{"id":"https://openalex.org/W4417068121","doi":"https://doi.org/10.48550/arxiv.2503.22721","title":"PowerGNN: A Topology-Aware Graph Neural Network for Electricity Grids","display_name":"PowerGNN: A Topology-Aware Graph Neural Network for Electricity Grids","publication_year":2025,"publication_date":"2025-03-26","ids":{"openalex":"https://openalex.org/W4417068121","doi":"https://doi.org/10.48550/arxiv.2503.22721"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2503.22721","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.22721","pdf_url":"https://arxiv.org/pdf/2503.22721","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2503.22721","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002262953","display_name":"Dhruv Suri","orcid":"https://orcid.org/0000-0003-4839-7644"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Suri, Dhruv","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5120691952","display_name":"Mohak Mangal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mangal, Mohak","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/T11052","display_name":"Energy Load and Power Forecasting","score":0.3799999952316284,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.3799999952316284,"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/T12804","display_name":"Thermal Analysis in Power Transmission","score":0.15839999914169312,"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/T10305","display_name":"Power System Optimization and Stability","score":0.11860000342130661,"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/scalability","display_name":"Scalability","score":0.5848000049591064},{"id":"https://openalex.org/keywords/renewable-energy","display_name":"Renewable energy","score":0.5532000064849854},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.5403000116348267},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.534600019454956},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4909999966621399},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4578999876976013},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45399999618530273},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.39739999175071716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6029000282287598},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5848000049591064},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.5532000064849854},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.5403000116348267},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.534600019454956},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4909999966621399},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4578999876976013},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C140311924","wikidata":"https://www.wikidata.org/wiki/Q200928","display_name":"Electric power transmission","level":2,"score":0.383899986743927},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35019999742507935},{"id":"https://openalex.org/C423512","wikidata":"https://www.wikidata.org/wiki/Q383973","display_name":"Electricity generation","level":3,"score":0.3224000036716461},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.31349998712539673},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30300000309944153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2955000102519989},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.274399995803833},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C2983254600","wikidata":"https://www.wikidata.org/wiki/Q1096907","display_name":"Power grid","level":3,"score":0.2549999952316284},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2547999918460846},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2503.22721","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.22721","pdf_url":"https://arxiv.org/pdf/2503.22721","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2503.22721","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2503.22721","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2503.22721","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.22721","pdf_url":"https://arxiv.org/pdf/2503.22721","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,108,154],"increasing":[1],"penetration":[2],"of":[3,70,159,182],"renewable":[4,62,124,198],"energy":[5],"sources":[6],"introduces":[7],"significant":[8],"variability":[9],"and":[10,76,81,83,102,112,144,167,174,188],"uncertainty":[11],"in":[12,105,151,193],"modern":[13],"power":[14,31,57,72,190],"systems,":[15],"making":[16],"accurate":[17],"state":[18],"prediction":[19],"critical":[20],"for":[21,55,186],"reliable":[22],"grid":[23],"operation.":[24],"Conventional":[25],"forecasting":[26,192],"methods":[27],"often":[28],"neglect":[29],"the":[30,71,115,131,180],"grid's":[32],"inherent":[33],"topology,":[34],"limiting":[35],"their":[36],"ability":[37],"to":[38,98,161],"capture":[39],"complex":[40],"spatio":[41],"temporal":[42,103],"dependencies.":[43],"This":[44],"paper":[45],"proposes":[46],"a":[47,66,85],"topology":[48,183],"aware":[49,184],"Graph":[50],"Neural":[51],"Network":[52],"(GNN)":[53],"framework":[54],"predicting":[56],"system":[58,106,119,191],"states":[59],"under":[60],"high":[61,197],"integration.":[63],"We":[64],"construct":[65],"graph":[67],"based":[68],"representation":[69],"network,":[73],"modeling":[74],"buses":[75],"transmission":[77],"lines":[78],"as":[79],"nodes":[80],"edges,":[82],"introduce":[84],"specialized":[86],"GNN":[87,133,155],"architecture":[88],"that":[89,130],"integrates":[90],"GraphSAGE":[91],"convolutions":[92],"with":[93,196],"Gated":[94],"Recurrent":[95],"Units":[96],"(GRUs)":[97],"model":[99,109],"both":[100],"spatial":[101,172],"correlations":[104],"dynamics.":[107],"is":[110],"trained":[111],"evaluated":[113],"on":[114],"NREL":[116],"118":[117],"test":[118],"using":[120],"realistic,":[121],"time":[122],"synchronous":[123],"generation":[125],"profiles.":[126],"Our":[127],"results":[128,178],"show":[129],"proposed":[132],"outperforms":[134],"baseline":[135],"approaches":[136],"including":[137],"fully":[138],"connected":[139],"neural":[140],"networks,":[141],"linear":[142],"regression,":[143],"rolling":[145],"mean":[146],"models,":[147],"achieving":[148],"substantial":[149],"improvements":[150],"predictive":[152],"accuracy.":[153],"achieves":[156],"average":[157],"RMSEs":[158],"0.13":[160],"0.17":[162],"across":[163,171],"all":[164],"predicted":[165],"variables":[166],"demonstrates":[168],"consistent":[169],"performance":[170],"locations":[173],"operational":[175],"conditions.":[176],"These":[177],"highlight":[179],"potential":[181],"learning":[185],"scalable":[187],"robust":[189],"future":[194],"grids":[195],"penetration.":[199]},"counts_by_year":[],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}