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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: closed (13 September 2021) | Viewed by 45085
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Special Issue Editors

Prof. Dr. Sukanta Basu

E-Mail Website
Guest Editor

Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CD Delft, The Netherlands
Interests: atmospheric turbulence; boundary-layer meteorology; large-eddy simulation; mesoscale modeling; short-term forecasting; wake modeling; wind resource assessment
Special Issues, Collections and Topics in MDPI journals

Dr. Javier Sanz Rodrigo

E-Mail Website
Guest Editor

National Renewable Energy Centre (CENER), 31621 Sarriguren, Spain
Interests: wind resource assessment; wake modeling; wind power forecasting; remote sensing; multi-scale atmospheric physics; farm-farm interaction; uncertainty quantification

Special Issue Information

Dear Colleagues,

In recent years, the wind energy community has started to recognize the impact of various weather phenomena (e.g., low-level jets, downbursts) on wind energy production and structural loading. At the same time, intriguing atmosphere–wind farm interactions (e.g., global blockage effect, deep array effect) have been discovered, and their relationship to atmospheric stability conditions has been quantified. Owing to the tremendous advances in the arena of deep learning and data science, significant progress has also been made in wind resource assessment, micrositing, and wind power forecasting during this period. Some of these new findings have been reported in recent conferences and workshops. We believe that the time is opportune to devote a Special Issue to these various new findings pertaining to wind power meteorology. Specifically, we welcome articles on the following topics (including but not limited to):

Wind resource estimation and micrositing

Flow over complex terrain;
Offshore wind resource;
High-altitude wind resource;
Novel instrumentations (e.g., scanning lidar, ADM-aeolus);
Advanced numerical modeling (e.g., gray-zone and large-eddy simulations);
Physical and statistical downscaling;
Uncertainty quantification;
Impact of low-level jets, land-sea breeze circulations, etc.;

Wind farm wakes

In situ and remote sensing of wakes;
Parameterization and modeling of wakes;
Model intercomparison studies

Wind farm–atmosphere interactions

Global blockage effect;
Deep array effect;
Farm–farm interactions

Wind forecasting

Numerical weather prediction;
Data-based forecasting;
Hybrid approaches;
Seasonal forecasting;

Wind ramps and associated weather phenomena

Frontal passage;
Thunderstorm outflow;
Dry line;

Extreme winds and their impact on loadings

Wind gust;
Downburst, tornado, waterspout;
Tropical and mid-latitude cyclones;

Microclimatic impacts of wind farms

Future wind energy developments in a changing climate.

Prof. Dr. Sukanta Basu
Dr. Javier Sanz Rodrigo
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

farm–farm interactions
forecasting
global blockage
lidar
micrositing
numerical weather prediction
resource assessment
uncertainty quantification
wake
wind ramp

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Published Papers (11 papers)

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Research

26 pages, 5378 KiB

Open AccessArticle

Evaluating Terrain as a Turbulence Generation Method

by Patrick Hawbecker and Matthew Churchfield

Energies 2021, 14(21), 6858; https://doi.org/10.3390/en14216858 - 20 Oct 2021

Cited by 3 | Viewed by 1795

Abstract

When driving microscale large-eddy simulations with mesoscale model solutions, turbulence will take space to develop, known as fetch, on the microscale domain. To reduce fetch, it is common to add perturbations near the boundaries to speed up turbulence development. However, when simulating domains over complex terrain, it is possible that the terrain itself can quickly generate turbulence within the boundary layer. It is shown here that rugged terrain is able to generate turbulence without the assistance of a perturbation strategy; however, the levels of turbulence generated are improved when adding perturbations at the inlet. Flow over smoothed, but not flat, terrain fails to generate adequate turbulence throughout the boundary layer in all tests conducted herein. Sensitivities to the strength of the mean wind speed and boundary layer height are investigated and show that higher wind speeds produce turbulence over terrain features that slower wind speeds do not. Further, by increasing the height of the capping inversion, the effectiveness of topography alone to generate turbulence throughout the depth of the boundary is diminished. In all cases, the inclusion of a perturbation strategy improved simulation performance with respect to turbulence development. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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14 pages, 1282 KiB

