coredcoilaroundthefeederconduc- torseparatedbypolyethyleneisolation—wassettomeasure leaning-tree fault Partial discharges (PD) pulses. The au- thorsarguedthatsuchcoilshavetheadvantageofpossessing ahighsignaltonoiseratioinwidebandfrequencyresponse. Hence, they would be eﬀective at detecting short and high-frequency PDs generated by leaning trees. Its strengths are thecertainpossibilityofbeingalessexpensivecouplingand non-invasive installation. Its possible main disadvantage, however, is the consequent need for communication meth- odsanddataprocessing. Investedontheapproach,nonethe- less, the authors continued to publish on the use the device in a further review [79] and in an attempt of validated their method [80]. It is important to note that, these publications mainlytargetedthePDdetectionresearchﬁeld. Thedevices were not described as a HIF but as a PD detector. Nev- ertheless, in a non-eﬀectively grounded system, a leaning tree that touches a faulty covered conductor is most proba- bly a HIF. Therefore, this work can be seen as representing a novel literature intersection of the PD and HIF detection ﬁelds. A further work proposing PD sensing in overhead distribution lines [81] using frequencies as high as 25 MHz withRogowskicoilscanalsobecitedasanexampleofsuch an intersection. Ultimately, it is hard to deny the possible beneﬁtsandaccessibilitythatsuchsensor-basedapproaches could bring. They probably represent the most likely can- didates for future HIF sensing and detection. Recent works andpatentsgrantedwithverysimilarideas[82,83]canalso becountedasevidencefortheinterestinsensor-basedsam- pling technologies. On the commercial ﬁeld, development and discussions of solutions from key industry players continued to evolve. Competitorcompaniessuchas ABBandSELfelttheneedto proposetheirHIFsolutionsfollowingthepioneeringeﬀorts ofGE.In2004,ABBpublishedanannouncementofitsHIF detectionphilosophytobeincludedintheirfeederprotection devices [84]. Sampling signals in 32 samples per cycle (1.6 kHzat50Hzfundamental),themethodcomprisedofacom- bination of wavelet analysis and ANN. High order statistics were applied to the wavelet coeﬃcients while a two-layer network was fed ﬁve cycles of raw current samples. Al- thoughmentionedinthedocumentasa‘votingsystem’,the decisionlogiconthewaveletfeaturesandANNoutputswas unclear. Suchamethodology,however,attestedfortheinter- estofthecompanyinusingtrendingandmodernbottom-up and top-down approaches. The same could not be said for the algorithms proposed by SEL [52]. In the paper, the author argued that a de- terministic methodology using traditional relay logic would be easier to understand and simpler to implement. In a somewhat contradictory stance, favouring deterministic ap- proachesanddismissing“black-boxmethods”suchasneural networks to detect the faults, the author proposed a method consisting of a heuristic applied to the current signals. It starts with the extraction of its single main feature: a run- ning average of a quantity named “Sum of Diﬀerence Cur- rent” (SDI). Deﬁned as a one-cycle diﬀerentiator set to rep- resentallthecumulativeeﬀectofnon-harmonicfrequencies, the SDI can allegedly assert the occurrence of arcing HIFs. The feature is compared to a trend, which could be adap- tivelytunedfordiﬀerentenvironmentalconditions,andsent to the decision logic algorithm. The classiﬁcation label is then given by a counter responsible for tracking how many DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 11 of 23 High-Impedance Faults in Power Distribution Systems times the SDI exceeded the threshold within the previous seconds. Validated in apparently four tests in the disclos- ing paper, this methodology would then evolve to the cur- rent commercial Arc SenseTMTechnology present in many feederprotectiondevicesbySEL[85]. Thesameauthoralso published a paper reviewing HIF detection in systems with diﬀerentgroundingtypesanddescribingtheperformanceof thealgorithminstagedfaults[51]. Inthisanalysis,strongar- gumentswerepresentedforthespecializationhypothesisby criticizing methods that claim speciﬁc detection rates with- out specifying distinct conducting surfaces. From GE and TAMU, however, only one paper describ- ing the ﬁeld experience with their previously proposed HIF detection algorithms was published [3]. The discussion revolved around a power company’s experiences from in- stalling relays with HIF detection in 280 feeders over a period of two years. Being the ﬁrst to do it on such a widespread basis, interesting ﬁndings were presented. For example, interviews with line crews indicated that around one-third of downed conductors were still energized when theygottothepointedlocation. Inthecompany’slog,forty- eightoutoftheseventy-oneconﬁrmedfaultshaddataavail- able. Forty-six of them armed the relay (96%) but only twenty-eight were detected as downed conductors (58%). The authors explain such diﬀerence was due to the bias to- wards security purposely programmed in the algorithms to havethesmallestnumberoffalse-positiveaspossible. Over- all, the commercial works from these key industry players asserted, with their individual and competing solutions, the relevancy and importance of HIF detection problem. Lastly, brief comments on novel approaches regarding HIF location are worth making. Its relevancy becomes apparent when considering tripping a long and branched faulted feeder where ﬁnding such a HIF by visual inspec- tion may take a considerable amount of time. This decision will also depend on the importance of the supplied loads andenvironmentalconditions. QuicklylocatingHIFswould thus be always advantageous, possibly increasing service continuity and chances of preventing damaging ﬁres. Such an important idea was discussed in a simple but inﬂuential work[86]. Inafullysimulation-basedapproach,theauthors learned an ANN with sequence currents and their harmon- ics to estimate the fault location. It is not hard to ﬁnd many issues with this methodology, despite its novel idea. It ne- glects the fact that the current amplitude, network topology and harmonic content created by the load can signiﬁcantly vary. Itusedanapparentlysmallamountofdatawhentrain- ing the network and made stretching considerations when validating its results. Overall,mostnoticeabledevelopmentsandcontributing ideas from the 00s can be summarized: •Wavelettransformasasignalrepresentationtechnique surginginpopularity,equatingtoFourier-basedtrans- forms [8, 58, 60, 56, 62, 57, 63]. •TheubiquitoususeofHIFmodels,leadingtoanover- whelmingamountofsimulation-basedworks[50,58,68, 87, 62, 8, 66, 57, 65, 63]. •Consideration of diﬀerent types of neutral grounding as a HIF detection specialization [71, 58, 70, 71, 8, 77]. •Discussion on the use of sensor-based approaches as apossiblenon-invasive,low-cost,samplingtechnique [78, 10, 79, 80, 81]. •Presentation of commercial solutions from other key industry players [84, 52, 85]. 