scholarly journals Analysis of wind speed data and wind energy potential using Weibull distribution in Zagora, Morocco

2019 ◽  
Vol 8 (3) ◽  
pp. 267-273 ◽  
Author(s):  
Daoudi Mohammed ◽  
Ait Sidi Mou Abdelaziz ◽  
Elkhomri Mohammed ◽  
Elkhouzai Elmostapha
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Weibull Distribution ◽  
Energy Output ◽  
Energy Potential ◽  
Distribution Method ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
The Mean ◽  
Primary Evaluation

This paper presents the wind energy potential at 10 m during a period of 09 years (2009-2017) in the province of Zagora using the Weibull distribution method. Extrapolation of the 10 m data, using the power Law, has been used to determine the wind data at heights of 30 m; 50 m and 70 m. The objective is to evaluate the most important characteristics of wind energy in the studied site . The statistical attitudes permit us to estimate the mean wind speed, the wind speed distribution function and the mean wind power density in the site at the height of 30 m; 50 m and 70 m. From the primary evaluation indicate that the annual energy output and capacity factor increases with increasing the wind speed, it can obtain about 2.62 GWh/year, that is acceptable quantity for the wind energy. ©2019. CBIORE-IJRED. All rights reserved

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.

scholarly journals Climate Change Induced Uncertainty of Wind Energy Potential for the Azov and Black Seas Coastal Zone

2020 ◽  
Author(s):  
V. P. Evstigneev ◽  
◽  
N. A. Lemeshko ◽  
V. A. Naumova ◽  
M. P. Evstigneev ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Black Sea ◽  
Operating Time ◽  
Energy Output ◽  
Energy Potential ◽  
Wind Energy Potential ◽  
Wind Climate

The paper deals with assessing an impact of wind climate change on the wind energy potential of the Azov and Black Sea coast region. A lower estimate of operating time for wind power installation and a potential annual energy output for the region are given for the case of Vestas V117-4.2MW. Calculation has been performed of a long-term mean wind speed for two adjacent climatic periods (1954–1983 and 1984–2013) based on data from meteorological stations of the Black and Azov Sea region. The results show a decrease in wind speed at all meteorological stations except for Novorossiysk. The wind climate change is confirmed by comparing two adjoined 30-year periods and by estimating linear trends of the mean annual wind speed for the period 1954–2013, which are negative and significant for almost all meteorological stations in the region (α = 1 %). The trend values were estimated by the nonparametric method of robust linear smoothing using the Theil – Sen function. In the present study, the uncertainty of wind energy resource induced by a gradual wind climate change is estimated for perspective planning of this branch of energy sector. Despite the observed trends in the wind regime, average wind speeds in the Azov and Black Sea region are sufficient for planning the location of wind power plants.

scholarly journals Assessment of wind energy potential in East Azarbaijan province of Iran (Case Stady: Sahand station)

2015 ◽  
Vol 17 (2) ◽  
pp. 418-425
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Fossil Fuels ◽  
Ground Level ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Seasonal Wind

<p>Today&#39;s world requires a change in how the use of different types of energy. With declining reserves of fossil fuels for renewable energies is of course the best alternative. Among the renewable energy from the wind can be considered one of the best forms of energy can be introduced. Accordingly, most countries are trying to identify areas with potential to benefit from this resource.</p> <p>The aim of this study was to assess the potential wind power in Sahand station of Iran country. Hourly measured long term wind speed data of Sahand during the period of 2000-2013 have been statistically analyzed. In this study the wind speed frequency distribution of location was found by using Weibull distribution function. The wind energy potential of the location has been studied based on the Weibull mode. The results of this study show that mean wind speed measured at 10 m above ground level is determined as 5.16 m/s for the studied period. This speed increases by, respectively, 34.78 % and 41.21 %, when it is extrapolated to 40 and 60 m hub height.</p> <div> <p>Long term seasonal wind speeds were found to be relatively higher during the period from January to September. At the other hand, higher wind speeds were observed between the period between 06:00 and 18:00 in the day. These periods feet well with annual and daily periods of maximum demand of electricity, respectively.&nbsp;</p> </div> <p>&nbsp;</p>

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.

scholarly journals Long-Term Wind Characteristics at Selected Locations in Mauritius for Power Generation

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
A. Z. Dhunny ◽  
M. R. Lollchund ◽  
S. D. D. V. Rughooputh
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbines ◽  
Fossil Fuels ◽  
Energy Output ◽  
Energy Potential ◽  
Wind Speed Data ◽  
Average Wind ◽  
Small Wind Turbines ◽  
Mean Wind Speed

