001031813 001__ 1031813
001031813 005__ 20250203124516.0
001031813 0247_ $$2doi$$a10.1109/AMPS62611.2024.10706699
001031813 0247_ $$2WOS$$aWOS:001344552300035
001031813 037__ $$aFZJ-2024-05832
001031813 1001_ $$0P:(DE-HGF)0$$aPegoraro, Paolo Attilio$$b0$$eCorresponding author
001031813 1112_ $$a2024 IEEE 14th International Workshop on Applied Measurements for Power Systems (AMPS)$$cCaserta$$d2024-09-18 - 2024-09-20$$wItaly
001031813 245__ $$aFault Identification Method in Three-Phase Distribution Networks Leveraging Traceable PMU Measurements
001031813 260__ $$bIEEE$$c2024
001031813 300__ $$a1-6
001031813 3367_ $$2ORCID$$aCONFERENCE_PAPER
001031813 3367_ $$033$$2EndNote$$aConference Paper
001031813 3367_ $$2BibTeX$$aINPROCEEDINGS
001031813 3367_ $$2DRIVER$$aconferenceObject
001031813 3367_ $$2DataCite$$aOutput Types/Conference Paper
001031813 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1728895294_31825
001031813 520__ $$aSeveral fault detection methods and location algorithms in the literature are founded on state estimation. In recent approaches, in most cases, the state estimation process is performed based on synchronized measurements provided by phasor measurement units (PMUs). However, coupling fault identification with phasor measurements is a challenging task, which can present several risks. Particularly, in dynamic scenarios related to faults, the traceability of the measurements could be compromised. To reduce decision-making risks, this paper proposes the application of a dynamics detection policy in a fault detection and location method based on PMU measurements. Such policy permits selecting only traceable measurements. Consequently, decision risks can be reduced. The validity of the proposed approach is confirmed by the simulations carried out by means of a Real-Time Digital Simulator (RTDS) on a three-phase CIGRE European Medium Voltage distribution network.
001031813 536__ $$0G:(DE-HGF)POF4-1122$$a1122 - Design, Operation and Digitalization of the Future Energy Grids (POF4-112)$$cPOF4-112$$fPOF IV$$x0
001031813 536__ $$0G:(DE-HGF)POF4-1123$$a1123 - Smart Areas and Research Platforms (POF4-112)$$cPOF4-112$$fPOF IV$$x1
001031813 588__ $$aDataset connected to CrossRef Conference
001031813 7001_ $$0P:(DE-Juel1)184450$$aSitzia, Carlo$$b1
001031813 7001_ $$0P:(DE-HGF)0$$aSolinas, Antonio Vincenzo$$b2
001031813 7001_ $$0P:(DE-HGF)0$$aSulis, Sara$$b3
001031813 7001_ $$0P:(DE-Juel1)186779$$aCarta, Daniele$$b4$$ufzj
001031813 7001_ $$0P:(DE-Juel1)179029$$aBenigni, Andrea$$b5$$ufzj
001031813 773__ $$a10.1109/AMPS62611.2024.10706699
001031813 8564_ $$uhttps://ieeexplore.ieee.org/abstract/document/10706699
001031813 909CO $$ooai:juser.fz-juelich.de:1031813$$pVDB
001031813 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a University of Cagliari$$b0
001031813 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)184450$$a University of Cagliari$$b1
001031813 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a University of Cagliari$$b2
001031813 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a University of Cagliari$$b3
001031813 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)186779$$aForschungszentrum Jülich$$b4$$kFZJ
001031813 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)179029$$aForschungszentrum Jülich$$b5$$kFZJ
001031813 9131_ $$0G:(DE-HGF)POF4-112$$1G:(DE-HGF)POF4-110$$2G:(DE-HGF)POF4-100$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-1122$$aDE-HGF$$bForschungsbereich Energie$$lEnergiesystemdesign (ESD)$$vDigitalisierung und Systemtechnik$$x0
001031813 9131_ $$0G:(DE-HGF)POF4-112$$1G:(DE-HGF)POF4-110$$2G:(DE-HGF)POF4-100$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-1123$$aDE-HGF$$bForschungsbereich Energie$$lEnergiesystemdesign (ESD)$$vDigitalisierung und Systemtechnik$$x1
001031813 9141_ $$y2024
001031813 920__ $$lno
001031813 9201_ $$0I:(DE-Juel1)ICE-1-20170217$$kICE-1$$lModellierung von Energiesystemen$$x0
001031813 980__ $$acontrib
001031813 980__ $$aVDB
001031813 980__ $$aI:(DE-Juel1)ICE-1-20170217
001031813 980__ $$aUNRESTRICTED