14:30 - 16:00 Wake modelling and forecasting
Resource assessment
![Onshore Onshore](onshore-neg.png)
![Offshore Offshore](offshore-neg.png)
Room: Hall E
In the session there will be five presentations on wake modelling and forecasting. They will focus on the limitations in wake modelling including comparison with field data, and will move into short-term power production forecasting as well as studies of uncertainty in wind power forecast methods.
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Learning objectives
- Understand the latest news regarding limitations and possibilities within wake modelling approaches;
- Exemplify forecast methods and their ability to accurately predict short time ahead production output;
- Address the importance of atmospheric stability in wind power forecasting and wake modelling;
- Determine whether simple linear wake combination methods as presently used in commercial analytical software can correctly represent turbine interactions.
![](../submit-an-abstract/thumb/ADMIN_172Ivanell_Stephan.jpg)
Presenter
![](../submit-an-abstract/thumb/73_1608796222.jpeg)
Co-authors:
Kester Gunn (1) F Clym Stock-Williams (1) Richard Willden (2) Chris Vogel (2) Tim Stallard (3) Meagan Burke (1) William Hunter (2) Nick Robinson (4) Sarah Ruth Schmidt (5)
(1) Uniper, Nottingham, United Kingdom (2) The University of Oxford, Oxford, United Kingdom (3) The University of Manchester, Manchester, United Kingdom (4) AWS Truepower, New York, United States (5) E.ON, Malmo, Sweden
Presenter's biography
Biographies are supplied directly by presenters at WindEurope Summit 2016 and are published here uneditedDr. Kester Gunn CEng MIMechE completed a MEng and PhD in Engineering at Lancaster University. Since entering industry in 2010, he has worked in the field of renewable energy, with an emphasis on the analysis of environmental data. Recently he has been working on applying advanced optimisation methods to the design of wind farms layouts, combining modelling of windfarm systems with novel evolutionary algorithms to improve the cost of energy of large wind farms.
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