{"id":"https://openalex.org/W4310174140","doi":"https://doi.org/10.1109/isgt-europe54678.2022.9960569","title":"Effect of Clustering in Federated Learning on Non-IID Electricity Consumption Prediction","display_name":"Effect of Clustering in Federated Learning on Non-IID Electricity Consumption Prediction","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4310174140","doi":"https://doi.org/10.1109/isgt-europe54678.2022.9960569"},"language":"en","primary_location":{"id":"doi:10.1109/isgt-europe54678.2022.9960569","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt-europe54678.2022.9960569","pdf_url":null,"source":{"id":"https://openalex.org/S4363608096","display_name":"2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","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/A5045973067","display_name":"James S. Nightingale","orcid":null},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"James S. Nightingale","raw_affiliation_strings":["The University of Manchester,Department of Computer Science,UK","Department of Computer Science, The University of Manchester, UK"],"affiliations":[{"raw_affiliation_string":"The University of Manchester,Department of Computer Science,UK","institution_ids":["https://openalex.org/I28407311"]},{"raw_affiliation_string":"Department of Computer Science, The University of Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350015","display_name":"Yingjie Wang","orcid":"https://orcid.org/0000-0003-0920-9305"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yingjie Wang","raw_affiliation_strings":["(ESAT-ELECTA) &amp; EnergyVille,Dept. of Electrical Engineering,Leuven,KU,Belgium","Dept. of Electrical Engineering, (ESAT-ELECTA) & EnergyVille, Leuven, KU, Belgium"],"affiliations":[{"raw_affiliation_string":"(ESAT-ELECTA) &amp; EnergyVille,Dept. of Electrical Engineering,Leuven,KU,Belgium","institution_ids":[]},{"raw_affiliation_string":"Dept. of Electrical Engineering, (ESAT-ELECTA) & EnergyVille, Leuven, KU, Belgium","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017565535","display_name":"Fairouz Zobiri","orcid":"https://orcid.org/0000-0002-1898-1308"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fairouz Zobiri","raw_affiliation_strings":["(ESAT-ELECTA) &amp; EnergyVille,Dept. of Electrical Engineering,Leuven,KU,Belgium","Dept. of Electrical Engineering, (ESAT-ELECTA) & EnergyVille, Leuven, KU, Belgium"],"affiliations":[{"raw_affiliation_string":"(ESAT-ELECTA) &amp; EnergyVille,Dept. of Electrical Engineering,Leuven,KU,Belgium","institution_ids":[]},{"raw_affiliation_string":"Dept. of Electrical Engineering, (ESAT-ELECTA) & EnergyVille, Leuven, KU, Belgium","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074423181","display_name":"Mustafa Mustafa","orcid":"https://orcid.org/0000-0002-8772-8023"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]},{"id":"https://openalex.org/I4210114974","display_name":"IMEC","ror":"https://ror.org/02kcbn207","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I4210114974"]}],"countries":["BE","GB"],"is_corresponding":false,"raw_author_name":"Mustafa A. Mustafa","raw_affiliation_strings":["The University of Manchester,Department of Computer Science,UK","Department of Computer Science, The University of Manchester, UK","Imec-COSIC, Leuven, KU, Belgium"],"affiliations":[{"raw_affiliation_string":"The University of Manchester,Department of Computer Science,UK","institution_ids":["https://openalex.org/I28407311"]},{"raw_affiliation_string":"Department of Computer Science, The University of Manchester, UK","institution_ids":["https://openalex.org/I28407311"]},{"raw_affiliation_string":"Imec-COSIC, Leuven, KU, Belgium","institution_ids":["https://openalex.org/I4210114974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5045973067"],"corresponding_institution_ids":["https://openalex.org/I28407311"],"apc_list":null,"apc_paid":null,"fwci":3.6932,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.95081301,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9902999997138977,"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":0.9830999970436096,"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":0.8180317878723145},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7435413002967834},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.6996196508407593},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.6273398399353027},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.6200176477432251},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5265063643455505},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5260205864906311},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.518325686454773},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4834059774875641},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45583510398864746},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.45578259229660034},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.44456878304481506},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4198296070098877