Wind power meteorology. Part II: siting and models

Abstract

The data used in wind power meteorology stem mainly from three sources: on‐site wind measurements, the synoptic networks and the reanalysis projects. Wind climate analysis, wind resource estimation and siting further require a detailed description of the topography of the terrain—with respect to the roughness of the surface, near‐by obstacles and orographical features. Finally, the meteorological models used for estimation and prediction of the wind are described; their classification, inputs, limitations and requirements. A comprehensive modelling concept, meso/microscale modelling, is introduced and a procedure for short‐term prediction of the wind resource is described. Copyright © 1998 John Wiley & Sons, Ltd.

A Comparison of Wind Flow Models for Wind Resource Assessment in Wind Energy Applications

“…Several methods are available to model the wind in the atmospheric boundary layer (ABL) at both the mesoscale and the microscale levels [6,18,19]. Depending on the application and the information needed, assumptions can be made that greatly simplify the problem at the price of representativeness [20,21].…”

“…In the context of wind resource estimation, they are dedicated to the modelling of the flow in the lowest part of the ABL, i.e., the surface layer. Generally, in these applications, the flow is commonly considered as neutral [5,18,19,22,26]. Methods to predict wind fields in the surface layer range from the simplest model, strongly relying on flow assumptions (such as a mass-conserving model or the slightly more evolved linearize Navier Stokes equation model), to advanced and more universal Computational Fluid Dynamics (CFD) models such as the Reynolds Averaged Navier Stokes (RANS) and Large Eddy Simulation (LES) models [6,18,19].…”

“…Generally, in these applications, the flow is commonly considered as neutral [5,18,19,22,26]. Methods to predict wind fields in the surface layer range from the simplest model, strongly relying on flow assumptions (such as a mass-conserving model or the slightly more evolved linearize Navier Stokes equation model), to advanced and more universal Computational Fluid Dynamics (CFD) models such as the Reynolds Averaged Navier Stokes (RANS) and Large Eddy Simulation (LES) models [6,18,19]. However, while an increase in the complexity of the model generally results in an increase of the computational cost, it does not necessary imply that better results are obtained [6,18,19,26].…”

“…Methods to predict wind fields in the surface layer range from the simplest model, strongly relying on flow assumptions (such as a mass-conserving model or the slightly more evolved linearize Navier Stokes equation model), to advanced and more universal Computational Fluid Dynamics (CFD) models such as the Reynolds Averaged Navier Stokes (RANS) and Large Eddy Simulation (LES) models [6,18,19]. However, while an increase in the complexity of the model generally results in an increase of the computational cost, it does not necessary imply that better results are obtained [6,18,19,26]. Indeed, linear models, such as the ones based on the Jackson and Hunt model [27] of flow over low hills, i.e., WAsP [10] and MsMicro [9], require a fraction of the computational cost of the RANS methods and are proven to be as capable to reproduce the average neutral ABL velocity fields over gentle terrains, i.e., when the slope of the surface is lower than 0.3 (values at which separation of the flow becomes highly probable) [6,9,18,19,28].…”

“…However, while an increase in the complexity of the model generally results in an increase of the computational cost, it does not necessary imply that better results are obtained [6,18,19,26]. Indeed, linear models, such as the ones based on the Jackson and Hunt model [27] of flow over low hills, i.e., WAsP [10] and MsMicro [9], require a fraction of the computational cost of the RANS methods and are proven to be as capable to reproduce the average neutral ABL velocity fields over gentle terrains, i.e., when the slope of the surface is lower than 0.3 (values at which separation of the flow becomes highly probable) [6,9,18,19,28]. WAsP and MsMicro differ in their approach to include surface roughness and roughness changes, where the method used by WAsP appears to be slightly more evolved [9,18,29].…”