{"id":"https://openalex.org/W4210957435","doi":"https://doi.org/10.1109/tsg.2022.3148699","title":"FPSeq2Q: Fully Parameterized Sequence to Quantile Regression for Net-Load Forecasting With Uncertainty Estimates","display_name":"FPSeq2Q: Fully Parameterized Sequence to Quantile Regression for Net-Load Forecasting With Uncertainty Estimates","publication_year":2022,"publication_date":"2022-02-02","ids":{"openalex":"https://openalex.org/W4210957435","doi":"https://doi.org/10.1109/tsg.2022.3148699"},"language":"en","primary_location":{"id":"doi:10.1109/tsg.2022.3148699","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2022.3148699","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Smart Grid","raw_type":"journal-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/A5024522295","display_name":"Anthony Faustine","orcid":"https://orcid.org/0000-0002-7838-533X"},"institutions":[{"id":"https://openalex.org/I4210123295","display_name":"I-Form Advanced Manufacturing Research Centre","ror":"https://ror.org/022715v20","country_code":"IE","type":"facility","lineage":["https://openalex.org/I4210123295"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Anthony Faustine","raw_affiliation_strings":["ITI, LARSyS, Técnico Lisboa, Lisbon, Portugal","Irish Manufacturing Research, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"ITI, LARSyS, Técnico Lisboa, Lisbon, Portugal","institution_ids":[]},{"raw_affiliation_string":"Irish Manufacturing Research, Dublin, Ireland","institution_ids":["https://openalex.org/I4210123295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047119987","display_name":"Lucas Pereira","orcid":"https://orcid.org/0000-0002-9110-8775"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lucas Pereira","raw_affiliation_strings":["ITI, LARSyS, Técnico Lisboa, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"ITI, LARSyS, Técnico Lisboa, Lisbon, Portugal","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5024522295"],"corresponding_institution_ids":["https://openalex.org/I4210123295"],"apc_list":null,"apc_paid":null,"fwci":4.8784,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.95932662,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"13","issue":"3","first_page":"2440","last_page":"2451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":1.0,"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":1.0,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9829000234603882,"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/parameterized-complexity","display_name":"Parameterized complexity","score":0.6805115342140198},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.6215644478797913},{"id":"https://openalex.org/keywords/quantile-regression","display_name":"Quantile regression","score":0.6132075786590576},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.580867350101471},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5523803234100342},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4937480390071869},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4116092324256897},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38896363973617554},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3260008692741394},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1705593466758728}],"concepts":[{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.6805115342140198},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6215644478797913},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.6132075786590576},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.580867350101471},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5523803234100342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4937480390071869},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4116092324256897},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38896363973617554},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3260008692741394},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1705593466758728},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsg.2022.3148699","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2022.3148699","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Smart Grid","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.75,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G3663357362","display_name":null,"funder_award_id":"UIDB/50009/2020","funder_id":"https://openalex.org/F4320334779","funder_display_name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia"},{"id":"https://openalex.org/G7093072058","display_name":null,"funder_award_id":"CEECIND/01179/2017","funder_id":"https://openalex.org/F4320334779","funder_display_name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia"}],"funders":[{"id":"https://openalex.org/F4320334779","display_name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","ror":"https://ror.org/00snfqn58"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W1637550","https://openalex.org/W1522301498","https://openalex.org/W1677182931","https://openalex.org/W1977079033","https://openalex.org/W2045570758","