{"id":"https://openalex.org/W7138855729","doi":"https://doi.org/10.48550/arxiv.2603.17418","title":"PowerDAG: Supervisory Agentic AI System for Automating Distribution Grid Analysis","display_name":"PowerDAG: Supervisory Agentic AI System for Automating Distribution Grid Analysis","publication_year":2026,"publication_date":"2026-03-18","ids":{"openalex":"https://openalex.org/W7138855729","doi":"https://doi.org/10.48550/arxiv.2603.17418"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17418","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17418","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2603.17418","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129870302","display_name":"Emmanuel O. Badmus","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Badmus, Emmanuel O.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067002514","display_name":"Amritanshu Pandey","orcid":"https://orcid.org/0000-0002-4431-6889"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pandey, Amritanshu","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/T11986","display_name":"Scientific Computing and Data Management","score":0.388700008392334,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.388700008392334,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.06390000134706497,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.028200000524520874,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/workflow","display_name":"Workflow","score":0.6517000198364258},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5471000075340271},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5465999841690063},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5227000117301941},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.4438000023365021},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.3901999890804291}],"concepts":[{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6517000198364258},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.629800021648407},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5471000075340271},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5465999841690063},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5227000117301941},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.429500013589859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42879998683929443},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.3901999890804291},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37610000371932983},{"id":"https://openalex.org/C163164238","wikidata":"https://www.wikidata.org/wiki/Q2737027","display_name":"Failure rate","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2590000033378601},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17418","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17418","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2603.17418","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17418","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":{"Distribution":[0],"grid":[1,86],"analyses":[2,48],"include":[3],"tasks":[4,21],"such":[5],"as":[6,119],"network":[7],"information":[8],"retrieval,":[9],"power-flow":[10],"analysis,":[11],"hosting-capacity":[12],"assessment,":[13],"DER":[14],"planning,":[15],"and":[16,40,58,88,100,124,136,146,183,237],"state":[17,98],"estimation.":[18],"Completing":[19],"these":[20,47],"often":[22,69],"requires":[23],"long-horizon,":[24],"stateful":[25],"workflows":[26,118],"in":[27,128],"which":[28],"an":[29,84,110,151,170,173],"engineer":[30],"retrieves":[31],"data,":[32],"loads":[33],"a":[34,185,196,218,225],"feeder,":[35],"runs":[36],"simulations,":[37],"evaluates":[38,163],"results,":[39],"exports":[41],"outputs.":[42],"The":[43],"growing":[44],"volume":[45],"of":[46,203,220,228],"is":[49],"outpacing":[50],"the":[51,80,96,157,176,181,204],"limited":[52],"engineering":[53],"workforce,":[54],"causing":[55],"suboptimal":[56],"outcomes":[57],"delays.":[59],"Large":[60],"Language":[61],"Model":[62],"(LLM)-orchestrated":[63],"agents":[64],"can":[65],"help,":[66],"but":[67],"they":[68,75,90],"struggle":[70],"for":[71,83,217],"two":[72,132],"reasons:":[73],"(i)":[74],"lack":[76],"algorithms":[77],"to":[78,246],"determine":[79],"right":[81],"context":[82],"unseen":[85],"task,":[87],"(ii)":[89],"cannot":[91],"verify":[92],"proposed":[93],"actions":[94],"against":[95],"environment":[97],"beforehand":[99],"instead":[101],"rely":[102],"on":[103,191],"feedback":[104],"after":[105],"execution.":[106],"We":[107,188],"propose":[108],"PowerDAG,":[109],"agentic":[111,212],"artificial":[112],"intelligence":[113],"(AI)":[114],"system":[115],"that":[116,155,200],"formalizes":[117],"directed":[120],"acyclic":[121],"graphs":[122],"(DAGs)":[123],"addresses":[125],"current":[126],"gaps":[127],"this":[129],"formalism":[130],"through":[131],"mechanisms,":[133],"adaptive":[134,152],"retrieval":[135],"Just-in-Time":[137],"supervision.":[138],"To":[139],"dynamically":[140],"retrieve":[141],"relevant":[142],"context,":[143],"it":[144,162],"curates":[145],"ranks":[147],"expert":[148],"exemplars":[149],"using":[150],"score-decay":[153],"cutoff":[154],"matches":[156],"query":[158],"complexity.":[159],"For":[160],"supervision,":[161],"prerequisites":[164],"before":[165],"every":[166],"tool":[167],"call.":[168],"If":[169],"agent":[171],"proposes":[172],"invalid":[174],"action,":[175],"supervisor":[177],"blocks":[178],"execution,":[179],"preserves":[180],"environment,":[182],"returns":[184],"corrective":[186],"advisory.":[187],"evaluate":[189],"PowerDAG":[190,223],"150":[192],"held-out":[193],"queries":[194],"from":[195],"200-record":[197],"expert-verified":[198],"benchmark":[199],"covers":[201],"10":[202,215],"most":[205],"commonly":[206],"performed":[207],"distribution-grid":[208],"analyses,":[209],"comparing":[210],"6":[211,245],"systems":[213],"across":[214],"LLMs":[216],"total":[219],"9,000":[221],"runs.":[222],"reaches":[224],"success":[226,242],"rate":[227],"98.0%":[229],"with":[230,233,239],"GPT-5.5,":[231],"97.3%":[232],"Gemini":[234],"3.1":[235],"Pro,":[236],"92.7%":[238],"Qwen3.6-27B,":[240],"improving":[241],"rates":[243],"by":[244],"50":[247],"percentage":[248],"points":[249],"over":[250],"baselines.":[251]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-20T00:00:00"}
