Abstract
We present a wind simulation framework for offshore and onshore wind farms. The simulation framework involves an automatic hybrid high-quality mesh generation process, a pre-processing to impose initial and boundary conditions, and a solver for the Reynolds Averaged Navier-Stokes (RANS) equations with two different turbulence models, a modified standard k-ϵ model and a realizable k-ϵ model in which we included the Coriolis effects. Wind turbines are modeled as actuator discs. The wind farm simulation framework has been implemented in Alya, an in-house High Performance Computing (HPC) multi-physics finite element parallel solver. An application example is shown for an onshore wind farm composed of 165 turbines.
Highlights
A Computational Fluid Dynamics (CFD) framework for offshore and onshore wind farm simulationThis content has been downloaded from IOPscience
Simulation of wind farms with Computational Fluid Dynamics (CFD) models involves the resolution of the turbulent Atmospheric Boundary Layer (ABL) and the effects induced by wind turbines, including wind speed deficit, increase of turbulent kinetic energy, and interaction among wakes
Wind turbines are simulated under the actuator disc theory [7]
Summary
This content has been downloaded from IOPscience. Ser. 854 012002 (http://iopscience.iop.org/1742-6596/854/1/012002) View the table of contents for this issue, or go to the journal homepage for more. You may be interested in: Wind power moves out to sea Andrew Henderson CFD and Experimental Studies on Wind Turbines in Complex Terrain by Improved Actuator Disk Method Xin Liu, Shu Yan, Yanfei Mu et al A CFD model of the wake of an offshore wind farm: using a prescribed wake inflow P-E Réthoré, A Bechmann, N N Sørensen et al DDG4 A Simulation Framework based on the DD4hep Detector Description Toolkit M. Casartelli et al A Generic Simulation Framework for Non-Entangled based Experimental Quantum Cryptography and Communication: Quantum Cryptography and Communication Simulator (QuCCs) Abudhahir Buhari, Zuriati Ahmad Zukarnain, Roszelinda Khalid et al. Wake Conference 2017 IOP Conf.
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