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3664267659187317},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1102840006351471}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8180317878723145},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7435413002967834},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.6996196508407593},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.6273398399353027},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.6200176477432251},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5265063643455505},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5260205864906311},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.518325686454773},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4834059774875641},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45583510398864746},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.45578259229660034},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.44456878304481506},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4198296070098877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3664267659187317},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1102840006351471},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/isgt-europe54678.2022.9960569","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt-europe54678.2022.9960569","pdf_url":null,"source":{"id":"https://openalex.org/S4363608096","display_name":"2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","raw_type":"proceedings-article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:20.500.12942/720977","is_oa":false,"landing_page_url":"https://lirias.kuleuven.be/handle/20.500.12942/720977","pdf_url":null,"source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Novi Sad, Serbia, 10-12 October 2022","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/3b8ea7ec-3a12-44a5-8371-e6ed9e5aaf65","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/3b8ea7ec-3a12-44a5-8371-e6ed9e5aaf65","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Nightingale, J S, Wang, Y, Zobiri, F & Mustafa, M A 2022, Effect of Clustering in Federated Learning on Non-IID Electricity Consumption Prediction. in IEEE PES ISGT EUROPE 2022.","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9200000166893005,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G849311619","display_name":null,"funder_award_id":"EP/T026995/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2060530165","https://openalex.org/W2064675550","https://openalex.org/W2140405352","https://openalex.org/W2275543810","https://openalex.org/W2754252319","https://openalex.org/W2900120080","https://openalex.org/W2970658101","https://openalex.org/W2989289980","https://openalex.org/W2999869395","https://openalex.org/W3007607795","https://openalex.org/W3016632787","https://openalex.org/W3043303805","https://openalex.org/W3091635927","https://openalex.org/W3135032840","https://openalex.org/W3156841666","https://openalex.org/W3164333910","https://openalex.org/W3214919557","https://openalex.org/W4200227341","https://openalex.org/W6755988804","https://openalex.org/W6760157594","https://openalex.org/W6780438843","https://openalex.org/W6795265983"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W4394895745","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4394231753","https://openalex.org/W4393848201"],"abstract_inverted_index":{"When":[0],"applied":[1],"to":[2,27,36,70],"short-term":[3],"energy":[4],"consumption":[5,115,125],"forecasting,":[6],"the":[7,13,28,37,40,46,68,121],"federated":[8,33,128],"learning":[9,34],"framework":[10],"allows":[11],"for":[12,107],"creation":[14],"of":[15,39,48,53,61,86,123],"a":[16,25,57,112,131],"predictive":[17],"model":[18],"without":[19],"sharing":[20],"raw":[21],"data.":[22],"There":[23],"is":[24,56],"limit":[26],"accuracy":[29],"achieved":[30],"by":[31],"standard":[32],"due":[35],"heterogeneity":[38,126],"individual":[41],"clients'":[42],"data,":[43,50],"especially":[44],"in":[45,67],"case":[47],"electricity":[49,114,124],"where":[51],"prediction":[52,72],"peak":[54],"demand":[55],"challenge.":[58],"A":[59],"set":[60],"clustering":[62,105],"techniques":[63,106],"has":[64],"been":[65,82],"explored":[66],"literature":[69],"improve":[71],"quality":[73],"while":[74],"maintaining":[75],"user":[76],"privacy.":[77],"These":[78],"studies":[79],"have":[80],"mainly":[81],"conducted":[83],"using":[84],"sets":[85],"clients":[87],"with":[88],"similar":[89],"attributes":[90],"that":[91],"may":[92],"not":[93],"reflect":[94],"real-world":[95],"consumer":[96],"diversity.":[97],"This":[98],"paper":[99],"explores,":[100],"implements":[101],"and":[102,130],"compares":[103],"these":[104],"privacy-preserving":[108],"load":[109,136],"forecasting":[110,129],"on":[111,127,135],"representative":[113],"dataset.":[116],"The":[117],"experimental":[118],"results":[119],"demonstrate":[120],"effects":[122],"non-representative":[132],"sample's":[133],"impact":[134],"forecasting.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
