{"id":"https://openalex.org/W4407951791","doi":"https://doi.org/10.1109/ispec59716.2024.10892557","title":"Optimizing Energy Management Systems with Fine-Grained Interval Demand Forecasting","display_name":"Optimizing Energy Management Systems with Fine-Grained Interval Demand Forecasting","publication_year":2024,"publication_date":"2024-11-24","ids":{"openalex":"https://openalex.org/W4407951791","doi":"https://doi.org/10.1109/ispec59716.2024.10892557"},"language":"en","primary_location":{"id":"doi:10.1109/ispec59716.2024.10892557","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispec59716.2024.10892557","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Sustainable Power and Energy Conference (iSPEC)","raw_type":"proceedings-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":null,"display_name":"Difei Miao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Difei Miao","raw_affiliation_strings":["NTT DOCOMO, INC.,X-Tech Development Department,TOKYO,JAPAN"],"affiliations":[{"raw_affiliation_string":"NTT DOCOMO, INC.,X-Tech Development Department,TOKYO,JAPAN","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091455495","display_name":"Masaki Nakamura","orcid":"https://orcid.org/0000-0002-4062-6847"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Masaki Nakamura","raw_affiliation_strings":["NTT DOCOMO, INC.,X-Tech Development Department,TOKYO,JAPAN"],"affiliations":[{"raw_affiliation_string":"NTT DOCOMO, INC.,X-Tech Development Department,TOKYO,JAPAN","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2028,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56170463,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9735000133514404,"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":0.9735000133514404,"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":0.9538000226020813,"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/interval","display_name":"Interval (graph theory)","score":0.6226370334625244},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6221818327903748},{"id":"https://openalex.org/keywords/demand-forecasting","display_name":"Demand forecasting","score":0.5600823163986206},{"id":"https://openalex.org/keywords/energy-management","display_name":"Energy management","score":0.5095977783203125},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.39004582166671753},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.23807626962661743},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0853075385093689},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08466815948486328}],"concepts":[{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.6226370334625244},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6221818327903748},{"id":"https://openalex.org/C193809577","wikidata":"https://www.wikidata.org/wiki/Q3409300","display_name":"Demand forecasting","level":2,"score":0.5600823163986206},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.5095977783203125},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.39004582166671753},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.23807626962661743},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0853075385093689},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08466815948486328},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispec59716.2024.10892557","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispec59716.2024.10892557","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Sustainable Power and Energy Conference (iSPEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1586335931","https://openalex.org/W2020026289","https://openalex.org/W2064675550","https://openalex.org/W2156604062","https://openalex.org/W2792961021","https://openalex.org/W2794778778","https://openalex.org/W2897247335","https://openalex.org/W2905388713"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2354768891","https://openalex.org/W4229332389","https://openalex.org/W1510108650","https://openalex.org/W2322968447","https://openalex.org/W2356819012"],"abstract_inverted_index":{"Accurate":[0],"electricity":[1,104],"demand":[2,31,105],"forecasting":[3,26,79],"is":[4],"a":[5],"crucial":[6],"component":[7],"of":[8,24,54,97],"effective":[9],"energy":[10,128,134],"management.":[11],"Recent":[12],"advancements":[13],"in":[14],"data":[15,42,75,106],"analytics":[16],"and":[17,32,43,72,107,126],"machine":[18],"learning":[19],"have":[20],"enabled":[21],"the":[22,52,67,73,95],"development":[23],"advanced":[25],"models":[27,36,111],"that":[28,84],"leverage":[29],"historical":[30,103],"climate":[33],"data.":[34],"Traditional":[35],"often":[37],"relied":[38],"solely":[39],"on":[40],"hourly":[41],"were":[44],"evaluated":[45],"at":[46,90],"specific":[47],"time":[48],"points.":[49],"However,":[50],"evaluating":[51],"accuracy":[53],"predictions":[55,71],"across":[56],"various":[57],"timeframes,":[58],"rather":[59],"than":[60],"just":[61],"fixed":[62],"intervals,":[63,92],"can":[64,112],"help":[65],"determine":[66],"optimal":[68],"timing":[69],"for":[70,77],"appropriate":[74],"window":[76],"each":[78],"model.":[80],"Our":[81],"study":[82],"demonstrates":[83],"utilizing":[85],"fine-grained":[86],"interval":[87],"data,":[88],"particularly":[89],"30-minute":[91],"significantly":[93],"enhances":[94],"precision":[96],"these":[98,110],"models.":[99],"By":[100],"incorporating":[101],"detailed":[102],"meteorological":[108],"information,":[109],"better":[113],"predict":[114],"short-term":[115],"fluctuations,":[116],"providing":[117],"more":[118,124],"reliable":[119],"forecasts.":[120],"This":[121],"improvement":[122],"facilitates":[123],"responsive":[125],"adaptive":[127],"management":[129],"strategies,":[130],"ultimately":[131],"enhancing":[132],"overall":[133],"efficiency.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}