{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T17:46:19Z","timestamp":1778694379946,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T00:00:00Z","timestamp":1717113600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100006374","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["ALLRP 549804-19"],"award-info":[{"award-number":["ALLRP 549804-19"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006374","name":"Canada First Research Excellence Fund","doi-asserted-by":"publisher","award":["CFREF-2015-00001"],"award-info":[{"award-number":["CFREF-2015-00001"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,6,4]]},"DOI":"10.1145\/3632775.3661949","type":"proceedings-article","created":{"date-parts":[[2024,7,9]],"date-time":"2024-07-09T15:31:37Z","timestamp":1720539097000},"page":"134-146","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Efficient Trading of Aggregate Bidirectional EV Charging Flexibility with Reinforcement Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9430-9509","authenticated-orcid":false,"given":"Javier","family":"Sales-Ortiz","sequence":"first","affiliation":[{"name":"University of Alberta, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6711-5502","authenticated-orcid":false,"given":"Omid","family":"Ardakanian","sequence":"additional","affiliation":[{"name":"University of Alberta, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,5,31]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"d.]. Bidirectional EV chargers to finally materialize","year":"2024","unstructured":"[n. d.]. Bidirectional EV chargers to finally materialize in 2024. https:\/\/www.solarpowerworldonline.com\/2024\/01\/bidirectional-ev-chargers-to-finally-materialize-in-2024\/"},{"key":"e_1_3_2_1_2_1","unstructured":"[n. d.]. ElaadNL Open Data. https:\/\/platform.elaad.io\/download-data\/"},{"key":"e_1_3_2_1_3_1","unstructured":"[n. d.]. Tennet Export data. https:\/\/www.tennet.org\/english\/operational_management\/export_data.aspx"},{"key":"e_1_3_2_1_4_1","volume-title":"d.]. U.S. electricity customers averaged five and one-half hours of power interruptions","year":"2022","unstructured":"[n. d.]. U.S. electricity customers averaged five and one-half hours of power interruptions in 2022. https:\/\/www.eia.gov\/todayinenergy\/detail.php?id=61303"},{"key":"e_1_3_2_1_5_1","volume-title":"Differentiable convex optimization layers. Advances in neural information processing systems 32","author":"Agrawal Akshay","year":"2019","unstructured":"Akshay Agrawal, Brandon Amos, Shane Barratt, Stephen Boyd, Steven Diamond, and J\u00a0Zico Kolter. 2019. Differentiable convex optimization layers. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3396851.3397706"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3575813.3595205"},{"key":"e_1_3_2_1_8_1","first-page":"6","article-title":"Mosek optimizer API for Python","volume":"9","author":"MOSEK","year":"2022","unstructured":"MOSEK ApS. 2022. Mosek optimizer API for Python. Version 9, 17 (2022), 6\u20134.","journal-title":"Version"},{"key":"e_1_3_2_1_9_1","volume-title":"Contract theory","author":"Bolton Patrick","unstructured":"Patrick Bolton and Mathias Dewatripont. 2004. Contract theory. MIT press."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i8.16841"},{"key":"e_1_3_2_1_11_1","volume-title":"2012 IEEE Global Communications Conference (GLOBECOM). IEEE, 1156\u20131161","author":"Cao Yanming","year":"2012","unstructured":"Yanming Cao, Qi Shi, Xinbing Wang, Xiaohua Tian, and Yu Cheng. 2012. Two-dimensional contract theory in cognitive radio networks. In 2012 IEEE Global Communications Conference (GLOBECOM). IEEE, 1156\u20131161."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447555.3464874"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3555006.3555007"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447555.3464851"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyr.2023.03.080"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2013.2257184"},{"key":"e_1_3_2_1_17_1","first-page":"1","article-title":"CVXPY: A Python-embedded modeling language for convex optimization","volume":"17","author":"Diamond Steven","year":"2016","unstructured":"Steven Diamond 2016. CVXPY: A Python-embedded modeling language for convex optimization. Journal of Machine Learning Research 17, 83 (2016), 1\u20135.