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Abstract Details
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Activity Number:
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269
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Type:
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Roundtables
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Date/Time:
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Tuesday, August 2, 2011 : 7:00 AM to 8:15 AM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #301908 |
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Title:
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Statistics for Wind Energy
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Author(s):
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Marc G. Genton*+
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Companies:
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Texas A & M University
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Address:
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Department of Statistics, College Station, TX, 77843-3143, USA
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Keywords:
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Energy ;
Forecast ;
Spatial statistics ;
Time series ;
Wind
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Abstract:
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Global large scale penetration of wind energy is accompanied by significant challenges due to the intermittent and unstable nature of wind. High quality short-term wind speed forecasting is critical to reliable and secure power system operations. We will discuss how statistical techniques can enable wind energy to be more efficiently incorporated into the electrical grid.
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Authors who are presenting talks have a * after their name.
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