{"id":"https://openalex.org/W4206391753","doi":"https://doi.org/10.1109/jetcas.2022.3142051","title":"Data-Driven Priors for Robust PSSE via Gauss-Newton Unrolled Neural Networks","display_name":"Data-Driven Priors for Robust PSSE via Gauss-Newton Unrolled Neural Networks","publication_year":2022,"publication_date":"2022-01-11","ids":{"openalex":"https://openalex.org/W4206391753","doi":"https://doi.org/10.1109/jetcas.2022.3142051"},"language":"en","primary_location":{"id":"doi:10.1109/jetcas.2022.3142051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jetcas.2022.3142051","pdf_url":null,"source":{"id":"https://openalex.org/S142323794","display_name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","issn_l":"2156-3357","issn":["2156-3357","2156-3365"],"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 Journal on Emerging and Selected Topics in Circuits and Systems","raw_type":"journal-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":"https://openalex.org/A5015683686","display_name":"Qiuling Yang","orcid":"https://orcid.org/0000-0001-7789-6552"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]},{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CA","CN"],"is_corresponding":true,"raw_author_name":"Qiuling Yang","raw_affiliation_strings":["State Key Laboratory of Intelligent Control and Decision of Complex Systems and the School of Automation, Beijing Institute of Technology, Beijing, China","Department of Mechanical Engineering, Donadeo Innovation Centre for Engineering, University of Alberta, Edmonton, AB, Canada"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Control and Decision of Complex Systems and the School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Donadeo Innovation Centre for Engineering, University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101510493","display_name":"Alireza Sadeghi","orcid":"https://orcid.org/0000-0003-1280-7592"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alireza Sadeghi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100367403","display_name":"Gang Wang","orcid":"https://orcid.org/0000-0002-7266-2412"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Wang","raw_affiliation_strings":["State Key Laboratory of Intelligent Control and Decision of Complex Systems and the School of Automation, Beijing Institute of Technology, Beijing, China","Beijing Institute of Technology Chongqing Innovation Center, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Control and Decision of Complex Systems and the School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology Chongqing Innovation Center, Chongqing, China","institution_ids":["https://openalex.org/I50632499","https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015683686"],"corresponding_institution_ids":["https://openalex.org/I125839683","https://openalex.org/I154425047"],"apc_list":null,"apc_paid":null,"fwci":1.687,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.82648669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"12","issue":"1","first_page":"172","last_page":"181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10876","display_name":"Fault Detection and Control Systems","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9890000224113464,"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/prior-probability","display_name":"Prior probability","score":0.6877553462982178},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5570983290672302},{"id":"https://openalex.org/keywords/gauss","display_name":"Gauss","score":0.515007734298706},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46914687752723694},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43231403827667236},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.34977608919143677},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3312695324420929},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29626280069351196},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2693721652030945},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.210148423910141},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.07816651463508606}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6877553462982178},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5570983290672302},{"id":"https://openalex.org/C161794534","wikidata":"https://www.wikidata.org/wiki/Q177493","display_name":"Gauss","level":2,"score":0.515007734298706},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46914687752723694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43231403827667236},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.34977608919143677},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3312695324420929},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29626280069351196},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2693721652030945},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.210148423910141},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.07816651463508606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jetcas.2022.3142051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jetcas.2022.3142051","pdf_url":null,"source":{"id":"https://openalex.org/S142323794","display_name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","issn_l":"2156-3357","issn":["2156-3357","2156-3365"],"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 Journal on Emerging and Selected Topics in