Kurt Schaldemose Hansen

Quantifying the Impact of Wind Turbine Wakes on Power Output at Offshore Wind Farms

Abstract There is an urgent need to develop and optimize tools for designing large wind farm arrays for deployment offshore. This research is focused on improving the understanding of, and modeling of, wind turbine wakes in order to make more accurate power output predictions for large offshore wind farms. Detailed data ensembles of power losses due to wakes at the large wind farms at Nysted and Horns Rev are presented and analyzed. Differences in turbine spacing (10.5 versus 7 rotor diameters) are not differentiable in wake-related power losses from the two wind farms. This is partly due to the high variability in the data despite careful data screening. A number of ensemble averages are simulated with a range of wind farm and computational fluid dynamics models and compared to observed wake losses. All models were able to capture wake width to some degree, and some models also captured the decrease of power output moving through the wind farm. Root-mean-square errors indicate a generally better model pe...

Modelling and measurements of wakes in large 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.

Solving the Turbine Positioning Problem for Large Offshore Wind Farms by Simulated Annealing

The current paper is concerned with determining the optimal layout of the turbines inside large offshore wind farms by means of an optimization algorithm. We call this the Turbine Positioning Problem. To achieve this goal a simulated annealing algorithm has been devised, where three types of local search operations are performed recursively until the system converges. The effectiveness of the proposed algorithm is demonstrated on a suite of real life test cases, including Horns Rev offshore wind farm. The results are verified using a commercial wind resource software indicating that this method represents an effective strategy for the wind turbine positioning problem. The findings enable the comparison of the optimized and the grid layouts and the study of the wake differences between these configurations. It is seen that for very large offshore wind farms the difference in wake losses is negligible while, as the wind farms size reduces, the differences start becoming significant. A sensitivity analysis is also performed showing that greater density of turbines in the perimeter of the optimized wind farm reduces the wake losses even if the wind climate changes.

IEA-Task 31 WAKEBENCH: Towards a protocol for wind farm flow model evaluation. Part 2: Wind farm wake models

Researchers within the International Energy Agency (IEA) Task 31: Wakebench have created a framework for the evaluation of wind farm flow models operating at the microscale level. The framework consists of a model evaluation protocol integrated with a web-based portal for model benchmarking (www.windbench.net). This paper provides an overview of the building-block validation approach applied to wind farm wake models, including best practices for the benchmarking and data processing procedures for validation datasets from wind farm SCADA and meteorological databases. A hierarchy of test cases has been proposed for wake model evaluation, from similarity theory of the axisymmetric wake and idealized infinite wind farm, to single-wake wind tunnel (UMN-EPFL) and field experiments (Sexbierum), to wind farm arrays in offshore (Horns Rev, Lillgrund) and complex terrain conditions (San Gregorio). A summary of results from the axisymmetric wake, Sexbierum, Horns Rev and Lillgrund benchmarks are used to discuss the state-of-the-art of wake model validation and highlight the most relevant issues for future development.

Simulation of inhomogeneous, non-stationary and non-Gaussian turbulent winds

Turbulence time series are needed for wind turbine load simulation. The multivariate Fourier simulation method often used for this purpose is extended for inhomogeneous and non-stationary processes of general probability distribution. This includes optional conditional simulation matching simulated series to field measurements at selected points. A probability model for the application of turbine wind loads is discussed, and finally the technique for non-stationary processes is illustrated by turbulence simulation during a front passage.

Analysing wind farm efficiency on complex terrains

Actual performances of onshore wind farms are deeply affected both by wake interactions and terrain complexity: therefore monitoring how the efficiency varies with the wind direction is a crucial task. Polar efficiency plot is therefore a useful tool for monitoring wind farm performances. The approach deserves careful discussion for onshore wind farms, where orography and layout commonly affect performance assessment. The present work deals with three modern wind farms, owned by Sorgenia Green, located on hilly terrains with slopes from gentle to rough. Further, onshore wind farm of Nprrekffir Enge has been analysed as a reference case: its layout is similar to offshore wind farms and the efficiency is mainly driven by wakes. It is shown and justified that terrain complexity imposes a novel and more consistent way for defining polar efficiency. Dependency of efficiency on wind direction, farm layout and orography is analysed and discussed. Effects of atmospheric stability have been also investigated through MERRA reanalysis data from NASA satellites. Monin-Obukhov Length has been used to discriminate climate regimes.

Some experimental investigations on the influence of the mounting arrangements on teh accuracy of cup-anemometer measurements

Abstract Through experiments carried out both in the field and in a large wind-tunnel it is demonstrated, that the way an anemometers is mounted on its supporting boom can cause the anemometer reading to be dependent on wind direction to an unacceptable large degree. Suggestions for removing this source of error in determining the correct wind speed are given.

Characterising Turbulence Intensity for Fatigue Load Analysis of Wind Turbines

Turbulence in wind velocity presents a major factor for modern wind turbine design as cost reduction as are sort for the dynamic structures. Therefore this paper contains a parametrisation of the turbulence intensity at given sites, relevant for the calculation of fatigue loading of wind turbines. The parameterisation is based on wind speed measurements extracted from the “Database on Wind Characteristics” (www.winddata.com). The parameterisation is based on the LogNormal distribution, which has proven to be suitable distribution to describe the turbulence intensity distribution.

IEA-Task 31 WAKEBENCH: Towards a protocol for wind farm flow model evaluation. Part 1: Flow-over-terrain models

The IEA Task 31 Wakebench is setting up a framework for the evaluation of wind farm flow models operating at microscale level. The framework consists on a model evaluation protocol integrated on a web-based portal for model benchmarking (www.windbench.net). This paper provides an overview of the building-block validation approach applied to flow-over-terrain models, including best practices for the benchmarking and data processing procedures for the analysis and qualification of validation datasets from wind resource assessment campaigns. A hierarchy of test cases has been proposed for flow-over-terrain model evaluation, from Monin- Obukhov similarity theory for verification of surface-layer properties, to the Leipzig profile for the near-neutral atmospheric boundary layer, to flow over isolated hills (Askervein and Bolund) to flow over mountaneous complex terrain (Alaiz). A summary of results from the first benchmarks are used to illustrate the model evaluation protocol applied to flow-over-terrain modeling in neutral conditions.

Dependence of offshore wind turbine fatigue loads on atmospheric stratification

The stratification of the atmospheric boundary layer (ABL) is classified in terms of the M-O length and subsequently used to determine the relationship between ABL stability and the fatigue loads of a wind turbine located inside an offshore wind farm. Recorded equivalent fatigue loads, representing blade-bending and tower bottom bending, are combined with the operational statistics from the instrumented wind turbine as well as with meteorological statistics defining the inflow conditions. Only a part of all possible inflow conditions are covered through the approximately 8200 hours of combined measurements. The fatigue polar has been determined for an (almost) complete 360° inflow sector for both load sensors, representing mean wind speeds below and above rated wind speed, respectively, with the inflow conditions classified into three different stratification regimes: unstable, neutral and stable conditions. In general, impact of ABL stratification is clearly seen on wake affected inflow cases for both blade and tower fatigue loads. However, the character of this dependence varies significantly with the type of inflow conditions – e.g. single wake inflow or multiple wake inflow.