5. Contemporary literature — More specializations, sensors, and fault location The research published after the 10s, considered herein as contemporary literature, represents the largest number of publications when compared with other decades. It is not clear that the same could be said in terms of innovation in theﬁeld. Mostcontributionsprobablycamefrommorespe- cializations in the HIFs surface types, continuing investiga- tions on wireless-based sampling approaches, and more in- depthdiscussionsonHIFlocation. Thelattershowedaslight change in ﬁeld direction, suggesting some transcendence on the problem of detection. It is possible that some re- searchersweresatisﬁedorsaturatedwiththelargenumberof approaches targeting fault detection and wanted to progress theﬁeldtomoresigniﬁcantchallenges. Suchpossibilitybe- comes more evident if one investigates the number of repli- cation works, i.e. works that do not present more contribu- tions but instead apply a slight variation of an already pro- posedtechnique,publishedinthisperiod. Notwithstanding, discussions and ﬁndings presented in specialization works assert the fact that much still needs to be understood about the HIF phenomenon behaviour. Unsatisﬁed with the current state of HIF modelling, re- searcherscontinuedtoproposenewideasforimprovingphe- nomena representation. A model proposed at the beginning of this decade [88] aimed at building on the ﬁrst described model [42] to increase the represented frequency band to componentsupto12kHz. Byusing40testsstagedonmany types of surfaces such as asphalt, cement, soil, and tree, the proposed model consists of six branches of the previous model (see Fig. 1) in parallel. When ﬁtting the model pa- rameters, the authors used FFT for extracting features from thecurrentsignals,PCAfordimensionreduction,andanit- erativeminimizationontheBonferroniintervalascostfunc- tion. TheworktriedtoﬁtdiﬀerenttypesofHIFsinasingle model, which would make it deﬁcient if high-variance be- tween surface types is indeed present. A further work [12] addressedthishypothesisandpresentedsomeevidenceinits modelproposition. Theauthors,decidedtobuildonanother previously discussed work [68], proposed a model with the same characteristics (see Fig. 4) but with parameters indi- vidually ﬁtted for each surface. On their results, one can see a signiﬁcant variance in the impedance parameters and current waveforms for each of the studied surfaces. With DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 12 of 23 High-Impedance Faults in Power Distribution Systems approximatelytentestseach,avarietyofsurfacetypeswere considered: grass, cobblestones, gravel, asphalt, sand, and local soil. A recent modelling approach [11] presents itself as the oneofthemostinnovativemodelspecialization: tree-related HIFs. This type of faults are especially crucial due to their implications in HIF-related ﬁre ignition and that they can havesigniﬁcant,particularcharacteristics. Twodiﬀerentbe- haviours described in the paper, from the initial phases of conduction(thatcanlastforseveralseconds),aresigniﬁcant insights: (1) the fault current is smaller than other surface types, in the range of milliamperes; (2) its impedance be- haves closely to a linear resistor, meaning that there is no arcing and no signiﬁcant levels of harmonic injection. Re- sults from other vegetation-related HIF works [54, 89, 14] corroborate these robust ﬁndings, attesting for the recurrent mA-rangefaultcurrentsandsmootherconductionnearzero- crossings. Researchers will need to take these vegetation- speciﬁccharacteristicsintoaccountwhendevelopingdetec- tion methods if they have the goal of ﬁre mitigation. Ac- cording to recent evidence, the only chance of doing so is to act on the ﬁrst few seconds of the fault [9]. The data usedtoconceptualizethemodel[11],despitebeingcollected fromasmallnumberofreal,stagedtests,wascollectedwith the non-traditional sampling rate of 1 MSa/s. Such sam- pling rate is much higher than the vast majority of works discussedhereinandallowsforabetterrepresentationofthe fault HF components. Its parameters were calculated using the Hammerstein-Wiener model to ﬁt low-frequency com- ponents of the fault impedance, while the high-frequencies were approximated by a sum of sinusoids determined via the least-squares method. Moreover, in the same paper, the authors also proposed an approach for detecting the faults based on the innovative idea of using the Magnetic Field (MF) strength instead of voltage or current signals. Recent tree/vegetation HIF specialization works high- light the relevance of particularly addressing these faults. The authors of the model [11] published two more works on tree-related HIFs features and detection [90, 91]. One used the empirical mode decomposition to extract features andthelinearregressionslopeonresultedcomponentsquan- tiles to classify the faults [90]. The other [91] presented the same idea but discussing the use of the magnetic ﬁeld strength as the domain of the extracted features. The au- thors argued that using MF sensors would be a more acces- sible way of sampling the signals and that the MF strength signal is independent of the sensor location on the feeder. The latter, if true, would mean that one sensor would be enough to monitor the whole feeder. However, the authors didnotpresentcompellingevidenceforthisstrongclaimbe- sides presenting ﬁnite element model simulations from part of the studied system. Further questions can then be raised given that no modelling details on the system stray