scholarly journals Idealized WRF model sensitivity simulations of sea breeze types and their effects on offshore windfields

2012 ◽  
Vol 12 (6) ◽  
pp. 15837-15881 ◽  
Author(s):  
C. J. Steele ◽  
S. R. Dorling ◽  
R. von Glasow ◽  
J. Bacon
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Wrf Model ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Eastern Coast ◽  
State University ◽  
Sea Breezes ◽  
Gradient Wind

Abstract. The behaviour and characteristics of the marine component of sea breeze cells have received little attention relative to their onshore counterparts. Yet there is a growing interest and dependence on the offshore wind climate from, for example, a wind energy perspective. Using idealized model experiments, we investigate the sea breeze circulation at scales which approximate to those of the Southern North Sea, a region of major ongoing offshore wind farm development. We also contrast the scales and characteristics of the pure and the little known corkscrew and backdoor sea breeze types, where the type is pre-defined by the orientation of the synoptic scale flow relative to the shoreline. We find, crucially, that pure sea breezes, in contrast to corkscrew and backdoor types, can lead to substantial wind speed reductions offshore and that the addition of a second eastern coastline emphasises this effect through generation of offshore "calm zones". The offshore extent of all sea breeze types is found to be sensitive to both the influence of Coriolis acceleration and to the boundary layer scheme selected. These extents range, for example for a pure sea breeze produced in a 2 m s−1 offshore gradient wind, from 10 km to 40 km between the Mellor-Yamada-Nakanishi-Niino and the Yonsei State University schemes, respectively. The corkscrew type restricts the development of a backdoor sea breeze on the eastern coast and is also capable of traversing a 100 km offshore domain even under high gradient wind speed (>15 m s−1) conditions. Realistic variations in sea surface skin temperature during the sea breeze season do not significantly affect the circulation, suggesting that a thermal contrast is only needed as a precondition to the development of the sea breeze. We highlight how sea breeze impacts on circulation need to be considered in order to improve the accuracy of assessments of the offshore wind energy climate.

scholarly journals Idealized WRF model sensitivity simulations of sea breeze types and their effects on offshore windfields

2013 ◽  
Vol 13 (1) ◽  
pp. 443-461 ◽  
Author(s):  
C. J. Steele ◽  
S. R. Dorling ◽  
R. von Glasow ◽  
J. Bacon
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Wrf Model ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Energy Output ◽  
State University ◽  
Sea Breezes ◽  
Gradient Wind

Abstract. The behaviour and characteristics of the marine component of sea breeze cells have received little attention relative to their onshore counterparts. Yet there is a growing interest and dependence on the offshore wind climate from, for example, a wind energy perspective. Using idealized model experiments, we investigate the sea breeze circulation at scales which approximate to those of the southern North Sea, a region of major ongoing offshore wind farm development. We also contrast the scales and characteristics of the pure and the little known corkscrew and backdoor sea breeze types, where the type is pre-defined by the orientation of the synoptic scale flow relative to the shoreline. We find, crucially, that pure sea breezes, in contrast to corkscrew and backdoor types, can lead to substantial wind speed reductions offshore and that the addition of a second eastern coastline emphasises this effect through generation of offshore "calm zones". The offshore extent of all sea breeze types is found to be sensitive to both the influence of Coriolis acceleration and to the boundary layer scheme selected. These extents range, for example for a pure sea breeze produced in a 2 m s−1 offshore gradient wind, from 0 km to 21 km between the Mellor-Yamada-Nakanishi-Niino and the Yonsei State University schemes respectively. The corkscrew type restricts the development of a backdoor sea breeze on the opposite coast and is also capable of traversing a 100 km offshore domain even under high along-shore gradient wind speed (>15 m s−1) conditions. Realistic variations in sea surface skin temperature and initializing vertical thermodynamic profile do not significantly alter the resulting circulation, though the strengths of the simulated sea breezes are modulated if the effective land-sea thermal contrast is altered. We highlight how sea breeze impacts on circulation need to be considered in order to improve the accuracy of both assessments of the offshore wind energy climate and forecasts of wind energy output.

