scholarly journals Wind speed analysis based on the logarithmic wind shear model: a case study for some brazilian cities

2020 ◽  
Vol 9 (7) ◽  
pp. e298973984
Author(s):  
Anny Key de Souza Mendonça ◽  
Antonio Cezar Bornia
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Shear ◽  
Wind Farms ◽  
Shear Model ◽  
The Public ◽  
Wind Speeds ◽  
Generating Capacity ◽  
Mean Wind Speed ◽  
The Mean

The wind power’ share in electricity generating capacity has increased significantly in recent years. Due to the variability in wind power generation, given the variations in wind speed and considering the increase in wind participation in the Brazilian energy matrix, a fact that reinforces the relevance of the source, this article aims to present the methods used to analyze the wind speed more used in the literature and to analyze the wind speed in several Brazilian cities. The logarithmic wind shear model was used to analyze mean wind speeds based on historical data of twelve Brazilian cities available to the public on the ESRL database for a period of eight years 2010 to 2018. The study showed that in localities such as Uruguaiana/RS, Campo Grande/MS, Uberlândia/MG, São Luiz/MA and Corumba/MS, mean wind speeds are strong in all altitudes of reference, with a gain of ± 2m/s of wind speed as the operational altitude increases. The logarithmic wind gain in high altitudes or low altitudes can be seen in z = 100 meters, where the mean wind speed found was Wn ≈ 8 m/s in Uruguaiana/RS and Campo Grande/MS, whereas in Manaus it was Wn ≈ 5 m/s. In Porto Alegre (RS), Florianópolis (SC), Curitiba/PR and Brasília/DF, the mean wind speed in altitudes ≥ 250 m becomes significant, allowing the implementation of wind farms if the technology proves to be economically feasible.

scholarly journals Statistical Analysis of Wind Speed & Wind Direction in Tantan Province, Morocco

2019 ◽  
Vol 8 (4) ◽  
pp. 3955-3959
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Direction ◽  
Energy System ◽  
Average Frequency ◽  
Wind Rose ◽  
Data Set ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
The Mean

In this paper, a two-parameter Weibull statistical distribution is used to analyze the characteristics of the wind from the Saharan area, located in the Tantan province, Morocco, for 08 years at 10 m. During those 08 years (2009-2017) the frequency distribution of the wind speed, the wind direction, the mean wind speed, the shape and scale (k & c) Weibull parameters have been calculated for the province. The mean wind speed for the entire data set is 6.4 m/s. The parameters k & c are found as 1.9 and 2.52 m/s in relative order. The study also provides an analysis of the wind direction along with a wind rose chart for the province. The analysis suggests that the highest wind speeds that vary (vm = 5.1m/s; vmax = 18.5m/s) prevail between sectors 165-175 ° with an average frequency of 1.4% and lower wind speeds (vm = 2.5m/s; vmax = 9.7m/s) occur between sectors 245-255° with an average frequency of 0.6%. The results of this document help to understand the wind power potential of the province and serve as a source of wind power projects. From a perspective, the wind energy system is an alternative to the future of the Sahara province of Morocco.

scholarly journals Wind Power potential in Kigali and Western provinces of Rwanda

2015 ◽  
Vol 2 (1) ◽  
pp. 25-36
Author(s):  
Otieno Fredrick Onyango ◽  
Sibomana Gaston ◽  
Elie Kabende ◽  
Felix Nkunda ◽  
Jared Hera Ndeda
Keyword(s):  
Wind Speed ◽  
Probability Density ◽  
Wind Power ◽  
Wind Direction ◽  
Small Scale ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Low Wind Speeds

Wind speed and wind direction are the most important characteristics for assessing wind energy potential of a location using suitable probability density functions. In this investigation, a hybrid-Weibull probability density function was used to analyze data from Kigali, Gisenyi, and Kamembe stations. Kigali is located in the Eastern side of Rwanda while Gisenyi and Kamembe are to the West. On-site hourly wind speed and wind direction data for the year 2007 were analyzed using Matlab programmes. The annual mean wind speed for Kigali, Gisenyi, and Kamembe sites were determined as 2.36m/s, 2.95m/s and 2.97m/s respectively, while corresponding dominant wind directions for the stations were ,  and  respectively. The annual wind power density of Kigali was found to be  while the power densities for Gisenyi and Kamembe were determined as and . It is clear, the investigated regions are dominated by low wind speeds thus are suitable for small-scale wind power generation especially at Kamembe site.

scholarly journals Supplying Baseload Power and Reducing Transmission Requirements by Interconnecting Wind Farms

