Research Papers

Least Squares Fitting of Computational Fluid Dynamics Results to Measured Vertical Wind Profiles

[+] Author and Article Information
Adaiana F. Gomes da Silva

Mechanical Engineering Division,
Technological Institute of Aeronautics (ITA),
Praça Marechal Eduardo Gomes, 50,
Vila das Acácias,
São José dos Campos 12228-900, SP, Brazil
e-mail: adaiana1@yahoo.com.br

Edson Luiz Zaparoli

Mechanical Engineering Division,
Technological Institute of Aeronautics (ITA),
Praça Marechal Eduardo Gomes, 50,
Vila das Acácias,
São José dos Campos 12228-900, SP, Brazil
e-mail: elzaparoli@gmail.com

Cláudia R. Andrade

Aeronautical Engineering Division,
Technological Institute of Aeronautics (ITA),
Praça Marechal Eduardo Gomes, 50,
Vila das Acácias,
São José dos Campos 12228-900, SP, Brazil
e-mail: claudia@ita.br

1Corresponding author.

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received November 1, 2016; final manuscript received March 29, 2017; published online April 25, 2017. Assoc. Editor: Yves Gagnon.

J. Sol. Energy Eng 139(3), 031014 (Apr 25, 2017) (7 pages) Paper No: SOL-16-1465; doi: 10.1115/1.4036413 History: Received November 01, 2016; Revised March 29, 2017

Microscale numerical modeling is currently the main tool used in wind industry to assess local wind resources. This paper presents a systematic procedure to adjust computational fluid dynamics (CFD) predicted wind profiles to experimental measurements in order to minimize their differences. It can be applied when wind measurements are available. Data from ten masts with several measurement heights from the well-known Bolund hill experiment provided the observed wind profiles. Simulated profiles were calculated with windsim CFD model for the aforementioned site. Speed-up correction factors were defined through the least squares method to cross-correlate each mast as reference to all the others inside the Bolund hill domain. After, the observed and the adjusted wind profiles at the same position were compared. Moreover, root mean square errors (RMSEs) were used as a metric to evaluate the estimations and the ability of each position to be predicted and predictor. Results have shown that the quality of the adjustment process depends on the flow characteristics at each position related to the incoming wind direction. Most affected positions, i.e., when the airflow overcomes the Bolund hill escarpment, present the less accurate wind profile estimations. The reference mast should be installed upstream of the potential wind turbines' locations and after the main local characteristics of topographical changes.

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Grahic Jump Location
Fig. 2

Positioning of the masts (adapted from Ref. [5])

Grahic Jump Location
Fig. 1

Bolund hill view: (a) Google Earth and (b) Bolund background [23]

Grahic Jump Location
Fig. 4

Observed, simulated, and estimated vertical wind profiles, with correction through M7 as reference to all predicted positions, all for 270 deg

Grahic Jump Location
Fig. 3

Observed, simulated, and adjusted vertical wind profiles, all for 270 deg



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