https://openalex.org/W2124934380","https://openalex.org/W2132477882","https://openalex.org/W2275088575","https://openalex.org/W2343586331","https://openalex.org/W2486209400","https://openalex.org/W2512474546","https://openalex.org/W2552991604","https://openalex.org/W2751802138","https://openalex.org/W2764018574","https://openalex.org/W2789709604","https://openalex.org/W2800410101","https://openalex.org/W2803308811","https://openalex.org/W2884414452","https://openalex.org/W2911933099","https://openalex.org/W2912960432","https://openalex.org/W2918013114","https://openalex.org/W2956805085","https://openalex.org/W2961011421","https://openalex.org/W2975879372","https://openalex.org/W2980994438","https://openalex.org/W2982637766","https://openalex.org/W2994110319","https://openalex.org/W3004437308","https://openalex.org/W3004665231","https://openalex.org/W3005377970","https://openalex.org/W3005392995","https://openalex.org/W3006543788","https://openalex.org/W3011427446","https://openalex.org/W3012035124","https://openalex.org/W3017233978","https://openalex.org/W3028575248","https://openalex.org/W3034448642","https://openalex.org/W3034868650","https://openalex.org/W3091263342","https://openalex.org/W3092107260","https://openalex.org/W3095080867","https://openalex.org/W3095582408","https://openalex.org/W3097505757","https://openalex.org/W3102961490","https://openalex.org/W3106672452","https://openalex.org/W3107922427","https://openalex.org/W3113264736","https://openalex.org/W3117135573","https://openalex.org/W3126557344","https://openalex.org/W3129628875","https://openalex.org/W3157506437","https://openalex.org/W3162100006","https://openalex.org/W3171884590","https://openalex.org/W3194355893","https://openalex.org/W4212774754","https://openalex.org/W4231057675","https://openalex.org/W4287365706","https://openalex.org/W4287594739","https://openalex.org/W6631190155","https://openalex.org/W6748381273","https://openalex.org/W6751576797","https://openalex.org/W6751629939","https://openalex.org/W6759086998","https://openalex.org/W6762839895","https://openalex.org/W6763087592","https://openalex.org/W6767112054","https://openalex.org/W6767572230","https://openalex.org/W6768118886","https://openalex.org/W6783858723","https://openalex.org/W6784318611","https://openalex.org/W6784896029","https://openalex.org/W6788328477","https://openalex.org/W6795140394"],"related_works":["https://openalex.org/W4206511378","https://openalex.org/W4206618949","https://openalex.org/W2526321210","https://openalex.org/W3205863630","https://openalex.org/W4318833145","https://openalex.org/W2364275385","https://openalex.org/W4388704167","https://openalex.org/W2007977664","https://openalex.org/W4376874882","https://openalex.org/W2224749288"],"abstract_inverted_index":{"The":[0,165],"increased":[1],"penetration":[2],"of":[3,10,28,53,61,70,121],"Renewable":[4],"Energy":[5],"Sources":[6],"(RES)":[7],"as":[8],"part":[9],"a":[11,20,107,128,152,180],"decentralized":[12],"and":[13,26,118,139,156,178,186],"distributed":[14],"power":[15,29],"system":[16],"makes":[17],"net-load":[18,40,73,96],"forecasting":[19,97,184],"critical":[21,80],"component":[22],"in":[23,163,197],"the":[24,34,43,50,58,68,71,82,99,115,122,133,144,170],"planning":[25],"operation":[27],"systems.":[30],"However,":[31],"compared":[32],"to":[33,49,57,66,112],"transmission":[35],"level,":[36],"producing":[37],"accurate":[38],"short-term":[39,94],"forecasts":[41,172],"at":[42,74,98],"distribution":[44,100,154],"level":[45],"is":[46,64,79],"complex":[47],"due":[48],"small":[51],"number":[52],"consumers.":[54],"Moreover,":[55],"owing":[56],"stochastic":[59],"nature":[60],"RES,":[62],"it":[63],"necessary":[65],"quantify":[67],"uncertainty":[69,137,188],"forecasted":[72],"any":[75],"given":[76],"time,":[77],"which":[78],"for":[81,93],"real-world":[83,149],"decision":[84],"process.":[85],"This":[86],"work":[87],"presents":[88],"parameterized":[89],"deep":[90],"quantile":[91,116,119,123],"regression":[92],"probabilistic":[95],"level.":[101],"To":[102],"be":[103],"precise,":[104],"we":[105,126],"use":[106],"Deep":[108],"Neural":[109],"Network":[110],"(DNN)":[111],"learn":[113],"both":[114],"fractions":[117],"values":[120],"function.":[124],"Furthermore,":[125],"propose":[127],"scoring":[129],"metric":[130],"that":[131,169,190],"reflects":[132],"trade-off":[134,182],"between":[135,183],"predictive":[136,187],"performance":[138,189],"forecast":[140],"accuracy.":[141],"We":[142],"evaluate":[143],"proposed":[145],"techniques":[146],"on":[147],"historical":[148],"data":[150],"from":[151,173],"low-voltage":[153],"substation":[155],"further":[157],"assess":[158],"its":[159],"robustness":[160],"when":[161,195],"applied":[162,196],"real-time.":[164,198],"experiment\u2019s":[166],"outcomes":[167],"show":[168],"resulting":[171],"our":[174],"approach":[175],"are":[176,191],"well-calibrated":[177],"provide":[179],"desirable":[181],"accuracies":[185],"very":[192],"robust":[193],"even":[194]},"counts_by_year":[{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":13}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}