{"id":"https://openalex.org/W6884704420","doi":"https://doi.org/10.1184/r1/21357516.v1","title":"Bridging Deep Learning and Electric Power Systems","display_name":"Bridging Deep Learning and Electric Power Systems","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W6884704420","doi":"https://doi.org/10.1184/r1/21357516.v1"},"language":"en","primary_location":{"id":"pmh:oai:figshare.com:article/21357516","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Donti, Priya","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Donti, Priya","raw_affiliation_strings":["Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16824573,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.12559999525547028,"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":0.12559999525547028,"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":0.12039999663829803,"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/T10454","display_name":"Optimal Power Flow Distribution","score":0.08500000089406967,"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/deep-learning","display_name":"Deep learning","score":0.7192999720573425},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6590999960899353},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.5522000193595886},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4684000015258789},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.427700012922287},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4131999909877777},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.39879998564720154},{"id":"https://openalex.org/keywords/electric-power","display_name":"Electric power","score":0.3734999895095825}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7192999720573425},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6590999960899353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6460000276565552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5795999765396118},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.5522000193595886},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4684000015258789},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.427700012922287},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42160001397132874},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4131999909877777},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.39879998564720154},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3808000087738037},{"id":"https://openalex.org/C40293303","wikidata":"https://www.wikidata.org/wiki/Q27137","display_name":"Electric power","level":3,"score":0.3734999895095825},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3714999854564667},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C2777826224","wikidata":"https://www.wikidata.org/wiki/Q5250404","display_name":"Deep integration","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27869999408721924},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C423512","wikidata":"https://www.wikidata.org/wiki/Q383973","display_name":"Electricity generation","level":3,"score":0.263700008392334},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:figshare.com:article/21357516","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.1184/r1/21357516.v1","is_oa":true,"landing_page_url":"https://doi.org/10.1184/r1/21357516.v1","pdf_url":null,"source":{"id":"https://openalex.org/S7407050927","display_name":"KiltHub Repository","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/21357516","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.87245112657547}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Climate":[0],"change":[1,42],"is":[2],"one":[3,30],"of":[4,9,16,57,80,135,149,157,186,199,293,420],"the":[5,13,34,52,72,77,102,133,146,155,164,173,184,200,235,243,290,321,334],"most":[6],"pressing":[7],"issues":[8],"our":[10],"time,":[11],"requiring":[12],"rapid":[14],"mobilization":[15],"many":[17],"tools":[18,99],"and":[19,38,55,86,104,168,271,346,373,402],"approaches":[20,88],"from":[21,142,302,343,399],"across":[22],"society.":[23],"Machine":[24],"learning":[25,159,191,287,304,350,401],"has":[26],"been":[27,382],"proposed":[28],"as":[29,226,228,261,263],"such":[31],"tool,":[32],"with":[33,223,242],"potential":[35],"to":[36,67,89,100,112,131,172,192,255,328,354,359,388,416,422],"supplement":[37],"strengthen":[39],"existing":[40],"climate":[41,423],"efforts.":[43],"In":[44,76,180],"this":[45,81,143,150,294,393],"thesis,":[46,82,151,295],"we":[47,83,97,152,182,296,315],"provide":[48,355],"several":[49],"directions":[50,284,308],"for":[51,124,205,220,268,285,309],"principled":[53],"design":[54,156,193,215],"use":[56],"machine-learning-based":[58],"methods":[59,160,195,251,318,410],"(with":[60],"a":[61,120,207],"particular":[62],"focus":[63,153],"on":[64,93,127,154,333],"deep":[65,158,190,229,286,303,349,400],"learning)":[66],"address":[68],"climate-relevant":[69],"problems":[70,222,256,332,362,419],"in":[71,145,175,189,245,257,289,311,363,411,414],"electric":[73,258,403],"power":[74,94,114,128,259,279,312,335,364,371,376,404],"sector.":[75],"first":[78],"part":[79,148,275,292],"present":[84],"statistical":[85],"optimization-based":[87],"estimate":[90],"critical":[91],"quantities":[92],"grids.":[95],"Specifically,":[96,314],"employregression-based":[98],"assess":[101,329],"climate-":[103],"health":[105],"related":[106],"emissions":[107],"factors":[108],"that":[109,161,196,232,379],"are":[110,178,197,248,252],"used":[111,327],"evaluate":[113],"system":[115],"interventions.":[116],"We":[117,213,337],"also":[118],"propose":[119],"matrix":[121],"completion-based":[122],"method":[123],"estimating":[125],"voltages":[126],"distribution":[129],"systems,":[130,260],"enable":[132],"integration":[134],"distributed":[136],"solar":[137],"power.":[138],"Motivated":[139],"by":[140,320],"insights":[141,301,342,398],"work,":[144],"second":[147],"explicitly":[162],"capture":[163],"physics,":[165],"hard":[166,224],"constraints,":[167,225],"domain":[169],"knowledge":[170],"relevant":[171,267],"settings":[174],"which":[176,206,246],"they":[177,247],"employed.":[179],"particular,":[181],"leverage":[183],"toolkit":[185],"implicit":[187,322,344],"layers":[188,323,345],"forecasting":[194],"cognizant":[198],"downstream":[201],"(stochastic)":[202],"decision-making":[203],"processes":[204],"model\u2019s":[208],"outputs":[209],"will":[210],"be":[211,326],"used.":[212],"additionally":[214],"fast,":[216],"feasibility-preserving":[217],"neural":[218],"approximators":[219],"optimization":[221],"well":[227,262],"learning-based":[230],"controllers":[231],"provably":[233],"enforce":[234],"stability":[236],"criteria":[237],"or":[238],"operational":[239],"constraints":[240],"associated":[241],"systems":[244,280,365,405],"deployed.":[249],"These":[250],"directly":[253],"applicable":[254],"being":[264],"more":[265],"broadly":[266],"other":[269],"physical":[270],"safety-critical":[272],"domains.":[273],"While":[274],"two":[276,360],"demonstrates":[277,395],"how":[278,300,317,340,396],"can":[281,305,325,351,406],"yield":[282,306],"fruitful":[283,307],"research,":[288],"last":[291],"demonstrate":[297],"vice":[298],"versa":[299],"research":[310],"systems.":[313],"show":[316,339],"inspired":[319],"literature":[324],"policy-relevant":[330],"inverse":[331],"grid.":[336],"further":[338],"combining":[341],"adversarially":[347],"robust":[348],"allow":[352],"us":[353],"scalable":[356],"heuristic":[357],"solutions":[358],"central":[361],"\u2013":[366,378],"N-k":[367],"security":[368],"constrained":[369],"optimal":[370,375],"flow":[372,377],"stochastic":[374],"have":[380],"seldom":[381],"addressed":[383],"at":[384],"realistic":[385],"scale":[386],"due":[387],"their":[389],"computational":[390],"intractability.":[391],"Overall,":[392],"thesis":[394],"bridging":[397],"help":[407],"significantly":[408],"advance":[409],"both":[412],"fields,":[413],"addition":[415],"addressing":[417],"high-impact":[418],"relevance":[421],"action.":[424]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}