scholarly journals Recovery processes in coastal wind farms under sea-breeze conditions

2021 ◽  
Vol 56 ◽  
pp. 129-139
Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy
Keyword(s):  
Wind Farm ◽  
Wrf Model ◽  
Wind Farms ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Dominant Factor ◽  
Offshore Wind Farms ◽  
Sea Breezes ◽  
Wind Speeds ◽  
Recovery Processes

Abstract. With the rapid growth in offshore wind energy, it is important to understand the dynamics of offshore wind farms. Most of the offshore wind farms are currently installed in coastal regions where they are often affected by sea-breezes. In this work, we quantitatively study the recovery processes for coastal wind farms under sea-breeze conditions. We use a modified Borne's method to identify sea breeze days off the west coast of India in the Arabian Sea. For the identified sea breeze days, we simulate a hypothetical wind farm covering 50×50 km2 area using the Weather Research and Forecasting (WRF) model driven by realistic initial and boundary conditions. We use three wind farm layouts with the turbines spaced 0.5, 1, and 2 km apart. The results show an interesting power generation pattern with a peak at the upwind edge and another peak at the downwind edge due to sea breeze. Wind farms affect the circulation patterns, but the effects of these modifications are very weak compared to the sea breezes. Vertical recovery is the dominant factor with more than half of the momentum extracted by wind turbines being replenished by vertical turbulent mixing. However, horizontal recovery can also play a strong role for sparsely packed wind farms. Horizontal recovery is stronger at the edges where the wind speeds are higher whereas vertical recovery is stronger in the interior of the wind farms. This is one of the first studies to examine replenishment processes in offshore wind farms under sea breeze conditions. It can play an important role in advancing our understanding wind farm-atmospheric boundary layer interactions.

scholarly journals Wind Characteristics in the Taiwan Strait: A Case Study of the First Offshore Wind Farm in Taiwan

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6492
Author(s):  
Ke-Sheng Cheng ◽  
Cheng-Yu Ho ◽  
Jen-Hsin Teng
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Direction ◽  
Wind Farm ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Wind Speed Profile ◽  
Mean Wind Speed

This study analyzed the wind speed data of the met mast in the first commercial-scale offshore wind farm of Taiwan from May 2017 to April 2018. The mean wind speed and standard deviation, wind rose, histogram, wind speed profile, and diurnal variation of wind speed with associated changes in wind direction revealed some noteworthy findings. First, the standard deviation of the corresponding mean wind speed is somewhat high. Second, the Hellmann exponent is as low as 0.05. Third, afternoons in winter and nights and early mornings in summer have the highest and lowest wind speed in a year, respectively. Regarding the histogram, the distribution probability of wind is bimodal, which can be depicted as a mixture of two gamma distributions. In addition, the corresponding change between the hourly mean wind speed and wind direction revealed that the land–sea breeze plays a significant role in wind speed distribution, wind profile, and wind energy production. The low Hellmann exponent is discussed in detail. To further clarify the effect of the land–sea breeze for facilitating future wind energy development in Taiwan, we propose some recommendations.

scholarly journals Prospects for the development of offshore wind power along the coast of the Sea of Azov

2019 ◽  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Coastal Zone ◽  
Offshore Wind ◽  
Eastern Coast ◽  
Sea Of Azov ◽  
Offshore Wind Energy ◽  
Energy Potential ◽  
The Sea Of Azov

