Radiation and wind projections for Poland based on downscaled EuroCORDEX ensemble

2021 ◽  
Author(s):  
Joanna Struzewska ◽  
Maciej Jefimow ◽  
Aneta Gienibor ◽  
Maria Kleczek ◽  
Anahita Sattari ◽  
...  
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Future Climate ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Average Wind ◽  
Wind Speed Distribution ◽  
North Eastern ◽  
The Future ◽  
Most Significant Change

<p>Forecasted trends of solar radiation and wind speed serve as an input for climate risk assessment as well as the estimation of renewable energy potential in the future climate.</p><p>In the frame of the project “Adaption strategies to Climate Change in Poland” the projections of solar radiation and the wind speed were developed based on the EURO-CORDEX. The RCM results for an area covering central Europe with a resolution of 0.11 ° (approx. 12.5 km) were used. The analyses were carried out for RCP4.5 and RCP8.5 scenarios.</p><p> </p><p>To represent better the local variability the statistical downscaling was applied based on various historical gridded datasets (ERA5 and IMWM for the wind speed and ERA5, IMWM, and SARAH-II for the shortwave solar radiation). Ensemble analyses were undertaken to assess the projection uncertainty.</p><p>Solar radiation in the future climate shows a slight downward trend. The annual sum of solar radiation at the end of the century will decrease by 12 kWh/m<sup>2</sup> to 40 kWh/m<sup>2</sup>, depending on the scenario. The most significant change will occur in eastern and north-eastern Poland. Forecasts of average wind speed values do not indicate significant changes in the 21st century, although the wind speed distribution showed changes in individual months - an increase in the winter and a decrease in the summer months.</p><p>Results are available via the interactive climate web portal https://klimada2.ios.gov.pl/klimat-scenariusze-portal/.</p>

Wind Energy Potential in Nine Coastal Sites in Malaysia

2013 ◽  
Vol 1 (1) ◽  
pp. 10-15
Author(s):  
Kamaruzzaman Sopian ◽  
Tamer Khatib
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Data Bank ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Speed Distribution ◽  
Average Wind ◽  
Wind Speed Distribution ◽  
Wind Energy Potential ◽  
Swept Area

 In this paper, the wind energy potential in Malaysia is examined by analyzing hourly wind speed data for nine coastal sites namely Bintulu, Kota Kinabalu, Kuala Terengganu, Kuching, Kudat, Mersing, Sandakan, Tawau and Pulau Langkawi. The monthly averages of wind speed and wind energy are calculated. Moreover, the wind speed distribution histogram is constructed for these sites. The results showed that the average wind speed for these sites is in the range of (1.8-2.9) m/s while the annual energy of the wind hitting a wind turbine with a 1 m2 swept area is in the range of (15.4-25.2) kWh/m2.annum. This paper provides a data bank for wind energy for Malaysia.

Wind Energy Potential in Nine Coastal Sites in Malaysia

2013 ◽  
Vol 1 (1) ◽  
pp. 10-15
Author(s):  
Kamaruzzaman Sopian ◽  
Tamer Khatib
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Data Bank ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Speed Distribution ◽  
Average Wind ◽  
Wind Speed Distribution ◽  
Wind Energy Potential ◽  
Swept Area

 In this paper, the wind energy potential in Malaysia is examined by analyzing hourly wind speed data for nine coastal sites namely Bintulu, Kota Kinabalu, Kuala Terengganu, Kuching, Kudat, Mersing, Sandakan, Tawau and Pulau Langkawi. The monthly averages of wind speed and wind energy are calculated. Moreover, the wind speed distribution histogram is constructed for these sites. The results showed that the average wind speed for these sites is in the range of (1.8-2.9) m/s while the annual energy of the wind hitting a wind turbine with a 1 m2 swept area is in the range of (15.4-25.2) kWh/m2.annum. This paper provides a data bank for wind energy for Malaysia.

