Constrained optimization of offshore wind turbine positions under uncertain wind conditions with correlated data

Offshore wind power production is subject to substantial uncertainty due to variability in wind conditions. Planning of new wind parks should take these uncertainties into account by means of stochastic modeling and uncertainty quantification. Wind speed and wind direction exhibit dependence that ne...

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Bibliographic Details
Published in:Journal of physics. Conference series 2023-10, Vol.2626 (1), p.12056
Main Authors: Pettersson, Per, Aursjø, Olav, Helland, Johan Olav, Jettestuen, Espen
Format: Article
Language:English
Subjects:
Offshore energy sources
Optimization
Physics
Quadratures
Robust design
Stochastic models
Uncertainty
Wind direction
Wind power generation
Wind speed
Wind turbines
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Summary:Offshore wind power production is subject to substantial uncertainty due to variability in wind conditions. Planning of new wind parks should take these uncertainties into account by means of stochastic modeling and uncertainty quantification. Wind speed and wind direction exhibit dependence that needs to be properly modeled to yield reliable uncertainty estimates. In particular, the dependence is strong when data are averaged over a short time-horizon, e.g., on a monthly rather than an annual basis. In this work we introduce a stochastic model for wind speed and wind direction using Rosenblatt transformation and an empirical model. This allows efficient numerical quadrature that replaces thousands of Monte Carlos samples by a few tens of model evaluations at quadrature points in parametric space. A robust design formulation for maximizing power production honoring dependent data is proposed and demonstrated on data from the North Sea site Sørlige Nordsjø II.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2626/1/012056