{"id":"https://openalex.org/W3175044079","doi":"https://doi.org/10.1145/3447555.3464866","title":"HeatFlex","display_name":"HeatFlex","publication_year":2021,"publication_date":"2021-06-22","ids":{"openalex":"https://openalex.org/W3175044079","doi":"https://doi.org/10.1145/3447555.3464866","mag":"3175044079"},"language":"en","primary_location":{"id":"doi:10.1145/3447555.3464866","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3447555.3464866","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3447555.3464866","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Future Energy Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3447555.3464866","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073079125","display_name":"Jonas Brusokas","orcid":"https://orcid.org/0000-0001-9538-5633"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jonas Brusokas","raw_affiliation_strings":["Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061064237","display_name":"Torben Bach Pedersen","orcid":"https://orcid.org/0000-0002-1615-777X"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Torben Bach Pedersen","raw_affiliation_strings":["Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073908480","display_name":"Laurynas \u0160ik\u0161nys","orcid":"https://orcid.org/0000-0002-1454-4709"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Laurynas \u0160ik\u0161nys","raw_affiliation_strings":["Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101753289","display_name":"Dalin Zhang","orcid":"https://orcid.org/0000-0002-5869-6544"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Dalin Zhang","raw_affiliation_strings":["Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010775700","display_name":"Kaixuan Chen","orcid":"https://orcid.org/0000-0003-3904-0395"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Kaixuan Chen","raw_affiliation_strings":["Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8136,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.71873881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"160","last_page":"170"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9995999932289124,"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":0.9995999932289124,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9988999962806702,"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/flexibility","display_name":"Flexibility (engineering)","score":0.7530756592750549},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6930314302444458},{"id":"https://openalex.org/keywords/heat-pump","display_name":"Heat pump","score":0.6768076419830322},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5653137564659119},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.4794979691505432},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4141681492328644},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3263075053691864},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21142876148223877},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.11077156662940979},{"id":"https://openalex.org/keywords/heat-exchanger","display_name":"Heat exchanger","score":0.08731865882873535}],"concepts":[{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.7530756592750549},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6930314302444458},{"id":"https://openalex.org/C2776461528","wikidata":"https://www.wikidata.org/wiki/Q131313","display_name":"Heat pump","level":3,"score":0.6768076419830322},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5653137564659119},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.4794979691505432},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4141681492328644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3263075053691864},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21142876148223877},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.11077156662940979},{"id":"https://openalex.org/C107706546","wikidata":"https://www.wikidata.org/wiki/Q189124","display_name":"Heat exchanger","level":2,"score":0.08731865882873535},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3447555.3464866","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3447555.3464866","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3447555.3464866","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Future Energy Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/d4c4bee7-f248-4b2b-92ee-a537f6266efe","is_oa":true,"landing_page_url":"https://vbn.aau.dk/da/publications/d4c4bee7-f248-4b2b-92ee-a537f6266efe","pdf_url":"https://vbn.aau.dk/ws/files/457819425/3447555.3464866.pdf","source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Brusokas, J, Pedersen, T B, Siksnys, L, Zhang, D & Chen, K 2021, HeatFlex: Machine learning based data-driven flexibility prediction for individual heat pumps. in e-Energy '21: Proceedings of the Twelfth ACM International Conference on Future Energy Systems. Association for Computing Machinery (ACM), New York, pp. 160-170, 12th ACM International Conference on Future Energy Systems, e-Energy 2021, Virtual, Online, Italy, 28/06/2021. https://doi.org/10.1145/3447555.3464866","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1145/3447555.3464866","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3447555.3464866","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3447555.3464866","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Future Energy Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1387364460","display_name":null,"funder_award_id":"864537","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3175044079.pdf","grobid_xml":"https://content.openalex.org/works/W3175044079.