capaci- tanceweredetailed,whichwillattenuatethesmallfaultcur- rent (magneto-motive force) in considerable distances. The authors of the present paper would like to be transparent to the fact of their bias towards the importance of this subject(vegetation-related HIFs) since it was the focus in their past publications[54,92,93,13]. Theﬁrstpresentsastudyonthe vegetationHIFsmostperceivablecharacteristics[54],while thesecondproposesaHIFdetectionmethodbasedonfault’s high-frequency features [92]. The other two works [93, 13] are evidence gathering studies where the importance of the high-frequency components are discussed and fault signa- tures are extracted and illustrated in the time domain. Magneticﬁeldsensingisoneofthenovelideasdiscussed in contemporary literature. An innovative work [94] dis- cussedsuchanapproachtoreplacethethreecurrentsensors mounted under each phase with one MF strength sensor. In itsfeatureextractionpart,theadditionalnovelideaof math- ematical morphology for signal representation is used. A SVMclassiﬁerperformstheclassiﬁcationwithfeatureselec- tion done by a genetic algorithm. The results proposed, in a partly simulation-based approach, show considerable de- tectionaccuracywithafresh,attractive,solution. Similarly, afollowingrecentwork[95]proposedanothernon-invasive MFstrengthsensorasacontinuationofapreviousdetection method[96]. Withthegoalofpresentingalow-costmethod, a coil-shaped sensor to be mounted under (not around) the primaryfeederconductorswasproposed. Theclassiﬁcation of the faults was based on the inter-harmonic current level, as previous work [96], estimated by an accessible Arduino microprocessor. Despitebeingundoubtedlynovel,itishard toassesstherealeﬀectivenessofthesemethodsintheﬁeld. They are partially or fully simulation-based methods that stillaimedatdetectingallHIFstypeswithasingleapproach. Nevertheless, they are indeed evidence for the direction of preference in using non-invasive, sensor-based, approaches to sample signals able to indicate HIF occurrences. Wavelet-based feature extractors maintained their pop- ularity, but other possible signal representation candidates were also discussed. With the assertion of the ﬁeld rele- vancy,accessibleHIFmodels,andpopularitysurge,theidea ofusingwaveletstoextractfeatureswasquicklyexploredin the past decade. This saturation led to an increasing num- berofpaperspresentingreplicatedmethodologieswithvery few novel aspects. A fraction of the surveyed works herein wasselectedtobediscussedinthissection. Fromthechosen ones, none presented the use of wavelet as its main contri- bution, with a few using it as support for their primary spe- cialization. Mathematical Morphology (MM), used to analyse spa- tialstructuresintheﬁeldofimageprocessing,wasoneofthe novelsignalrepresentationideasintroduced. Itusesastruc- turing element and two important concepts, Dilationand Erosion, to encode information regarding the form, shape, and size of structures. These concepts are respectively de- ﬁnedin(8)and(9)wherethefunction grepresentsthestruc- turingelement,whichneedstobechosenaccordinglytothe sample time to reveal the relevant patterns in the function f.DfandDgaredeﬁnitiondomainsofthefunctions fand g, respectively, and the main feature of MM is given by the Morphological Gradient as in (10). TheapplicationofMMinHIFdetectionismainlymade DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 13 of 23 High-Impedance Faults in Power Distribution Systems byusingittorepresenttheparticularirregularshapesofHIF- generated waveforms [16, 94, 97]. Such application, how- ever, was based on two assumptions with thin evidence: (1) the arbitrarily chosen structuring element will be adequate to represent the transients created by the fault, and (2) the consequent representation will exclusively represent HIFs. In the ﬁrst paper [16], the authors used a variation of MM to propose a feature named multi-resolution morphological gradient. It was used in an ANN-based classiﬁer learned from a data set composed of a mixture of a small number ofreal,stagedtestsandalargedatasetfromsimulations. In theirresults,theauthorsarguedthattheexperimentsshowed MM to be more eﬀective than WT and Fourier-based trans- forms at representing HIFs. The previously discussed MM- based work [94] is a translation of this approach to the do- mainofMFstrengthsignals. Inthefollowingyears,another fully simulation-based work [97] also made a case for us- ing MM to represent HIF signals with just a change in the structuring element and a threshold-based heuristic. g.f/.x/=max^f.x*s/+g.s/ð.x*s/ËDf;sËDg`(8) g.f/.x/=min^f.x+s/*g.s/ð.x+s/ËDf;sËDg`(9) =g.f/*g.f/ (10) Other two relevant works using diﬀerent signal repre- sentation are also worth discussing. The ﬁrst relates a work, quickly recognized in the literature, that used a time- frequency analysis based on the Choi-Williams distribution [98] to represent signals. Intending to propose a simple and eﬀective method, staged tests with tree branches, grass, and concrete were performed in a laboratory as part of the methodology. Its feature extraction, going in a diﬀerent di- rection as most works in the ﬁeld, was performed by time- frequencydecompositionfollowedbyajointtime-frequency moment calculation. After the application of PCA for di- mensionality reduction, the results from learning a SVM classiﬁer showed perfect dependability but deﬁcient secu- rity. Itsrelevantinﬂuenceontheﬁeldwasnotonlyresultant from its consistent methodology but also due to its discus- sion on establishing evaluation criteria for future proposed methods such as cost, objectivity, speed, and completeness. Thesecriteria,despitepreviouslydiscussedinpastmethods, arenotalwayspresentinmethod-proposingworks. Theyare usually discussed individually when the proposed method wants to highlight a particular advantage in related criteria. In this critical discussion, the authors also drew attention to the need for a systematic presentation of future methods. These standards would include reporting concepts inspired by the machine learning literature: confusion matrix, ac- curacy, dependability, security, safety, and sensibility. The authors soon followed this work with an important analy- sis [99] where a similar detection method