It is well known that when wind turbines are deployed in large arrays, their efficiency decreases due to complex interactions among themselves and with the atmospheric boundary layer (ABL). For wind farms whose length exceeds the height of the ABL by over an order of magnitude, a “fully developed” flow regime can be established. In this asymptotic regime, changes in the streamwise direction can be neglected and the relevant exchanges occur in the vertical direction. Such a fully developed wind-turbine array boundary layer (WTABL) has not been studied systematically before. A suite of large eddy simulations (LES), in which wind turbines are modeled using the classical “drag disk” concept, is performed for various wind-turbine arrangements, turbine loading factors, and surface roughness values. The results are used to quantify the vertical transport of momentum and kinetic energy across the boundary layer. It is shown that the vertical fluxes of kinetic energy are of the same order of magnitude as the power...

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Large eddy simulation study of fully developed wind-turbine array boundary layers

A new analytical model for wind-turbine wakes

Average power losses due to wind turbine wakes are of the order of 10 to 20% of total power output in large offshore wind farms. Accurately quantifying power losses due to wakes is, therefore, an important part of overall wind farm economics. The focus of this research is to compare different types of models from computational fluid dynamics (CFD) to wind farm models in terms of how accurately they represent wake losses when compared with measurements from offshore wind farms. The ultimate objective is to improve modelling of flow for large wind farms in order to optimize wind farm layouts to reduce power losses due to wakes and loads.

The research presented is part of the EC-funded UpWind project, which aims to radically improve wind turbine and wind farm models in order to continue to improve the costs of wind energy. Reducing wake losses, or even reduce uncertainties in predicting power losses from wakes, contributes to the overall goal of reduced costs. Here, we assess the state of the art in wake and flow modelling for offshore wind farms, the focus so far has been cases at the Horns Rev wind farm, which indicate that wind farm models require modification to reduce under-prediction of wake losses while CFD models typically over-predict wake losses. Further investigation is underway to determine the causes of these discrepancies. Copyright © 2009 John Wiley & Sons, Ltd.

Modelling and measuring flow and wind turbine wakes in large wind farms offshore

Wind energy, commonly recognized to be a clean and environmentally friendly renewable energy resource that can reduce our dependency on fossil fuels, has developed rapidly in recent years. Its mature technology and comparatively low cost make it promising as an important primary energy source in the future. However, there are potential environmental impacts due to the installation and operation of the wind turbines that cannot be ignored. This paper aims to provide an overview of world wind energy scenarios, the current status of wind turbine development, development trends of offshore wind farms, and the environmental and climatic impact of wind farms. The wake effect of wind turbines and modeling studies regarding this effect are also reviewed.

Wind energy development and its environmental impact: A review

Carbon dioxide (CO2) emissions from biomass combustion are traditionally assumed climate neutral if the bioenergy system is carbon (C) flux neutral, i.e. the CO2 released from biofuel combustion approximately equals the amount of CO2 sequestered in biomass. This convention, widely adopted in life cycle assessment (LCA) studies of bioenergy systems, underestimates the climate impact of bioenergy. Besides CO2 emissions from permanent C losses, CO2 emissions from C flux neutral systems (that is from temporary C losses) also contribute to climate change: before being captured by biomass regrowth, CO2 molecules spend time in the atmosphere and contribute to global warming. In this paper, a method to estimate the climate impact of CO2 emissions from biomass combustion is proposed. Our method uses CO2 impulse response functions (IRF) from C cycle models in the elaboration of atmospheric decay functions for biomass-derived CO2 emissions. Their contributions to global warming are then quantified with a unit-based index, the GWPbio. Since this index is expressed as a function of the rotation period of the biomass, our results can be applied to CO2 emissions from combustion of all the different biomass species, from annual row crops to slower growing boreal forest.

https://www.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1757-1707.2011.01102.x

CO2 emissions from biomass combustion for bioenergy: atmospheric decay and contribution to global warming

The proposed model for the wind speed deficit in wind farms is analytical and encompasses both small wind farms and wind farms extending over large areas. As is often the need for offshore wind farms, the model handles a regular array geometry with straight rows of wind turbines and equidistant spacing between units in each row and equidistant spacing between rows. Firstly, the case with the flow direction being parallel to rows in a rectangular geometry is considered by defining three flow regimes. Secondly, when the flow is not in line with the main rows, solutions are suggested for the patterns of wind turbine units corresponding to each wind direction. The presentation is an outline of a model complex that will be adjusted and calibrated with measurements in the near future. Copyright © 2006 John Wiley & Sons, Ltd.

