{"id":"https://openalex.org/W4402673474","doi":"https://doi.org/10.1109/tnnls.2024.3437741","title":"A Trustable Data-Driven Optimal Power Flow Computational Method With Robust Generalization Ability","display_name":"A Trustable Data-Driven Optimal Power Flow Computational Method With Robust Generalization Ability","publication_year":2024,"publication_date":"2024-09-20","ids":{"openalex":"https://openalex.org/W4402673474","doi":"https://doi.org/10.1109/tnnls.2024.3437741","pmid":"https://pubmed.ncbi.nlm.nih.gov/39302792"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3437741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3437741","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5029968972","display_name":"Maosheng Gao","orcid":"https://orcid.org/0000-0002-4655-2981"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Maosheng Gao","raw_affiliation_strings":["State Key Laboratory of Power Transmission Equipment Technology, College of Electrical Engineering, Chongqing University, Chongqing, China","College of Electrical Engineering, State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Power Transmission Equipment Technology, College of Electrical Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"College of Electrical Engineering, State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409835","display_name":"Juan Yu","orcid":"https://orcid.org/0000-0001-9724-6960"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Yu","raw_affiliation_strings":["State Key Laboratory of Power Transmission Equipment Technology, College of Electrical Engineering, Chongqing University, Chongqing, China","College of Electrical Engineering, State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Power Transmission Equipment Technology, College of Electrical Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"College of Electrical Engineering, State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012474682","display_name":"Salah Kamel","orcid":"https://orcid.org/0000-0001-9505-5386"},"institutions":[{"id":"https://openalex.org/I86310350","display_name":"Aswan University","ror":"https://ror.org/048qnr849","country_code":"EG","type":"education","lineage":["https://openalex.org/I86310350"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Salah Kamel","raw_affiliation_strings":["Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan, Egypt"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan, Egypt","institution_ids":["https://openalex.org/I86310350"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070021733","display_name":"Zhifang Yang","orcid":"https://orcid.org/0000-0001-6899-8303"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhifang Yang","raw_affiliation_strings":["State Key Laboratory of Power Transmission Equipment Technology, College of Electrical Engineering, Chongqing University, Chongqing, China","College of Electrical Engineering, State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Power Transmission Equipment Technology, College of Electrical Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"College of Electrical Engineering, State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029968972"],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":0.4614,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63409388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"36","issue":"5","first_page":"8049","last_page":"8059"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10454","display_name":"Optimal Power Flow Distribution","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/T10454","display_name":"Optimal Power Flow Distribution","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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9456999897956848,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9028000235557556,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7178364396095276},{"id":"https://openalex.org/keywords/power-flow","display_name":"Power flow","score":0.7077975273132324},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5794803500175476},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.49297523498535156},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4295289218425751},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3451695144176483},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29291144013404846},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.20020437240600586}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7178364396095276},{"id":"https://openalex.org/C2986056383","wikidata":"https://www.wikidata.org/wiki/Q556030","display_name":"Power