{"id":"https://openalex.org/W7162090405","doi":"https://doi.org/10.48550/arxiv.2605.21550","title":"PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting","display_name":"PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7162090405","doi":"https://doi.org/10.48550/arxiv.2605.21550"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.21550","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21550","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.21550","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063059144","display_name":"Wangzhi Yu","orcid":"https://orcid.org/0009-0008-0371-9519"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Wangzhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136737385","display_name":"Peng Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136768250","display_name":"Qing Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Qing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119268538","display_name":"Yiwen Jiang","orcid":"https://orcid.org/0009-0002-4626-4688"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yiwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136735435","display_name":"Dawei Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Dawei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9549999833106995,"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":0.9549999833106995,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.008100000210106373,"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/T10603","display_name":"Smart Grid Energy Management","score":0.003599999938160181,"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/smoothing","display_name":"Smoothing","score":0.7563999891281128},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.6572999954223633},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5288000106811523},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.5181000232696533},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.49050000309944153},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.48579999804496765},{"id":"https://openalex.org/keywords/intensity","display_name":"Intensity (physics)","score":0.4837999939918518},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.45590001344680786}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.7563999891281128},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6599000096321106},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.6572999954223633},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5288000106811523},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.5181000232696533},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.49050000309944153},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.48579999804496765},{"id":"https://openalex.org/C93038891","wikidata":"https://www.wikidata.org/wiki/Q1061524","display_name":"Intensity (physics)","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.45590001344680786},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.44699999690055847},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.42800000309944153},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.37070000171661377},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.35569998621940613},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.35409998893737793},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3244999945163727},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3093000054359436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30790001153945923},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.30469998717308044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3000999987125397},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28360000252723694},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C133710760","wikidata":"https://www.wikidata.org/wiki/Q775837","display_name":"Exponential smoothing","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2563999891281128},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.21550","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21550","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.21550","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21550","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Electricity":[0,181,189],"load":[1],"peak":[2,7,55,65,130,156,173],"forecasting":[3],"(ELPF),":[4],"simultaneously":[5],"predicting":[6],"timing":[8,58,66,148,157,200],"and":[9,18,41,57,110,136,171,184,202],"intensity,":[10],"is":[11],"a":[12,30,89,101,114,143],"prerequisite":[13],"for":[14,92],"effective":[15],"grid":[16],"scheduling":[17],"risk":[19],"management.":[20],"However,":[21],"existing":[22],"methods":[23],"face":[24],"three":[25],"limitations.":[26],"First,":[27],"they":[28,45],"adopt":[29],"two-stage":[31],"predict-then-locate":[32],"paradigm,":[33],"which":[34],"severs":[35],"the":[36,49,61,160,179],"link":[37],"between":[38],"temporal":[39,108],"localization":[40,109],"intensity":[42,69,72,111,161,169,174,203],"regression.":[43],"Second,":[44],"still":[46],"struggle":[47],"with":[48],"multi-scale":[50],"representation":[51],"conflict,":[52],"leading":[53],"to":[54,105,128,146,167],"misjudgment":[56,131],"misalignment.":[59,149],"Third,":[60],"lack":[62],"of":[63],"explicit":[64,165],"context":[67,158],"during":[68],"regression":[70,162],"causes":[71],"smoothing":[73,80,170],"because":[74],"predictions":[75],"are":[76],"dominated":[77],"by":[78,133],"global":[79],"trends.":[81],"To":[82],"address":[83],"these":[84],"limitations,":[85],"we":[86],"propose":[87],"PeakFocus,":[88],"unified":[90],"framework":[91],"ELPF.":[93],"(i)":[94],"A":[95,119,151],"Unified":[96],"Peak-Aware":[97],"Pipeline":[98],"(UPAP)":[99],"utilizes":[100],"triple":[102],"hybrid":[103],"loss":[104],"jointly":[106],"supervise":[107],"regression,":[112],"alongside":[113],"tolerance-based":[115],"evaluation":[116],"protocol.":[117],"(ii)":[118],"Multi-Scale":[120],"Mixing":[121],"Peak":[122],"Locator":[123],"(MSM-PL)":[124],"exploits":[125],"coarse-grained":[126],"features":[127,141],"mitigate":[129],"caused":[132],"local":[134],"fluctuations,":[135],"injects":[137,155],"them":[138],"into":[139,159],"fine-grained":[140],"via":[142],"cascade":[144],"mechanism":[145],"resolve":[147],"(iii)":[150],"Location-Aware":[152],"Decoder":[153],"(LAD)":[154],"process,":[163],"providing":[164],"guidance":[166],"counteract":[168],"improve":[172],"estimation.":[175,204],"Extensive":[176],"experiments":[177],"on":[178],"public":[180],"(ELC)":[182],"dataset":[183,192],"our":[185],"industrial-scale":[186],"World":[187],"Large-scale":[188],"Load":[190],"(WLEL)":[191],"show":[193],"that":[194],"PeakFocus":[195],"outperforms":[196],"baselines":[197],"in":[198],"both":[199],"precision":[201]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-23T00:00:00"}
