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 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 Analysing uncertainties in offshore wind farm power output using measure–correlate–predict methodologies

2020 ◽  
Vol 5 (2) ◽  
pp. 601-621
Author(s):  
Michael Denis Mifsud ◽  
Tonio Sant ◽  
Robert Nicholas Farrugia
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Power Output ◽  
Wind Farm ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Offshore Wind ◽  
Energy Yield ◽  
Offshore Wind Farm ◽  
Power And Energy

Abstract. This paper investigates the uncertainties resulting from different measure–correlate–predict (MCP) methods to project the power and energy yield from a wind farm. The analysis is based on a case study that utilises short-term data acquired from a lidar wind measurement system deployed at a coastal site in the northern part of the island of Malta and long-term measurements from the island's international airport. The wind speed at the candidate site is measured by means of a lidar system. The predicted power output for a hypothetical offshore wind farm from the various MCP methodologies is compared to the actual power output obtained directly from the input of lidar data to establish which MCP methodology best predicts the power generated. The power output from the wind farm is predicted by inputting wind speed and direction derived from the different MCP methods into windPRO® (https://www.emd.dk/windpro, last access: 8 May 2020). The predicted power is compared to the power output generated from the actual wind and direction data by using the normalised mean absolute error (NMAE) and the normalised mean-squared error (NMSE). This methodology will establish which combination of MCP methodology and wind farm configuration will have the least prediction error. The best MCP methodology which combines prediction of wind speed and wind direction, together with the topology of the wind farm, is that using multiple linear regression (MLR). However, the study concludes that the other MCP methodologies cannot be discarded as it is always best to compare different combinations of MCP methodologies for wind speed and wind direction, together with different wake models and wind farm topologies.

scholarly journals Analysing Uncertainties in Offshore Wind Farm Power Output using Measure Correlate Predict Methodologies

2019 ◽  
Author(s):  
Michael Denis Mifsud ◽  
Tonio Sant ◽  
Robert Nicholas Farrugia
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Power Output ◽  
Wind Farm ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Offshore Wind ◽  
Energy Yield ◽  
Offshore Wind Farm ◽  
The Mean

Abstract. This paper investigates the uncertainties resulting from different Measure-Correlate-Predict methods to project the power and energy yield from a wind farm. The analysis is based on a case study that utilizes short-term data acquired from a LiDAR wind measurement system deployed at a coastal site in the northern part of the island of Malta and long-term measurements from the island’s international airport. The wind speed at the candidate site is measured by means of a LiDAR system. The predicted power output for a hypothetical offshore wind farm from the various MCP methodologies is compared to the actual power output obtained directly from the input of LiDAR data to establish which MCP methodology best predicts the power generated. The power output from the wind farm is predicted by inputting wind speed and direction derived from the different MCP methods into windPRO® (https://www.emd.dk/windpro). The predicted power is compared to the power output generated from the actual wind and direction data by using the Mean Squared Error (MSE) and the Mean Absolute Error (MAE) measures. This methodology will establish which combination of MCP methodology and wind farm configuration will have the least prediction error. The best MCP methodology which combines prediction of wind speed and wind direction, together with the topology of the wind farm, is that using Artificial Neural Networks. However, the study concludes that the other MCP methodologies cannot be discarded as it is always best to compare different combinations of MCP methodologies for wind speed and wind direction, together with different wake models and wind farm topologies.

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.

scholarly journals Analysis of Wind Speed Shear and Turbulence LiDAR Measurements to Support Offshore Wind in the Northeast United States

2018 ◽  
Author(s):  
Anthony Viselli ◽  
Nathan Faessler ◽  
Matthew Filippelli
Keyword(s):  
United States ◽  
Wind Speed ◽  
Wind Farm ◽  
Mesoscale Model ◽  
American Petroleum Institute ◽  
Offshore Wind ◽  
Wind Speed Profile ◽  
Northeast United States ◽  
Lidar Measurements ◽  
Wind Shears

This paper presents wind speed measurements collected at 40m to 200m above sea-level to support the New England Aqua Ventus I 12 MW Floating Offshore Wind Farm to be located 17km offshore the Northeast United States. The high-altitude wind speed data are unique and represent some of the first measurements made offshore in this part of the country which is actively being developed for offshore wind. Multiple LiDAR measurements were made using a DeepCLiDAR floating buoy and LiDARs located on land on a nearby island. The LiDARs compared favorably thereby confirming the LiDAR buoy measurements. Wind speed shear profiles are presented. The measurements are compared against industry standard mesoscale model outputs and offshore design codes including the American Bureau of Shipping, American Petroleum Institute, and DNV-GL guides. Significant variation in the vertical wind speed profile occurs throughout the year. This variation is not currently addressed in offshore wind design standards which typically recommend the use of only a few values for wind shear in operational and extreme conditions. The mean wind shears recorded were also higher than industry recommended values. Additionally, turbulence measurements made from the LiDAR, although not widely accepted in the scientific community, are presented and compared against industry guidelines.

