Abstract
Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with a paramount information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform on the development of the forecast uncertainty through forecast series. This issue is addressed here by describing a method that permits to generate statistical scenarios of wind generation that accounts for the interdependence structure of prediction errors, in plus of respecting predictive distributions of wind generation. The approach is evaluated on the test case of a multi-MW wind farm over a period of more than two years. Its interest for a large range of applications is discussed.
Original language | English |
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Title of host publication | IEEE PowerTech Conference 2007, Lausanne, Switzerland |
Publisher | IEEE |
Publication date | 2007 |
ISBN (Print) | 978-1-4244-2189-3 |
DOIs | |
Publication status | Published - 2007 |
Event | 2007 IEEE Lausanne Power Tech - Swiss Federal Institute of Technology, Lausanne, Switzerland Duration: 1 Jul 2007 → 5 Jul 2007 https://ieeexplore.ieee.org/xpl/conhome/4534843/proceeding |
Conference
Conference | 2007 IEEE Lausanne Power Tech |
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Location | Swiss Federal Institute of Technology |
Country/Territory | Switzerland |
City | Lausanne |
Period | 01/07/2007 → 05/07/2007 |
Internet address |