Methodolgy for Preliminary Assessment of Regional Wind Energy Potential

2009 ◽  
Author(s):  
Thomas J. Wenning ◽  
J. Kelly Kissock
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Site Location ◽  
Preliminary Assessment ◽  
Energy Potential ◽  
Annual Average ◽  
Average Wind Speed ◽  
Average Wind ◽  
Hourly Data ◽  
Wind Energy Potential

This paper describes a methodology for a preliminary assessment of a region’s wind energy potential. The methodology begins by discussing four primary considerations for site location: wind resources, wildlife corridors, proximity to transmission grids, and required land area. Algorithms to calculate wind energy production using both hourly and annual average wind speed are presented. The hourly data method adjusts for differences in height, air density and terrain effects between the measurement site and the proposed turbine site. The annual average wind data method adjusts for these factors, and uses the average annual wind speed to generate a Rayleigh distribution of wind speeds over the year. Wind turbine electricity generation is calculated using the wind speed data and the turbine power curve. The lifecycle cost of electricity is calculated from operating costs, purchase costs, a discount rate, and the project lifetime. A case study demonstrates the use of the methodology to investigate the potential for producing electricity from wind turbines in Southwest Ohio. This information is useful to utilities, power producers and municipalities as they look to incorporate renewable energy generation into their portfolios.

scholarly journals Lake Michigan Wind Assessment Analysis, 2012 and 2013

2017 ◽  
Vol 6 (1) ◽  
pp. 19-27
Author(s):  
Charles R Standridge ◽  
Daivd Zeitler ◽  
Aaron Clark ◽  
Tyson Spoolma ◽  
Erik Nordman ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Lake Michigan ◽  
Floating Platform ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Average Wind ◽  
Wind Energy Potential ◽  
Lower Height

A study was conducted to address the wind energy potential over Lake Michigan to support a commercial wind farm.  Lake Michigan is an inland sea in the upper mid-western United States.  A laser wind sensor mounted on a floating platform was located at the mid-lake plateau in 2012 and about 10.5 kilometers from the eastern shoreline near Muskegon Michigan in 2013.  Range gate heights for the laser wind sensor were centered at 75, 90, 105, 125, 150, and 175 meters.  Wind speed and direction were measured once each second and aggregated into 10 minute averages.  The two sample t-test and the paired-t method were used to perform the analysis.  Average wind speed stopped increasing between 105 m and 150 m depending on location.  Thus, the collected data is inconsistent with the idea that average wind speed increases with height. This result implies that measuring wind speed at wind turbine hub height is essential as opposed to using the wind energy power law to project the wind speed from lower heights.  Average speed at the mid-lake plateau is no more that 10% greater than at the location near Muskegon.  Thus, it may be possible to harvest much of the available wind energy at a lower height and closer to the shoreline than previously thought.  At both locations, the predominate wind direction is from the south-southwest.  The ability of the laser wind sensor to measure wind speed appears to be affected by a lack of particulate matter at greater heights.Article History: Received June 15th 2016; Received in revised form January 16th 2017; Accepted February 2nd 2017 Available onlineHow to Cite This Article: Standridge, C., Zeitler, D., Clark, A., Spoelma, T., Nordman, E., Boezaart, T.A., Edmonson, J.,  Howe, G., Meadows, G., Cotel, A. and Marsik, F. (2017) Lake Michigan Wind Assessment Analysis, 2012 and 2013. Int. Journal of Renewable Energy Development, 6(1), 19-27.http://dx.doi.org/10.14710/ijred.6.1.19-27

scholarly journals THE IMPACT OF LONG CANYON DESIGN AND WATERFRONT BARRIER BUILDINGS ON WIND VELOCITY IN A COASTAL AREA OF SELATPANJANG CITY

Arsitektura ◽  
2018 ◽  
Vol 16 (2) ◽  
pp. 231 ◽  
Author(s):  
Boby Rahman ◽  
Asri Dinapradipta ◽  
Ima Defiana
Keyword(s):  
Wind Speed ◽  
Urban Environments ◽  
Average Wind Speed ◽  
Speed Reduction ◽  
Speed Distribution ◽  
Average Wind ◽  
Wind Speed Distribution ◽  
Urban Waterfront ◽  
Wind Distribution ◽  
The Impact

<p class="Abstract"><em>The increase of waterfront buildings’ height has an effect on wind distribution in the urban canyon. On the other hand, the distribution of wind is needed in providing thermal balance in urban environments, especially in urban waterfront coastal areas. This study aimed at observing and analyzing the effect of building height (H) on waterfront buildings and aspects of the length to width (L/W) ratio related to the length of the canyon design. The observation was focused on the wind speed distribution. The research was an experimental research using ENVI-met V3.1 software for simulation. The results indicated that short canyon (low L/W value) results in lower wind speed changes compared to that of long one (higher L/W value) at all altitude levels. The short canyons provided more stability in wind speed reduction. The 15 meters wide of canyon design contributed to the highest average wind speed. Overall, the existence of a barrier building would result in a negative area of air flow and create a calm area within the distance of  ± 50 meters.</em></p><em></em>

scholarly journals Trends and Variations of Monthly Solar Radiation, Temperature and Rainfall Data over Birnin Kebbi Metropolis for the Period of 2014-2016