performance wascompared considering data sets with diﬀerent origins: sim- ulations (using a HIF model) and real data. The expressive resultswereaproxyoftheeﬀectivenessofsimulation-based works at representing real-world scenarios. The method’s security reduced from 100% in the simulations to 38.4% in the real data scenario, while dependability went from 100% to88.2%. Thesecondworkaddressingsignalrepresentation presented an innovative mathematical method for analysing the fault signals [17]. The authors proposed a whole novel orthogonal decomposition where the basis functions were derivedfromtheactualfaultsignalssampledinstagedtests. The main advantage of this approach is the non-reliance on a predeﬁned set of basis functions like the ones present in theFourierandwavelettransforms. Theauthorsarguedthat suchdecompositionwashighlyeﬀectiveduetoitssensitivity to phase unbalances present in a HIF occurrence (phase-to- ground fault). Moreover, they tried to make a case that the resultedcomponentshighlycorrelatewiththefaultdistance and thus could be used to guide fault location. The method was validated with the use of real data, and promising re- sults were presented for relatively moderate current ampli- tudes (<20 A). 5.1. HIF location Altogether, no subject in the HIF literature presented more innovation than fault location. Most fault location methods categorized as exactapproaches can be divided in travellingwave orparameterestimation technologies. Other proposedtechniquescanbecategorizedasfaultlocation es- timators, as they are used as support in search of the fault location, usually reducing the fault search space. From travelling wave-based methods, a work presented in a series of three papers [100, 101, 102] targeting HIF location can be regarded as one of the most inﬂuential. It was conceptualized to detect and locate a HIF using Power LineCommunication(PLC)devices. Thedetectionwasper- formedbyaPLCdevicethatcontinuallymonitorsthefeeder impedance and detects the fault when an abrupt change in theHFimpedanceisasserted. Afterdetection,onePLCde- vice (transmitter) starts to inject impulses into the network, which are to be received by another PLC device (receiver). Based on the travelling wave phenomena, the received im- pulsebythereceiver,andthereﬂectedimpulseonthetrans- mitter, the exact fault location can be theoretically calcu- lated. In this manner, the fault location always occurs be- tweentwosuccessivecommunicationdevices. Themethod- ology, ﬁrst conceptualized for rural single-phase rural net- works with earth return [100, 101], was further generalized to multi-phase systems [102]. The results presented in their simulation analysis for fault location are promising but also raisequestionstosevereconstraints. Forexample,itrequires knowledge of the topology, impedance, and resonant fre- quencies of the system for the best narrow frequency range selection. Since the detection and location system merely indicates changes in the system topology (HIF as a small topology change), it has to consider such a topology to be stationary. Thefaultsweresimulatedasconstantimpedance, DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 14 of 23 High-Impedance Faults in Power Distribution Systems asaretheloads,farfromthecomplexbehaviourcomprehen- sively described by other authors. Moreover, as it considers the end of the line as open-ended, band-stop ﬁlters may be required on the primary side of low-voltage transformers. One of the most relevant parameters estimation-based works[103]alsosuﬀeredfromstrictconstraints. Itproposed the calculation of the fault distance with a time diﬀerential ﬁlter on the feeder current. In the methodology, the time- domainsubtractiononthecurrentsignalsisperformedfrom subsequentcyclesobservedinthefeedersothefaultparam- eters can be estimated. If an abrupt change in the param- eter calculation is asserted, a fault is detected. Then, the faultdistanceisgivenbyapolynomialestimationofthepa- rameters with Newton’s gradient descent method. Another recently published work also uses a similar diﬀerential cur- rent approach but with parameter estimation done via ANN [19]. The authors claimed that such ANN would not need prior training as it was conceptualized to train on-line as it acquiresdata. Theresultswerecomparedtothemethodpre- viously discussed [103], resulting in less estimated distance error. Many issues could be pointed out with these works, butprobablythemostrelevantoneisthefactthatbothbuilt theirmethodsonthepresuppositionthatthefaultparameters and non-linearity are known. The models used by the au- thors may reﬂect the non-linearity of certain HIF types but will, at best, closely represent a single type of fault. These methods, moreover, are conceptualized with currents much higherthanHIFscanassume(fromsingle-digitamperes),in the range of 60-100 A. Otherfaultlocationsearchsupportsarealsorecentlypro- posed. As the ones formerly discussed, they require full knowledge of the system topology, loads, and system accu- rate modelling. A work using wavelets in MRA [104] pro- posed HIF detection and location by comparing the values of signals coeﬃcients with a pre-developed data set. Such data should come from system simulations for many faults in all the branches, so calculated values can be compared and ranked in regards to distance. Another work [105] that proposedHIFdetectionwiththeuseofdistributedmeasure- ments throughout the network described fault location esti- mation by how intensely these were sensitized. Thus, with a reasonable number of allocated monitors, the fault search space could be signiﬁcantly reduced. For the most part, HIF location solutions are still in the earlystagesandhavemanyobstaclestodealwithuntilattest- ing generalization. Some intrinsic characteristics of power distribution systems pose critical constraints to the eﬀec- tiveness of these theoretical solutions. The conductors’ size change between branches, making the impedance calcula- tions non-linear. There is a possible existence of multiple feeder taps and laterals, phase imbalances, and inaccurate load representation/aggregation, which are challenging to model. But most importantly, one still needs to resolve the problemofthenon-linearandnon-eﬀectivelymodelledHIF behaviour when relying only on simulations. In fairness, however, one should not expect that works from an emerg- ing sub-ﬁeld as HIF location to have all obstacles solved.Future development in this ﬁeld is probably going to use diﬀerent strategies to be more generalizable and have con- siderable potential to improve with better HIF models and sensor-based technologies. 