Open AccessArticle

A Brief Climatology of Dunkelflaute Events over and Surrounding the North and Baltic Sea Areas

by Bowen Li, Sukanta Basu, Simon J. Watson and Herman W. J. Russchenberg

Energies 2021, 14(20), 6508; https://doi.org/10.3390/en14206508 - 11 Oct 2021

Cited by 20 | Viewed by 8808

Abstract

In the coming decades, the European energy system is expected to become increasingly reliant on non-dispatchable generation such as wind and solar power. Under such a renewable energy scenario, a better characterization of the extreme weather condition ‘Dunkelflaute’, which can lead to a sustained reduction of wind and solar power, is important. In this paper, we report findings from the very first climatological study of Dunkelflaute events occurring in eleven countries surrounding the North and Baltic Sea areas. By utilizing multi-year meteorological and power production datasets, we have quantified various statistics pertaining to these events and also identified their underlying meteorological drivers. It was found that almost all periods tagged as Dunkelflaute events (with a length of more than 24 h) are in November, December, and January for these countries. On average, there are 50–100 h of such events happening in each of these three months per year. The limited wind and solar power production during Dunkelflaute events is shown to be mainly driven by large-scale high-pressure systems and extensive low-cloud coverage. Even though the possibility of simultaneous Dunkelflaute events in neighboring countries can be as high as 30–40%, such events hardly occur simultaneously in all the eleven countries. Through an interconnected EU-11 power system, the mean frequency of Dunkelflaute drops from 3–9% for the individual countries to approximately 3.5% for the combined region, highlighting the importance of aggregating production over a wide area to better manage the integration of renewable energy generation. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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16 pages, 2150 KiB

Open AccessArticle

Time-Dependent Upper Limits to the Performance of Large Wind Farms Due to Mesoscale Atmospheric Response

by Kelan Patel, Thomas D. Dunstan and Takafumi Nishino

Energies 2021, 14(19), 6437; https://doi.org/10.3390/en14196437 - 8 Oct 2021

Cited by 10 | Viewed by 3007

Abstract

A prototype of a new physics-based wind resource assessment method is presented, which allows the prediction of upper limits to the performance of large wind farms (including the power loss due to wind farm blockage) in a site-specific and time-dependent manner. The new method combines the two-scale momentum theory with a numerical weather prediction (NWP) model to assess the “extractability” of wind, i.e., how high the wind speed at a given site can be maintained as we increase the number of turbines installed. The new method is applied to an offshore wind farm site in the North Sea to demonstrate that: (1) Only a pair of NWP simulations (one without wind farm and the other with wind farm with an arbitrary level of flow resistance) are required to predict the extractability. (2) The extractability varies significantly from time to time, which may cause more than 30% of change in the upper limit of the performance of medium-to-high-density offshore wind farms. These results suggest the importance of considering not only the natural wind speed but also its extractability in the prediction of (both long- and short-term) power production of large wind farms. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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28 pages, 6377 KiB

Open AccessEditor’s ChoiceArticle

A Simulation Study on Risks to Wind Turbine Arrays from Thunderstorm Downbursts in Different Atmospheric Stability Conditions

by Nan-You Lu, Lance Manuel, Patrick Hawbecker and Sukanta Basu

Energies 2021, 14(17), 5407; https://doi.org/10.3390/en14175407 - 31 Aug 2021

Cited by 3 | Viewed by 2570

Abstract

Thunderstorm downbursts have been reported to cause damage or failure to wind turbine arrays. We extend a large-eddy simulation model used in previous work to generate downburst-related inflow fields with a view toward defining correlated wind fields that all turbines in an array would experience together during a downburst. We are also interested in establishing what role contrasting atmospheric stability conditions can play on the structural demands on the turbines. This interest is because the evening transition period, when thunderstorms are most common, is also when there is generally acknowledged time-varying stability in the atmospheric boundary layer. Our results reveal that the structure of a downburst’s ring vortices and dissipation of its outflow play important roles in the separate inflow fields for turbines located at different parts of the array; these effects vary with stability. Interacting with the ambient winds, the outflow of a downburst is found to have greater impacts in an “average” sense on structural loads for turbines farther from the touchdown center in the stable cases. Worst-case analyses show that the largest extreme loads, although somewhat dependent on the specific structural load variable considered, depend on the location of the turbine and on the prevailing atmospheric stability. The results of our calculations show the highest simulated foreaft tower bending moment to be 85.4 MN-m, which occurs at a unit sited in the array farther from touchdown center of the downburst initiated in a stable boundary layer. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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14 pages, 35536 KiB

