{"id":"https://openalex.org/W4413088708","doi":"https://doi.org/10.1109/ssp64130.2025.11073459","title":"PUL-DERs: Distributed Energy Resources Prediction Algorithm Via Pseudo-Labeling Unsupervised Learning","display_name":"PUL-DERs: Distributed Energy Resources Prediction Algorithm Via Pseudo-Labeling Unsupervised Learning","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4413088708","doi":"https://doi.org/10.1109/ssp64130.2025.11073459"},"language":"en","primary_location":{"id":"doi:10.1109/ssp64130.2025.11073459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp64130.2025.11073459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Statistical Signal Processing Workshop (SSP)","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/A5109656639","display_name":"Yihan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yihan Huang","raw_affiliation_strings":["Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071271171","display_name":"Jing Jiang","orcid":"https://orcid.org/0000-0002-2646-8635"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jing Jiang","raw_affiliation_strings":["Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100963251","display_name":"Zhilin Gao","orcid":"https://orcid.org/0009-0008-1330-4691"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhilin Gao","raw_affiliation_strings":["Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119266230","display_name":"Yue Yin","orcid":"https://orcid.org/0009-0005-5685-0367"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yue Yin","raw_affiliation_strings":["Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100694341","display_name":"Hongjian Sun","orcid":"https://orcid.org/0000-0001-8660-8081"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"HongJian Sun","raw_affiliation_strings":["Durham University,Dept. of Engineering,Durham,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Durham University,Dept. of Engineering,Durham,United Kingdom","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101739295","display_name":"Zhiwei Gao","orcid":"https://orcid.org/0009-0003-7700-304X"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhiwei Gao","raw_affiliation_strings":["Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northumbria University,Dept. of Mathematics, Physics&amp; Electrical Engineering,Newcastle,United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":"191","last_page":"195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9796000123023987,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10603","display_name":"Smart Grid Energy Management","score":0.9764999747276306,"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":0.6997547149658203},{"id":"https://openalex.org/keywords/distributed-generation","display_name":"Distributed generation","score":0.48939910531044006},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4486531913280487},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4440481662750244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3965398073196411},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3586813807487488},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3262791931629181},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10395827889442444},{"id":"https://openalex.org/keywords/renewable-energy","display_name":"Renewable energy","score":0.10339853167533875},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09301590919494629},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.06383708119392395},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06181773543357849}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6997547149658203},{"id":"https://openalex.org/C544738498","wikidata":"https://www.wikidata.org/wiki/Q861135","display_name":"Distributed generation","level":3,"score":0.48939910531044006},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4486531913280487},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4440481662750244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3965398073196411},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3586813807487488},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3262791931629181},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10395827889442444},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.10339853167533875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09301590919494629},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.06383708119392395},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06181773543357849}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssp64130.2025.11073459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp64130.2025.11073459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.41999998688697815}],"awards":[],"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":12,"referenced_works":["https://openalex.org/W2949831805","https://openalex.org/W2969375742","https://openalex.org/W2994797293","https://openalex.org/W3003545385","https://openalex.org/W3028695255","https://openalex.org/W3157139731","https://openalex.org/W4211021439","https://openalex.org/W4226490191","https://openalex.org/W4286444778","https://openalex.org/W4297094590","https://openalex.org/W4312964829","https://openalex.org/W4315473680"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W3196155444","https://openalex.org/W4321844043","https://openalex.org/W3210156800","https://openalex.org/W4390062853","https://openalex.org/W4297883248","https://openalex.org/W4255830763","https://openalex.org/W1583266947","https://openalex.org/W4286799911"],"abstract_inverted_index":{"The":[0,79],"prediction":[1,135],"of":[2,45,133],"Distributed":[3],"Energy":[4],"Resources":[5],"(DERs)":[6],"has":[7],"become":[8],"increasingly":[9],"vital":[10],"for":[11,23,35,139,144],"future":[12],"power":[13],"networks":[14],"to":[15,86,122],"achieve":[16],"net-zero":[17],"carbon":[18],"emissions.":[19],"However,":[20],"existing":[21],"methods":[22],"this":[24],"problem":[25],"rely":[26],"heavily":[27],"on":[28,127],"supervised":[29],"learning":[30],"with":[31,111],"extensive":[32],"labeled":[33],"data":[34,104],"training":[36],"and":[37,67,88,142],"high":[38],"computational":[39],"costs,":[40],"greatly":[41],"restricting":[42],"the":[43,58,72,95,117,128,131],"applicability":[44],"traditional":[46],"algorithms":[47],"in":[48,71],"DERs":[49,109],"monitoring.":[50],"To":[51],"address":[52],"these,":[53],"we":[54],"propose":[55],"PUL-DERs,":[56],"predicting":[57],"characteristic":[59],"electrical":[60],"profiles":[61],"produced":[62],"by":[63],"electric":[64],"vehicles":[65],"(EV)":[66],"photovoltaic":[68],"(PV)":[69],"systems":[70],"distribution":[73],"network":[74],"utilizing":[75],"pseudo-labeling":[76,103],"unsupervised":[77],"learning.":[78],"optimized":[80],"K-medoids":[81],"clustering":[82],"algorithm":[83],"is":[84],"applied":[85],"EV":[87,140],"PV":[89,145],"prediction,":[90],"incorporating":[91],"cosine":[92],"similarity":[93],"as":[94],"distance":[96],"metric.":[97],"Our":[98],"approach":[99],"concatenates":[100],"synthetically":[101],"generated":[102],"that":[105],"closely":[106],"mimics":[107],"real-world":[108],"distributions":[110],"smart":[112],"meter":[113],"data,":[114],"thus":[115],"enriching":[116],"dataset":[118],"while":[119],"maintaining":[120],"relevance":[121],"actual":[123],"values.":[124],"Experimental":[125],"results":[126],"datasets":[129],"demonstrate":[130],"advantage":[132],"PUL-DER's":[134],"accuracy,":[136],"achieving":[137],"95.01%":[138],"usage":[141],"98.15%":[143],"generation.":[146]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