2007 ◽  
Vol 46 (11) ◽  
pp. 1701-1717 ◽  
Author(s):  
Cristina L. Archer ◽  
Mark Z. Jacobson
Keyword(s):  
Wind Speed ◽  
Electric Power ◽  
Wind Power ◽  
Electric Energy ◽  
Wind Farms ◽  
Long Distance ◽  
Annual Average ◽  
Transmission Grid ◽  
Wind Speeds ◽  
Average Wind

Abstract Wind is the world’s fastest growing electric energy source. Because it is intermittent, though, wind is not used to supply baseload electric power today. Interconnecting wind farms through the transmission grid is a simple and effective way of reducing deliverable wind power swings caused by wind intermittency. As more farms are interconnected in an array, wind speed correlation among sites decreases and so does the probability that all sites experience the same wind regime at the same time. The array consequently behaves more and more similarly to a single farm with steady wind speed and thus steady deliverable wind power. In this study, benefits of interconnecting wind farms were evaluated for 19 sites, located in the midwestern United States, with annual average wind speeds at 80 m above ground, the hub height of modern wind turbines, greater than 6.9 m s−1 (class 3 or greater). It was found that an average of 33% and a maximum of 47% of yearly averaged wind power from interconnected farms can be used as reliable, baseload electric power. Equally significant, interconnecting multiple wind farms to a common point and then connecting that point to a far-away city can allow the long-distance portion of transmission capacity to be reduced, for example, by 20% with only a 1.6% loss of energy. Although most parameters, such as intermittency, improved less than linearly as the number of interconnected sites increased, no saturation of the benefits was found. Thus, the benefits of interconnection continue to increase with more and more interconnected sites.

Wind tunnel tests on the characteristics of wind fields over a simplified gorge

2016 ◽  
Vol 20 (10) ◽  
pp. 1599-1611 ◽  
Author(s):  
Peng Hu ◽  
Yongle Li ◽  
Yan Han ◽  
CS Cai ◽  
Guoji Xu
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Direction ◽  
Wind Field ◽  
Small Range ◽  
Wind Fields ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
The Mean

Characteristics of wind fields over the gorge or valley terrains are becoming more and more important to the structural wind engineering. However, the studies on this topic are very limited. To obtain the fundamental characteristics information about the wind fields over a typical gorge terrain, a V-shaped simplified gorge, which was abstracted from some real deep-cutting gorges where long-span bridges usually straddle, was introduced in the present wind tunnel studies. Then, the wind characteristics including the mean wind speed, turbulence intensity, integral length scale, and the wind power spectrum over the simplified gorge were studied in a simulated atmospheric boundary layer. Furthermore, the effects of the oncoming wind field type and oncoming wind direction on these wind characteristics were also investigated. The results show that compared with the oncoming wind, the wind speeds at the gorge center become larger, but the turbulence intensities and the longitudinal integral length scales become smaller. Generally, the wind fields over the gorge terrain can be approximately divided into two layers, that is, the gorge inner layer and the gorge outer layer. The different oncoming wind field types have remarkable effects on the mean wind speed ratios near the ground. When the angle between the oncoming wind and the axis of the gorge is in a certain small range, such as smaller than 10°, the wind fields are very close to those associated with the wind direction of 0°. However, when the angle is in a larger range, such as larger than 20°, the wind fields in the gorge will significantly change. The research conclusions can provide some references for civil engineering practices regarding the characteristics of wind fields over the real gorge terrains.

ANALYSIS OF PEDESTRIAN-LEVEL WIND VELOCITY IN FOUR NEIGHBOURHOODS IN KLANG VALLEY

2015 ◽  
Vol 76 (5) ◽  
Author(s):  
Azli Abd Razak ◽  
Mohd Azhari Mohd Rodzi ◽  
Amirul Hakim Jumali ◽  
Sheikh Ahmad Zaki
Keyword(s):  
Wind Speed ◽  
Field Measurements ◽  
Area Ratio ◽  
Frontal Area ◽  
Speed Ratio ◽  
Pollution Dispersion ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Klang Valley ◽  
The Mean

Urban ventilation is important for the purpose of pollution dispersion, indoor ventilation for free running buildings and urban thermal comfort. In comparison to suburban cities, high-density cities have very low wind speeds at pedestrian level due to the densely built buildings blocking the wind and creating stagnant zones locally. Under this circumstance, field measurements were performed to investigate the performance of pedestrian wind at four major cities in Klang Valley. Mean wind speed was measured using anemometers at 1 minute data interval for 3 hours  and the  data collection for each case were obtained at pedestrian level. The mean wind speed ratio was plotted against the frontal area ratio and plan area ratio. The result indicates that: (1) the mean wind speed dramatically decreases with the increase of plan area ratio and (2) the mean wind speed exponentially decreases with the increase of frontal area ratio and qualitatively agrees with the power law relationship which is proposed by previous researcher. In addition, the frontal area ratio is considered as a better parameter to evaluate the performance of urban ventilation. 

