{"id":"https://openalex.org/W2574599408","doi":"https://doi.org/10.1109/ecc.2016.7810440","title":"Probabilistic short-term load forecasting with conditional mean-variance and quantile regression models","display_name":"Probabilistic short-term load forecasting with conditional mean-variance and quantile regression models","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2574599408","doi":"https://doi.org/10.1109/ecc.2016.7810440","mag":"2574599408"},"language":"en","primary_location":{"id":"doi:10.1109/ecc.2016.7810440","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecc.2016.7810440","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 European Control Conference (ECC)","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/A5068172648","display_name":"Can Bikcora","orcid":"https://orcid.org/0000-0003-4877-0648"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Can Bikcora","raw_affiliation_strings":["Department of Electrical Engineering, Eindhoven University of Technology, MB Eindhoven, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Eindhoven University of Technology, MB Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031952997","display_name":"Lennart Verheijen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lennart Verheijen","raw_affiliation_strings":["GreenFlux Assets B.V., 1092 AD Amsterdam, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GreenFlux Assets B.V., 1092 AD Amsterdam, The Netherlands","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006584942","display_name":"S. Weiland","orcid":"https://orcid.org/0000-0002-6131-4658"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Siep Weiland","raw_affiliation_strings":["Department of Electrical Engineering, Eindhoven University of Technology, MB Eindhoven, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Eindhoven University of Technology, MB Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.2253344,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1123","last_page":"1128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9997000098228455,"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":0.9997000098228455,"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/T12368","display_name":"Grey System Theory Applications","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-conditional-heteroskedasticity","display_name":"Autoregressive conditional heteroskedasticity","score":0.7092703580856323},{"id":"https://openalex.org/keywords/heteroscedasticity","display_name":"Heteroscedasticity","score":0.6309847235679626},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.6301174163818359},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6081705093383789},{"id":"https://openalex.org/keywords/quantile-regression","display_name":"Quantile regression","score":0.5336464643478394},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5113101005554199},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5048194527626038},{"id":"https://openalex.org/keywords/conditional-variance","display_name":"Conditional variance","score":0.48128050565719604},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4532037079334259},{"id":"https://openalex.org/keywords/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.43853676319122314},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.08560729026794434}],"concepts":[{"id":"https://openalex.org/C23922673","wikidata":"https://www.wikidata.org/wiki/Q180752","display_name":"Autoregressive conditional heteroskedasticity","level":3,"score":0.7092703580856323},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.6309847235679626},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.6301174163818359},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6081705093383789},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.5336464643478394},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5113101005554199},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5048194527626038},{"id":"https://openalex.org/C21430997","wikidata":"https://www.wikidata.org/wiki/Q5159279","display_name":"Conditional variance","level":4,"score":0.48128050565719604},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4532037079334259},{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.43853676319122314},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.08560729026794434}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1109/ecc.2016.7810440","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecc.2016.7810440","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 European Control Conference (ECC)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.tue.nl:openaire_cris_publications/d44cd5cf-599b-4bad-ae54-976a1f70d1de","is_oa":false,"landing_page_url":"https://research.tue.nl/en/publications/d44cd5cf-599b-4bad-ae54-976a1f70d1de","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bikcora, C, Verheijen, L & Weiland, S 2016, Probabilistic short-term load forecasting with conditional mean-variance and quantile