5.2. Contemporary commercial solutions Duetotheintensehistoryofcatastrophicwildﬁres,Aus- tralia has been heavily involved in the application and de- velopmentofcontemporarysolutions. Afteraseriesofﬁres that devastated the state of Victoria in 2009, there was an injection of government funding and pressure to mitigate potential powerline-ignited wildﬁres. It led to the funding ininfrastructuralchanges,butalsoinvegetationHIFstaged tests [9] and evaluation of potential solutions [106]. These projects inﬂuenced the further ‘Electricity Safety (Bush- ﬁre Mitigation) Amendment Regulations 2016’ [74], which made provision as requirements for power companies to in- crease safety standards of their operation. Between the re- quirementswastheroll-outof45RapidEarthFaultCurrent Limiters(REFCLs)bythefollowingsevenyears[107]with possible penalties of 2 million AUD per substation that did notaddresstheinstallationmandate[108]. Asmentionedin the last section, REFCLs are not a exactly new technology, but Australia has been installing them in recent years, thus undergoing an interesting experiment. The choice for REF- CLscouldhavebeeninﬂuencedbytheurgencyandpressure from the events. REFCLs are not particularly inexpensive, only work in three-phase feeders, and can’t guarantee pro- tection against HIF between phases. However, they are fast and sensitive enough to be applied was a direct protection system to mitigate potential ﬁres. ThewaveofincentivestoinvestinHIFsolutionsinAus- tralia also resulted in the development of new technology. The solution by IND Technology is not necessarily a HIF detection method but a Early Fault Detection (EFD) device [109]. It applies sensors in an wide-are monitoring sys- tembasedonpartialdischargeconceptstomonitoroverhead power lines and detect incipient faults before the turn to a low-impedance fault. Based on the premise that insulator deteriorationwillreleaseradio-frequencysignalsinthecon- ductor, the device uses frequencies in the range of MHz to detect potential HIFs. According to one of the founders, in highly-branched networks, the device needs to be installed in5-kilometresintervals[110]. Thesensorsarewirelessand installedinundertheprimaryconductors. Thecompanyre- portedthatthedevicehasshownsensitivitytodetectplenty of events: lighting, live-line workers, switching events, as- setswarrantingimmediatereplacement,andvegetationlying acrossconductors. Itisunclearthatthedevicecouldbeused as protection device since the patterns found in the signals are sent to the cloud and further analysed. The equipment has been installed in Australia, USA, China, and is in con- tinuing testing and development. TAMU also betted on the path of a predictive approach, rather than reactive (detection and responding). Their main solution was described in a paper revealing a development workofmorethanadecadewiththeElectricPowerResearch DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 15 of 23 High-Impedance Faults in Power Distribution Systems Institute(EPRI)[111]. Usingatechnologycoinedas Distri- bution FaultAnticipation (DAF), thedevice isallegedly ca- pableofdetectionincipientapparatusandlinefailures,using thewaveformofexistingCTsandPTsatthesubstationbus. The device also has the capability of clustering patterns of disturbances that may be intermittent, appearing in the in- tervals up to several days. The clustering framework is pre- sentedinamorerecentpaperwheretheautomatemethodto mine,cluster,andreportisdescribed[112]. Althoughinitial ﬁeldtestsoftheequipmentwerediscussedinthepresenting paper[111],amorecomprehensiveapplicationwasrecently reported[113]. FundedbytheTexasgovernment,thedevice was tested in 11 distribution feeders of a local power util- ity. If successful, the device can work to monitor events on single-phaselaterals,butprecisevaluesforthesensitivityof the equipment and speed for protection integration appears still to be reported. As one of the most traditional players, Schweitzer En- gineering Laboratories believes the solution for powerline- ignitedﬁreswillcomefromaholisticapproach. Theframe- work includes four strategies: (1) preventive maintenance, involvinginspectionsandproactivevegetationmanagement; (2) enhanced system protection, to produce more visibility and control of the system; (3) strategic operational prac- tices for assessment of risk and forecasting; (4) and sys- tem hardening, which includes assets replacement such as polesandoverheadconductors[114]. Thecompanydoesnot present any innovative technology for HIF signal classiﬁca- tion. It relies on the previous discussed technology, which is based on the inter-harmonic signals in the load current, applied through traditional timer and counter logic. How- ever, the company does present some interesting hardware that could allegedly detect broken conductor faults before the wire touches the ground [115]. Such a system relies on sensors distributed throughout the network called Fault andLoadTransmitterandReceivers(FLTandFLR)thatcan wirelessly communicate SCADA when a loss of current or unbalancing is detected. The advantages of the hardware is that is can be installed up to 10 miles from the receiver point and up to 168 devices can use the same DNP3 map- ping,asopposedtooneforeachdevice. Theprotection-level speed has been reported in a paper [115] where faults were staged in a collaboration with a utility company. Similarly to the TAMU approach, sensitivity is yet another gray con- cept for these devices, specially considering that the com- pany deﬁnes HIF currents having amplitudes below 100 A in grounded systems [114]. A relatively new company from China, SilverFern Power, it is also bringing their sensor-based solution to the market [116]. As well as SEL, this company sensors are also mounted on the conductors, gathering data with sam- pling rates of 256 