Circuits and Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8799999952316284,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2059183635","display_name":null,"funder_award_id":"61925303","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2575069074","display_name":null,"funder_award_id":"62088101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2923177588","display_name":null,"funder_award_id":"62173034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4574445286","display_name":null,"funder_award_id":"2021YFB1714800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6968088389","display_name":null,"funder_award_id":"61720106011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7192999862","display_name":null,"funder_award_id":"U20B2073","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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":47,"referenced_works":["https://openalex.org/W385466589","https://openalex.org/W1522301498","https://openalex.org/W1570089119","https://openalex.org/W1979418981","https://openalex.org/W2045490871","https://openalex.org/W2048028546","https://openalex.org/W2070678378","https://openalex.org/W2081770709","https://openalex.org/W2103559027","https://openalex.org/W2106424475","https://openalex.org/W2114610379","https://openalex.org/W2146502635","https://openalex.org/W2312656909","https://openalex.org/W2583497101","https://openalex.org/W2616591171","https://openalex.org/W2739010045","https://openalex.org/W2773850766","https://openalex.org/W2789184469","https://openalex.org/W2793242787","https://openalex.org/W2885208219","https://openalex.org/W2900620189","https://openalex.org/W2914811233","https://openalex.org/W2950936580","https://openalex.org/W2963213142","https://openalex.org/W2963542245","https://openalex.org/W2964015378","https://openalex.org/W2980514433","https://openalex.org/W2980968713","https://openalex.org/W2991859550","https://openalex.org/W3016115436","https://openalex.org/W3020265068","https://openalex.org/W3100730608","https://openalex.org/W3115750094","https://openalex.org/W3124187518","https://openalex.org/W3165331239","https://openalex.org/W3188891218","https://openalex.org/W3195665885","https://openalex.org/W3203784605","https://openalex.org/W3209083247","https://openalex.org/W3212277304","https://openalex.org/W3214004626","https://openalex.org/W4254313632","https://openalex.org/W4299356147","https://openalex.org/W6631190155","https://openalex.org/W6681435938","https://openalex.org/W6726873649","https://openalex.org/W6745454490"],"related_works":["https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W2580650124","https://openalex.org/W3122088529","https://openalex.org/W3041320102","https://openalex.org/W2111669074","https://openalex.org/W2085259108","https://openalex.org/W3123087812","https://openalex.org/W2071416974"],"abstract_inverted_index":{"Renewable":[0],"energy":[1],"sources,":[2],"elastic":[3],"loads,":[4],"and":[5,14,25,32,54,71,196],"purposeful":[6],"manipulation":[7],"of":[8,16,33,41,199],"meter":[9],"readings":[10],"challenge":[11],"the":[12,42,60,81,110,136,149,164,187,193,200],"monitoring":[13],"control":[15],"today\u2019s":[17],"power":[18,150],"systems":[19],"(PS).":[20],"In":[21],"this":[22],"context,":[23],"fast":[24],"robust":[26],"state":[27],"estimation":[28,195],"(SE)":[29],"is":[30,120,131,177],"timely":[31],"major":[34],"importance":[35],"to":[36,69,74,90],"maintaining":[37],"a":[38,52,93,98,103,115,127,154],"comprehensive":[39],"view":[40],"system":[43,191],"in":[44],"real-time.":[45],"Conventional":[46],"PSSE":[47,95,113,143],"solvers":[48,65],"typically":[49],"entail":[50],"minimizing":[51],"nonlinear":[53],"nonconvex":[55],"least-squares":[56],"cost":[57],"using":[58,182],"e.g.,":[59],"Gauss-Newton":[61],"method.":[62],"Those":[63],"iterative":[64],"however,":[66],"are":[67],"sensitive":[68],"initialization":[70],"may":[72],"converge":[73],"local":[75],"minima.":[76],"To":[77,123,161],"overcome":[78],"these":[79],"hurdles,":[80],"present":[82],"paper":[83],"draws":[84],"recent":[85],"advances":[86],"on":[87,186],"image":[88],"denoising":[89],"put":[91,178],"forth":[92],"novel":[94,128],"formulation":[96],"with":[97,167,204],"data-driven":[99],"regularization":[100],"term":[101],"capturing":[102],"deep":[104,142],"neural":[105,156],"network":[106,151,157],"(DNN)":[107],"prior.":[108,160],"For":[109],"resultant":[111],"regularized":[112],"objective,":[114],"\u201cGauss-Newton-type\u201d":[116],"alternating":[117,138],"minimization":[118,139],"solver":[119],"developed":[121],"first.":[122],"accommodate":[124],"real-time":[125],"monitoring,":[126],"end-to-end":[129],"DNN":[130,166,174],"constructed":[132],"subsequently":[133],"by":[134],"unrolling":[135],"proposed":[137,201],"solver.":[140],"The":[141],"architecture":[144],"can":[145],"further":[146,162],"account":[147],"for":[148],"topology":[152],"through":[153],"graph":[155],"(GNN)":[158],"based":[159],"endow":[163],"physics-based":[165],"robustness":[168,197],"against":[169],"bad":[170],"data,":[171],"an":[172],"adversarial":[173],"training":[175],"method":[176],"forth.":[179],"Numerical":[180],"tests":[181],"real":[183],"load":[184],"data":[185],"IEEE":[188],"118-bus":[189],"benchmark":[190],"showcase":[192],"improved":[194],"performance":[198],"scheme":[202],"compared":[203],"several":[205],"state-of-the-art":[206],"alternatives.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}