regression models. in Proceedings of European Control Conference (ECC), Aalborg, Denmark, Jun. 2016., Paper ThA8.1, Institute of Electrical and Electronics Engineers, pp. 1123-1128, 15th European Control Conference, ECC 2016, Aalborg, Denmark, 29/06/16. https://doi.org/10.1109/ECC.2016.7810440","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:856952","is_oa":false,"landing_page_url":"http://library.tue.nl/csp/dare/LinkToRepository.csp?recordnumber=856952","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"pmh:884372","is_oa":false,"landing_page_url":"http://library.tue.nl/csp/dare/LinkToRepository.csp?recordnumber=884372","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"pmh:oai:library.tue.nl:856952","is_oa":false,"landing_page_url":"http://repository.tue.nl/856952","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"pmh:oai:library.tue.nl:884372","is_oa":false,"landing_page_url":"http://repository.tue.nl/884372","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"pmh:tue:oai:pure.tue.nl:publications/d44cd5cf-599b-4bad-ae54-976a1f70d1de","is_oa":false,"landing_page_url":"https://research.tue.nl/nl/publications/d44cd5cf-599b-4bad-ae54-976a1f70d1de","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of European Control Conference (ECC), Aalborg, Denmark, Jun. 2016, 1123 - 1128","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W129305155","https://openalex.org/W1484221176","https://openalex.org/W1601526042","https://openalex.org/W1950001864","https://openalex.org/W1968865311","https://openalex.org/W1999996900","https://openalex.org/W2007260076","https://openalex.org/W2025720061","https://openalex.org/W2065089656","https://openalex.org/W2096904991","https://openalex.org/W2107885789","https://openalex.org/W2109468805","https://openalex.org/W2133479700","https://openalex.org/W2133720763","https://openalex.org/W2135797872","https://openalex.org/W2142635246","https://openalex.org/W2145072343","https://openalex.org/W2152271106","https://openalex.org/W2153529786","https://openalex.org/W2168175751","https://openalex.org/W2261958379","https://openalex.org/W2275088575","https://openalex.org/W2797165166","https://openalex.org/W2811507150","https://openalex.org/W3015420945","https://openalex.org/W3100067787","https://openalex.org/W3124216392","https://openalex.org/W4293282014","https://openalex.org/W6629026822","https://openalex.org/W6694717592"],"related_works":["https://openalex.org/W1608601224","https://openalex.org/W2017138702","https://openalex.org/W2549520657","https://openalex.org/W1978494725","https://openalex.org/W2776656900","https://openalex.org/W1980431701","https://openalex.org/W2031589205","https://openalex.org/W2550351598","https://openalex.org/W3029813487","https://openalex.org/W4312286080"],"abstract_inverted_index":{"For":[0],"the":[1,11,14,21,39,48,76,110,116,120,124,135,137,147,151,155,158,169],"day-ahead":[2],"density":[3],"forecasting":[4,87],"of":[5,13,30,59,92,103,134,181],"electricity":[6],"load,":[7],"this":[8],"paper":[9],"proposes":[10],"combination":[12],"autoregressive":[15,23],"moving":[16],"average":[17],"(ARMA)":[18],"model":[19,139],"and":[20,42,68,118,142],"generalized":[22],"conditional":[24,40],"heteroskedasticity":[25],"(GARCH)":[26],"model,":[27,78],"with":[28],"both":[29],"them":[31],"admitting":[32],"exogenous":[33],"inputs.":[34],"This":[35],"composite":[36],"structure":[37],"on":[38,64],"mean":[41],"variance":[43],"is":[44,129],"referred":[45],"to":[46,54,97,114,165],"as":[47,119],"ARMAX-GARCHX":[49,77,138],"model.":[50],"As":[51,131],"an":[52,132],"alternative":[53],"its":[55,144,166],"estimation":[56,145],"by":[57],"means":[58],"log-likelihood":[60],"maximization,":[61],"approaches":[62],"based":[63],"iterative":[65],"least-squares":[66,70],"(ILS)":[67],"nonlinear":[69],"(NLS)":[71],"are":[72,83,94,112,160],"considered.":[73],"Apart":[74],"from":[75,109],"quantile":[79],"regression":[80],"models":[81],"(QRMs)":[82],"also":[84],"tested":[85],"in":[86,157,183],"where":[88],"a":[89,99,174],"wide":[90],"range":[91],"quantiles":[93],"separately":[95],"modeled":[96],"approximate":[98],"density.":[100],"Phase":[101],"currents":[102],"several":[104],"low":[105],"voltage":[106],"transformer":[107],"cables":[108],"Netherlands":[111],"forecasted":[113],"compare":[115],"performances,":[117],"probabilistic":[121],"evaluation":[122],"criterion,":[123],"continuous":[125],"ranked":[126],"probability":[127],"score":[128],"used.":[130],"outline":[133],"results,":[136],"outperformed":[140],"QRMs":[141],"among":[143],"techniques,":[146],"likelihood-based":[148],"approach":[149],"had":[150],"best":[152],"performance,":[153],"though":[154],"differences":[156],"errors":[159],"often":[161],"minor.":[162],"Thus,":[163],"owing":[164],"computational":[167],"simplicity,":[168],"ILS":[170],"solution":[171],"can":[172],"be":[173],"valuable":[175],"option":[176],"when":[177],"processing":[178],"large":[179],"batches":[180],"data":[182],"practice.":[184]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}