Sa/cycle. The communication, however, is done through 3G/4G networks. The company does nec- essarily focuses on HIF, but as most systems in China are non-eﬀectively grounded, fault currents are usually much smaller. Inpublicreports,thecompanystatesthatwithsuch a system can detect and locate any single-phase earth faultcurrentmorethan1A[116]. Italsostatesthattensofthou- sands of sensors have already been put in operation in more than 600 substations. With the largest number of works proposed, contempo- raryliteraturewasresponsibleforrelevantcontributionsand many validations studies. The highlights from this research period can be summarized: •Modelling and detection specialization of tree/vegetation HIFs [11, 89, 90, 91]. •Increasingnumberofsensor-basedsolutions,pointing to increasing interest and consensus on their advan- tages [82, 83, 94, 95]. •Magnetic ﬁeld strength sensors as the sampling do- main for HIF detection [94, 95]. •DeeperdiscussionsonHIFlocationassertingitasale- gitimateHIFsub-ﬁeldofresearch[102,103,19,104, 105]. •Contemporary solutions moving to a predictive mon- itoring approaches [110, 111]. For the sake of contextualizing and highlighting impor- tantdevelopmentsandseminalcontributions,Fig. 7issetto illustrate the timeline of relevant events in the HIF research ﬁeld. 6. Discussions To bring such a survey closer to a quantitative analysis, this section illustrates and discusses some statistical ﬁgures calculated from the analysed works. Before beginning such discussions, it is worth to note that there is a diﬀerence be- tween the number of works previously described in detail and the total considered in the following quantitative evalu- ation. The total number of papers and technical documents analysed pertains to many classes: 131 total works, includ- ing 94 HIF detection papers, 9 HIF modelling methodolo- gies, 7 HIF location papers, and 4 literature reviews. The remainingincludemethodvalidationworks,commercialpa- pers, tutorials, related technology, and patents. Although being less than the total amount of papers published in the topic, it is still a representative sample of the direction and distribution of techniques used in the ﬁeld. The ﬁrst quantitative ﬁgure presented is an illustration ofhistoricalgrowthoftheﬁeld. Thenumberofpaperspub- lished by decade and by year in the IEEExplore repository is illustrated in Fig. 8. As seen in Fig. 8a, the number of publications consistently increased throughout the decades. Itmorethandoubledtwice,andmorepaperswerepublished in the 10s than all previous decades added together. In the 2010s, papers were consistently published every year with an overall positive trend from the beginning to the end of the decade, as shown by Fig. 8b. The number of papers published in 2018 was certainly a record and outlier. The DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 16 of 23 High-Impedance Faults in Power Distribution Systems TAMU proposes a digital- framework method to detect HIFs [4] 1970 1980 1982First application of Neural Networks (MLP) for HIF detection [41] Emanuel's et al. HIF Model [42] 1978 1990 TAMU and GE discloses the ﬁrst substation-ready panel cut-off HIF detector based on Expert Sytems, inspiring initial conversations on the dependability vs. security trade-off [36]1994 Singapore enters the ﬁeld, ﬁrst wavelet application for feature extraction [15] Brazil enters the ﬁeld, ﬁrst active travelling-wave and fuzzy system method for HIF detection [34]1998 Beginning of discussions of distributed sensor- based approaches for HIF detection based on PLC [78]2000 ABB presents its commercial HIF detection solution based on wavelets and ANNs [84]2004PP&L publishes the ﬁrst formal electro-mechanical relay for "fallen conductors" [21] TAMU presents the prototype of the digital HIF relay and formalizes many of today's known HIF features [2] Nam et al. [68] model accounting for Build-up and Shoulder features 2001Presentation of a fast ground-fault neutralizer by Swedish Neutral for compensated systems [75] 20052006 Initial discussions on HIF location with ANNs [86]2007SEL presents its commercial HIF detection, based on current time- series analysis and inter- harmonic distortion [52] Use of Rogowski coil as a sensor-based approach, based on Partial Discharge theory [10] Works focusing on tree- related HIFs as specialization [71, 8, 77] 20082010Discussions on PLC technology for HIF location [100] 2012 First application of mathematical morphology with magnetic ﬁeld sensing for sampling [94]2013Model specialization: Tree-related faults [1 1] 20182020 TAMU and EPRI Distribution Fault Anticipation Device [1 11] Figure 7: Timeline of important developments in the HIF research ﬁeld. exactreasonsforthisphenomenonisnotknown,butthehy- pothesis that it may be linked to the recurrency and inten- sityofthewildﬁresignitedbypowerlinesinthecurrentand pastdecademightbeaninterestingsubjectofresearch. The number of works analysed in detail, mentioned in the last paragraph, is a set of the works presented in Fig. 8b as it includes all the papers listed in IEEExplore with the words “high-impedance fault”. Itisalsousefultoillustratehowthetechniquestoextract HIF features from fault signals are distributed in the previ- ously presented methods. As repeatedly discussed in pre- vious sections, signal representation and feature extraction techniques are often the primary contribution to knowledge attempted by HIF detection works. The pie chart shown inFig. 