{"id":"https://openalex.org/W4385881815","doi":"https://doi.org/10.7148/2023-0148","title":"Predicting HVAC-Based Demand Flexibility In Grid- Interactive Efficient Buildings Utilizing Deep Neural Networks","display_name":"Predicting HVAC-Based Demand Flexibility In Grid- Interactive Efficient Buildings Utilizing Deep Neural Networks","publication_year":2023,"publication_date":"2023-06-23","ids":{"openalex":"https://openalex.org/W4385881815","doi":"https://doi.org/10.7148/2023-0148"},"language":"en","primary_location":{"id":"doi:10.7148/2023-0148","is_oa":true,"landing_page_url":"https://doi.org/10.7148/2023-0148","pdf_url":"http://www.scs-europe.net/dlib/2023/ecms2023acceptedpapers/0148_ocms_ecms2023_0029.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ECMS 2023 Proceedings edited by Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://www.scs-europe.net/dlib/2023/ecms2023acceptedpapers/0148_ocms_ecms2023_0029.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071921415","display_name":"Italo Aldo Campodonico Avendano","orcid":"https://orcid.org/0009-0009-3240-3174"},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Italo Aldo Campodonico Avendano","raw_affiliation_strings":["Norwegian University of Science and Technology Larsg\u00e5rdsvegen 2, 6009 \u00c5lesund, NO"],"affiliations":[{"raw_affiliation_string":"Norwegian University of Science and Technology Larsg\u00e5rdsvegen 2, 6009 \u00c5lesund, NO","institution_ids":["https://openalex.org/I204778367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043771504","display_name":"Amin Moazami","orcid":"https://orcid.org/0000-0003-1622-2444"},"institutions":[{"id":"https://openalex.org/I4387930280","display_name":"SINTEF Community","ror":"https://ror.org/01zj15q98","country_code":null,"type":"facility","lineage":["https://openalex.org/I173888879","https://openalex.org/I4387930280"]},{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]},{"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":false,"raw_author_name":"Amin Moazami","raw_affiliation_strings":["SINTEF Community, SINTEF AS B\u00f8rrestuveien 3, 0373 Oslo, NO","Norwegian University of Science and Technology Larsg\u00e5rdsvegen 2, 6009 \u00c5lesund, NO"],"affiliations":[{"raw_affiliation_string":"SINTEF Community, SINTEF AS B\u00f8rrestuveien 3, 0373 Oslo, NO","institution_ids":["https://openalex.org/I173888879","https://openalex.org/I4387930280"]},{"raw_affiliation_string":"Norwegian University of Science and Technology Larsg\u00e5rdsvegen 2, 6009 \u00c5lesund, NO","institution_ids":["https://openalex.org/I204778367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077741554","display_name":"Farzad Dadras Javan","orcid":"https://orcid.org/0000-0002-0014-4835"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Farzad Dadras Javan","raw_affiliation_strings":["Energy Department Politecnico di Milano Campus Bovisa -Via Lambruschini, 4a -20156 Milano","Department of Ocean Operations and Civil Engineering","Department of Architectural Engineering"],"affiliations":[{"raw_affiliation_string":"Energy Department Politecnico di Milano Campus Bovisa -Via Lambruschini, 4a -20156 Milano","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"Department of Ocean Operations and Civil Engineering","institution_ids":[]},{"raw_affiliation_string":"Department of Architectural Engineering","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022275321","display_name":"Behzad Najafi","orcid":"https://orcid.org/0000-0003-4405-2956"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Behzad Najafi","raw_affiliation_strings":["Department of Ocean Operations and Civil Engineering","Department of Architectural Engineering","Energy Department Politecnico di Milano Campus Bovisa -Via Lambruschini, 4a -20156 Milano"],"affiliations":[{"raw_affiliation_string":"Department of Ocean Operations and Civil Engineering","institution_ids":[]},{"raw_affiliation_string":"Department of Architectural Engineering","institution_ids":[]},{"raw_affiliation_string":"Energy Department Politecnico di Milano Campus Bovisa -Via Lambruschini, 4a -20156 Milano","institution_ids":["https://openalex.org/I93860229"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071921415"],"corresponding_institution_ids":["https://openalex.org/I204778367"],"apc_list":null,"apc_paid":null,"fwci":0.5355,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.6479802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"148","last_page":"154"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10603","display_name":"Smart Grid Energy Management","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9941999912261963,"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"}},{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9563000202178955,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/setpoint","display_name":"Setpoint","score":0.8376456499099731},{"id":"https://openalex.org/keywords/demand-response","display_name":"Demand response","score":0.8059538006782532},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.7189649343490601},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6532304286956787},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.5917534232139587},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.590110182762146},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49226441979408264},{"id":"https://openalex.org/keywords/hvac","display_name":"HVAC","score":0.4813183546066284},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.4789305627346039},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.46571826934814453},{"id":"https://openalex.org/keywords/peak-demand","display_name":"Peak demand","score":0.4596102237701416},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4435121715068817},{"id":"https://openalex.org/keywords/building-model","display_name":"Building model","score":0.438212513923645},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.4138174057006836},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3603617548942566},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.2600034177303314},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21343928575515747},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20643404126167297},{"id":"https://openalex.org/keywords/air-conditioning","display_name":"Air