scholarly journals An Evaluation of the Wind Energy Resources along the Spanish Continental Nearshore

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3986 ◽  
Author(s):  
Florin Onea ◽  
Andrés Ruiz ◽  
Eugen Rusu
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbines ◽  
Offshore Wind ◽  
Time Interval ◽  
Average Wind Speed ◽  
Important Conclusion ◽  
Comprehensive Picture ◽  
Mean Wind Speed ◽  
Wind Resources

The main objective of the present work is to provide a comprehensive picture of the wind conditions in the Spanish continental nearshore considering a state-of-the-art wind dataset. In order to do this, the ERA5 wind data, covering the 20-year time interval from 1999 to 2018, was processed and evaluated. ERA stands for ’ECMWF Re-Analysis’ and refers to a series of research projects at ECMWF (European Centre for Medium-Range Weather Forecasts) which produced various datasets. In addition to the analysis of the wind resources (reported for a 100 m height), the performances of several wind turbines, ranging from 3 to 9.5 MW, were evaluated. From the analysis of the spatial maps it was observed that the Northern part of this region presents significant wind resources, the mean wind speed values exceeding 9 m/s in some locations. On the other hand, in regard to the Southern sector, more energetic conditions are visible close to the Strait of Gibraltar and to the Gulf of Lion. Nevertheless, from the analysis of the data corresponding to these two Southern nearshore points it was observed that the average wind speed was lower than 8 m/s in both summer and winter months. Regarding the considered wind turbines, the capacity factor did in general not exceed 20%—however, we did observe some peaks that could reach to 30%. Finally, it can be highlighted that the Northern part of the Spanish continental nearshore is significant from the perspective of extracting offshore wind energy, especially considering the technologies based on floating platforms. Furthermore, because of the clear synergy between wind and wave energy, which are characteristic to this coastal environment, an important conclusion of the present work is that the implementation of joint wind–wave projects might be effective in the Northwestern side of the Iberian nearshore.

scholarly journals Recovery processes in a large offshore wind farm

2021 ◽  
Vol 6 (5) ◽  
pp. 1089-1106
Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
High Wind ◽  
Offshore Wind Farm ◽  
High Wind Speed ◽  
Recovery Processes ◽  
Speed Range

Abstract. 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 the sides into the wakes replenishes 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 a hypothetical offshore wind farm with particular emphasis on comparing the spatial patterns and magnitudes of horizontal- and vertical-recovery processes and understanding the role of mesoscale processes in momentum recovery in wind farms. For this purpose, we use the Weather Research and Forecasting (WRF) model, a state-of-the-art mesoscale model equipped with a wind turbine parameterization, to simulate a hypothetical large offshore wind farm with different wind turbine spacings under realistic initial and boundary conditions. Different inter-turbine spacings range from a densely packed wind farm (case I: low inter-turbine distance of 0.5 km ∼ 5 rotor diameter) to a sparsely packed wind farm (case III: high inter-turbine distance of 2 km ∼ 20 rotor diameter). In this study, apart from the inter-turbine spacings, we also explored the role of different ranges of background wind speeds over which the wind turbines operate, ranging from a low wind speed range of 3–11.75 m s−1 (case A) to a high wind speed range of 11–18 m s−1 (case C). Results show that vertical turbulent transport of momentum from aloft is the main contributor to recovery in wind farms except in cases with high-wind-speed range and sparsely packed wind farms, where horizontal advective momentum transport can also contribute equally. Vertical recovery shows a systematic dependence on wind speed and wind farm density that is quantified using low-order empirical equations. Wind farms significantly alter the mesoscale flow patterns, especially for densely packed wind farms under high-wind-speed conditions. In these cases, the mesoscale circulations created by the wind farms can transport high-momentum air from aloft into the atmospheric boundary layer (ABL) and thus aid in recovery in wind farms. To the best of our knowledge, this is one of the first studies to look at wind farm replenishment processes under realistic meteorological conditions including the role of mesoscale processes. Overall, this study advances our understanding of recovery processes in wind farms and wind farm–ABL interactions.

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