Introduction. One of the most popular alternative sources is wind energy. Offshore power stations are those which use kinetic energy of the wind and are built in shallow seas. Ukraine has access to the Black Sea and the Sea of Azov and has set the course to intensify the use of its own energy sources. It is therefore advisable to consider the development of offshore wind energy in its coastal zones. The purpose of this article is to analyze the energy potential of the coastal zone of the Sea of Azov to determine the prospects for offshore wind energy development. The main material. The economically feasible wind power of Ukraine is 16 GW but a significant percentage of its territory is not suitable for the installation of wind power plants, so it is advisable to use the seas area. In the coastal regions of Ukraine the average wind speed exceeds 5 m/s, which makes them effective in terms of using wind energy. Using GIS modeling, based on the data from the Global Atlas for Renewable Energy «IRENA», the spatial distribution of the average annual wind speed over the Sea of Azov at an altitude of 50, 100, 200 m has been analyzed. Due to the wind speed from 6 to 9 m/s, the Sea of Azov has significant wind energy potential. Wind speed rising from west to east has been detected. The concentration zone of maximum wind speed is the northern and north-eastern coast of the Sea of Azov. Accordingly, most electricity can be produced in Taganrog Bay, and the smallest amount– at the western coast of the sea. The data on the the generated power that could be extracted by a turbine installed in these areas at different altitudes has been calculated. At an altitude of 200 m, the figures are maximum and range from 9.4 to 30.3 GWh/year. In general, the wind indexes as well as the area of the zones suitable for the installation of wind farms increase with a height. In this case, it is economically advantageous to install large wind turbines with a tower height at 100 m. Conclusions and further research. The offshore wind energy in the coastal zone of the Sea of Azov can be developed, but it needs support at the state level. The prospect of this study is to analyze the limiting factors for this water area and to clarify the design areas of the industry.

scholarly journals An intercomparison of mesoscale models at simple sites for wind energy applications

2017 ◽  
Vol 2 (1) ◽  
pp. 211-228 ◽  
Author(s):  
Bjarke T. Olsen ◽  
Andrea N. Hahmann ◽  
Anna Maria Sempreviva ◽  
Jake Badger ◽  
Hans E. Jørgensen
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Weather Prediction ◽  
Atmospheric Stability ◽  
Resource Assessment ◽  
Offshore Wind ◽  
Grid Spacing ◽  
Energy Applications ◽  
Wind Resource

Abstract. Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated using a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft (< 4 %) and larger biases closer to the surface over land (> 7 %). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction.

scholarly journals Applications of satellite winds for the offshore wind farm site Anholt

2018 ◽  
Vol 3 (2) ◽  
pp. 573-588 ◽  
Author(s):  
Tobias Ahsbahs ◽  
Merete Badger ◽  
Patrick Volker ◽  
Kurt S. Hansen ◽  
Charlotte B. Hasager
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Weather Prediction ◽  
Wind Farms ◽  
Offshore Wind ◽  
Horizontal Wind ◽  
Offshore Wind Energy ◽  
Site Assessment ◽  
Scada System

Abstract. Rapid growth in the offshore wind energy sector means more offshore wind farms are placed closer to each other and in the lee of large land masses. Synthetic aperture radar (SAR) offers maps of the wind speed offshore with high resolution over large areas. These can be used to detect horizontal wind speed gradients close to shore and wind farm wake effects. SAR observations have become much more available with the free and open-access data from European satellite missions through Copernicus. Examples of applications and tools for using large archives of SAR wind maps to aid offshore site assessment are few. The Anholt wind farm operated by the utility company Ørsted is located in coastal waters and experiences strong spatial variations in the mean wind speed. Wind speeds derived from the Supervisory Control And Data Acquisition (SCADA) system are available at the turbine locations for comparison with winds retrieved from SAR. The correlation is good, both for free-stream and waked conditions. Spatial wind speed variations along the rows of wind turbines derived from SAR wind maps prior to the wind farm construction agree well with information gathered by the SCADA system and a numerical weather prediction model. Wind farm wakes are detected by comparisons between images before and after the wind farm construction. SAR wind maps clearly show wakes for long and constant fetches but the wake effect is less pronounced for short and varying fetches. Our results suggest that SAR wind maps can support offshore wind energy site assessment by introducing observations in the early phases of wind farm projects.

