{"id":"https://openalex.org/W3032524856","doi":"https://doi.org/10.1109/tsg.2020.2998080","title":"A Deep Generative Model for Non-Intrusive Identification of EV Charging Profiles","display_name":"A Deep Generative Model for Non-Intrusive Identification of EV Charging Profiles","publication_year":2020,"publication_date":"2020-05-27","ids":{"openalex":"https://openalex.org/W3032524856","doi":"https://doi.org/10.1109/tsg.2020.2998080","mag":"3032524856"},"language":"en","primary_location":{"id":"doi:10.1109/tsg.2020.2998080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2020.2998080","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Smart Grid","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.osti.gov/biblio/1811306","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101944241","display_name":"Shengyi Wang","orcid":"https://orcid.org/0000-0003-0117-040X"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shengyi Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Temple University, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0117-040X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052534353","display_name":"Liang Du","orcid":"https://orcid.org/0000-0002-2663-0751"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Du","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Temple University, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2663-0751","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447775","display_name":"Jin Ye","orcid":"https://orcid.org/0000-0001-7756-5104"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin Ye","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-7756-5104","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057667244","display_name":"Dongbo Zhao","orcid":"https://orcid.org/0000-0003-4401-5792"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongbo Zhao","raw_affiliation_strings":["Energy Systems Division, Argonne National Laboratory, Lemont, IL, USA"],"raw_orcid":"https://orcid.org/0000-0003-4401-5792","affiliations":[{"raw_affiliation_string":"Energy Systems Division, Argonne National Laboratory, Lemont, IL, USA","institution_ids":["https://openalex.org/I1282105669"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6956,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.90816584,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"11","issue":"6","first_page":"4916","last_page":"4927"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9998999834060669,"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/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9998999834060669,"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/T10663","display_name":"Advanced Battery Technologies Research","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10603","display_name":"Smart Grid Energy Management","score":0.9970999956130981,"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/computer-science","display_name":"Computer science","score":0.6089670062065125},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5933867692947388},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5747027397155762},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5562665462493896},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4893040359020233},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47406190633773804},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4626726806163788},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4420415759086609},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4371457099914551},{"id":"https://openalex.org/keywords/electric-vehicle","display_name":"Electric vehicle","score":0.42990052700042725},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42470043897628784},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37987005710601807},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.31490376591682434},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.1779252290725708},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15397751331329346}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6089670062065125},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5933867692947388},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5747027397155762},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5562665462493896},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4893040359020233},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47406190633773804},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4626726806163788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4420415759086609},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4371457099914551},{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.42990052700042725},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42470043897628784},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37987005710601807},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.31490376591682434},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.1779252290725708},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15397751331329346},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsg.2020.2998080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2020.2998080","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Smart Grid","raw_type":"journal-article"},{"id":"pmh:oai:osti.gov:1811306","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/1811306","pdf_url":null,"source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:osti.gov:1811306","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/1811306","pdf_url":null,"source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.5400000214576721}],"awards":[{"id":"https://openalex.org/G5546901699","display_name":"MRI: Acquisition of a Power-Hardware-in-the-Loop (PHIL) System to Enhance Research and Student Research Training in Engineering and Computer Science","funder_award_id":"1946057","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308963","display_name":"Oak Ridge Associated Universities","ror":"https://ror.org/0526p1y61"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W168840469","https://openalex.org/W1479651931","https://openalex.org/W1499798934","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1554113330","https://openalex.org/W1663973292","https://openalex.org/W1860790817","https://openalex.org/W1943316307","https://openalex.org/W1949468118","https://openalex.org/W2043381281","https://openalex.org/W2050304929","https://openalex.org/W2078834385","https://openalex.org/W2083928083","https://openalex.org/W2093135704","https://openalex.org/W2114461427","https://openalex.org/W2152012918","https://openalex.org/W2177899970","https://openalex.org/W2338862287","https://openalex.org/W2344833099","https://openalex.org/W2791314885","https://openalex.org/W2791402521","https://openalex.org/W2794156279","https://openalex.org/W2889282255","https://openalex.org/W2892035503","https://openalex.org/W2893320833","https://openalex.org/W2897967520","https://openalex.org/W2899095930","https://openalex.org/W2910137584","https://openalex.org/W2962851448","https://openalex.org/W2963501406","https://openalex.org/W2964121744","https://openalex.org/W2969353469","https://openalex.org/W3043744295","https://openalex.org/W3099873379","https://openalex.org/W3100352530","https://openalex.org/W4212863985","https://openalex.org/W4255101542","https://openalex.org/W6606938059","https://openalex.org/W6629687487","https://openalex.org/W6631943919","https://openalex.org/W6685674053","https://openalex.org/W6781153356"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W2097963413","https://openalex.org/W2294335174","https://openalex.org/W2025614924","https://openalex.org/W3145575561","https://openalex.org/W2001275470","https://openalex.org/W2073996508","https://openalex.org/W1591475660","https://openalex.org/W2559776840"],"abstract_inverted_index":{"The":[0,165],"proliferation":[1],"of":[2,27,80,131],"electric":[3],"vehicles":[4],"(EVs)":[5],"brings":[6],"environmental":[7],"benefits":[8],"and":[9,72,102,134,157],"technical":[10],"challenges":[11],"to":[12,74,88],"power":[13,130],"grids.":[14],"An":[15],"identification":[16,42],"algorithm":[17],"which":[18,49],"can":[19,124,147],"accurately":[20],"extract":[21],"individual":[22],"EV":[23,45,107,121,132],"charging":[24,46,108,122],"profiles":[25],"out":[26],"widely":[28],"available":[29,81],"smart":[30],"meter":[31],"measurements":[32],"has":[33],"attracted":[34],"great":[35],"interests.":[36],"This":[37],"paper":[38],"proposes":[39],"a":[40,64],"non-intrusive":[41],"framework":[43,146,167],"for":[44],"profile":[47,123],"extraction,":[48],"is":[50,61,87,110,168],"driven":[51],"by":[52,92,99,127,170],"deep":[53],"generative":[54],"models":[55,133],"(DGM).":[56],"First,":[57],"the":[58,69,76,106,113,119,128,139,144,174],"proposed":[59,145,166],"DGM":[60,114],"designed":[62],"as":[63],"representation":[65],"layer":[66],"embedded":[67],"into":[68],"Markov":[70,142],"process":[71],"used":[73],"model":[75],"joint":[77],"probability":[78],"distribution":[79],"time-series":[82],"data.":[83],"A":[84],"novel":[85],"contribution":[86],"approximate":[89],"posterior":[90],"distributions":[91],"neural":[93],"networks":[94],"whose":[95],"parameters":[96],"are":[97],"obtained":[98],"variational":[100],"inference":[101],"supervised":[103],"learning.":[104],"Second,":[105],"status":[109],"inferred":[111,135],"from":[112],"via":[115],"dynamic":[116],"programming.":[117],"Lastly,":[118],"desired":[120],"be":[125],"reconstructed":[126],"rated":[129],"status.":[136],"Compared":[137],"with":[138,153,162],"benchmark":[140],"Hidden":[141],"Models,":[143],"better":[148,158],"handle":[149],"noise":[150],"in":[151],"data":[152],"less":[154],"computational":[155],"complexity":[156],"overall":[159],"accuracy":[160],"performances":[161],"smaller":[163],"recall.":[164],"validated":[169],"numerical":[171],"experiments":[172],"on":[173],"Pecan":[175],"Street":[176],"dataset.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":4}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}