Open AccessArticle

Associating Synoptic-Scale Weather Patterns with Aggregated Offshore Wind Power Production and Ramps

by Bedassa R. Cheneka, Simon J. Watson and Sukanta Basu

Energies 2021, 14(13), 3903; https://doi.org/10.3390/en14133903 - 29 Jun 2021

Cited by 6 | Viewed by 2536

Abstract

Large-scale weather patterns and their variability can influence both the amount of wind power production and its temporal variation, i.e., wind power ramps. In this study, we use a self-organizing map to cluster hourly sea level pressure into a discrete number of weather patterns. The dependency of wind power production and wind power ramps on these weather patterns is studied for the Belgian offshore wind farm fleet. A newly developed wavelet-surrogate ramp-detection algorithm is used for the identification of wind power ramps. It was observed that low-pressure systems, southwesterly and northeasterly wind flows are often associated with high levels of wind power production. Regarding wind power ramps, the type of transition between weather patterns was shown to determine whether ramp up or ramp down events would occur. Ramp up events tend to occur due to the transition from a high-pressure to a low-pressure system, or the weakening of the intensity of a deep low-pressure system. The reverse is associated with ramp down events. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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22 pages, 12669 KiB

Open AccessArticle

Advancing Wind Resource Assessment in Complex Terrain with Scanning Lidar Measurements

by Julia Gottschall, Alkistis Papetta, Hassan Kassem, Paul Julian Meyer, Linda Schrempf, Christian Wetzel and Johannes Becker

Energies 2021, 14(11), 3280; https://doi.org/10.3390/en14113280 - 3 Jun 2021

Cited by 6 | Viewed by 4495

Abstract

The planning and realization of wind energy projects requires an as accurate and precise wind resource estimation as possible. Standard procedures combine shorter on-site measurements with the application of numerical models. The uncertainties of the numerical data generated from these models are, particularly in complex onshore terrain, not just rather high but typically not well quantified. In this article we propose a methodology for using a single scanning Doppler wind lidar device to calibrate the output data of a numerical flow model and with this not just quantify but potentially also reduce the uncertainties of the final wind resource estimate. The scanning lidar is configured to perform Plan Position Indicator (PPI) scans and the numerical flow data are projected onto this geometry. Deviations of the derived from the recorded line-of-sight wind speeds are used to identify deficiencies of the model and as starting point for an improvement and tuning. The developed methodology is demonstrated based on a study for a site in moderately complex terrain in central Germany and using two rather different types of numerical flow models. The findings suggest that the use of the methodology and the introduced scanning wind lidar technology offers a promising opportunity to control the uncertainty of the applied flow models, which can otherwise only be estimated very roughly. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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14 pages, 4285 KiB

Open AccessArticle

Hourly Variation of Wind Speeds in the Philippines and Its Potential Impact on the Stability of the Power System

by Kevin Ray Español Lucas, Tomonori Sato and Masamichi Ohba

Energies 2021, 14(8), 2310; https://doi.org/10.3390/en14082310 - 20 Apr 2021

Cited by 3 | Viewed by 5475

Abstract

Wind energy development has been limited by concerns associated to the varying features in wind speed which tends to destabilize the power system. This study aims to clarify the variability of winds within a day in the Philippines, specifically the hourly changes of onshore horizontal winds at 100-m hub-heights. A whole one-year experiment using the Weather Research and Forecasting model shows that onshore wind speeds decrease during the transitional hours between land breeze and sea breeze. The decreases in wind speed are most significant over coastal regions with high sloping topography. The extreme decreases in wind speed during morning hours, due to the natural processes, are found to often occur at the same time as the extreme electricity undersupply caused by the morning increase in energy demand. This result warns that the power system stability in the Philippines may become more sensitive to the variability of wind as the share of wind energy generation increases in the future. The findings of this study can contribute to promote sustainability in the operation of existing wind-reliant power systems and planning of future wind energy developments. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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22 pages, 4722 KiB

