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

Proceedings of the Institution of Civil Engineers - Energy ◽

10.1680/jener.21.00010 ◽

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.

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

Pakistan Journal of Statistics and Operation Research ◽

10.18187/pjsor.v16i4.3456 ◽

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).

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Wind Energy Potential in Nine Coastal Sites in Malaysia

مجلة جامعة فلسطين التقنية للأبحاث ◽

10.53671/ptukrj.v1i1.7 ◽

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.

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Assessment of Wind Energy Potential In Zwara, Libya

Solar Energy and Sustainable Development ◽

10.51646/jsesd.v8i2.21 ◽

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.

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Wind Energy Potential in Nine Coastal Sites in Malaysia

مجلة جامعة فلسطين التقنية للأبحاث ◽

10.53671/pturj.v1i1.7 ◽

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

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Methodolgy for Preliminary Assessment of Regional Wind Energy Potential

ASME 2009 3rd International Conference on Energy Sustainability, Volume 2 ◽

10.1115/es2009-90469 ◽

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.

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Lake Michigan Wind Assessment Analysis, 2012 and 2013

International Journal of Renewable Energy Development ◽

10.14710/ijred.6.1.19-27 ◽

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

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Assessments of Wind-Energy Potential in Selected Sites from Three Geopolitical Zones in Nigeria: Implications for Renewable/Sustainable Rural Electrification

The Scientific World JOURNAL ◽

10.1155/2015/581679 ◽

2015 ◽

Vol 2015 ◽

pp. 1-13 ◽

Cited By ~ 17

Author(s):

Joshua Olusegun Okeniyi ◽

Olayinka Soledayo Ohunakin ◽

Elizabeth Toyin Okeniyi

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Electricity Generation ◽

Rural Electrification ◽

Energy Potential ◽

Southeastern Nigeria ◽

Low Wind Speed ◽

Wind Energy Potential ◽

Study Sites ◽

Wind Resource

Electricity generation in rural communities is an acute problem militating against socioeconomic well-being of the populace in these communities in developing countries, including Nigeria. In this paper, assessments of wind-energy potential in selected sites from three major geopolitical zones of Nigeria were investigated. For this, daily wind-speed data from Katsina in northern, Warri in southwestern and Calabar in southeastern Nigeria were analysed using the Gumbel and the Weibull probability distributions for assessing wind-energy potential as a renewable/sustainable solution for the country’s rural-electrification problems. Results showed that the wind-speed models identified Katsina with higher wind-speed class than both Warri and Calabar that were otherwise identified as low wind-speed sites. However, econometrics of electricity power simulation at different hub heights of low wind-speed turbine systems showed that the cost of electric-power generation in the three study sites was converging to affordable cost per kWh of electric energy from the wind resource at each site. These power simulations identified cost/kWh of electricity generation at Kaduna as €0.0507, at Warri as €0.0774, and at Calabar as €0.0819. These bare positive implications on renewable/sustainable rural electrification in the study sites even as requisite options for promoting utilization of this viable wind-resource energy in the remote communities in the environs of the study sites were suggested.

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Potential for wind energy generation in Piracicaba, SP, Brazil

Revista Brasileira de Engenharia Agrícola e Ambiental ◽

10.1590/s1415-43662014000500014 ◽

2014 ◽

Vol 18 (5) ◽

pp. 559-564 ◽

Cited By ~ 1

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.

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Techno-economic analysis of wind energy potential in Kazakhstan

Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy ◽

10.1177/09576509211001598 ◽

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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