| Description |
1 online resource (14 pages) : color illustrations, color map |
|
text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Series |
NREL/PR ; 5D00-73976 |
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NREL/PR ; 5D00-73976.
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| Note |
Slideshow presentation. |
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"May 16, 2019." |
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"Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office"--Page 4 of cover |
| Funding |
DE-AC36-08GO28308 |
| Note |
Online resource; title from PDF title screen (NREL, viewed on September 4, 2019). |
| Summary |
Provides an overview of the innovations and challenges from the algorithm development portion of the GO-Solar project, including plain language introductions to matrix-completion based state estimation, multi-kernel learning based state forecasting, 'slow-scale' voltage-load sensitivity matrix linearized optimal power flow, and 'fast-scale' OPF plan following using on-line Provides an overview of the innovations and challenges from the algorithm development portion of the GO-Solar project, including plain language introductions to matrix-completion based state estimation, multi-kernel learning based state forecasting, 'slow-scale' voltage-load sensitivity matrix linearized optimal power flow, and 'fast-scale' OPF plan following using on-line multi-objective state. |
| Subject |
Electric power production -- United States.
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Solar energy -- United States.
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Electric utilities -- United States.
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Électricité -- Production -- États-Unis.
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Énergie solaire -- États-Unis.
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Services publics d'électricité -- États-Unis.
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Electric power production. (OCoLC)fst00905475
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Electric utilities. (OCoLC)fst00905974
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Solar energy. (OCoLC)fst01124984
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United States. (OCoLC)fst01204155 https://id.oclc.org/worldcat/entity/E39PBJtxgQXMWqmjMjjwXRHgrq
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| Indexed Term |
distributed PV |
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OMOO |
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online multi-objective optimization |
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predictive state estimation |
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PSE |
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solar |
| Added Author |
National Renewable Energy Laboratory (U.S.), issuing body.
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United States. Department of Energy. Office of Energy Efficiency and Renewable Energy, sponsoring body.
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| Added Title |
Data-driven and machine learning approaches for high-pen PV grids |
| Standard No. |
1524333 OSTI ID |
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0000-0002-1452-0715 |
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0000-0002-5559-0971 |
| Gpo Item No. |
0430-P-09 (online) |
| Sudoc No. |
E 9.22:NREL/PR-5 D 00-73976 E 9.22:NREL/PR-5D 00-73976 |
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