{"id":"https://openalex.org/W7166831741","doi":"https://doi.org/10.48550/arxiv.2606.31314","title":"A Novel Method for Differential-Algebraic Dynamic Model Discovery in Power Systems: An LLM-Based Multi-Agent Collaborative Framework","display_name":"A Novel Method for Differential-Algebraic Dynamic Model Discovery in Power Systems: An LLM-Based Multi-Agent Collaborative Framework","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7166831741","doi":"https://doi.org/10.48550/arxiv.2606.31314"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.31314","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31314","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.31314","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139736198","display_name":"Xinming Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xinming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139730881","display_name":"Fan Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Fan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103657685","display_name":"Wei Yingli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Yingli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121999607","display_name":"Y He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Yakun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139737680","display_name":"Zhe Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139806573","display_name":"Ping Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Ping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113485823","display_name":"H. Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Haoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139718001","display_name":"Zihan Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Zihan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139756069","display_name":"Chao Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.4900999963283539,"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":0.4900999963283539,"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":0.26429998874664307,"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/T10223","display_name":"Microgrid Control and Optimization","score":0.12300000339746475,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5849999785423279},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.49459999799728394},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48980000615119934},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.47450000047683716},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42669999599456787},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4189999997615814},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4156999886035919},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.4090999960899353},{"id":"https://openalex.org/keywords/closure","display_name":"Closure (psychology)","score":0.40540000796318054}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6128000020980835},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5849999785423279},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.49459999799728394},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48980000615119934},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.47450000047683716},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42669999599456787},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4237000048160553},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4189999997615814},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C146834321","wikidata":"https://www.wikidata.org/wiki/Q2979672","display_name":"Closure (psychology)","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3862000107765198},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C178911571","wikidata":"https://www.wikidata.org/wiki/Q593143","display_name":"Power electronics","level":3,"score":0.3246999979019165},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.3244999945163727},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.3190999925136566},{"id":"https://openalex.org/C79610928","wikidata":"https://www.wikidata.org/wiki/Q1656743","display_name":"Parameter identification problem","level":3,"score":0.31290000677108765},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.3125},{"id":"https://openalex.org/C23917780","wikidata":"https://www.wikidata.org/wiki/Q50698","display_name":"Algebraic equation","level":3,"score":0.2985000014305115},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C129537906","wikidata":"https://www.wikidata.org/wiki/Q7603913","display_name":"State variable","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C45872418","wikidata":"https://www.wikidata.org/wiki/Q5318966","display_name":"Dynamic demand","level":3,"score":0.2865999937057495},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2685000002384186},{"id":"https://openalex.org/C78045399","wikidata":"https://www.wikidata.org/wiki/Q11214","display_name":"Differential equation","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25870001316070557}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.31314","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31314","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.31314","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31314","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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"large-scale":[1],"integration":[2],"of":[3,131],"emerging":[4],"power":[5,12,72],"electronic":[6],"devices":[7],"represented":[8],"by":[9,190],"grid-forming":[10,150],"inverters,":[11],"system":[13],"dynamics":[14],"increasingly":[15],"exhibit":[16],"strong":[17],"nonlinearity,":[18],"multi-timescale":[19],"coupling,":[20],"and":[21,35,85,87,108,124,136,149,161,171],"black-box":[22],"control":[23],"logic.":[24],"These":[25],"features":[26],"hinder":[27],"conventional":[28,162],"parameter":[29,83],"identification":[30,37],"requiring":[31],"known":[32],"model":[33,47,69,81],"structures":[34,99],"structure":[36,122],"based":[38],"on":[39,146],"predefined":[40],"function":[41],"libraries,":[42],"making":[43],"complete":[44],"differential-algebraic":[45,67],"dynamic":[46,68],"recovery":[48,130],"difficult":[49],"under":[50],"weak":[51],"prior":[52,142],"information.":[53,143],"To":[54],"address":[55],"this":[56,58],"challenge,":[57],"paper":[59],"proposes":[60],"an":[61],"LLM-based":[62,159],"multi-agent":[63],"collaborative":[64],"framework":[65],"for":[66],"discovery":[70,123,160,186],"in":[71,100,165,182],"systems.":[73],"It":[74],"integrates":[75],"heterogeneous":[76],"exploratory":[77],"agents,":[78],"individual":[79],"candidate":[80,97],"memories,":[82],"fitting":[84],"evaluation,":[86],"a":[88],"coordinator":[89],"agent.":[90],"Under":[91],"unified":[92],"measurement-data":[93],"constraints,":[94,135],"agents":[95],"generate":[96],"equation":[98,121],"parallel,":[101],"while":[102],"candidates":[103],"are":[104],"optimized,":[105],"evaluated,":[106],"retained,":[107],"summarized":[109],"to":[110],"provide":[111],"closed-loop":[112],"search":[113,169],"guidance.":[114],"The":[115],"task":[116],"is":[117,188],"decomposed":[118],"into":[119],"differential":[120],"algebraic":[125,134],"closure":[126],"discovery,":[127],"enabling":[128],"joint":[129],"state":[132],"dynamics,":[133],"key":[137],"intermediate":[138],"variables":[139],"with":[140,193],"incomplete":[141],"Case":[144],"studies":[145],"synchronous":[147],"generators":[148],"inverters":[151],"show":[152],"that":[153],"the":[154,175,183,194],"proposed":[155],"method":[156],"outperforms":[157],"single-agent":[158,195],"symbolic":[163],"regression":[164],"reconstruction":[166],"accuracy,":[167],"generalization,":[168],"efficiency,":[170],"noise":[172],"robustness.":[173],"In":[174],"generator":[176],"case,":[177,185],"OOD":[178],"MAPE":[179],"reaches":[180],"0.19\\%;":[181],"inverter":[184],"time":[187],"reduced":[189],"25.7\\%":[191],"compared":[192],"LLM":[196],"baseline.":[197]},"counts_by_year":[],"updated_date":"2026-07-02T06:18:51.028212","created_date":"2026-07-02T00:00:00"}
