PowerNet: Multi-Agent Deep Reinforcement Learning for Scalable Powergrid Control.
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| Title: | PowerNet: Multi-Agent Deep Reinforcement Learning for Scalable Powergrid Control. |
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| Authors: | Chen, Dong1, chendon9@msu.edu, Chen, Kaian1, chenkaia@msu.edu, Li, Zhaojian1, lizhaoj1@egr.msu.edu, Chu, Tianshu2, cts198859@hotmail.com, Yao, Rui3, yaorui.thu@gmail.com, Qiu, Feng3, fqiu@anl.gov, Lin, Kaixiang4, linkaixi@msu.edu |
| Source: | IEEE Transactions on Power Systems; Mar2022, Vol. 37 Issue 2, p1007-1017, 11p |
| Database: | Applied Science & Technology Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 155754072 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: PowerNet: Multi-Agent Deep Reinforcement Learning for Scalable Powergrid Control. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Chen%2C+Dong%22">Chen, Dong</searchLink><relatesTo>1</relatesTo>, <i>chendon9@msu.edu</i><br /><searchLink fieldCode="AU" term="%22Chen%2C+Kaian%22">Chen, Kaian</searchLink><relatesTo>1</relatesTo>, <i>chenkaia@msu.edu</i><br /><searchLink fieldCode="AU" term="%22Li%2C+Zhaojian%22">Li, Zhaojian</searchLink><relatesTo>1</relatesTo>, <i>lizhaoj1@egr.msu.edu</i><br /><searchLink fieldCode="AU" term="%22Chu%2C+Tianshu%22">Chu, Tianshu</searchLink><relatesTo>2</relatesTo>, <i>cts198859@hotmail.com</i><br /><searchLink fieldCode="AU" term="%22Yao%2C+Rui%22">Yao, Rui</searchLink><relatesTo>3</relatesTo>, <i>yaorui.thu@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Qiu%2C+Feng%22">Qiu, Feng</searchLink><relatesTo>3</relatesTo>, <i>fqiu@anl.gov</i><br /><searchLink fieldCode="AU" term="%22Lin%2C+Kaixiang%22">Lin, Kaixiang</searchLink><relatesTo>4</relatesTo>, <i>linkaixi@msu.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Power+Systems%22">IEEE Transactions on Power Systems</searchLink>; Mar2022, Vol. 37 Issue 2, p1007-1017, 11p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=155754072 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/TPWRS.2021.3100898 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1007 Titles: – TitleFull: PowerNet: Multi-Agent Deep Reinforcement Learning for Scalable Powergrid Control. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chen, Dong – PersonEntity: Name: NameFull: Chen, Kaian – PersonEntity: Name: NameFull: Li, Zhaojian – PersonEntity: Name: NameFull: Chu, Tianshu – PersonEntity: Name: NameFull: Yao, Rui – PersonEntity: Name: NameFull: Qiu, Feng – PersonEntity: Name: NameFull: Lin, Kaixiang IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 08858950 Numbering: – Type: volume Value: 37 – Type: issue Value: 2 Titles: – TitleFull: IEEE Transactions on Power Systems Type: main |
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