{"id":"https://openalex.org/W2907179976","doi":"https://doi.org/10.1109/smartgridcomm.2018.8587454","title":"Residential Load Profile Clustering via Deep Convolutional Autoencoder","display_name":"Residential Load Profile Clustering via Deep Convolutional Autoencoder","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2907179976","doi":"https://doi.org/10.1109/smartgridcomm.2018.8587454","mag":"2907179976"},"language":"en","primary_location":{"id":"doi:10.1109/smartgridcomm.2018.8587454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2018.8587454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","raw_type":"proceedings-article"},"type":"article","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/A5005676924","display_name":"Seunghyoung Ryu","orcid":"https://orcid.org/0000-0001-7969-2924"},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seunghyoung Ryu","raw_affiliation_strings":["Department of Electronic Engineering, Sogang University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Sogang University, Seoul, Korea","institution_ids":["https://openalex.org/I148751991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056354340","display_name":"Hyungeun Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyungeun Choi","raw_affiliation_strings":["Department of Electronic Engineering, Sogang University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Sogang University, Seoul, Korea","institution_ids":["https://openalex.org/I148751991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048224768","display_name":"Hyoseop Lee","orcid":"https://orcid.org/0000-0002-8596-2369"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hyoseop Lee","raw_affiliation_strings":["Encored Technologies, Inc., Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Encored Technologies, Inc., Seoul, Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049420521","display_name":"Hongseok Kim","orcid":"https://orcid.org/0000-0002-5744-2358"},"institutions":[{"id":"https://openalex.org/I148751991","display_name":"Sogang University","ror":"https://ror.org/056tn4839","country_code":"KR","type":"education","lineage":["https://openalex.org/I148751991"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hongseok Kim","raw_affiliation_strings":["Department of Electronic Engineering, Sogang University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Sogang University, Seoul, Korea","institution_ids":["https://openalex.org/I148751991"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003037377","display_name":"Vincent W. S. Wong","orcid":"https://orcid.org/0000-0003-3821-4365"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Vincent W. S. Wong","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5005676924"],"corresponding_institution_ids":["https://openalex.org/I148751991"],"apc_list":null,"apc_paid":null,"fwci":1.8025,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.86354785,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"28","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9994000196456909,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9994000196456909,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9993000030517578,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9785000085830688,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8406888842582703},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8338313102722168},{"id":"https://openalex.org/keywords/load-profile","display_name":"Load profile","score":0.700681209564209},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6732944250106812},{"id":"https://openalex.org/keywords/load-management","display_name":"Load management","score":0.48814138770103455},{"id":"https://openalex.org/keywords/load-balancing","display_name":"Load balancing (electrical power)","score":0.44443973898887634},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4435872435569763},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4008522033691406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.365029513835907},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3471663296222687},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.23741397261619568},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16118144989013672},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14258059859275818},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.07921692728996277}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8406888842582703},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8338313102722168},{"id":"https://openalex.org/C2777908891","wikidata":"https://www.wikidata.org/wiki/Q1806775","display_name":"Load profile","level":3,"score":0.700681209564209},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6732944250106812},{"id":"https://openalex.org/C2779370713","wikidata":"https://www.wikidata.org/wiki/Q357554","display_name":"Load management","level":2,"score":0.48814138770103455},{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.44443973898887634},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4435872435569763},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4008522033691406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.365029513835907},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3471663296222687},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.23741397261619568},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16118144989013672},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14258059859275818},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.07921692728996277},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smartgridcomm.2018.8587454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2018.8587454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","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":25,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1531910981","https://openalex.org/W1532325895","https://openalex.org/W1578468649","https://openalex.org/W1977556410","https://openalex.org/W1977632775","https://openalex.org/W1989866797","https://openalex.org/W2043568875","https://openalex.org/W2066384055","https://openalex.org/W2091283109","https://openalex.org/W2116721403","https://openalex.org/W2150593711","https://openalex.org/W2321807518","https://openalex.org/W2513590440","https://openalex.org/W2535095268","https://openalex.org/W2560168210","https://openalex.org/W2562403923","https://openalex.org/W2953384591","https://openalex.org/W2964121744","https://openalex.org/W4213009331","https://openalex.org/W4235539094","https://openalex.org/W6631190155","https://openalex.org/W6644682428","https://openalex.org/W6713134421","https://openalex.org/W6730667015"],"related_works":["https://openalex.org/W1583194654","https://openalex.org/W1964245459","https://openalex.org/W2185389245","https://openalex.org/W2147320702","https://openalex.org/W2248871425","https://openalex.org/W4377970692","https://openalex.org/W2162063029","https://openalex.org/W2944222538","https://openalex.org/W2022863591","https://openalex.org/W2563943286"],"abstract_inverted_index":{"In":[0,52],"energy":[1],"data":[2],"analytics,":[3],"load":[4,18,36,62,80,120,131,142,158],"profile":[5,37,63,81],"clustering":[6,27,64,168,176],"is":[7,86],"essential":[8],"for":[9],"various":[10],"smart":[11],"grid":[12],"applications":[13],"such":[14],"as":[15],"demand":[16],"response,":[17],"forecasting,":[19],"and":[20,42,45,70,122,164,167],"tariff":[21],"design.":[22],"Most":[23],"of":[24,182],"the":[25,43,78,83,93,105,109,113,125,148,170,175],"conventional":[26],"techniques":[28],"are":[29,48,100],"based":[30,60,103],"on":[31,104],"a":[32,39,57,89,151],"representative":[33,90],"time":[34,84],"domain":[35,85],"within":[38],"certain":[40],"period,":[41],"daily":[44,69,163],"seasonal":[46,71,165],"variations":[47],"not":[49],"well":[50],"captured.":[51],"this":[53],"paper,":[54],"we":[55],"propose":[56],"deep":[58],"learning":[59],"customer":[61],"framework":[65,115],"that":[66,124],"jointly":[67],"captures":[68],"variations.":[72],"By":[73],"leveraging":[74],"convolutional":[75],"autoencoder":[76],"(CAE),":[77],"yearly":[79,119],"in":[82,92,169],"converted":[87],"into":[88,133],"vector":[91],"smaller":[94,137],"dimensional":[95,138],"encoded":[96,107,141,171],"space.":[97,139],"The":[98,140,156],"clusters":[99],"then":[101],"determined":[102],"vectors":[106],"by":[108,147,178],"CAE.":[110],"We":[111],"apply":[112],"proposed":[114],"to":[116],"1,405":[117],"households'":[118],"profiles":[121,132,143],"verify":[123],"trained":[126],"CAE":[127,149],"can":[128,144,160],"encode":[129],"those":[130],"approximately":[134],"100":[135],"times":[136],"be":[145],"decoded":[146],"with":[150],"negligible":[152],"loss":[153],"between":[154],"1-3%.":[155],"clustered":[157],"images":[159],"visualize":[161],"both":[162],"variations,":[166],"space":[172],"speeds":[173],"up":[174],"process":[177],"almost":[179],"three":[180],"orders":[181],"magnitude.":[183]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}