Algorithms to Harvest the Wind.
The article examines wind-generated electricity and algorithms that are being proposed by researchers to reorient turbines to improve their output. Topics discussed include how as of 2018 wind energy made up 6.6% of utility-scale electricity generation, the overall tendency to build higher and bigge...
| Publicado en: | Communications of the ACM Vol. 63; no. 3; pp. 13 - 15 |
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| Formato: | Artículo |
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Association for Computing Machinery
Mar2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=141926839&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 141926839 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Mar2020 vid: 63 iid: 3 pid: 68 pub: Association for Computing Machinery artinfo: ui: 141926839 10.1145/3379497 ppf: 13 ppct: 2 formats: tig: atl: Algorithms to Harvest the Wind. aug: au: Monroe, Don su: Wind power research Algorithms Renewable energy sources Fleming, Paul Wind power plants sug: subj: Wind power research Algorithms Renewable energy sources Fleming, Paul Wind power plants ab: The article examines wind-generated electricity and algorithms that are being proposed by researchers to reorient turbines to improve their output. Topics discussed include how as of 2018 wind energy made up 6.6% of utility-scale electricity generation, the overall tendency to build higher and bigger turbines and the work of Paul Fleming, who worked to develop tools with colleagues at the U.S. National Renewable Energy Labs (NREL). pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2020 holdings: @attributes: islocal: N |
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