172 research outputs found
Atmospheric stability in CFD – Representation of the diurnal cycle in the atmospheric boundary layer
Development and Verification of CFD Models for Modeling Wind Conditions on Forested Wind Turbine Sites
Diurnal cycle RANS simulations applied to wind resource assessment
Microscale computational fluid dynamics (CFD) models can be used for wind resource assessment on complex terrains. These models generally assume neutral atmospheric stratification, an assumption that can lead to inaccurate modeling results and to large uncertainties at certain sites. We propose a methodology for wind resource evaluation based on unsteady Reynolds averaged Navier‐Stokes (URANS) simulations of diurnal cycles including the effect of thermal stratification. Time‐dependent boundary conditions are generated by a 1D precursor to drive 3D diurnal cycle simulations for a given geostrophic wind direction sector. Time instants of the cycle representative of four thermal stability regimes are sampled within diurnal cycle simulations and combined with masts time series to obtain the wind power density (WPD). The methodology has been validated on a complex site instrumented with seven met masts. The WPD spatial distribution is in good agreement with observations with the mean absolute error improving 17.1% with respect to the neutral stratification assumption.This work has been partially supported by the three EU H2020 projects, New European Wind Atlas ERA‐NET PLUS (NEWA, FP7‐ENERGY.2013.10.1.2, European Commission's grant agreement 618122), High Performance Computing for Energy (HPC4E, grant agreement 689772), and the Energy oriented Centre of Excellence (EoCoE, grant agreement 676629), and the SEDAR (“Simulación eólica de alta resolución”) project. Jordi Barcons is grateful to a PhD fellowship from the Industrial Doctorates Plan of the Government of Catalonia (Ref. eco/2497/2013). We also thank Iberdrola Renovables Energa S.A. and Impulsora Latinoamericana de Energa Renovables S.A. for providing the access to Puebla met masts data for validation and to Luis Prieto and Daniel Paredes for their help. We also thank the reviewers for their productive comments and observations.Peer ReviewedPostprint (published version
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