Uncertainty quantification of offshore wind farms using Monte Carlo and sparse grid

• Published in: Energy sources. Part B, Economics, planning and policy Vol. 17; no. 1
• Main Authors: Richter, Pascal, Wolters, Jannick, Frank, Martin
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 31.12.2022
• Subjects: Offshore wind farm; Quasi-Monte Carlo; Sensitivity Analysis; Stochastic Collocation; Uncertainty Quantification
• ISSN: 1556-7249; 1556-7257
• DOI: 10.1080/15567249.2021.2000520

The power produced by an offshore wind farm is subject to multiple uncertainties, such as volatile wind, turbine performance wear, and availability losses. Knowledge about the propagation of these uncertainties and their effect on the produced power is crucial in the design stage of a wind farm. Due to the multitude of uncertainties, an analysis requires high-dimensional numerical integration to determine these parameter sensitivities. Such an analysis has not been done in the current literature for the full set of parameters. In this work, a thorough analysis of all uncertainties is provided, modeled from several years of collected data from the existing wind farms Horns Rev 1, DanTysk, and Sandbank. The analysis reveals four major parameters, allowing the other parameters to be neglected in future measurement data acquisitions and sensitivity analysis processes. Furthermore, the accuracy of several Uncertainty Quantification techniques is analyzed and a recommendation for future analysis is given.