2019 ◽  
pp. 1-10
Author(s):  
Usman Zayyanu Magawata ◽  
Abubakar Aliero Yahaya
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Abrupt Change ◽  
Global Solar Radiation ◽  
Maximum Temperature ◽  
Average Wind Speed ◽  
Monthly Average ◽  
Average Wind ◽  
Significant Downward Trend ◽  
Precipitation Events

The investigation of rainfall, temperature and solar radiation variability at Birnin Kebbi metropolis, Kebbi State, Nigeria was carried out using observations of air temperature (°C) rainfall (mm) and solar radiation (W/m2) for the period of 2014 -2016 (3 years), data was obtained at Sir Ahmadu Bello international Airport, analysis of data indicate for the occurrences of abrupt change in temperature, rainfall and solar radiation values. It was observed from the distributions of monthly average wind speed for the (3) three years are fairly similar with maximum wind speed with variation in some months, having deficit values in February and April 2014, February and March 2015, January and February 2016, its revealed that, the least global solar radiation in 2014 followed by the month of January 2015 and June in 2016. The variation between maximum solar radiation and minimum is said to be great in the months of January to March where there is increase in the intensity of heat as there is strong expectation of precipitation events that become extremely in the month of August/September 2016. The slight difference between maximum and minimum in the period advocates a different seasonal period between the regime of large difference and low difference in the Relative Humidity in the year. However 2016 show the maximum temperature which in turn when compared with 2014 and 2015 as the case reverse, significant increases in precipitation indicated in 2014 compare to other years (2015, 2016). It was concluded that there is a significant downward trend in the yearly total and mean rainfalls at Birnin Kebbi showing that 2014 has highest rainfall compared with 2015 and 2016.

Measuring Sub-second Wind Velocity Changes for Agricultural Drift One Meter Above the Ground

2019 ◽  
Vol 35 (5) ◽  
pp. 697-704
Author(s):  
Matthew W. Schramm ◽  
H Mark Hanna ◽  
Matt J. Darr ◽  
Steven J. Hoff ◽  
Brian L. Steward
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Wind Velocity ◽  
Wind Direction ◽  
Weather Conditions ◽  
Spray Drift ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind ◽  
Velocity Changes

Abstract. Agricultural spray drift is affected by many factors including current weather conditions, topography of the surrounding area, fluid properties at the nozzle, and the height at which the spray is released. During the late spring/summer spray seasons of 2014 and 2015, wind direction, speed, and solar radiation (2014 only) were measured at 10 Hz, 1 m above the ground to investigate conditions that are typically encountered by a droplet when released from a nozzle on an agricultural sprayer. Measurements of wind velocity as the wind passed from an upwind sensor to a downwind sensor were used to evaluate what conditions wind may be most likely to have a significant direction or speed change which affects droplet trajectory. For two individual datasets in which the average wind speed was 3.6 and 1.5 m/s (8.0 and 3.4 mi/h), there exists little linear correlation of wind speed or wind direction between an upwind and downwind anemometer separated by 30.5 m (100 ft). The highest observed correlation, resulting from a 12-s lag between the upwind and downwind datasets, was 0.29 when the average wind speed was 3.6 m/s (8.0 mi/h). Correlations greater than 0.1 were only found for wind speeds exceeding 3 m/s. Using this lag time, it was observed that the wind direction 30 s into the future had a 30% chance to be different by more than 20° from current conditions. A wind speed difference of more than 1 m/s (2.2 mi/h) from current conditions [mean wind speed was 3.6 m/s (8.0 mi/h)] was observed about 50% of the time. Analyzing 36 days of the 2014 and 2015 spray season wind velocity data showed that the most variability in wind direction occurred with wind speeds below 2 m/s (4.5 mi/h). Greater wind direction variability occurred in the mid-afternoon with higher solar radiation. Keywords: Sprayers, Spray drift, Spray droplets, Turbulence, Wind effects.

scholarly journals Potential for wind energy generation in Piracicaba, SP, Brazil

