Quantifying and clustering the wake-induced perturbations within a wind farm for load analysis

The main objective of the HIPERWIND project is to reduce the Levelized Cost Of Energy by controlling the uncertainties in a chain of numerical models simulating an offshore wind farm. This paper studies the wake-induced perturbations of the ambient wind conditions inside a wind farm. A theoretical f...

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Bibliographic Details
Published in:Journal of physics. Conference series 2023-05, Vol.2505 (1), p.012011
Main Authors: Lovera, A., Fekhari, E., Jézéquel, B., Dupoiron, M., Guiton, M., Ardillon, E.
Format: Article
Language:English
Subjects:
Aerodynamics
Clustering
Computing costs
Cost analysis
Mathematical models
Numerical models
Offshore
Offshore energy sources
Perturbation
Physics
Reliability analysis
Simulation
Structural response
Turbulence intensity
Uncertainty
Wind farms
Wind forces
Wind power
Wind speed
Wind turbines
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Summary:The main objective of the HIPERWIND project is to reduce the Levelized Cost Of Energy by controlling the uncertainties in a chain of numerical models simulating an offshore wind farm. This paper studies the wake-induced perturbations of the ambient wind conditions inside a wind farm. A theoretical floating offshore wind farm off the coast of South Brittany in France is considered as a test case, and a numerical model simulating the wake of this farm is exploited. This model gives an analytical prediction of wake deficit and added turbulence, also considering the influence of the floaters’ position due to mean wind forces. An uncertainty propagation on the wake model is performed, considering the multivariate joint distribution of ambient wind conditions as input. This results, for each turbine, in a wake-modified probabilistic distribution on the wind speed and turbulence intensity averaged over the rotor. A new approach for clustering these wake-modified distributions is proposed in this paper to regroup the wind turbines exposed to similar environmental conditions, leading to a similar structural response. This analysis is essential to ensure the practical feasibility of the reliability analysis of an overall project with the computational cost of aero-servo-hydro-elastic simulations of offshore wind turbines. Several methods classically used for clustering are compared. Finally, four clusters only are sufficient to represent the whole set of turbines in the wind farm.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2505/1/012011