{"id":"https://openalex.org/W7140196243","doi":"https://doi.org/10.1109/tsg.2026.3677277","title":"Physics-Aware Recurrent and Graphical Learning for Robust Distribution System State Estimation Across Unseen Networks","display_name":"Physics-Aware Recurrent and Graphical Learning for Robust Distribution System State Estimation Across Unseen Networks","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7140196243","doi":"https://doi.org/10.1109/tsg.2026.3677277"},"language":"en","primary_location":{"id":"doi:10.1109/tsg.2026.3677277","doi":"https://doi.org/10.1109/tsg.2026.3677277","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2026.3677277","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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 Smart Grid","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7140196243"],"child_works_count":0,"type":"article","is_traditional":true,"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/A5002245809","display_name":"Jun-Hyeok Kim","orcid":"https://orcid.org/0000-0003-2009-4596","observed_orcids":["https://orcid.org/0000-0003-2009-4596","https://orcid.org/0000-0001-5338-8625"]},"institutions":[{"id":"https://openalex.org/I4405270225","display_name":"SK Innovation (South Korea)","ror":"https://ror.org/009cyjs32","country_code":"KR","type":"company","lineage":["https://openalex.org/I4405270225"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jun-Hyeok Kim","raw_affiliation_strings":["Environmental Science and Technology, SK Innovation"],"raw_orcid":"https://orcid.org/0000-0001-5338-8625","affiliations":[{"raw_affiliation_string":"Environmental Science and Technology, SK Innovation","institution_ids":["https://openalex.org/I4405270225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091011409","display_name":"Jeuk Kang","orcid":"https://orcid.org/0000-0001-7482-6225","observed_orcids":["https://orcid.org/0000-0001-7482-6225"]},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeuk Kang","raw_affiliation_strings":["Gwangju Institute of Science and Technology"],"raw_orcid":"https://orcid.org/0000-0001-7482-6225","affiliations":[{"raw_affiliation_string":"Gwangju Institute of Science and Technology","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088743006","display_name":"Keon Baek","orcid":"https://orcid.org/0000-0002-4006-8152","observed_orcids":["https://orcid.org/0000-0002-4006-8152"]},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Keon Baek","raw_affiliation_strings":["Chosun University"],"raw_orcid":"https://orcid.org/0000-0002-4006-8152","affiliations":[{"raw_affiliation_string":"Chosun University","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075681374","display_name":"Yun-Su Kim","orcid":"https://orcid.org/0000-0002-6803-929X","observed_orcids":["https://orcid.org/0000-0002-6803-929X"]},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yun-Su Kim","raw_affiliation_strings":["Gwangju Institute of Science and Technology"],"raw_orcid":"https://orcid.org/0000-0002-6803-929X","affiliations":[{"raw_affiliation_string":"Gwangju Institute of Science and Technology","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":1.3169,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73676692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"17","issue":"5","first_page":"4334","last_page":"4346"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10305","display_name":"Power System Optimization and Stability","score":0.9663000106811523,"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/T10305","display_name":"Power System Optimization and Stability","score":0.9663000106811523,"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":0.021800000220537186,"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/T12451","display_name":"Smart Grid and Power Systems","score":0.008100000210106373,"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/distribution-system-state-estimation","display_name":"distribution system state estimation","score":1.0},{"id":"https://openalex.org/keywords/graph-neural-networks","display_name":"graph neural networks","score":0.9760000109672546},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.9710000157356262},{"id":"https://openalex.org/keywords/transferability","display_name":"transferability","score":0.7950000166893005},{"id":"https://openalex.org/keywords/robustness","display_name":"robustness","score":0.6859999895095825},{"id":"https://openalex.org/keywords/feature-aggregation","display_name":"feature aggregation","score":0.6930000185966492},{"id":"https://openalex.org/keywords/power-distribution-networks","display_name":"power distribution networks","score":0.4050000011920929}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.775600016117096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6898999810218811},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6358000040054321},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5516999959945679},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5504000186920166},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.5378999710083008},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.527899980545044},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5019999742507935},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42500001192092896},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42260000109672546},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.3693000078201294},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.29750001430511475},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsg.2026.3677277","doi":"https://doi.org/10.1109/tsg.2026.3677277","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2026.3677277","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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 