{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T19:18:21Z","timestamp":1768072701142,"version":"3.49.0"},"reference-count":27,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,4,24]],"date-time":"2022-04-24T00:00:00Z","timestamp":1650758400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,4,24]],"date-time":"2022-04-24T00:00:00Z","timestamp":1650758400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006233","name":"National Renewable Energy Laboratory","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006233","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000015","name":"U.S. Department of Energy","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006132","name":"Office of Science","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006132","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006210","name":"Workforce Development for Teachers and Scientists","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006210","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,4,24]]},"DOI":"10.1109\/isgt50606.2022.9817509","type":"proceedings-article","created":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T19:36:17Z","timestamp":1657654577000},"page":"1-5","source":"Crossref","is-referenced-by-count":14,"title":["OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets"],"prefix":"10.1109","author":[{"given":"Trager","family":"Joswig-Jones","sequence":"first","affiliation":[{"name":"University of Washington,Seattle,WA,USA"}]},{"given":"Kyri","family":"Baker","sequence":"additional","affiliation":[{"name":"University of Colorado Boulder,Boulder,CO,USA"}]},{"given":"Ahmed S.","family":"Zamzam","sequence":"additional","affiliation":[{"name":"National Renewable Energy Laboratory,Golden,CO,USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2011.2160974"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2016.02.008"},{"key":"ref3","article-title":"History of optimal power flow and formulations optimal power flow","author":"Cain","year":"2012","journal-title":"FERC Technical Report"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/HICSS.2004.1265164"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/tpwrs.2021.3127189"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/tpwrs.2021.3114092"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5403"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP.2019.8918690"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/SC41405.2020.00067"},{"key":"ref10","article-title":"Learning an optimally reduced formulation of opf through meta-optimization","author":"Robson","year":"2019"},{"key":"ref11","article-title":"High-fidelity machine learning approximations of large-scale optimal power flow","author":"Chatzos","year":"2020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SmartGridComm47815.2020.9303008"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2021.106908"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/PESGM41954.2020.9281941"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2015.2407363"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2006.879234"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2015.2463111"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1287\/opre.46.1.84"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s00209-011-0924-5"},{"key":"ref20","article-title":"Uniform distribution over a convex polytope (v1.2.0.0)","author":"Benham"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2020.106614"},{"key":"ref22","article-title":"The power grid library for benchmarking AC optimal power flow algorithms","author":"Babaeinejadsarookolaee","year":"2021"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.23919\/PSCC.2018.8442948"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-004-0559-y"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1137\/15M1020575"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2007.12.003"},{"key":"ref27","article-title":"TensorFlow: Large-scale machine learning on heterogeneous systems","author":"Abadi","year":"2015"}],"event":{"name":"2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","location":"New Orleans, LA, USA","start":{"date-parts":[[2022,4,24]]},"end":{"date-parts":[[2022,4,28]]}},"container-title":["2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9817414\/9817460\/09817509.pdf?arnumber=9817509","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,28]],"date-time":"2024-09-28T05:26:04Z","timestamp":1727501164000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9817509\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,24]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/isgt50606.2022.9817509","relation":{},"subject":[],"published":{"date-parts":[[2022,4,24]]}}}