Interests in wind energy have gained impetus in many developed and developing countries worldwide during the last three decades. This is due to awareness of the population about the depletion of fossil fuels as well as Government campaigns and initiatives to encourage the use of renewable sources of energy. This work focuses on the wind energy potential at two selected locations (Plaisance and Vacoas) in Mauritius. The emphasis is to assess whether small-wind turbines have a potential in these regions for generation of power for domestic applications. Such wind turbines can range in size from 400 W to 10 kW depending on the amount of electricity to be generated. The assessment is based on the correlation of the local wind speed data to a two-parameter Weibull probability distribution in order to effectively estimate the average wind power density of the sites. Nearly 40 years of mean wind speed data is utilized. Of the two sites investigated it is found that Plaisance yielded the highest wind velocity (as compared to Vacoas). The study also estimates the energy output of six commercial small-wind turbines of capacity ranging from 1 kW to 3 kW at these two sites, placed at multiple heights.

scholarly journals Assessment of Wind Energy Potential as a Power Generation Source: A Case Study of Eight Selected Locations in Northern Cyprus

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2697 ◽  
Author(s):  
Mohamad Alayat ◽  
Youssef Kassem ◽  
Hüseyin Çamur
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Actual Data ◽  
Small Scale ◽  
Energy Potential ◽  
Northern Cyprus ◽  
Mean Wind Speed ◽  
Wind Energy Potential

This paper presents a techno-economic assessment of the wind power potential for eight locations distributed over the Northern part of Cyprus. The wind speed data were collected from the meteorological department located in Lefkoşa, Northern Cyprus.Ten distribution models were used to analyze the wind speed characteristics and wind energy potential at the selected locations. The maximum-likelihood method was used for calculating the parameters of the distribution functions.The power law model is utilized to determine the mean wind speed at various heights. In addition, the wind power density for each location was estimated. Furthermore, the performances of different small-scale vertical axis 3–10 kW wind turbines were evaluated to find those that were suitable and efficient for power generation in the studied locations.The results showed that the annual mean wind speed in the regions is greater than 2 m/s at a height of 10 m. Moreover, it is indicated that Generalized Extreme Value distribution provided the best fit to the actual data for the regions of Lefkoşa, Ercan, Girne, Güzelyurt, and Dipkarpaz. However, the Log-Logistic, Weibull, and Gamma distributions gave a better fit to the actual data of Gazimağusa, YeniBoğaziçi, and Salamis, respectively. The Rayleigh distribution does not fit the actual data from all regions. Furthermore, the values of wind power densityat the areas studied ranged from 38.76 W/m2 to 134.29 W/m2 at a height of 50 m, which indicated that wind energy sources in these selected locations are classified as poor. Meanwhile, based on the wind analysis, small-scale wind turbine use can be suitable for generating electricity in the studied locations. Consequently, an Aeolos-V2 with a rating of 5 kW was found to be capable of producing the annual energy needs of an average household in Northern Cyprus.

Analysis of wind speed data and wind energy potential in Faya-Largeau, Chad, using Weibull distribution

2018 ◽  
Vol 121 ◽  
pp. 1-8 ◽  
Author(s):  
M.H. Soulouknga ◽  
S.Y. Doka ◽  
N.Revanna ◽  
N.Djongyang ◽  
T.C.Kofane
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Weibull Distribution ◽  
Energy Potential ◽  
Wind Speed Data ◽  
Wind Energy Potential

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).

scholarly journals Wind Energy Potential Assessment of Great Cumbrae Island Using Weibull Distribution Function

2019 ◽  
pp. 1-8 ◽  
Author(s):  
Emmanuel Yeri Kombe ◽  
Joseph Muguthu
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Demand ◽  
Probability Distributions ◽  
Energy Resource ◽  
Horizontal Wind ◽  
Energy Potential ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Scottish Government

Wind energy is among the fastest growing energy generation technology which is highly preferred alternative to conventional sources of energy. The major Scottish Government target is to deliver 30% of her energy demand by 2020 from renewable sources of energy as well as meeting the emission targets as set under the Scotland Climate Change Act 2009. In this paper, wind energy potential assessment of Great Cumbrae Island was investigated. For this, a ten year mean monthly wind speed at height 50 m obtained from the National Aeronautic Space Administration (NASA) were analysed using the Weibull probability distributions to assess the wind energy potential of Great Cumbrae Island as a clean, sustainable energy resource. Results from the wind-speed model showed that Great Cumbrae Island as high wind-speed site with a mean wind speed of 7.598 m/s and having power density . The annual energy captured by four selected horizontal wind turbine models was determined. The result shows that GE 2.0 platform can capture 4.5 GWh energy in a year which is an acceptable quantity for wind energy.

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