flow","level":4,"score":0.7077975273132324},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5794803500175476},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.49297523498535156},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4295289218425751},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3451695144176483},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29291144013404846},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.20020437240600586},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3437741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3437741","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:39302792","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39302792","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2828572372","display_name":null,"funder_award_id":"52377076","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6752024351","display_name":null,"funder_award_id":"2021YFE0191000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2616333561","https://openalex.org/W2945771709","https://openalex.org/W2962264188","https://openalex.org/W2962824341","https://openalex.org/W2973782063","https://openalex.org/W2981041116","https://openalex.org/W2984666782","https://openalex.org/W2987146532","https://openalex.org/W2988167007","https://openalex.org/W3004151245","https://openalex.org/W3008258033","https://openalex.org/W3015689570","https://openalex.org/W3034990881","https://openalex.org/W3036286896","https://openalex.org/W3087060148","https://openalex.org/W3088315405","https://openalex.org/W3115185893","https://openalex.org/W3117855720","https://openalex.org/W3169365733","https://openalex.org/W3169670456","https://openalex.org/W3214004626","https://openalex.org/W4200098840","https://openalex.org/W4206512102","https://openalex.org/W4210806007","https://openalex.org/W4226240952","https://openalex.org/W4312074644","https://openalex.org/W4364375123","https://openalex.org/W4378373496","https://openalex.org/W4382601184","https://openalex.org/W4383752690","https://openalex.org/W4384466575","https://openalex.org/W4392806152","https://openalex.org/W6754543342","https://openalex.org/W6790879498","https://openalex.org/W6804343242","https://openalex.org/W6810300553"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W3083152911","https://openalex.org/W3022347918","https://openalex.org/W2118170298"],"abstract_inverted_index":{"Data-driven":[0],"optimal":[1],"power":[2],"flow":[3],"(OPF)":[4],"approach":[5,53,159,224],"has":[6,94],"been":[7],"a":[8],"research":[9],"focus":[10],"in":[11],"recent":[12],"years.":[13],"However,":[14],"the":[15,21,25,48,51,65,69,75,79,83,91,103,109,132,136,147,156,166,175,194,199,215,219,222,234,245],"current":[16],"data-driven":[17,26,52,70,84,137,157,223],"OPF":[18,71,80,92,138,158],"approaches":[19],"face":[20],"following":[22],"difficulties:":[23],"1)":[24],"solutions":[27,49],"may":[28],"have":[29],"large":[30],"deviations":[31],"and":[32,40],"are":[33,99],"not":[34,100],"trustable,":[35],"facing":[36],"out-of-distribution":[37],"(OOD)":[38],"samples":[39,182],"2)":[41],"it":[42],"is":[43,151],"hard":[44],"to":[45,119,130,153,172,188,242],"judge":[46],"whether":[47,155],"of":[50,68,78,105,123,135,177,202,208,221,236,248],"can":[54,127,160,197,225],"be":[55,115,128,184],"trusted.":[56],"To":[57],"handle":[58],"these":[59],"problems,":[60],"this":[61],"article":[62],"first":[63],"improves":[64],"generalization":[66],"ability":[67],"method":[72,144,196],"by":[73,102,205],"embedding":[74],"inherent":[76,121],"pattern":[77],"solution":[81,93],"into":[82],"learning":[85,133],"process.":[86],"As":[87],"an":[88,120,141,206],"optimization":[89],"problem,":[90],"certain":[95],"fixed":[96],"patterns":[97],"that":[98],"influenced":[101],"distribution":[104],"samples.":[106],"For":[107],"example,":[108],"load":[110],"balance":[111],"constraints":[112],"should":[113],"always":[114],"satisfied.":[116],"This":[117],"leads":[118],"requirement":[122],"output":[124],"vectors,":[125],"which":[126],"utilized":[129],"guide":[131],"process":[134],"method.":[139],"Second,":[140],"adaptability":[142,176,216],"judging":[143],"based":[145],"on":[146,191,244],"decoder":[148],"neural":[149,178],"network":[150],"proposed":[152,195],"determine":[154],"produce":[161],"trustable":[162],"solutions.":[163],"By":[164],"measuring":[165],"decoding":[167],"error":[168],"from":[169,240],"latent":[170],"features":[171],"input":[173,181],"features,":[174],"networks":[179],"for":[180,230],"could":[183],"accurately":[185],"judged.":[186],"According":[187],"extensive":[189],"results":[190],"various":[192],"systems,":[193],"improve":[198],"calculation":[200],"accuracy":[201,220,235],"OOD":[203,231,249],"data":[204],"average":[207],"30.19%":[209],"compared":[210],"with":[211],"state-of-the-art":[212],"methods.":[213],"With":[214],"judgment":[217],"method,":[218],"achieve":[226],"higher":[227],"than":[228],"98%":[229],"data,":[232],"whereas":[233],"other":[237],"methods":[238],"ranges":[239],"34.08%":[241],"94.50%":[243],"same":[246],"set":[247],"test":[250],"data.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
