Complex terrain experiments in the New European Wind Atlas

Deploying Taller Turbines in Complex Terrain: A Hill Flow Study (HilFlowS) Perspective

Terrain-induced flow acceleration is presented for the summertime, peak power season at Lawrence Livermore National Laboratory’s Site 300 for the Hill Flow Study (HilFlowS). HilFlowS, designed as an adjunct field campaign to the Department of Energy’s Second Wind Forecasting Improvement Project (WFIP2), provides wind profile observations at a second location in complex terrain for validating numerical atmospheric model simulations and for better understanding flow behavior over hills for wind power generation. One unique feature of HilFlowS was the inclusion of an undergraduate university student who helped plan and execute the experiment as well as analyze wind data from two remote sensing laser detection and ranging (lidar) instruments deployed along parallel ridgelines. HilFlowS examines the trend of building higher into the atmosphere for the purpose of increasing wind turbine power production and evaluates the wind resource in the Altamont Pass Region of Northern California for a set of wind turbines of differing hub-heights and rotor-disk diameters found in the area. The wind profiles show strongly channeled onshore flow above both hills, enhanced by strong subsidence aloft, which produces a wind maximum (Umax) around z = 10 m and strong negative shear throughout all of the evaluated rotor-disks for much of the summer wind season. Under these conditions, shear becomes more negative with increasing hub-height and increasing rotor-disk size. Rotor-disk equivalent wind speed (Uequiv), a measure of the average wind speed across the entire rotor-disk, is compared to hub-height, rotor length, and rated capacity factor for the set of turbines. Uequiv is most closely related to turbine hub-height and is negatively correlated given the low altitude of Umax. Based on these results, building the largest capacity, large rotor-disk wind turbine at the lowest possible hub-height appears to provide turbines in the Altamont with a fast, near-surface, onshore wind resource during the peak power season.

A Multi-Point Meso–Micro Downscaling Method Including Atmospheric Stratification

In wind energy site assessment, one major challenge is to represent both the local characteristics as well as general representation of the wind climate on site. Micro-scale models (e.g., Reynolds-Averaged-Navier-Stokes (RANS)) excel in the former, while meso-scale models (e.g., Weather Research and Forecasting (WRF)) in the latter. This paper presents a fast approach for meso–micro downscaling to an industry-applicable computational fluid dynamics (CFD) modeling framework. The model independent postprocessing tool chain is applied using the New European Wind Atlas (NEWA) on the meso-scale and THETA on the micro-scale side. We adapt on a previously developed methodology and extend it using a micro-scale model including stratification. We compare a single- and multi-point downscaling in critical flow situations and proof the concept on long-term mast data at Rödeser Berg in central Germany. In the longterm analysis, in respect to the pure meso-scale results, the statistical bias can be reduced up to 45% with a single-point downscaling and up to 107% (overcorrection of 7%) with a multi-point downscaling. We conclude that single-point downscaling is vital to combine meso-scale wind climate and micro-scale accuracy. The multi-point downscaling is further capable to include wind shear or veer from the meso-scale model into the downscaled velocity field. This adds both, accuracy and robustness, by minimal computational cost. The new introduction of stratification in the micro-scale model provides a marginal difference for the selected stability conditions, but gives a prospect on handling stratification in wind energy site assessment for future applications.

Power and Wind Shear Implications of Large Wind Turbine Scenarios in the US Central Plains

Continued growth of wind turbine physical dimensions is examined in terms of the implications for wind speed, power and shear across the rotor plane. High-resolution simulations with the Weather Research and Forecasting model are used to generate statistics of wind speed profiles for scenarios of current and future wind turbines. The nine-month simulations, focused on the eastern Central Plains, show that the power scales broadly as expected with the increase in rotor diameter (D) and wind speeds at hub-height (H). Increasing wind turbine dimensions from current values (approximately H = 100 m, D = 100 m) to those of the new International Energy Agency reference wind turbine (H = 150 m, D = 240 m), the power across the rotor plane increases 7.1 times. The mean domain-wide wind shear exponent (α) decreases from 0.21 (H = 100 m, D = 100 m) to 0.19 for the largest wind turbine scenario considered (H = 168 m, D = 248 m) and the frequency of extreme positive shear (α > 0.2) declines from 48% to 38% of 10-min periods. Thus, deployment of larger wind turbines potentially yields considerable net benefits for both the wind resource and reductions in fatigue loading related to vertical shear.

Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements

To study the wake development characteristics of wind farms in complex terrains, two different types of Light Detection and Ranging (LiDAR) were used to conduct the field measurements in a mountain wind farm in Hebei Province, China. Under two different incoming wake conditions, the influence of wind shear, terrain and incoming wind characteristics on the development trend of wake was analyzed. The results showed that the existence of wind shear effect causes asymmetric distribution of wind speed in the wake region. The relief of the terrain behind the turbine indicated a subsidence of the wake centerline, which had a linear relationship with the topography altitudes. The wake recovery rates were calculated, which comprehensively validated the conclusion that the wake recovery rate is determined by both the incoming wind turbulence intensity in the wake and the magnitude of the wind speed.

Spatial Variability of the Lower Atmospheric Boundary Layer over Hilly Terrain as Observed with an RPAS

The operation of a Remotely Piloted Aircraft System (RPAS) over a hilly area in northern Germany allows inspection of the variability of the profiles of temperature, humidity, and wind speed next to a small hill. Four cases in nearly stationary conditions are analyzed. Two events are windy, one overcast and the other with clear skies, whereas the two other cases have weak winds, one overcast, and one with clear skies and dissipating mist. The profiles are made at five locations surrounding the hill, separated by a distance from each other of 5 km at most, sampling up to 130 m above the ground. The average profiles and their standard deviations indicate that the variability in the windy cases is approximately constant with height, likely linked to the turbulent flow itself, whereas, for the weak wind cases, the variability diminishes with height, and it is probably linked to the surface variability. The variability between soundings is large. The computation of the root mean square error with respect to the average of the soundings for each case shows that the site closest to the average is the one over open terrain and low vegetation, whereas the site in the forest is the farthest from average. Comparison with the profiles to the nearest grid point of the European Centre for Medium-Range Weather Forecasts (ECMWF) model shows that the closest values are provided by the average of the soundings and by the site closest to the average. Despite the small dataset collected during this exercise, the methodology developed here can be used for more cases and locations with the aim to characterize better the local variability in the lower atmosphere. In this sense, a non-dimensional heterogeneity index is proposed to quantify the topographically and thermally induced variability in complex terrain.

A Review of Progress and Applications of Pulsed Doppler Wind LiDARs

Doppler wind LiDAR (Light Detection And Ranging) makes use of the principle of optical Doppler shift between the reference and backscattered radiations to measure radial velocities at distances up to several kilometers above the ground. Such instruments promise some advantages, including its large scan volume, movability and provision of 3-dimensional wind measurements, as well as its relatively higher temporal and spatial resolution comparing with other measurement devices. In recent decades, Doppler LiDARs developed by scientific institutes and commercial companies have been well adopted in several real-life applications. Doppler LiDARs are installed in about a dozen airports to study aircraft-induced vortices and detect wind shears. In the wind energy industry, the Doppler LiDAR technique provides a promising alternative to in-situ techniques in wind energy assessment, turbine wake analysis and turbine control. Doppler LiDARs have also been applied in meteorological studies, such as observing boundary layers and tracking tropical cyclones. These applications demonstrate the capability of Doppler LiDARs for measuring backscatter coefficients and wind profiles. In addition, Doppler LiDAR measurements show considerable potential for validating and improving numerical models. It is expected that future development of the Doppler LiDAR technique and data processing algorithms will provide accurate measurements with high spatial and temporal resolutions under different environmental conditions.

