Presentations

Abstract

The accurate characterization of freestream Turbulence Intensity (TI) is crucial for various offshore wind engineering analyses, including wind turbine design and energy yield assessments. Long-term TI time series are essential inputs for wake modelling, power curve verification studies, wind turbine site suitability assessments and structural design processes. However, cup-anemometer measured long-term TI time series are seldom available for offshore wind farms under development and thus challenges arise related to either the use of model turbulence or the addition of conservatism to mitigate risks under certification review. The absence of in-situ cup or sonic anemometer measurements, coupled with uncertainties in TI corrections for Floating Lidar Systems, necessitates alternative approaches for generating accurate TI time series. This study introduces a novel analytical TI model based on Townsend’s attached eddies hypothesis, validated against multiple offshore met mast measurements by C2Wind. The model inherently incorporates key drivers of TI, including friction velocity, atmospheric stability, and boundary layer height. It enables site-specific, directional, and seasonal analyses of TI conditions and is particularly advantageous for offshore regions with atmospheric conditions that differ from Northern Europe and where there is a lack of wind energy-grade offshore met mast measurements, such as Japan, Taiwan, and the United States. The proposed model relies solely on freely available input data and is designed for simplicity, accessibility, reproducibility and transparency. Validation results demonstrate strong agreement with publicly available measurements from four offshore met masts under varying stability conditions. Comparisons with publicly available large eddy simulation (LES) time series further highlight the model’s robustness. The practical applications of this analytical TI model are extensive. It provides an efficient and reliable method for generating TI data for wake modelling and power curve verification studies, supporting accurate energy yield assessments and robust WTG layout optimizations. Additionally, the model contributes to the assessment of site conditions for design purposes, facilitating more informed engineering decisions. Furthermore, the successful validation of the model against several measurement datasets provides confidence in its ability to highlight the key physical drivers for turbulence intensity conditions at a given site and thus derive a sound and site-specific characterization. This work introduces an innovative and practical approach to offshore TI modelling, validated across diverse conditions and leveraging freely available inputs. Its broad applicability to regions with unique atmospheric characteristics and its utility in wake modelling, power curve verification, and design processes make it a valuable tool for advancing offshore wind energy projects.