{"id":"https://openalex.org/W3212183624","doi":"https://doi.org/10.1109/access.2021.3121988","title":"A Temporal Neural Network Model for Probabilistic Multi-Period Forecasting of Distributed Energy Resources","display_name":"A Temporal Neural Network Model for Probabilistic Multi-Period Forecasting of Distributed Energy Resources","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3212183624","doi":"https://doi.org/10.1109/access.2021.3121988","mag":"3212183624"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3121988","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3121988","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2021.3121988","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004474101","display_name":"Markus L\u00f6schenbrand","orcid":"https://orcid.org/0000-0002-4614-4558"},"institutions":[{"id":"https://openalex.org/I173888879","display_name":"SINTEF","ror":"https://ror.org/01f677e56","country_code":"NO","type":"facility","lineage":["https://openalex.org/I173888879"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Markus Loschenbrand","raw_affiliation_strings":["SINTEF Energy Research, Trondheim, Norway"],"raw_orcid":"https://orcid.org/0000-0002-4614-4558","affiliations":[{"raw_affiliation_string":"SINTEF Energy Research, Trondheim, Norway","institution_ids":["https://openalex.org/I173888879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004474101"],"corresponding_institution_ids":["https://openalex.org/I173888879"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.4917,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.63960717,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":null,"first_page":"147029","last_page":"147041"},"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/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9957000017166138,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9883999824523926,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7614116668701172},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.582410991191864},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.47228604555130005},{"id":"https://openalex.org/keywords/distributed-generation","display_name":"Distributed generation","score":0.45572346448898315},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44119542837142944},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4152931869029999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4134463965892792},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3340270519256592},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.2894393503665924},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10663497447967529}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7614116668701172},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.582410991191864},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.47228604555130005},{"id":"https://openalex.org/C544738498","wikidata":"https://www.wikidata.org/wiki/Q861135","display_name":"Distributed generation","level":3,"score":0.45572346448898315},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44119542837142944},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4152931869029999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4134463965892792},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3340270519256592},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2894393503665924},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10663497447967529},{"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/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2021.3121988","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3121988","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0373dab8d2c44356b1f51940e950d2ed","is_oa":true,"landing_page_url":"https://doaj.org/article/0373dab8d2c44356b1f51940e950d2ed","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 147029-147041 (2021)","raw_type":"article"},{"id":"pmh:oai:sintef.brage.unit.no:11250/2980578","is_oa":true,"landing_page_url":"https://hdl.handle.net/11250/2980578","pdf_url":null,"source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"147029-147041","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3121988","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3121988","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8799999952316284,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G4736329859","display_name":null,"funder_award_id":"257626/E20","funder_id":"https://openalex.org/F4320323299","funder_display_name":"Norges Forskningsr\u00e5d"}],"funders":[{"id":"https://openalex.org/F4320323299","display_name":"Norges