Smart Grid","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.8970999717712402},{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.75}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335199","display_name":"Korea Institute of Energy Technology Evaluation and Planning","ror":"https://ror.org/02zq38y32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2009722970","https://openalex.org/W2045490871","https://openalex.org/W2081920865","https://openalex.org/W2085752380","https://openalex.org/W2090135854","https://openalex.org/W2093882311","https://openalex.org/W2121239749","https://openalex.org/W2154910132","https://openalex.org/W2166569007","https://openalex.org/W2296521892","https://openalex.org/W2527136714","https://openalex.org/W2559962737","https://openalex.org/W2592050215","https://openalex.org/W2773727643","https://openalex.org/W2903638091","https://openalex.org/W2912636151","https://openalex.org/W2925104992","https://openalex.org/W2926729814","https://openalex.org/W2951063491","https://openalex.org/W2963213142","https://openalex.org/W2963590654","https://openalex.org/W2980210142","https://openalex.org/W3133637983","https://openalex.org/W3173732237","https://openalex.org/W3209161810","https://openalex.org/W4220699563","https://openalex.org/W4281625496","https://openalex.org/W4294691187","https://openalex.org/W4313410357","https://openalex.org/W4321608455","https://openalex.org/W4379116801","https://openalex.org/W4382468303","https://openalex.org/W4386766750","https://openalex.org/W4390630915","https://openalex.org/W4394585908","https://openalex.org/W4396766224","https://openalex.org/W4396910066","https://openalex.org/W4401748719","https://openalex.org/W4404183004","https://openalex.org/W4417439024"],"related_works":["https://openalex.org/W4417331732","https://openalex.org/W4410734664","https://openalex.org/W4394585908","https://openalex.org/W4382468303","https://openalex.org/W4379116801","https://openalex.org/W4414547931","https://openalex.org/W4406276018","https://openalex.org/W7162469125","https://openalex.org/W7165131006","https://openalex.org/W4390535957"],"abstract_inverted_index":{"Robust":[0],"distribution":[1,138],"system":[2],"state":[3,192],"estimation":[4,193],"(DSSE)":[5],"is":[6,131],"increasingly":[7],"vital":[8],"in":[9,63,160,195],"modern,":[10],"complex":[11],"networks.":[12,165],"However,":[13,57],"conventional":[14],"optimization-based":[15],"DSSE":[16,31,55,65,90],"approaches":[17],"often":[18],"face":[19],"challenges":[20,62],"with":[21,101],"real-time":[22],"complexity.":[23],"Consequently,":[24],"recent":[25],"advancements":[26],"have":[27,49],"introduced":[28],"learning-based,":[29],"physics-aware":[30,89],"methods":[32,149],"that":[33],"leverage":[34],"network":[35,98,123],"structural":[36],"information":[37],"to":[38,68,147],"enhance":[39],"model":[40,114],"effectiveness.":[41],"Among":[42],"these":[43],"methods,":[44],"graph":[45],"neural":[46,97],"networks":[47],"(GNNs)":[48],"gained":[50],"prominence":[51],"as":[52],"an":[53,151],"effective":[54],"solution.":[56],"GNN-based":[58],"models":[59],"encounter":[60],"significant":[61],"practical":[64],"applications,":[66],"due":[67],"their":[69],"reliance":[70],"on":[71,136],"aggregating":[72],"and":[73,99,111,118,156,168,176],"propagating":[74],"features":[75],"only":[76],"from":[77],"adjacent":[78],"nodes.":[79],"To":[80],"address":[81],"this":[82,84],"limitation,":[83],"paper":[85],"presents":[86],"a":[87,94,185],"novel":[88],"framework.":[91,181],"It":[92],"integrates":[93],"structure-aware":[95],"recurrent":[96],"GNN":[100],"convolutional":[102],"autoregressive":[103],"moving":[104],"average":[105,152],"layers":[106],"for":[107,188],"improved":[108],"feature":[109],"aggregation":[110],"propagation.":[112],"This":[113],"significantly":[115],"enhances":[116],"robustness":[117,175],"transferability":[119],"across":[120],"diverse":[121],"unseen":[122,164],"topologies.":[124],"The":[125,140,182],"scalability":[126],"of":[127,153,178],"the":[128,174,179],"proposed":[129,141,180],"framework":[130,183],"demonstrated":[132],"through":[133],"extensive":[134],"testing":[135],"real":[137],"systems.":[139],"method":[142],"demonstrates":[143],"superior":[144],"performance":[145],"compared":[146],"existing":[148],"by":[150],"0.625%":[154],"MAPE":[155],"0.0093":[157],"rad.":[158],"MAE":[159],"normal":[161],"scenario":[162],"under":[163],"Additional":[166],"ablation":[167],"measurement":[169],"availability":[170],"studies":[171],"further":[172],"verify":[173],"effectiveness":[177],"offers":[184],"pragmatic":[186],"solution":[187],"DSSE,":[189],"ensuring":[190],"precise":[191],"even":[194],"challenging":[196],"environments.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-01T11:40:01.658920","created_date":"2026-03-25T00:00:00"}