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOM.2013.6566906"},{"key":"e_1_3_2_1_19_1","unstructured":"Logan Goldie-Scot. 2019. A behind the scenes take on lithium-ion battery prices. https:\/\/about.bnef.com\/blog\/behind-scenes-take-lithium-ion-battery-prices\/"},{"key":"e_1_3_2_1_20_1","volume-title":"Soft actor-critic algorithms and applications. arXiv preprint arXiv:1812.05905","author":"Haarnoja Tuomas","year":"2018","unstructured":"Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, 2018. Soft actor-critic algorithms and applications. arXiv preprint arXiv:1812.05905 (2018)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2021.112410"},{"key":"e_1_3_2_1_22_1","first-page":"1","article-title":"CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms","volume":"23","author":"Huang Shengyi","year":"2022","unstructured":"Shengyi Huang, Rousslan Fernand\u00a0Julien Dossa, Chang Ye, Jeff Braga, Dipam Chakraborty, Kinal Mehta, and Jo\u00e3o\u00a0G.M. Ara\u00fajo. 2022. CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms. Journal of Machine Learning Research 23, 274 (2022), 1\u201318. http:\/\/jmlr.org\/papers\/v23\/21-1342.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3036415"},{"key":"e_1_3_2_1_24_1","volume-title":"Charging and rate control for elastic traffic. European transactions on Telecommunications 8, 1","author":"Kelly Frank","year":"1997","unstructured":"Frank Kelly. 1997. Charging and rate control for elastic traffic. European transactions on Telecommunications 8, 1 (1997), 33\u201337."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2021.3094719"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/SmartGridComm51999.2021.9631999"},{"key":"e_1_3_2_1_27_1","volume-title":"Federated and Transfer Learning","author":"Liu Yuan","unstructured":"Yuan Liu, Mengmeng Tian, Yuxin Chen, Zehui Xiong, Cyril Leung, and Chunyan Miao. 2022. A contract theory based incentive mechanism for federated learning. In Federated and Transfer Learning. Springer, 117\u2013137."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077839.3077850"},{"key":"e_1_3_2_1_29_1","volume-title":"Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32","author":"Paszke Adam","year":"2019","unstructured":"Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, 2019. Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_1_30_1","volume-title":"Empirical Design in Reinforcement Learning. arXiv preprint arXiv:2304.01315","author":"Patterson Andrew","year":"2023","unstructured":"Andrew Patterson, Samuel Neumann, Martha White, and Adam White. 2023. Empirical Design in Reinforcement Learning. arXiv preprint arXiv:2304.01315 (2023)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3563357.3564067"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3575813.3597353"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2019.2920320"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2017.09.007"},{"key":"e_1_3_2_1_35_1","volume-title":"The economics of contracts: a primer","author":"Salani\u00e9 Bernard","unstructured":"Bernard Salani\u00e9. 2005. The economics of contracts: a primer. MIT press."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3396851.3397697"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3307772.3328296"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3208903.3208936"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2015.2393059"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2012.2213847"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2013.2259270"},{"key":"e_1_3_2_1_42_1","volume-title":"Virtual power plant containing electric vehicles scheduling strategies based on deep reinforcement learning. Electric power systems research 205","author":"Wang Jianing","year":"2022","unstructured":"Jianing Wang, Chunlin Guo, Changshu Yu, and Yanchang Liang. 2022. Virtual power plant containing electric vehicles scheduling strategies based on deep reinforcement learning. Electric power systems research 205 (2022), 107714."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2011.2166414"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.2997023"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/90.879352"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2015.2482948"}],"event":{"name":"e-Energy '24: The 15th ACM International Conference on Future and Sustainable Energy Systems","location":"Singapore Singapore","acronym":"e-Energy '24"},"container-title":["The 15th ACM International Conference on Future and Sustainable Energy Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3632775.3661949","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3632775.3661949","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T17:34:44Z","timestamp":1755884084000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3632775.3661949"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,31]]},"references-count":46,"alternative-id":["10.1145\/3632775.3661949","10.1145\/3632775"],"URL":"https:\/\/doi.org\/10.1145\/3632775.3661949","relation":{},"subject":[],"published":{"date-parts":[[2024,5,31]]},"assertion":[{"value":"2024-05-31","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}