conditioning","score":0.11941304802894592},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08787965774536133}],"concepts":[{"id":"https://openalex.org/C12302492","wikidata":"https://www.wikidata.org/wiki/Q1752097","display_name":"Setpoint","level":2,"score":0.8376456499099731},{"id":"https://openalex.org/C2779438525","wikidata":"https://www.wikidata.org/wiki/Q5255048","display_name":"Demand response","level":3,"score":0.8059538006782532},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.7189649343490601},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6532304286956787},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.5917534232139587},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.590110182762146},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49226441979408264},{"id":"https://openalex.org/C122346748","wikidata":"https://www.wikidata.org/wiki/Q1798773","display_name":"HVAC","level":3,"score":0.4813183546066284},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.4789305627346039},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.46571826934814453},{"id":"https://openalex.org/C147940328","wikidata":"https://www.wikidata.org/wiki/Q3393666","display_name":"Peak demand","level":3,"score":0.4596102237701416},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4435121715068817},{"id":"https://openalex.org/C2778530916","wikidata":"https://www.wikidata.org/wiki/Q1352349","display_name":"Building model","level":2,"score":0.438212513923645},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.4138174057006836},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3603617548942566},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.2600034177303314},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21343928575515747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20643404126167297},{"id":"https://openalex.org/C103742991","wikidata":"https://www.wikidata.org/wiki/Q173725","display_name":"Air conditioning","level":2,"score":0.11941304802894592},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08787965774536133},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.7148/2023-0148","is_oa":true,"landing_page_url":"https://doi.org/10.7148/2023-0148","pdf_url":"http://www.scs-europe.net/dlib/2023/ecms2023acceptedpapers/0148_ocms_ecms2023_0029.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ECMS 2023 Proceedings edited by Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.7148/2023-0148","is_oa":true,"landing_page_url":"https://doi.org/10.7148/2023-0148","pdf_url":"http://www.scs-europe.net/dlib/2023/ecms2023acceptedpapers/0148_ocms_ecms2023_0029.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ECMS 2023 Proceedings edited by Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4385881815.pdf"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1981780459","https://openalex.org/W2002016471","https://openalex.org/W2091085232","https://openalex.org/W2108152153","https://openalex.org/W2151049413","https://openalex.org/W2181900758","https://openalex.org/W2402144811","https://openalex.org/W2522326179","https://openalex.org/W2734510213","https://openalex.org/W2745349846","https://openalex.org/W2794034951","https://openalex.org/W2800620127","https://openalex.org/W2802011801","https://openalex.org/W2940930415","https://openalex.org/W2949802569","https://openalex.org/W2953384591","https://openalex.org/W3097299570","https://openalex.org/W3122943357","https://openalex.org/W3152400824","https://openalex.org/W4200059648","https://openalex.org/W4296337472","https://openalex.org/W6650873172","https://openalex.org/W6743032621","https://openalex.org/W6764046478"],"related_works":["https://openalex.org/W2955299595","https://openalex.org/W2125824188","https://openalex.org/W2980388055","https://openalex.org/W1994034588","https://openalex.org/W3159101362","https://openalex.org/W2990608314","https://openalex.org/W1922621424","https://openalex.org/W2972317891","https://openalex.org/W1969728024","https://openalex.org/W2903667954"],"abstract_inverted_index":{"Grid-interactive":[0],"efficient":[1],"buildings":[2],"(GEBs)":[3],"can":[4],"provide":[5],"flexibility":[6,29,87,162],"services":[7],"to":[8,22,110,114,145],"the":[9,24,49,53,57,63,67,84,92,112,120,125,150,152,155,161,174],"grid":[10],"through":[11],"demand":[12,28,33,51,85,101],"response.":[13],"This":[14],"paper":[15],"presents":[16],"a":[17,39,45,75,89,131,177,182],"novel":[18],"predictive":[19],"modeling":[20],"methodology":[21],"estimate":[23],"availability":[25],"of":[26,44,65,77,91,171,188],"electrical":[27,95],"in":[30,52,124,154],"GEBs":[31],"under":[32],"response":[34,102],"schemes.":[35],"In":[36],"this":[37,129],"context,":[38],"physics-based":[40],"energy":[41],"simulation":[42],"model":[43,113,135,175],"reference":[46],"building,":[47],"considering":[48],"cooling":[50,93],"summer":[54],"season":[55],"as":[56],"flexible":[58],"load,":[59,96],"is":[60,97,104,143,165],"utilized.":[61],"Accordingly,":[62],"impact":[64],"increasing":[66],"indoor":[68],"setpoint":[69],"temperature":[70],"by":[71],"1.5":[72],"\u00b0C":[73],"(for":[74],"maximum":[76],"3":[78,157],"hours":[79,158],"per":[80],"day),":[81],"which":[82],"enables":[83],"side":[86],"with":[88,168,181],"reduction":[90],"equipment\u2019s":[94],"simulated.":[98],"Next,":[99],"each":[100],"event":[103],"gathered,":[105],"sorted,":[106],"and":[107],"then":[108],"used":[109],"train":[111],"predict":[115,146],"similar":[116],"future":[117],"events":[118],"over":[119],"same":[121],"time":[122],"horizon":[123],"following":[126],"days.":[127],"For":[128],"purpose,":[130],"deep":[132],"neural":[133],"network":[134],"trained":[136],"using":[137],"an":[138],"expanding":[139],"window":[140],"training":[141,172],"scheme":[142],"utilized":[144],"(15":[147],"minutes":[148],"before":[149],"event)":[151],"load":[153],"next":[156],"while":[159],"undergoing":[160],"scenario.":[163],"It":[164],"demonstrated":[166],"that,":[167],"four":[169],"months":[170],"data,":[173],"offers":[176],"promising":[178],"prediction":[179],"accuracy":[180],"Mean":[183],"Absolute":[184],"Percentage":[185],"Error":[186],"(MAPE)":[187],"3.55%.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}