Turbulence Measurements with Dual-Doppler Scanning Lidars

Velocity-component variances can be directly computed from lidar measurements using information of the second-order statistics within the lidar probe volume. Specifically, by using the Doppler radial velocity spectrum, one can estimate the unfiltered radial velocity variance. This information is not always available in current lidar campaigns. The velocity-component variances can also be indirectly computed from the reconstructed velocities but they are biased compared to those computed from, e.g., sonic anemometers. Here we show, for the first time, how to estimate such biases for a multi-lidar system and we demonstrate, also for the first time, their dependence on the turbulence characteristics and the lidar beam scanning geometry relative to the wind direction. For a dual-Doppler lidar system, we also show that the indirect method has an advantage compared to the direct one for commonly-used scanning configurations due to the singularity of the system. We demonstrate that our estimates of the radial velocity and velocity-component biases are accurate by analysis of measurements performed over a flat site using a dual-Doppler lidar system, where both lidars stared over a volume close to a sonic anemometer at a height of 100 m. We also show that mapping these biases over a spatial domain helps to plan meteorological campaigns, where multi-lidar systems can potentially be used. Particularly, such maps help the multi-point mapping of wind resources and conditions, which improve the tools needed for wind turbine siting.

Grand challenges in the science of wind energy

Harvested by advanced technical systems honed over decades of research and development, wind energy has become a mainstream energy resource. However, continued innovation is needed to realize the potential of wind to serve the global demand for clean energy. Here, we outline three interdependent, cross-disciplinary grand challenges underpinning this research endeavor. The first is the need for a deeper understanding of the physics of atmospheric flow in the critical zone of plant operation. The second involves science and engineering of the largest dynamic, rotating machines in the world. The third encompasses optimization and control of fleets of wind plants working synergistically within the electricity grid. Addressing these challenges could enable wind power to provide as much as half of our global electricity needs and perhaps beyond.

Wind-Turbine and Wind-Farm Flows: A Review

Wind energy, together with other renewable energy sources, are expected to grow substantially in the coming decades and play a key role in mitigating climate change and achieving energy sustainability. One of the main challenges in optimizing the design, operation, control, and grid integration of wind farms is the prediction of their performance, owing to the complex multiscale two-way interactions between wind farms and the turbulent atmospheric boundary layer (ABL). From a fluid mechanical perspective, these interactions are complicated by the high Reynolds number of the ABL flow, its inherent unsteadiness due to the diurnal cycle and synoptic-forcing variability, the ubiquitous nature of thermal effects, and the heterogeneity of the terrain. Particularly important is the effect of ABL turbulence on wind-turbine wake flows and their superposition, as they are responsible for considerable turbine power losses and fatigue loads in wind farms. These flow interactions affect, in turn, the structure of the ABL and the turbulent fluxes of momentum and scalars. This review summarizes recent experimental, computational, and theoretical research efforts that have contributed to improving our understanding and ability to predict the interactions of ABL flow with wind turbines and wind farms.

The NEWA Ferry Lidar Experiment: Measuring Mesoscale Winds in the Southern Baltic Sea

This article presents the Ferry Lidar Experiment, which is one of the NEWA Experiments, a set of unique flow experiments conducted as part of the New European Wind Atlas (NEWA) project. These experiments have been prepared and conducted to create adequate datasets for mesoscale and microscale model validation. For the Ferry Lidar Experiment a Doppler lidar instrument was placed on a ferry connecting Kiel and Klaipeda in the Southern Baltic Sea from February to June 2017. A comprehensive set of all relevant motions was recorded together with the lidar data and processed in order to obtain and provide corrected wind time series. Due to the existence of the motion effects, the obtained data are essentially different from typical on-site data used for wind resource assessments in the wind industry. First comparisons show that they can be well related to mapped wind trajectories from the output of a numerical weather prediction model showing a reasonable correlation. More detailed validation studies are planned for the future.

