Adjoint-based calibration of inlet boundary condition for atmospheric computational fluid dynamics solvers

Akbarzadeh, Siamak; Kassem, Hassan; Buhr, Renko; Steinfeld, Gerald; Stoevesandt, Bernhard

doi:10.5194/wes-4-619-2019

Cited by 2 publications

(2 citation statements)

References 34 publications

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“…The wind speed over the entire site is predicted using a CFD simulation software on a fixed grid resolution and varying forest tree height values. For this work, we have used the software FIWind-OpenFOAM, an in-house CFD simulator which is an OpenFOAM based tool-chain for micro-siting by Fraunhofer IWES [9,10]. Five sets of CFD simulations were done for each site with forest height (5, 10, .…”

Section: Wind Speed Variability Response As a Function Of Varying For...mentioning

confidence: 99%

Enhancing standard CFD based practices for site assessment through polynomial surrogates for estimating uncertainty in wind speed

Lakdawala,

Kassem,

Schulte

2024

J. Phys.: Conf. Ser.

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One of the challenges in digitizing the wind energy sector is to have reliable, accurate and efficient data assessment and prediction tools. We believe that accurate surrogates are key towards improving efficiency and reliability for informed decision making. For a quantitative understanding of wind and energy in complex terrains, a detailed site assessment is done, most often using mesoscale and/or microscale computational fluid dynamics (CFD) based approach. Typically, one would require multiple scenarios/case for a CFD simulator to incorporate the influence of a parameter on variability of wind speed and energy production. These simulations are computationally expensive, and the industry is constantly on a look out for more efficient methods. Towards this end, we propose using a polynomial surrogate based on Polynomial Chaos Expansion (PCE) for uncertainty quantification that requires only a few CFD simulations to assess the variability of wind speed with respect to variability in an input parameter. The variability estimates from PCE were first validated against the standard Monte Carlo method on simple benchmarks and then tested for complex terrains. In this work, we present results that help us understand how canopy foliage, particularly its height, impacts the variability in wind speed in complex terrains. Since the polynomial surrogate relies only on a limited set of input variations (forest height) to estimate the variability distributions for wind speed locally (for specified points of interests), it has proven to be a low-cost and accurate method for estimating uncertainty. In this paper, we discuss the results for wind speed variability for five sites with varying complexity using the polynomial surrogate model. Furthermore, the singular value decomposition (SVD) entropy value is used to quantify terrain complexity for the sites considered. We show how the variability in wind speed can potentially be correlated to terrain complexity. This is our first attempt in providing an empirically (including multiple sites) derived relationship that can be used as a basis for fast and reliable variability estimator for wind resource planners.

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Section: Wind Speed Variability Response As a Function Of Varying For...mentioning

confidence: 99%

Enhancing standard CFD based practices for site assessment through polynomial surrogates for estimating uncertainty in wind speed

Lakdawala,

Kassem,

Schulte

2024

J. Phys.: Conf. Ser.

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“…The plant area density profiles for forest and grove type follow [26]. More details about the general FIWind formulation can be found in [25,27].…”

Section: Applied Flow Modellingmentioning

confidence: 99%

Advancing Wind Resource Assessment in Complex Terrain with Scanning Lidar Measurements

et al. 2021

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The planning and realization of wind energy projects requires an as accurate and precise wind resource estimation as possible. Standard procedures combine shorter on-site measurements with the application of numerical models. The uncertainties of the numerical data generated from these models are, particularly in complex onshore terrain, not just rather high but typically not well quantified. In this article we propose a methodology for using a single scanning Doppler wind lidar device to calibrate the output data of a numerical flow model and with this not just quantify but potentially also reduce the uncertainties of the final wind resource estimate. The scanning lidar is configured to perform Plan Position Indicator (PPI) scans and the numerical flow data are projected onto this geometry. Deviations of the derived from the recorded line-of-sight wind speeds are used to identify deficiencies of the model and as starting point for an improvement and tuning. The developed methodology is demonstrated based on a study for a site in moderately complex terrain in central Germany and using two rather different types of numerical flow models. The findings suggest that the use of the methodology and the introduced scanning wind lidar technology offers a promising opportunity to control the uncertainty of the applied flow models, which can otherwise only be estimated very roughly.

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Adjoint-based calibration of inlet boundary condition for atmospheric computational fluid dynamics solvers

Cited by 2 publications

References 34 publications

Enhancing standard CFD based practices for site assessment through polynomial surrogates for estimating uncertainty in wind speed

Enhancing standard CFD based practices for site assessment through polynomial surrogates for estimating uncertainty in wind speed

Advancing Wind Resource Assessment in Complex Terrain with Scanning Lidar Measurements

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