{"id":"https://openalex.org/W4415968713","doi":"https://doi.org/10.1109/iecon58223.2025.11221903","title":"Data-Driven Unsupervised Current Anomaly Excavation for Emerging Grid Scenarios","display_name":"Data-Driven Unsupervised Current Anomaly Excavation for Emerging Grid Scenarios","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W4415968713","doi":"https://doi.org/10.1109/iecon58223.2025.11221903"},"language":null,"primary_location":{"id":"doi:10.1109/iecon58223.2025.11221903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon58223.2025.11221903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2025 \u2013 51st Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101518135","display_name":"Wen\u2010Qiang Lu","orcid":"https://orcid.org/0000-0003-2755-6343"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqiang Lu","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,Jinan,China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101580018","display_name":"Feng Gao","orcid":"https://orcid.org/0000-0001-9551-903X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Gao","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,Jinan,China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101763060","display_name":"Tao Xu","orcid":"https://orcid.org/0000-0002-0501-6445"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Xu","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,Jinan,China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10573","display_name":"Power Quality and Harmonics","score":0.42829999327659607,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10573","display_name":"Power Quality and Harmonics","score":0.42829999327659607,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10305","display_name":"Power System Optimization and Stability","score":0.17679999768733978,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10454","display_name":"Optimal Power Flow Distribution","score":0.0794999971985817,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.652999997138977},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5633000135421753},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5095000267028809},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.45969998836517334},{"id":"https://openalex.org/keywords/current","display_name":"Current (fluid)","score":0.43050000071525574},{"id":"https://openalex.org/keywords/harmonics","display_name":"Harmonics","score":0.4251999855041504},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.40220001339912415},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.3391000032424927}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.652999997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208000183105469},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5633000135421753},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5095000267028809},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4853000044822693},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.45969998836517334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4309999942779541},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C188414643","wikidata":"https://www.wikidata.org/wiki/Q3001183","display_name":"Harmonics","level":3,"score":0.4251999855041504},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.40220001339912415},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.3391000032424927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.328900009393692},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.32850000262260437},{"id":"https://openalex.org/C2983254600","wikidata":"https://www.wikidata.org/wiki/Q1096907","display_name":"Power grid","level":3,"score":0.32710000872612},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.30660000443458557},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C2779665505","wikidata":"https://www.wikidata.org/wiki/Q1780079","display_name":"Power quality","level":3,"score":0.2992999851703644},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27239999175071716}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon58223.2025.11221903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon58223.2025.11221903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2025 \u2013 51st Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2107912313","https://openalex.org/W2111104557","https://openalex.org/W2492181757","https://openalex.org/W2553261477","https://openalex.org/W2599354622","https://openalex.org/W2914570111","https://openalex.org/W3114740739","https://openalex.org/W3138516171","https://openalex.org/W4312349930","https://openalex.org/W4398786112"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,9,88,104,111,115],"rapid":[2],"integration":[3],"of":[4,12,92,106,118],"distributed":[5],"renewable":[6],"generations":[7],"and":[8,37,43,48],"evolving":[10],"complexity":[11],"load":[13],"operation":[14],"patterns,":[15],"anomalies":[16],"in":[17,121,144],"grid":[18],"currents":[19],"are":[20],"increasingly":[21],"manifesting":[22],"as":[23,35,65],"steady-state":[24],"harmonics":[25],"or":[26,99],"transient":[27],"fluctuations.":[28],"Traditional":[29],"power":[30,62,105,146],"quality":[31,63],"analysis":[32],"techniques,":[33],"such":[34],"FFT":[36],"wavelet":[38],"transform,":[39],"identify":[40],"anomalous":[41,82,90],"voltage":[42],"current":[44,83,119,131],"by":[45],"decomposing":[46],"signals":[47],"comparing":[49],"them":[50],"to":[51],"predefined":[52],"standards.":[53],"Some":[54],"recent":[55],"approaches":[56],"also":[57,86],"apply":[58],"deep":[59],"learning,":[60],"framing":[61],"issues":[64],"supervised":[66],"classification":[67,100],"tasks.":[68],"Being":[69],"different,":[70],"this":[71],"paper":[72],"proposes":[73],"a":[74,134],"novel":[75],"data-driven":[76],"method":[77,113],"that":[78],"not":[79],"only":[80],"detects":[81],"behavior":[84],"but":[85],"uncovers":[87],"underlying":[89],"components":[91],"current,":[93],"without":[94],"relying":[95],"on":[96,129],"fixed":[97],"standards":[98],"labels.":[101],"By":[102],"leveraging":[103],"Generative":[107],"Adversarial":[108],"Networks":[109],"(GANs),":[110],"proposed":[112],"learns":[114],"distribution":[116],"patterns":[117],"data":[120,132],"an":[122],"unsupervised":[123],"manner.":[124],"The":[125],"approach":[126],"is":[127],"demonstrated":[128],"real-world":[130],"from":[133],"transformer,":[135],"showcasing":[136],"its":[137],"practical":[138],"potential":[139],"for":[140],"addressing":[141],"emerging":[142],"challenges":[143],"modern":[145],"grid.":[147]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-06T00:00:00"}