Forskningsr\u00e5d","ror":"https://ror.org/00epmv149"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1729198099","https://openalex.org/W1959608418","https://openalex.org/W2025129446","https://openalex.org/W2059742049","https://openalex.org/W2114196548","https://openalex.org/W2133564696","https://openalex.org/W2166851633","https://openalex.org/W2168285483","https://openalex.org/W2275088575","https://openalex.org/W2519091744","https://openalex.org/W2567112080","https://openalex.org/W2613278213","https://openalex.org/W2622052728","https://openalex.org/W2754252319","https://openalex.org/W2756959074","https://openalex.org/W2763128055","https://openalex.org/W2773359623","https://openalex.org/W2786918196","https://openalex.org/W2805797750","https://openalex.org/W2807966350","https://openalex.org/W2809899450","https://openalex.org/W2899494475","https://openalex.org/W2905358587","https://openalex.org/W2917883546","https://openalex.org/W2935877504","https://openalex.org/W2939518010","https://openalex.org/W2949382160","https://openalex.org/W2952673310","https://openalex.org/W2954123905","https://openalex.org/W2960560113","https://openalex.org/W2963188571","https://openalex.org/W2963403868","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W2965399094","https://openalex.org/W2967350632","https://openalex.org/W2972148356","https://openalex.org/W2979990517","https://openalex.org/W2996221603","https://openalex.org/W3007057000","https://openalex.org/W3008533347","https://openalex.org/W3010786997","https://openalex.org/W3011590044","https://openalex.org/W3016068557","https://openalex.org/W3027522260","https://openalex.org/W3101900901","https://openalex.org/W3102477513","https://openalex.org/W3113264736","https://openalex.org/W3119683607","https://openalex.org/W3142394151","https://openalex.org/W3157294059","https://openalex.org/W3160744338","https://openalex.org/W3164894090","https://openalex.org/W3171186964","https://openalex.org/W3184738396","https://openalex.org/W3203679490","https://openalex.org/W4294562888","https://openalex.org/W4297805092","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6637788867","https://openalex.org/W6640963894","https://openalex.org/W6679434410","https://openalex.org/W6684578138","https://openalex.org/W6732943021","https://openalex.org/W6737454906","https://openalex.org/W6739901393","https://openalex.org/W6774536461","https://openalex.org/W6794599215","https://openalex.org/W6801932625"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4290792893","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W3182838102","https://openalex.org/W2106478918","https://openalex.org/W4384812105","https://openalex.org/W2574982804","https://openalex.org/W2110658950"],"abstract_inverted_index":{"Probabilistic":[0],"forecasts":[1],"of":[2,11,40,85,112,129,161,166,174,193],"electrical":[3],"loads":[4],"and":[5,46,106,120,135,149,163],"photovoltaic":[6],"generation":[7,121],"provide":[8],"a":[9,32,38,70,126,145,150,158,164,182],"family":[10],"methods":[12,29,77,139],"able":[13],"to":[14,23,56,100,137,203],"incorporate":[15],"uncertainty":[16],"estimations":[17],"in":[18,98,133,197],"predictions.":[19],"This":[20],"paper":[21,52,180],"aims":[22],"extend":[24],"the":[25,51,87,104,107,113,169],"literature":[26],"on":[27,37,103,117],"these":[28],"by":[30],"proposing":[31],"novel":[33,183],"deep-learning":[34],"model":[35,88,170,184],"based":[36],"mixture":[39],"convolutional":[41],"neural":[42],"networks,":[43],"transformer":[44],"models":[45],"dynamic":[47],"Bayesian":[48],"networks.":[49],"Further,":[50],"also":[53,89],"illustrates":[54],"how":[55],"utilize":[57],"Stochastic":[58],"Variational":[59],"Inference":[60],"for":[61,74,154,190,206],"training":[62],"output":[63],"distributions":[64],"that":[65,94,185],"allow":[66],"time":[67,122,153,191],"series":[68,123,192],"sampling,":[69],"possibility":[71],"not":[72,80],"given":[73],"most":[75],"state-of-the-art":[76,138],"which":[78,199],"do":[79],"use":[81],"distributions.":[82],"On":[83],"top":[84],"this,":[86],"proposes":[90],"an":[91,155],"encoder-decoder":[92],"topology":[93],"uses":[95],"matrix":[96],"transposes":[97],"order":[99],"both":[101,118],"train":[102],"sequential":[105],"feature":[108],"dimension.":[109],"The":[110],"performance":[111,172],"work":[114],"is":[115],"illustrated":[116],"load":[119],"obtained":[124],"from":[125],"site":[127],"representative":[128],"distributed":[130,194],"energy":[131,195],"resources":[132,196],"Norway":[134],"compared":[136],"such":[140],"as":[141],"long-short-term":[142],"memory.":[143],"With":[144],"single-minute":[146],"prediction":[147],"resolution":[148],"single-second":[151],"computation":[152],"update":[156],"with":[157],"batch":[159],"size":[160],"100":[162],"horizon":[165],"24":[167],"hours,":[168],"promises":[171],"capable":[173],"real-time":[175],"application.":[176],"In":[177],"summary,":[178],"this":[179],"provides":[181],"allows":[186],"generating":[187],"future":[188],"scenarios":[189],"real-time,":[198],"can":[200],"be":[201],"used":[202],"generate":[204],"profiles":[205],"control":[207],"problems":[208],"under":[209],"uncertainty.":[210]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
