{"id":"https://openalex.org/W4280647458","doi":"https://doi.org/10.1109/wcnc51071.2022.9771618","title":"An Efficient Approach for User Power Consumption Forecasting Based on Feature Extraction in Virtual Power Plants","display_name":"An Efficient Approach for User Power Consumption Forecasting Based on Feature Extraction in Virtual Power Plants","publication_year":2022,"publication_date":"2022-04-10","ids":{"openalex":"https://openalex.org/W4280647458","doi":"https://doi.org/10.1109/wcnc51071.2022.9771618"},"language":"en","primary_location":{"id":"doi:10.1109/wcnc51071.2022.9771618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcnc51071.2022.9771618","pdf_url":null,"source":{"id":"https://openalex.org/S4363607776","display_name":"2022 IEEE Wireless Communications and Networking Conference (WCNC)","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 Wireless Communications and Networking Conference (WCNC)","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/A5103152402","display_name":"Min Yan","orcid":"https://orcid.org/0000-0002-8849-5823"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Min Yan","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Computer Science (National Pilot Software Engineering School),Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Computer Science (National Pilot Software Engineering School),Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118941484","display_name":"Li Wang","orcid":"https://orcid.org/0009-0006-0994-9564"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Computer Science (National Pilot Software Engineering School),Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Computer Science (National Pilot Software Engineering School),Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052560055","display_name":"Lianming Xu","orcid":"https://orcid.org/0009-0006-9142-8863"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianming Xu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Electronic Engineering,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Electronic Engineering,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090675101","display_name":"Aiguo Fei","orcid":"https://orcid.org/0000-0002-7053-9832"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aiguo Fei","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Computer Science (National Pilot Software Engineering School),Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Computer Science (National Pilot Software Engineering School),Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103152402"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03569674,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2387","last_page":"2392"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10603","display_name":"Smart Grid Energy Management","score":0.9998000264167786,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9998000264167786,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9994999766349792,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7258050441741943},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.7072165012359619},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6619834899902344},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5812956690788269},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5040268301963806},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5039357542991638},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4597274661064148},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42640021443367004},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.41080984473228455},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4018704891204834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37096303701400757},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3533817529678345},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.33073627948760986},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11101090908050537}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7258050441741943},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.7072165012359619},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6619834899902344},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5812956690788269},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5040268301963806},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5039357542991638},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4597274661064148},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42640021443367004},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.41080984473228455},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4018704891204834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37096303701400757},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3533817529678345},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.33073627948760986},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11101090908050537},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcnc51071.2022.9771618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcnc51071.2022.9771618","pdf_url":null,"source":{"id":"https://openalex.org/S4363607776","display_name":"2022 IEEE Wireless Communications and Networking Conference (WCNC)","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 Wireless Communications and Networking Conference (WCNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334977","display_name":"Beijing Municipal Natural Science Foundation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1802314291","https://openalex.org/W1995357300","https://openalex.org/W1998373023","https://openalex.org/W2064675550","https://openalex.org/W2286754961","https://openalex.org/W2555340976","https://openalex.org/W2575295112","https://openalex.org/W2797889343","https://openalex.org/W2898180565","https://openalex.org/W2969293360","https://openalex.org/W2981905451","https://openalex.org/W2999862096","https://openalex.org/W3015322982","https://openalex.org/W3024333932","https://openalex.org/W3122528762","https://openalex.org/W3135061476","https://openalex.org/W3182952669","https://openalex.org/W6729617664","https://openalex.org/W6732125658"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W2159099865"],"abstract_inverted_index":{"Virtual":[0],"Power":[1,18],"Plant":[2],"(VPP)":[3],"has":[4],"become":[5],"an":[6],"important":[7],"means":[8],"of":[9,15,25,30,43,104,130],"low-carbon":[10],"development":[11],"and":[12,65,97,100,127,141],"the":[13,22,41,69,75,82,91,101,110,122,124,134],"forecasting":[14,32,58,63,95,125],"user":[16],"Adjusted":[17],"Consumption":[19],"(APC)":[20],"is":[21,33,107,137],"key":[23],"part":[24],"VPP.":[26],"The":[27],"main":[28],"challenge":[29],"APC":[31,57],"how":[34],"to":[35,77],"extract":[36,78],"more":[37],"APC-related":[38,79],"features":[39,80],"under":[40],"limitation":[42],"feature":[44,105],"dimension":[45,103],"for":[46,61],"lower":[47],"communication":[48,66,98,128],"latency.":[49,67],"In":[50,68],"this":[51],"paper,":[52],"we":[53,73,89],"propose":[54,74],"a":[55],"Feature-based":[56],"(F-APC)":[59],"framework":[60],"reducing":[62],"error":[64,96,126],"F-APC":[70],"framework,":[71],"firstly,":[72],"method":[76],"using":[81],"Classification-based":[83],"Auto-Encoder":[84],"(CAE)":[85],"neural":[86],"network.":[87],"Secondly,":[88],"formulate":[90],"trade-off":[92],"problem":[93],"between":[94],"latency":[99,129],"optimal":[102,135],"vector":[106],"solved":[108],"by":[109,139],"closed-form":[111],"solution.":[112],"Experimental":[113],"results":[114],"on":[115],"real":[116],"data":[117],"show":[118],"that,":[119],"compared":[120],"with":[121,133],"benchmark,":[123],"our":[131],"scheme":[132],"setting":[136],"reduced":[138],"45.26%":[140],"33.33%,":[142],"respectively.":[143]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