Investigating the Influence of MCP Uncertainties on the Energy Storage Capacity Requirements for Offshore Windfarms

2019 ◽  
Author(s):  
Michael D. Mifsud ◽  
Robert N. Farrugia ◽  
Tonio Sant
Keyword(s):  
Time Series ◽  
Energy Storage ◽  
Wind Speed ◽  
Wind Energy ◽  
Power Output ◽  
Energy Demand ◽  
Wind Farm ◽  
High Energy ◽  
Offshore Wind ◽  
Wind Data

Abstract Recent studies have shown that the intermittency of wind energy can be mitigated by means of an energy storage system (ESS). Energy can be stored during periods of low energy demand and high wind availability to then be utilised during periods of high energy demand. Measure-Correlate-Predict (MCP) methodologies are used to predict the wind speed and direction at a wind farm candidate site, hence enabling the estimation of the power output from the wind farm. Once energy storage is integrated with the wind farm, it is no longer only a matter of estimating the power output from the windfarm, but it is also important to model the behaviour of the ESS in conjunction with the energy demand. The latter is expected to depend, amongst other factors, on the reliability of the MCP methodology used. This paper investigates how different MCP methodologies influence the projected time series behaviour and the capacity requirements of ESS systems coupled to offshore wind farms. The analysis is based on wind data captured by a LiDAR system installed at a coastal location and from the Meteorological Office at Malta International Airport in the Maltese Islands. Different MCP methodologies are used to generate wind speed and direction time series at a candidate offshore wind farm site for various array layouts. The latter are then used in WindPRO® to estimate the time series power production for each MCP methodology and wind farm layout. This is repeated with actual wind data, such that the percentage error in energy yield from each MCP methodology is quantified, and the more reliable methodology could be identified. While it is evident that the integration of storage will reduce the need for wind energy curtailment, the reliability of the MCP methodology used is found to be crucial for proper estimation of the behaviour of the ESS.

Recovery processes in coastal wind farms

2021 ◽  
Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Mesoscale Model ◽  
Turbulent Transport ◽  
Wind Farms ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Sea Breezes ◽  
Recovery Processes

&lt;p&gt;Wind turbines in a wind farm extract energy from the atmospheric flow and convert it into electricity, resulting in a localized momentum deficit in the wake that reduces energy availability for downwind turbines. Atmospheric momentum convergence from above, below, and sides into the wakes replenish the lost momentum, at least partially, so that turbines deep inside a wind farm can continue to function. In this study, we explore recovery processes in hypothetical offshore wind farms with particular emphasis on comparing the spatial patterns and magnitudes of horizontal and vertical recovery processes and understanding the role of mesoscale phenomena like sea breezes in momentum recovery in wind farms.&lt;/p&gt;&lt;p&gt;For this study, we use the Weather Research and Forecasting (WRF) model, a state-of-the-art mesoscale model equipped with a wind turbine parameterization, to simulate deep offshore and coastal wind farms with different wind turbine spacings under realistic initial and boundary conditions. The wind farms consist of 10000 turbines rated 3 MW spread over a 50 km x 50 km area. We conduct experiments with various background conditions, including low wind, high wind, and sea breeze cases identified using Borne&amp;#8217;s method.&lt;/p&gt;&lt;p&gt;Results show that for deep offshore wind farms, power generation peaks at the upwind edge and monotonically decreases downwind into the interior due to cumulative wake effects of multiple rows of turbines. Vertical turbulent transport of momentum from aloft is the main contributor to recovery except in cases with strong background winds and high inter-turbine spacing where horizontal advective momentum transport can also contribute equally. Coastal wind farms behave similarly in the absence of sea-breezes.&amp;#160; However, under sea breeze conditions, the power production is high at the upwind edge and decreases thereafter but starts to increase again towards the downwind edge of the wind farm because of the sea breeze. The results further show that the contribution of horizontal (vertical) recovery in case of sea breeze conditions increases (decreases) to around 14% (86%) as compared to the non-sea breeze conditions where the horizontal (vertical) recovery contributes 9% (90%) to the momentum recovery in the wind farms. Vertical recovery shows a systematic dependence on wind farm density and wind speed. This relationship can be quantified using low-order empirical equations that can perhaps be used to develop parameterizations for replenishment in linear wake models. Overall, this study is likely to significantly advance our understanding of recovery processes in wind farms and wind farm-ABL interactions.&lt;/p&gt;