Open AccessArticle

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

by Renko Buhr, Hassan Kassem, Gerald Steinfeld, Michael Alletto, Björn Witha and Martin Dörenkämper

Energies 2021, 14(4), 1191; https://doi.org/10.3390/en14041191 - 23 Feb 2021

Cited by 3 | Viewed by 3423

Abstract

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. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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19 pages, 13108 KiB

Open AccessArticle

Analysis of Random Forest Modeling Strategies for Multi-Step Wind Speed Forecasting

by Daniel Vassallo, Raghavendra Krishnamurthy, Thomas Sherman and Harindra J. S. Fernando

Energies 2020, 13(20), 5488; https://doi.org/10.3390/en13205488 - 20 Oct 2020

Cited by 37 | Viewed by 3222

Abstract

Although the random forest (RF) model is a powerful machine learning tool that has been utilized in many wind speed/power forecasting studies, there has been no consensus on optimal RF modeling strategies. This study investigates three basic questions which aim to assist in the discernment and quantification of the effects of individual model properties, namely: (1) using a standalone RF model versus using RF as a correction mechanism for the persistence approach, (2) utilizing a recursive versus direct multi-step forecasting strategy, and (3) training data availability on model forecasting accuracy from one to six hours ahead. These questions are investigated utilizing data from the FINO1 offshore platform and Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) C1 site, and testing results are compared to the persistence method. At FINO1, due to the presence of multiple wind farms and high inter-annual variability, RF is more effective as an error-correction mechanism for the persistence approach. The direct forecasting strategy is seen to slightly outperform the recursive strategy, specifically for forecasts three or more steps ahead. Finally, increased data availability (up to ∼8 equivalent years of hourly training data) appears to continually improve forecasting accuracy, although changing environmental flow patterns have the potential to negate such improvement. We hope that the findings of this study will assist future researchers and industry professionals to construct accurate, reliable RF models for wind speed forecasting. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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23 pages, 4103 KiB

Open AccessArticle

Single Column Model Simulations of Icing Conditions in Northern Sweden: Sensitivity to Surface Model Land Use Representation

by Erik Janzon, Heiner Körnich, Johan Arnqvist and Anna Rutgersson

Energies 2020, 13(16), 4258; https://doi.org/10.3390/en13164258 - 17 Aug 2020

Cited by 2 | Viewed by 2665

Abstract

In-cloud ice mass accretion on wind turbines is a common challenge that is faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests—including the cloud water response to surface roughness and albedo effects that are related to them—must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and, to the present date, not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME three-dimensional (3D) NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insolation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In autumn cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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26 pages, 1670 KiB

Open AccessArticle

Looking for an Offshore Low-Level Jet Champion among Recent Reanalyses: A Tight Race over the Baltic Sea

by Christoffer Hallgren, Johan Arnqvist, Stefan Ivanell, Heiner Körnich, Ville Vakkari and Erik Sahlée

Energies 2020, 13(14), 3670; https://doi.org/10.3390/en13143670 - 16 Jul 2020

Cited by 34 | Viewed by 5226

Abstract

With an increasing interest in offshore wind energy, focus has been directed towards large semi-enclosed basins such as the Baltic Sea as potential sites to set up wind turbines. The meteorology of this inland sea in particular is strongly affected by the surrounding land, creating mesoscale conditions that are important to take into consideration when planning for new wind farms. This paper presents a comparison between data from four state-of-the-art reanalyses (MERRA2, ERA5, UERRA, NEWA) and observations from LiDAR. The comparison is made for four sites in the Baltic Sea with wind profiles up to 300 m. The findings provide insight into the accuracy of reanalyses for wind resource assessment. In general, the reanalyses underestimate the average wind speed. The average shear is too low in NEWA, while ERA5 and UERRA predominantly overestimate the shear. MERRA2 suffers from insufficient vertical resolution, which limits its usefulness in evaluating the wind profile. It is also shown that low-level jets, a very frequent mesoscale phenomenon in the Baltic Sea during late spring, can appear in a wide range of wind speeds. The observed frequency of low-level jets is best captured by UERRA. In terms of general wind characteristics, ERA5, UERRA, and NEWA are similar, and the best choice depends on the application. Full article

(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)

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