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.

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.

scholarly journals Assessment of Wind Energy Potential In Zwara, Libya

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Alhassan A. Teyabeen ◽  
Fathi R. Akkari ◽  
Ali E. Jwaid ◽  
Ashraf Zaghwan ◽  
Rehab Abodelah
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Ground Level ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Wind Power Density ◽  
Wind Energy Potential ◽  
Wind Resource

To assess the wind energy potential at any site, the wind power density should be estimated; it evaluates the wind resource and indicates the amount of available wind energy. The purpose of this study is to estimate the monthly and annual wind power density based on the Weibull distribution using wind speed data collected in Zwara, Libya during 2007. The wind date are measured at the three hub heights of 10m, 30m, and 50m above ground level, and recorded every 10 minutes. The analysis showed that the annual average wind speed are 4.51, 5.86, 6.26 m/s for the respective mentioned heights. The average annual wind power densities at the mentioned heights were 113.71, 204.19, 243.48 , respectively.

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.

Assessment of Wind Energy Potential in Three Different Locations of Malaysia

2015 ◽  
Vol 785 ◽  
pp. 621-626
Author(s):  
R. Shamsipour ◽  
M. Fadaeenejad ◽  
M.A.M. Radzi
Keyword(s):  
Wind Speed ◽  
Energy Density ◽  
Wind Energy ◽  
Wind Power ◽  
Weibull Model ◽  
Energy Potential ◽  
Wind Speeds ◽  
Wind Potential ◽  
Mean Wind Speed ◽  
Wind Energy Potential

In this study, wind energy potential in three different stations in Malaysia in period of 5 years is analyzed. Base on Weibull distribution parameters, the mean wind speed, wind power density and wind energy density is estimated for each defined location. Although there are many works about wind potential in Malaysia, however a few of them have been provided a comprehensive study about wind power in different places in Malaysia. According to the findings, the annual mean wind speeds indicates that the highest wind speed variation is about 2 m/s and is belonged to the Subang station and the highest wind speed is 3.5 m/s in in Kudat. It is also found that the maximum wind power densities among these three sites are 22 W/m2, 24 W/m2 and 22 W/m2 in Kudat station in January, February and September respectively. The results of the study show that as the second parameter for Weibull model, the highest wind energy density has been 190 kWh/m2 per year in Kudat and the lowest one has been about 60 kWh/m2 in Kuching.

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 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 Optimum Method for Determining Weibull Distribution Parameters Used in Wind Energy Estimation

2020 ◽  
pp. 635-648
Author(s):  
Ulku Erisoglu ◽  
Nil Aras ◽  
Hasan Donat Yildizay
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Weibull Distribution ◽  
Wind Power ◽  
Estimation Method ◽  
Energy Potential ◽  
Average Wind ◽  
Distribution Parameters ◽  
Wind Energy Potential ◽  
Two Parameter

One of the well-known methods for the determination of wind energy potential is the two-parameter Weibull distribution. It is clear that the success of the Weibull distribution for wind energy applications depends on the estimation of the parameters which can be determined by using various numerical methods. In the present study, Monte Carlo simulation method is performed by using six parameters estimation method that is used in the estimation of Weibull distribution parameters such as Maximum Likelihood Estimation (MLE), Least Squares Method (LSM), Method of Moments (MOM), Method of Logarithmic Moments (MLM), Percentile Method (PM), and L-Moment Method (LM), and is compared to Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). In this study, the wind energy potential of the Meşelik region in Eskişehir was modeled with two-parameter Weibull distribution. The average wind speed (m/s) data, which are gathered in 10-minute intervals from the measuring device installed 10 meters about the ground in Meşelik Campus of Eskişehir Osmangazi University, is used. As a result of the simulation study, it has been determined that MLE is the best parameter estimation method for two-parameter Weibull distribution in large sample sizes, and LM has the closest performance to MLE. The wind speed (m/h) data of the region has been successfully modeled with two-parameter Weibull distribution and the highest average wind power density has been obtained in July as 49.38295 (W/m2) while the lowest average wind power density has been obtained in October as 19.30044 (W/m2).

Climate change impacts on wind power density over southeastern Mediterranean

2020 ◽  
Author(s):  
Chris G. Tzanis ◽  
Kostas Philippopoulos ◽  
Constantinos Cartalis ◽  
Konstantinos Granakis ◽  
Anastasios Alimissis ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Energy Production ◽  
Energy Potential ◽  
Wind Power Density ◽  
Climatic Scenarios ◽  
Wind Energy Potential

<p>Energy production from the utilization of wind energy potential depends on the variability of the wind field as determined by the interaction of natural processes on different scales. Global climate change can cause alterations in the surface wind and thus it may affect the geographical distribution and the wind energy potential variability. Wind energy production is sensitive to wind speed changes, especially in the upper percentile of the wind speed distributions, where energy production is more effective. The importance of wind energy production changes is enhanced by the fact that wind energy investments are long-term and are characterized by high initial costs and low operating costs. In the present study, these changes are examined for the southeastern Mediterranean region, based on simulations of the Regional Climate Model ALADIN 5.2 extracted from the Med-CORDEX database for the climatic scenarios RCP4.5 and RCP8.5. The results indicate a wind power density increase over the Aegean Sea, the Ionian Sea, the Dardanelles and the Black Sea, with similar levels of increase for both climatic scenarios. In contrast, during the winter period there is a decline across the southeastern Mediterranean, which is more significant in the case of the RCP8.5 scenario. Finally, for most areas of eastern Greece, there is a reduction in the number of wind speed cases for both below and above cut-in and cut-out wind speeds, while there is an increase in the number of wind speed cases that wind turbines operate at their maximum power. The results are expected to reduce the uncertainty associated with the impact of climate change on wind energy production. </p>

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