Uncertainty estimates from an experimental investigation of a scale model wind turbine array, conducted with (on the order of) 100 0.25 meter diameter model wind turbines in a high Reynolds number turbulent boundary layer facility, are reported. An expanded uncertainty analysis using the Taylor series method is executed to predict uncertainty for the system of interest in the mean flow. A workable comprise has been found for data acquisition time mitigating changing initial conditions due to exposure to atmospheric conditions and temperature drift. The study was conducted in the University of New Hampshire (UNH) Flow Physics Facility (FPF) which is the worlds largest flow physics quality turbulent boundary layer wind tunnel, with test section dimensions of 6 m wide, 2.7 m tall and 72 m long. Naturally grown turbulent boundary layers with scale ratios of energy-containing to dissipative scales (Karman number) of up to 20,000 can be generated, and are on the order of 1 m thick near the downstream end of the test section. The long fetch of the facility offers unique opportunities to study the downstream evolution of the wake of single wind turbines, and the flow through model wind turbine arrays over long distances. Far downstream within a wind farm it is proposed that the farm reaches a fully developed state where the flow field becomes similar from one row to the next. The goal of this work is to accurately determine the uncertainty associated with open to atmosphere wind tunnel data for use in validation of numerical models regarding the fully developed wind turbine array boundary layer.
- Fluids Engineering Division
Uncertainty Analysis in a Scale Model Wind Turbine Array Boundary Layer
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Turner, JJ, V, & Wosnik, M. "Uncertainty Analysis in a Scale Model Wind Turbine Array Boundary Layer." Proceedings of the ASME 2017 Fluids Engineering Division Summer Meeting. Volume 1B, Symposia: Fluid Measurement and Instrumentation; Fluid Dynamics of Wind Energy; Renewable and Sustainable Energy Conversion; Energy and Process Engineering; Microfluidics and Nanofluidics; Development and Applications in Computational Fluid Dynamics; DNS/LES and Hybrid RANS/LES Methods. Waikoloa, Hawaii, USA. July 30–August 3, 2017. V01BT07A001. ASME. https://doi.org/10.1115/FEDSM2017-69342
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