9, produced from the papers evaluated in detail, shows thedistributionoftechniquesusedtoextractthediscrimina- tiveinformationfromfaultsignals. Intheﬁgure,‘MM’rep- resentsMathematicalMorphologyand‘HH/EMD’signiﬁes the Hilbert-Huang transform or Empirical Mode Decom- position. ‘Wavelet’ and ‘Fourier’ represent methods based on their respective transforms while ‘Sequence’ depicts the analysedmethodsbasedonzeroandnegativesequencecur- rents and voltages. The ‘Impedance’ works are a few of the papers found where the detection is based on the ap- parent impedance measured from sampled voltage and cur- rentsignals. The‘Others’categoryincludealternativetime- frequency analysis techniques, impulse response and travel- ling wave-base methods, time series analysis, and mechan- DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 17 of 23 High-Impedance Faults in Power Distribution Systems (a) Papers published in IEEExplore by decade. (b) Papers published in IEEExplore in the 2010s by year. Figure 8: HIF ﬁeld popularity and growth. ical methods. From all the mentioned techniques, it is re- markable that wavelet-based methods clearly dominate the practice considering it was only popularized in the 00s. It is easier to ﬁnd wavelet-based methods than Fourier-based ones,eventhoughthelatterwereintroducedinthebeginning of the ﬁeld. Likewise, it is also remarkable that the ‘Other’ category is well represented, matching the same proportion as Fourier-based methods. One can hypothesise that this classhavesuchasigniﬁcantshareduetothefactthatfeature extractionandsignalrepresentationtechniquesareoftenthe main contribution to knowledge proposed in the papers. As authors need to introduce novelty in their work, many pub- lish on experiments and use of not-previously tested tech- niques so they can have a claim of original work. These works are seldom replicated, ending up in single or double mentions, hence the ‘Other’ classiﬁcation. Moreover, one lastnotablefactattestedbyFig. 9isthatthemajorityofthe works still use hand-engineered features. Hand-engineered features have the advantage of being closer to explaining causality but are also dependent on the human knowledge thatcreatesthem. Onecaninducttworeasonsforthedomi- nance of these symbolic approaches: (1) researches are still notproﬁcientwiththeuseoftechniquessuchasdeeplearn- ing and encoding techniques, or (2) researchers do not be- lieve that exploring such techniques are worth. The latter couldbeduetothelackofcausalityinthemethodsandtheir uncertainty,orbybeliefthatsuchapproacheswillnotbewell received by the community. Demonstrating the distribution of choices in the classi- ﬁcation techniques is as important as illustrating feature ex- tractionapproaches. Theyareresponsibleforthecrucialtask of classifying the signals as originating from a fault or not, which takes place after the discriminative information has Figure 9: Signal representation techniques in HIF detection works. beenextracted. Thepracticemainlyconsistsofestablishing decisionboundarieswhichwillresultintheclassiﬁcationof the observed data or feature. The technique used to clas- sify the signals can take many forms and assume diﬀerent levels of complexity; from a simple threshold value estab- lished on a calculated feature to complex decision bound- aries deﬁned by neural networks trained on labelled data. From the works analysed in detail, Fig. 10 shows the dis- tribution of classiﬁcation techniques labelled as ‘Determin- istic’ and ‘Probabilistic’. The chart illustrates the interest- ing fact that probabilistic decision boundary techniques re- lyingonobservationsarealmostasrepresentedasdetermin- istic ones. The fact probabilistic techniques started to be adopted later than thresholds and arbitrary decision bound- aries ones is the main reason for their representation being remarkable. Thiseﬀectispresentinthedistributionofprob- abilistic techniques as well, also shown in Fig. 10. Arti- ﬁcial Neural Network-based approaches (ANN-based in the chart)surprisinglydominatestheprobabilistictechniquesat- testing for the high interest from the research community. Other machine learning techniques such as support vector machines, random forest, and k-nearest neighbours occupy 39% of probabilistic techniques. Itisinterestingtomakeanoteonthesamplingratesused by the HIF detection works. From the analysed detection papers, only 53 made their data acquisition sampling rate clear. Close to half of them (24) adopted sampling rates lowerthan5kSa/swhile22adoptedvaluesbetween5and50 kSa/s. Only3ﬁttedtheexceptionofsamplingsignalsatrates higherthan50kSa/s. Nevertheless,oneofthemwasapurely simulation-based work while another was as active method based on travelling wave theory where a pulse gets injected into the line and its response is measured. The third was sampling signals at 64 kSa/s. The fact that higher sampling rates are not often adopted is not necessarily detrimental to the ﬁeld. Having accurate detection with smaller sampling rates is desired since it is less demanding and closer to the sampling of existing digitizers allocated on the ﬁeld. How- ever, if one accepts that HIF detection is a lasting problem tobestilldeﬁnitelysolved,investigatingtheeﬀectsoffaults DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 18 of 23 High-Impedance Faults in Power Distribution Systems Figure 10: Techniques used to deﬁne decision boundaries in HIF works. athighersamplingratesbecomesaveryinterestingresearch problem, which may prove to be crucial. The proportion of works that were purely simulation- based or specializing in diﬀerent fault surface type are also two aspects worth commenting. The introduction of HIF modellinginthe90s,asanattempttocircumventtheneedof real data by the use of simulations, was eﬀective at becom- ing a common practice. From the 88 investigated papers, 42 presented pure simulation-based works that made use of previouslyproposedHIFmodelstomakeclaimsaboutaccu- ratefaultdetectionbytheirmethods. Nevertheless,giventhe variance between fault types presented in the literature and here, one could argue that methods based purely on mod- elling are still to prove their capability of generalizing to real faults. There is no consensus, as seen from the present survey, on the best way to model HIFs or whether they can adequately represent all types of fault surfaces. In regards to works that focus on vegetation as the particular fault sur- face,conversely,onecanconﬁdentlystatethattheyarerare. Fromtheanalysedworks,8includesometypeofvegetation on their tests, but only 4 focuses solely on it as fault sur- face. From the research that is continuing, a few group of researchers presented original contribution regarding vege- tation HIFs [90, 117, 11, 91, 7, 14, 54, 92, 93, 13]. Having gone through the description of the ﬁeld, some perceived knowledge gaps can be also discussed. For ex- ample, between all the works discussed in this paper, few try to discriminate between fault conducting surfaces such as grass, tree