{"id":"https://openalex.org/W4285103584","doi":"https://doi.org/10.1109/isgt50606.2022.9817463","title":"Physics-Aware Fast Learning and Inference for Predicting Active Set of DC-OPF","display_name":"Physics-Aware Fast Learning and Inference for Predicting Active Set of DC-OPF","publication_year":2022,"publication_date":"2022-04-24","ids":{"openalex":"https://openalex.org/W4285103584","doi":"https://doi.org/10.1109/isgt50606.2022.9817463"},"language":"en","primary_location":{"id":"doi:10.1109/isgt50606.2022.9817463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt50606.2022.9817463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Power &amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)","raw_type":"proceedings-article"},"type":"conference-paper","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":"https://openalex.org/A5015089992","display_name":"Hossein Khazaei","orcid":"https://orcid.org/0000-0001-5712-1135"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hossein Khazaei","raw_affiliation_strings":["Stony Brook University,Department of Electrical and Computer Engineering,Stony Brook,NY,11794"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University,Department of Electrical and Computer Engineering,Stony Brook,NY,11794","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101755455","display_name":"Yue Zhao","orcid":"https://orcid.org/0000-0002-6702-8177"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Zhao","raw_affiliation_strings":["Stony Brook University,Department of Electrical and Computer Engineering,Stony Brook,NY,11794"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University,Department of Electrical and Computer Engineering,Stony Brook,NY,11794","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59553526"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10424","display_name":"Electric Power System Optimization","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/T10424","display_name":"Electric Power System Optimization","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/T10454","display_name":"Optimal Power Flow Distribution","score":0.9987999796867371,"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":0.9979000091552734,"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/computer-science","display_name":"Computer science","score":0.7017703652381897},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6197439432144165},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5744113326072693},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5100753903388977},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5088663101196289},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4797452688217163},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.4525465667247772},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.44657790660858154},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.44073110818862915},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42231640219688416},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.418459951877594},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14067471027374268},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13838693499565125}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7017703652381897},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6197439432144165},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5744113326072693},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5100753903388977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5088663101196289},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4797452688217163},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.4525465667247772},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.44657790660858154},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.44073110818862915},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42231640219688416},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.418459951877594},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14067471027374268},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13838693499565125},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isgt50606.2022.9817463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt50606.2022.9817463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Power &amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W368469426","https://openalex.org/W2098824882","https://openalex.org/W2295598076","https://openalex.org/W2781956327","https://openalex.org/W2971091630","https://openalex.org/W2989332036","https://openalex.org/W2990090413","https://openalex.org/W3006296698","https://openalex.org/W3198890660","https://openalex.org/W3210348837","https://openalex.org/W4250589301","https://openalex.org/W6758533370","https://openalex.org/W6769952219","https://openalex.org/W6774006684","https://openalex.org/W6783498434"],"related_works":["https://openalex.org/W4296209631","https://openalex.org/W4402452563","https://openalex.org/W2250488071","https://openalex.org/W3097449145","https://openalex.org/W2561617217","https://openalex.org/W2356150353","https://openalex.org/W2018643641","https://openalex.org/W2380744779","https://openalex.org/W4294811468","https://openalex.org/W2951122819"],"abstract_inverted_index":{"DC-OPF":[0,19],"stands":[1],"as":[2,53,128,170,172],"the":[3,27,49,67,77,82,95,108,118,137,142,150,220,227,238,246,264],"cornerstone":[4],"for":[5,60,116,122,140,262,268],"efficient":[6],"and":[7,21,32,94,182,200,209,215,235,237],"secure":[8],"operations":[9],"of":[10,29,38,76,80,97,110,248,259],"power":[11,165],"systems.":[12],"The":[13,187],"grid":[14],"operators":[15],"need":[16,247],"to":[17,25,86,204,217,241],"solve":[18],"repeatedly":[20],"in":[22,47,57,198,201],"large":[23],"numbers":[24],"maintain":[26],"balance":[28],"electricity":[30],"supply":[31],"demand,":[33],"especially":[34],"under":[35],"high":[36],"penetration":[37,159],"renewable":[39,158,164],"energies.":[40],"Recently,":[41],"research":[42],"efforts":[43],"have":[44],"been":[45],"made":[46],"predicting":[48,117,263],"optimal":[50,78,88,119,265],"active":[51,89,99,120,266],"sets":[52,100,121],"a":[54,72,92,129,156,195,256],"key":[55,73],"component":[56],"learning-based":[58,260],"solvers":[59],"DC-OPF.":[61,123,269],"In":[62,104],"this":[63],"paper,":[64],"we":[65,106,251],"investigate":[66,107],"classifiers":[68,115],"that":[69,136,191,253],"inherently":[70],"exploit":[71],"physical":[74],"property":[75],"solutions":[79],"DC-OPF:":[81],"input":[83],"space":[84],"corresponding":[85],"an":[87],"set":[90,267],"is":[91,125,211,255],"polyhedron,":[93],"classes":[96,143],"different":[98],"are":[101,144,147],"linearly":[102],"separable.":[103],"particular,":[105],"effectiveness":[109],"linear":[111],"discriminant":[112],"analysis":[113],"(LDA)":[114],"This":[124],"because":[126],"LDA,":[127],"natural":[130],"multi-class":[131],"classifier,":[132],"by":[133,162],"definition":[134],"guarantees":[135],"decision":[138,185],"regions":[139],"all":[141],"polyhedrons.":[145],"Simulations":[146],"conducted":[148],"on":[149],"IEEE\u2013162":[151],"bus":[152],"test":[153],"case":[154],"with":[155],"50%":[157],"level":[160],"provided":[161],"37":[163],"producers.":[166],"We":[167],"examine":[168],"LDA":[169,192,254],"well":[171],"other":[173,221],"classifier":[174],"candidates,":[175],"namely":[176],"support":[177],"vector":[178],"machines,":[179],"neural":[180,207],"networks,":[181,208],"gradient":[183],"boosted":[184],"trees.":[186],"numerical":[188],"results":[189],"suggest":[190],"a)":[193],"achieves":[194],"testing":[196,230],"performance":[197],"accuracy":[199],"run-time":[202],"similar":[203],"carefully":[205],"trained":[206],"b)":[210],"also":[212],"much":[213],"faster":[214],"easier":[216],"train":[218],"than":[219],"more":[222],"complicated":[223],"algorithms":[224],"compared.":[225],"Given":[226],"highly":[228],"competitive":[229],"accuracy,":[231],"extremely":[232],"fast":[233],"training":[234],"testing,":[236],"straightforward":[239],"application":[240],"any":[242],"problem":[243],"setting":[244],"without":[245],"algorithm":[249,261],"tuning,":[250],"advocate":[252],"top":[257],"choice":[258]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