Complex behaviour in complex terrain - Modelling bird migration in a high resolution wind field across mountainous terrain to simulate observed patterns

Crossing of large ecological barriers, such as mountains, is in terms of energy considered to be a demanding and critical step during bird migration. Besides forming a geographical barrier, mountains have a profound impact on the resulting wind flow. We use a novel framework of mathematical models to investigate the influences of wind and topography on nocturnal passerine bird behaviour, and to assess the energy costs for different flight strategies for crossing the Jura Mountains. The mathematical models include three biological models of bird behaviour: i) wind drift compensation; ii) adaptation of flight height for favourable winds; and, iii) avoidance of obstacles (cross over and/or circumvention of an obstacle following a minimum energy expenditure strategy), which are assessed separately and in combination. Further, we use a mesoscale weather model for high-resolution predictions of the wind fields. We simulate the broad front nocturnal passerine migration for autumn nights with peak migration intensities. The bird densities retrieved from a weather radar are used as the initial intensities and to specify the vertical distributions of the simulated birds. It is shown that migration over complex terrain represents the most expensive flight option in terms of energy expenditure, and wind is seen to be the main factor that influences the energy expenditure in the bird's preferred flight direction. Further, the combined effects of wind and orography lead to a high concentration of migratory birds within the favourable wind conditions of the Swiss lowlands and north of the Jura Mountains.

Meteorological Applications Benefiting from an Improved Understanding of Atmospheric Exchange Processes over Mountains

This paper reviews the benefits of a better understanding of atmospheric exchange processes over mountains. These processes affect weather and climate variables that are important in meteorological applications related to many scientific disciplines and sectors of the economy. We focus this review on examples of meteorological applications in hydrology, ecology, agriculture, urban planning, wind energy, transportation, air pollution, and climate change. These examples demonstrate the benefits of a more accurate knowledge of atmospheric exchange processes over mountains, including a better understanding of snow redistribution, microclimate, land-cover change, frost hazards, urban ventilation, wind gusts, road temperatures, air pollution, and the impacts of climate change. The examples show that continued research on atmospheric exchange processes over mountains is warranted, and that a recognition of the potential benefits can inspire new research directions. An awareness of the links between basic research topics and applications is important to the success and impact of new efforts that aim at better understanding atmospheric exchange processes over mountains. To maximize the benefits of future research for meteorological applications, coordinated international efforts involving scientists studying atmospheric exchange processes, as well as scientists and stakeholders representing many other scientific disciplines and economic sectors are required.

Reducing the Uncertainty of Lidar Measurements in Complex Terrain Using a Linear Model Approach

In complex terrain, ground-based lidar wind speed measurements sometimes show noticeable differences compared to measurements made with in-situ sensors mounted on meteorological masts. These differences are mostly caused by the inhomogeneities of the flow field and the applied reconstruction methods. This study investigates three different methods to optimize the reconstruction algorithm in order to improve the agreement between lidar measurements and data from sensors on meteorological masts. The methods include a typical velocity azimuth display (VAD) method, a leave-one-out cross-validation method, and a linear model which takes into account the gradients of the wind velocity components. In addition, further aspects such as the influence of the half opening angle of the scanning cone and the scan duration are considered. The measurements were carried out with two different lidar systems, that measured simultaneously. The reference was a 100 m high meteorological mast. The measurements took place in complex terrain characterized by a 150 m high escarpment. The results from the individual methods are quantitatively compared with the measurements of the cup anemometer mounted on the meteorological mast by means of the three parameters of a linear regression (slope, offset, R 2 ) and the width of the 5th–95th quantile. The results show that expanding the half angle of the scanning cone from 20 ∘ to 55 ∘ reduces the offset by a factor of 14.9, but reducing the scan duration does not have an observable benefit. The linear method has the lowest uncertainty and the best agreement with the reference data (i.e., lowest offset and scatter) of all of the methods that were investigated.

Introduction Wind farms in complex terrains: an introduction

Wind energy is one of the fastest growing sources of sustainable energy production. As more wind turbines are coming into operation, the best locations are already becoming occupied by turbines, and wind-farm developers have to look for new and still available areas-locations that may not be ideal such as complex terrain landscapes. In these locations, turbulence and wind shear are higher, and in general wind conditions are harder to predict. Also, the modelling of the wakes behind the turbines is more complicated, which makes energy-yield estimates more uncertain than under ideal conditions. This theme issue includes 10 research papers devoted to various fluid-mechanics aspects of using wind energy in complex terrains and illustrates recent progress and future developments in this important field.This article is part of the themed issue 'Wind energy in complex terrains'.