branches, gravel, asphalt, and sand. Detec- tion methods are often proposed with the alleged ability to detect all HIFs, despite the conducting surface. Neverthe- less, since seminal works in this ﬁeld, authors have already stated that it is unlikely that a single method would be able todetectalltypesonHIFs[118]. Afteranalysingnumerous publications from the ﬁeld of HIF detection, one could ar- gue that it is likely that the scarcity of HIF type speciﬁcity is one of the reasons for the lack of consensus regarding a deﬁnitive fault detection solution. If true, such assumption wouldmeanthattheaforementionedtraditionaldeﬁnition— HIFasfaultswithcurrentbelowprotectivedevicessensitiv-ity — is a condensed deﬁnition for a more intricate prob- lem. Basedontheconsensusoffaultvariability,therefore,it is reasonable to say that HIFs should also be investigated in sub-classesgivenbyparameterssuchasthetypeofthefault, contact surface, and network type. Researches have recently started to publish more on tree/vegetationfaultsasaspeciﬁctypeoffaulttobestudied [119,11,89,91,14]. Theyhavegatheredevidenceofessen- tial and distinct HIFs characteristics that diverge from other investigatedsurfaces. Oneoftheseisthecurrentmagnitude in the ﬁrst moments of the fault occurrence; initial values are often in the range of a few amperes [9, 14, 117]. This characteristic is conﬂictual to a large part of the works in theliteraturesince,asdiscussedinthispaper,mostmethods do not have their current sensitivity deﬁned but are instead presented as a generic solution to the traditional deﬁnition of HIFs. The second interesting characteristic relates to the ﬁrst in that, on those initial seconds of the fault, the current seems tohave analmost linearrelationship withthe voltage [54, 117, 9]. That behaviour also represents a conﬂict with part of the methods in the literature since they heavily rely on the harmonic content of current signals as the predictive information. The relevance of these two particular charac- teristics—lowcurrentamplitudeandlowharmoniccontent — further increases when aspects like detection speed are considered. According to a work testing hundreds of vege- tation species [9], VHIFs have to be detected and addressed in the ﬁrst ﬁve seconds of fault inception if a considerable ﬁre risk reduction is desired. Few works perform experiments that were conceptu- alisedwithparticularlimitationstothefaultcurrents. When proposing detection methods, most papers do not dedicate eﬀorttostablishthresholdsorstandardsforthefaultcurrent. This fact is consequential because it is not possible to know how sensitive are the results if the current is not carefully limited. Limiting the fault current to relatively small values (from0toafewamps)canbefurtherexploredsincetheystill canigniteﬁresinoverheadsystems. Havingpositiveresults inthisnichecurrentlevelalsorepresentsanunaddressedgap in the literature. DSP Gomes and C Ozansoy: Preprint submitted to Elsevier Page 19 of 23 High-Impedance Faults in Power Distribution Systems As mentioned in previous paragraphs, the vast majority of works do not cross the rates of 50 kSa/s when acquiring datafromtheirexperiments. Therefore,havingsignalssam- pled in such a large bandwidth represents a signiﬁcant gap. The large bandwidth can also allow distinct experiments. Forexample,inwhichthebandsareconcentratedimportant predicting information content for fault detection. Having accurate representations of the HIF behaviour can add evi- dence and ﬁll the gap of the phenomena understanding. Part of reason for a deﬁnite solution is clearly the prob- lem complexity, which is arguably higher than researchers initially thought. However, one can also argue that because it is not an immediate and asset-damaging problem, there are also not enough incentives to animate more elaborate solutions. There is a challenging aspect in creating such in- centives since producing and staging the necessary experi- ments is an onerous and expensive activity. When other or- ganizationsendupdoingrealexperiments,thefactthatthey are so burdensome results in negative incentives to sharing the experimental data. If the HIF phenomenon is indeed as high variant as seen here, one should expect that conclu- sive solutions for all types of conduction surfaces to only come from large data sets with a massive number of exper- iments. The lack of standard data sets results in convoluted literature where many solutions are presented for diﬀerent sub-problemsinsidetheHIFdetectionﬁeld. Thisconfusion leadstotheincapabilityofcomparingdiﬀerentmethodsper- formancesandleavemuchoftheproposedknowledgewith- out any speciﬁc use or application. Therefore, the author would like to propose a call to action for future researchers to include the vegetation ignition data set in their method validation. Another goes to the companies to make their data publicly available so researchers can have proper as- sessmentsoftheirmethodsandsootherscanbuildanopen- sourcedatasetsofHIFs. Theauthorsbelievethatthiswillbe thefastestwaytosolvetheHIFdetectionproblemandprob- ably save the overall community from the massive amount of damages resulting from powerline-ignited ﬁres. 7. Conclusions Thispaperpresentedahistoricalnarrativeandcommen- tary of the HIF ﬁeld in power distribution systems. De- scriptionswereorganizedindecades,fromtheﬁeldseminal worksandpioneeringresearcherstothecontemporarymeth- ods and technologies. Key players and how the advance- mentsunfoldedwerecontextualizedinthepoolofmostcited papers and technical documents. After analyzing the sur- veyed works, one can see that the HIF is a highly complex problemthatresultedinafruitfulbutconvolutedﬁeldofdis- cussions. Itisessentialtounderstandthehistoricalarcwhere thedevelopmentstookplacetobeabletoanalyzenovelwork critically. Theauthorshopethatsuchdescriptioncanbeused by readers in many ﬁelds, making them more familiar with theeﬀorts,struggles,andcoreideasintheﬁeld. Itisproba- blethatthebestscenarioforconvergenceofknowledgenow istohaveopen-sourcedatasetswithdiverseconductingsur-faces so methods can be properly compared and discussed. Thataremanylastingknowledgegaps,andfurtheradvance- ments can result in saving lives and mitigation of environ- mental damages.