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1889418052","https://openalex.org/W1924770834","https://openalex.org/W1988156359","https://openalex.org/W2001666598","https://openalex.org/W2030341478","https://openalex.org/W2064675550","https://openalex.org/W2073595019","https://openalex.org/W2102148524","https://openalex.org/W2107878631","https://openalex.org/W2116512828","https://openalex.org/W2474849879","https://openalex.org/W2487967714","https://openalex.org/W2493112503","https://openalex.org/W2604847698","https://openalex.org/W2614529600","https://openalex.org/W2777109794","https://openalex.org/W2782902016","https://openalex.org/W2795874419","https://openalex.org/W2796302702","https://openalex.org/W2798058877","https://openalex.org/W2803243563","https://openalex.org/W2804082871","https://openalex.org/W2898687135","https://openalex.org/W2903843912","https://openalex.org/W2907773120","https://openalex.org/W2950072808","https://openalex.org/W2964199361","https://openalex.org/W2991336976","https://openalex.org/W2992252352","https://openalex.org/W3002730961","https://openalex.org/W3004451017","https://openalex.org/W3007883387","https://openalex.org/W3036926095","https://openalex.org/W3043709469","https://openalex.org/W3082698726","https://openalex.org/W3095128182","https://openalex.org/W4246312069"],"related_works":["https://openalex.org/W2770234245","https://openalex.org/W96612179","https://openalex.org/W4229499248","https://openalex.org/W2566006169","https://openalex.org/W1567818861","https://openalex.org/W2987774938","https://openalex.org/W4256492088","https://openalex.org/W632915154","https://openalex.org/W2055733372","https://openalex.org/W3022067003"],"abstract_inverted_index":{"With":[0],"their":[1,32],"rising":[2],"adoption":[3],"and":[4,58,86,95,98,115,151,170,181,199],"integration":[5],"into":[6],"smart":[7],"grids,":[8],"heat":[9,68,99,109,134,189,196],"pumps":[10,110],"are":[11],"becoming":[12],"an":[13],"increasingly":[14],"important":[15],"source":[16],"of":[17,67,120,133,213],"flexible":[18],"energy.":[19],"Heat":[20],"pump":[21,69,100,135,190,197],"flexibility":[22,87,106,128,136],"can":[23],"be":[24],"utilized":[25],"by":[26],"using":[27,89,184],"controllers":[28],"to":[29,208],"remotely":[30],"manage":[31],"operation":[33],"while":[34],"maintaining":[35],"the":[36,52,65],"temperature":[37,45,84],"within":[38],"predefined":[39],"user":[40],"comfort":[41],"bounds.":[42],"Traditional":[43],"indoor":[44,83,94],"modelling":[46],"approaches":[47],"require":[48],"detailed":[49],"information":[50],"about":[51],"deployment":[53],"site,":[54],"device":[55,114],"specific":[56],"parameters":[57],"monitored":[59,92],"data,":[60],"making":[61],"them":[62],"inapplicable":[63],"for":[64,82],"majority":[66],"deployments.":[70],"This":[71,123],"paper":[72,124],"proposes":[73],"a":[74],"novel":[75,127],"data-driven":[76],"machine":[77],"learning":[78,144],"based":[79,141],"method":[80],"HeatFlex":[81,103,139,177,205],"forecasting":[85,174],"prediction":[88,107,137],"only":[90],"3":[91],"variables:":[93],"outdoor":[96],"temperatures":[97],"power":[101],"consumption.":[102],"enables":[104],"plug-and-play":[105],"from":[108,186],"without":[111],"requiring":[112],"exact":[113],"building":[116,194],"specifications":[117],"or":[118],"installation":[119],"additional":[121],"sensors.":[122],"also":[125],"introduces":[126],"metrics":[129],"enabling":[130],"quantitative":[131],"evaluation":[132,161],"performance.":[138],"is":[140,206],"on":[142],"deep":[143],"predictive":[145],"models:":[146],"Long":[147],"Short-Term":[148],"Memory":[149],"(LSTM)":[150],"Gated":[152],"Recurrent":[153],"Unit":[154],"(GRU)":[155],"recurrent":[156],"neural":[157],"networks.":[158],"Our":[159],"experimental":[160],"compared":[162],"these":[163],"networks":[164],"with":[165,192],"traditional":[166],"multivariate":[167],"linear":[168],"regression":[169],"SARIMAX":[171],"time":[172],"series":[173],"model":[175],"baselines.":[176],"performance":[178],"was":[179],"qualitatively":[180],"quantitatively":[182],"evaluated":[183],"data":[185],"three":[187],"real-world":[188],"deployments":[191],"different":[193],"sizes,":[195],"types":[198],"specifications.":[200],"Experimental":[201],"results":[202],"indicate":[203],"that":[204],"effective":[207],"accurately":[209],"predict":[210],"over":[211],"90%":[212],"available":[214],"potential":[215],"flexibility.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2021-07-05T00:00:00"}
