{"id":"https://openalex.org/W7160597736","doi":"https://doi.org/10.48550/arxiv.2605.06442","title":"Probabilistic Assessment of Rare Transient Instability Events via Kriging-based Active Learning Framework","display_name":"Probabilistic Assessment of Rare Transient Instability Events via Kriging-based Active Learning Framework","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160597736","doi":"https://doi.org/10.48550/arxiv.2605.06442"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.06442","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06442","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.06442","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135699505","display_name":"Jingyu Liu","orcid":"https://orcid.org/0009-0007-4596-577X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135674986","display_name":"Xiaoting Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiaoting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135727943","display_name":"Xiaozhe Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiaozhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T10305","display_name":"Power System Optimization and Stability","score":0.9426000118255615,"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":0.9426000118255615,"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":0.012900000438094139,"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":0.006200000178068876,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7103999853134155},{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.6456999778747559},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.5425000190734863},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.512499988079071},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.5095000267028809},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4918000102043152},{"id":"https://openalex.org/keywords/instability","display_name":"Instability","score":0.4514999985694885}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7103999853134155},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.6456999778747559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5465999841690063},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.5425000190734863},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.512499988079071},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.5095000267028809},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4918000102043152},{"id":"https://openalex.org/C207821765","wikidata":"https://www.wikidata.org/wiki/Q405372","display_name":"Instability","level":2,"score":0.4514999985694885},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.34860000014305115},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.33869999647140503},{"id":"https://openalex.org/C60782215","wikidata":"https://www.wikidata.org/wiki/Q3333679","display_name":"Probabilistic method","level":3,"score":0.32499998807907104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.314300000667572},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28780001401901245},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.2757999897003174},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.2750000059604645},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C2777317252","wikidata":"https://www.wikidata.org/wiki/Q18393516","display_name":"Rare events","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.06442","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06442","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.06442","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06442","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"},"sustainable_development_goals":[{"score":0.8400819301605225,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,99],"increasing":[1],"uncertainty":[2,80],"in":[3,52],"modern":[4],"power":[5],"systems,":[6],"driven":[7],"by":[8],"the":[9,19,63,78,84,134,147],"integration":[10],"of":[11,95],"intermittent":[12],"energy":[13],"sources":[14],"and":[15,37,82,116,119,127,141,154],"variable":[16],"loads,":[17],"underscores":[18],"need":[20],"for":[21,56],"probabilistic":[22],"transient":[23,48],"stability":[24,35],"assessment.":[25],"However,":[26],"existing":[27,135],"assessment":[28],"methods":[29,144],"primarily":[30],"focus":[31],"on":[32,107],"average":[33],"system":[34,58,112,123],"behavior":[36],"may":[38],"struggle":[39],"or":[40],"incur":[41],"high":[42],"computational":[43,155],"cost":[44],"when":[45],"identifying":[46],"rare":[47,74],"instability":[49,75,87],"events,":[50],"which":[51],"turn":[53],"are":[54],"critical":[55],"ensuring":[57],"resilience.":[59],"To":[60],"address":[61],"this,":[62],"paper":[64],"proposes":[65],"a":[66,92,108,120],"Kriging-based":[67],"active":[68,101,138],"learning":[69,102,139],"framework":[70,104,150],"to":[71],"accurately":[72],"characterize":[73],"regions":[76],"within":[77],"input":[79],"space":[81],"estimate":[83],"associated":[85],"small":[86],"probability,":[88],"while":[89],"requiring":[90],"only":[91],"limited":[93],"number":[94],"expensive":[96],"time-domain":[97],"simulations.":[98],"proposed":[100,148],"(AL)":[103],"is":[105],"tested":[106],"modified":[109],"IEEE":[110],"59-bus":[111],"with":[113,133],"simulated":[114],"load":[115],"wind":[117,126],"uncertainties,":[118],"WECC":[121],"240-bus":[122],"incorporating":[124],"real-world":[125],"solar":[128],"generation":[129],"data.":[130],"Comparative":[131],"studies":[132],"random":[136],"forest-based":[137],"method":[140],"three":[142],"non-AL":[143],"demonstrate":[145],"that":[146],"AL":[149],"achieves":[151],"superior":[152],"accuracy":[153],"efficiency.":[156]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-09T00:00:00"}