Analytical modelling of wind speed deficit in large offshore wind farms

The paper presents research conducted in the Flow workpackage of the EU funded UPWIND project which focuses on improving models of flow within and downwind of large wind farms in complex terrain and offshore. The main activity is modelling the behaviour of wind turbine wakes in order to improve power output predictions.

https://iopscience.iop.org/article/10.1088/1742-6596/75/1/012049/pdf

Modelling and measurements of wakes in large wind farms

The method of combining the Karlsruhe Atmospheric Mesoscale Model, KAMM, with the Wind Atlas Analysis and Application Program, WAsP, to make local predictions of the wind resource is presented. It combines the advantages of meso-scale modeling — overview over a big region and use of global data bases — with the local prediction capacity of the small-scale model WAsP. Results are presented for Denmark, Ireland, Northern Portugal and Galicia, and the Faroe Islands. Wind atlas files were calculated from wind data simulated with the meso-scale model using model grids with a resolution of 2.5, 5, and 10 km. Using these wind atlas files in WAsP the local prediction of the mean wind does not depend on the grid resolution of the meso-scale model. The local predictions combining KAMM and WAsP are much better than simple interpolation of the wind simulated by KAMM. In addition an investigation was made on the dependence of wind atlas data on the size of WAsP-maps. It is recommended that a topographic map around a site should extend 10 km out from it. If there is a major roughness change like a coast line further away in a frequent wind direction this should be included at even greater distances, perhaps up to 20 km away. ISBN 87–550–2850–0; ISBN 87-550-2909-4 (internet) ISSN 0106–2840 Print: Danka Services International · 2001

The numerical wind atlas - the KAMM/WAsP method

We extend the infinite wind-farm boundary-layer (IWFBL) model of Frandsen to take into account atmospheric static stability effects. This extended model is compared with the IWFBL model of Emeis and to the Park wake model used in Wind Atlas Analysis and Application Program (WAsP), which is computed for an infinite wind farm. The models show similar behavior for the wind-speed reduction when accounting for a number of surface roughness lengths, turbine to turbine separations and wind speeds under neutral conditions. For a wide range of atmospheric stability and surface roughness length values, the extended IWFBL model of Frandsen shows a much higher wind-speed reduction dependency on atmospheric stability than on roughness length (roughness has been generally thought to have a major effect on the wind-speed reduction). We further adjust the wake-decay coefficient of the Park wake model for an infinite wind farm to match the wind-speed reduction estimated by the extended IWFBL model of Frandsen for different roughness lengths, turbine to turbine separations and atmospheric stability conditions. It is found that the WAsP-recommended values for the wake-decay coefficient of the Park wake model are (i) larger than the adjusted values for a wide range of neutral to stable atmospheric stability conditions, a number of roughness lengths and turbine separations lower than ∼ 10 rotor diameters and (ii) too large compared with those obtained by a semiempirical formulation (relating the ratio of the friction to the hub-height free velocity) for all types of roughness and atmospheric stability conditions. © 2013 The Authors. Wind Energy published by John Wiley & Sons, Ltd.

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Ole Rathmann

Papers

Analytical modelling of wind speed deficit in large offshore wind farms

Modelling and measuring flow and wind turbine wakes in large wind farms offshore

Modelling and measurements of wakes in large wind farms

The numerical wind atlas - the KAMM/WAsP method

Atmospheric stability‐dependent infinite wind‐farm models and the wake‐decay coefficient