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

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 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.

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.

Calculation of Weibull Distribution parameters at low wind speed and performance analysis

2021 ◽  
pp. 1-24
Author(s):  
Yusuf Alper Kaplan
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Weibull Distribution ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Statistical Indicator ◽  
Low Wind Speed ◽  
Distribution Parameters ◽  
Wind Energy Potential ◽  
And Performance

In this study, the compatibility of the real wind energy potential to the estimated wind energy potential by Weibull Distribution Function (WDF) of a region with low average wind speed potential was examined. The main purpose of this study is to examine the performance of six different methods used to find the coefficients of the WDF and to determine the best performing method for selected region. In this study seven-year hourly wind speed data obtained from the general directorate of meteorology of this region was used. The root mean square error (RMSE) statistical indicator was used to compare the efficiency of all used methods. Another main purpose of this study is to observe the how the performance of the used methods changes over the years. The obtained results showed that the performances of the used methods showed slight changes over the years, but when evaluated in general, it was observed that all method showed acceptable performance. Based on the obtained results, when the seven-year data is evaluated in this selected region, it can be said that the MM method shows the best performance.

Wind resource assessment and wind farm modeling in Mossobo-Harena area, North Ethiopia

2020 ◽  
pp. 0309524X2092540
Author(s):  
Addisu Dagne Zegeye
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Power Density ◽  
Energy Production ◽  
Wind Farm ◽  
Ground Level ◽  
Energy Potential ◽  
Mean Power ◽  
Wind Energy Potential

Although Ethiopia does not have significant fossil fuel resource, it is endowed with a huge amount of renewable energy resources such as hydro, wind, geothermal, and solar power. However, only a small portion of these resources has been utilized so far and less than 30% of the nation’s population has access to electricity. The wind energy potential of the country is estimated to be up to 10 GW. Yet less than 5% of this potential is developed so far. One of the reasons for this low utilization of wind energy in Ethiopia is the absence of a reliable and accurate wind atlas and resource maps. Development of reliable and accurate wind atlas and resource maps helps to identify candidate sites for wind energy applications and facilitates the planning and implementation of wind energy projects. The main purpose of this research is to assess the wind energy potential and model wind farm in the Mossobo-Harena site of North Ethiopia. In this research, wind data collected for 2 years from Mossobo-Harena site meteorological station were analyzed using different statistical software to evaluate the wind energy potential of the area. Average wind speed and power density, distribution of the wind, prevailing direction, turbulence intensity, and wind shear profile of the site were determined. Wind Atlas Analysis and Application Program was used to generate the generalized wind climate of the area and develop resource maps. Wind farm layout and preliminary turbine micro-sitting were done by taking various factors into consideration. The IEC wind turbine class of the site was determined and an appropriate wind turbine for the study area wind climate was selected and the net annual energy production and capacity factor of the wind farm were determined. The measured data analysis conducted indicates that the mean wind speed at 10 and 40 m above the ground level is 5.12 and 6.41 m/s, respectively, at measuring site. The measuring site’s mean power density was determined to be 138.55 and 276.52 W/m2 at 10 and 40 m above the ground level, respectively. The prevailing wind direction in the site is from east to south east where about 60% of the wind was recorded. The resource grid maps developed by Wind Atlas Analysis and Application Program on a 10 km × 10 km area at 50 m above the ground level indicate that the selected study area has a mean wind speed of 5.58 m/s and a mean power density of 146 W/m2. The average turbulence intensity of the site was found to be 0.136 at 40 m which indicates that the site has a moderate turbulence level. According to the resource assessment done, the area is classified as a wind Class IIIB site. A 2-MW rated power ENERCON E-82 E2 wind turbine which is an IEC Class IIB turbine with 82 m rotor diameter and 98 m hub height was selected for estimation of annual energy production on the proposed wind farm. 88 ENERCON E-82 E2 wind turbines were properly sited in the wind farm with recommended spacing between the turbines so as to reduce the wake loss. The rated power of the wind farm is 180.4 MW and the net annual energy production and capacity factor of the proposed wind farm were determined to be 434.315 GWh and 27.48% after considering various losses in the wind farm.

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.

scholarly journals Energy and power estimation for three different locations in Palestine

2019 ◽  
Vol 14 (3) ◽  
pp. 1049 ◽  
Author(s):  
Ahmed S A Badawi ◽  
Nurul Fadzlin Hasbullaha ◽  
Siti Hajar Yusoff ◽  
Aisha Hassan Hashim
Keyword(s):  
Renewable Energy ◽  
Wind Speed ◽  
Wind Energy ◽  
Meteorological Data ◽  
Gaza Strip ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Average Wind ◽  
Mean Wind Speed ◽  
Power And Energy

In this paper power energy estimated based on wind speed records in three different areas in Palestine Nablus, Ramallah and Gaza. The main aims of this study to calculate the total amount of power and energy that can produce and to encourage investment in renewable energy in Palestine. Available meteorological data from local weather stations are used to study the wind energy potential in the West Bank (WB) for two sites and Gaza Strip (GS) for one site. The daily average wind speed data for three sites in Palestine analyzed, and fitted to the Weibull probability distribution function. The parameters of Weibull have been calculated by author using Graphical method. This study shed lights on the relationship between the wind energy and power versus the mean wind speed (MWS). The total gathered energy per unit area during 2006 in WB from Nablus site is 927.1 kwhr/m<sup>2</sup>, whereas 2008.0141 kwhr/m<sup>2</sup> from Ramallah site.This significant study to assess the wind energy production in Palestine to encourage investment in renewable energy sectors.

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