2014 ◽  
Vol 18 (5) ◽  
pp. 559-564 ◽  
Author(s):  
Vanessa de F. Grah ◽  
Isaac de M. Ponciano ◽  
Tarlei A. Botrel
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Potential ◽  
College Of Agriculture ◽  
Average Wind Speed ◽  
Wind Energy Generation ◽  
Average Wind ◽  
Wind Potential ◽  
Wind Energy Potential ◽  
Two Parameters

Wind power has gained space in Brazil's energy matrix, being a clean source and inexhaustible. Therefore, it becomes important to characterize the wind potential of a given location, for future applications. The main objective of the present study was to estimate the wind energy potential in Piracicaba, SP, Brazil. The wind speed data were collected by an anemometer installed at the Meteorological Station Luiz de Queiroz College of Agriculture, Piracicaba-SP. The wind speed variability was represented by the Weibull frequency distribution, a probability density function of two parameters (k and c). The parameters k and c were used to correlate the Gamma function with the annual average wind speed, the variance and power mean density. A wind profile was made to evaluate the behavior of historical average speeds at higher altitudes measured by anemometer, to estimate the gain in power density. The values of k for all heights were close to 1 which corresponds to a wind regime highly variable, and c values were also low representing a low average speed of the location. The location was characterized as being unfavorable for the application of wind turbines for power generation.

scholarly journals Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3048 ◽  
Author(s):  
Telesca ◽  
Guignard ◽  
Helbig ◽  
Kanevski
Keyword(s):  
Wind Speed ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Speed Distribution ◽  
Average Wind ◽  
Wind Speed Distribution ◽  
Extreme Wind ◽  
Wavelet Variance ◽  
Extreme Wind Speeds ◽  
Wind Extremes

The 10-min average wind speed series recorded at 130 stations distributed rather homogeneously in the territory of Switzerland are investigated. Fixing a percentile-based threshold of the wind speed distribution, a wind extreme is defined as the duration of the sequence of consecutive wind values above the threshold. This definition allows to analyze the sequence of extremes as a temporal point process marked by their duration. Representing the sequence of wind extremes by the inter-extreme interval series, the wavelet variance, a useful tool to investigate the variance of a time series across scales, was applied in order to find a link between the wavelet scales and several topographic parameters. Our findings suggest that the mean duration of wind extremes and mean inter-extreme time are positively correlated and that such relationship depends on the threshold of the wind speed. Furthermore, the threshold of the wind speed distribution correlates best with a terrain parameter related to the Laplacian of terrain elevations; and, in particular, for wavelet scales less than 3, the terrain exposure may explain the formation of extreme wind speeds.

Techno-economic analysis of wind energy potential in Kazakhstan

2021 ◽  
pp. 095765092110015
Author(s):  
Hamed H Pourasl ◽  
Vahid M Khojastehnezhad
Keyword(s):  
Wind Speed ◽  
Energy Density ◽  
Wind Energy ◽  
Wind Power ◽  
Energy Production ◽  
Energy Utilization ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Average Wind ◽  
Wind Energy Potential

The use of renewable energy as a future energy source is attracting considerable research interest globally. In particular, there is a significant growth in wind energy utilization during the last few years. This present study through a detailed and systematic literature survey assesses the wind energy potential of Kazakhstan for the first time. Using the Weibull distribution function and hourly wind speed data, the annual power and energy density of the sites are calculated. For the 50 sites considered in this study and at a height of 10 m above the ground, the annual average wind speed, the power density, and energy production of Kazakhstan range from 0.94–5.15 m/s, 4.50–169.34 W/m2 and 39.56–1502.50 kWh/m2/yr, respectively. It was found that Fort Sevcenko, Atbasar, and Akmola are the three best locations for wind turbine installation with wind power densities of 169.34, 135.30, and 111.51 W/m2, respectively. Fort Sevcenko demonstrates the highest potential for wind energy harvesting with an energy density of 1483.46 kWh/m2/yr. For the 15 commercial wind turbines, it was observed that the annual energy production of the selected turbines ranges between 3.8 GWh/yr in Petropavlovsk to 15.4 GWh/yr in Fort Sevcenko among the top six locations. The lowest and highest capacity factors correspond to the same sites with the values of 29.21% and 58.66%, respectively. Overall, it is the intention of this study to constitute a database for the users and developers of wind power in Kazakhstan.

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