scholarly journals Applications of satellite winds for the offshore wind farm site Anholt

2018 ◽  
Author(s):  
Tobias Ahsbahs ◽  
Merete Badger ◽  
Patrick Volker ◽  
Kurt S. Hansen ◽  
Charlotte B. Hasager
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Prediction Models ◽  
Weather Prediction ◽  
Offshore Wind ◽  
Horizontal Wind ◽  
Offshore Wind Energy ◽  
Site Assessment ◽  
Scada System

Abstract. Rapid growth in the offshore wind energy sector means more offshore wind farms are placed closer to each other and in the lee of large land masses. Synthetic Aperture Radar (SAR) offers maps of the wind speed offshore with high resolution over large areas. These can be used to detect horizontal wind speed gradients close to shore and wind farm wake effects. SAR observations have become much more available with the free and open access to data from European satellite missions through Copernicus. Examples of applications and tools for using large archives of SAR wind maps to aid offshore site assessment are few. The Anholt wind farm operated by the utility company Ørsted is located in coastal waters and experiences strong spatial variations in the mean wind speed. Wind speeds derived from the Supervisory Control And Data Acquisition (SCADA) system are available at the turbine locations for comparison with winds retrieved from SAR. The correlation is good, both for free stream and waked conditions. Spatial wind speed variations within the wind farm derived from SAR wind maps prior to the wind farm construction are found to agree well with information gathered by the SCADA system and numerical weather prediction models. Wind farm wakes are detected by comparisons between images before and after the wind farm construction. SAR wind maps clearly show wakes for long constant fetches but the wake effect is less pronounced for short varying fetches. Our results suggest that SAR wind maps can support offshore wind energy site assessment by introducing observations in the early phases of wind farm projects.

scholarly journals OFFSHORE WIND ENERGY RESOURCE ASSESSMENT IN MALAYSIA WITH SATELLITE ALTIMETRY

2020 ◽  
Vol 15 (6) ◽  
pp. 111-124
Author(s):  
FARAH ELLYZA HASHIM ◽  
◽  
OSCAR PEYRE ◽  
SARAH JOHNSON LAPOK ◽  
OMAR YAAKOB ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Satellite Altimetry ◽  
Wind Farm ◽  
Energy Resource ◽  
Energy Resources ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Offshore Wind Farm ◽  
Wind Energy Resources

Realistic view on the potential of offshore wind farm development in Malaysia is necessary and requires accurate and wide coverage of wind speed data. Long term global datasets of satellite altimetry of wind speed provide a potentially valuable resource to identify the potential of offshore wind energy in Malaysia. This paper presents three different assessments of offshore wind energy resources in Malaysia using satellite altimetry. The wind speed data obtained from Radar Altimeter Database System (RADS) were validated and identified to be in agreement with previous studies. The resources were then assessed at three different levels; theoretical, technical and practical offshore wind energy potential. The technical resource potential was assessed by taking into consideration the available offshore wind turbine technology. Conflicting uses and environmental constraints that define the practical offshore wind energy resources are plotted on the maps to present a practicality of offshore wind farm development in Malaysian sea. The study concluded that, in theoretical view, Malaysia does have potential of offshore wind energy resource especially in Borneo Water with average annual wind energy density above 500 kWh/m2. However, the development of offshore wind farm in Malaysia will be difficult taking into consideration the technical and practical challenge.

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