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 Assessing Variability of Wind Speed: Comparison and Validation of 27 Methodologies

2018 ◽  
Author(s):  
Joseph C. Y. Lee ◽  
M. Jason Fields ◽  
Julie K. Lundquist
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Resource Assessment ◽  
Assessment Process ◽  
Wind Speeds ◽  
Statistical Confidence ◽  
Monthly Total ◽  
Mean Wind Speed

Abstract. Because wind resources vary from year to year, the inter-monthly and inter-annual variability (IAV) of wind speed is a key component of the overall uncertainty in the wind resource assessment process thereby causing challenges to wind-farm operators and owners. We present a critical assessment of several common approaches for calculating variability by applying each of the methods to the same 37-year monthly wind-speed and energy-production time series to highlight the differences between these methods. We then assess the accuracy of the variability calculations by correlating the wind-speed variability estimates to the variabilities of actual wind-farm energy production. We recommend the Robust Coefficient of Variation (RCoV) for systematically estimating variability, and we underscore its advantages as well as the importance of using a statistically robust and resistant method. Using normalized spread metrics, including RCoV, high variability of monthly mean wind speeds at a location effectively denotes strong fluctuations of monthly total energy generations, and vice versa. Meanwhile, the wind-speed IAVs computed with annual-mean data fail to adequately represent energy-production IAVs of wind farms. Finally, we find that estimates of energy-generation variability require 10 ± 3 years of monthly mean wind-speed records to achieve 90 % statistical confidence. This paper also provides guidance on the spatial distribution of wind-speed RCoV.

Peak Wind Power Statistics

1990 ◽  
Vol 112 (3) ◽  
pp. 170-173 ◽  
Author(s):  
B. Alibe
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Gaussian Process ◽  
Wind Power ◽  
Wind Velocity ◽  
Distribution Functions ◽  
Stationary Gaussian Process ◽  
Probability Distribution Functions ◽  
Mean Wind Speed ◽  
The Mean

Probability distribution functions, mean upcrossing rates and other descriptors are developed for the power that can be potentially extracted from the wind. Wind power is proportional to the cube of the wind velocity. The wind velocity is modeled as a stationary Gaussian process. The distribution of the extreme power is developed from mean upcrossing rates and the assumption that crossings of high thresholds follow a Poisson probability law. The results obtained are valid for any amount of the mean wind speed.

Site-specific technical and economic analysis of wind power potential and energy generation using Weibull parameters

2018 ◽  
Vol 15 (1) ◽  
pp. 35-53 ◽  
Author(s):  
Zahid Hussain Hulio ◽  
Wei Jiang
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Economic Analysis ◽  
Wind Power ◽  
Wind Turbines ◽  
Energy Generation ◽  
Site Specific ◽  
Content Type ◽  
Mean Wind Speed ◽  
The Mean

Purpose The purpose of this paper is to find out a new potential site for energy generation to maximize the energy generation via installing utility wind turbines. Design/methodology/approach In this paper, Weibull two-parameter methodologies are used to determine the effectiveness of the wind speed at three different heights including 80, 60 and 30 m. Standard deviation and wind power density (WPD) are also calculated for the site. After analyzing the wind resource, the wind turbine selection is materialized to maximize the energy production, considering the best configuration of the wind turbines that is suitable for the site. In the end, economic aspect is also calculated. Findings The mean Weibull dimensionless parameter k is found to be 2.91, 2.845 and 2.617, respectively. The mean Weibull scale parameter c is found to be 6.736, 6.524 and 6.087 at the heights of 80, 60 and 30 m, respectively. The mean standard deviation is found to be 2.297, 2.249 and 2.157 at the heights of 80, 60 and 30 m at the heights of 80, 60 and 30 m, respectively. Wind power densities are calculated to be 265, 204 and 157.9 W/m2 at the heights of 80, 60 and 30 m, respectively (highest in the month of July when the mean wind speed is 7.707 m/s and WPD is 519 W/m2). Finally, site-specific economic analysis of wind turbines is carried out, which shows $0.0230 per kWh at the height of 80 m. Originality/value The results show that the site is beneficial for the installation of small and large wind turbines.

Wind Speed Profile and Gradient Height in Typhoons Observed by Vehicular Doppler Radar in South China

2010 ◽  
Vol 163-167 ◽  
pp. 3887-3892
Author(s):  
Li Xiao Li ◽  
Yi Qing Xiao ◽  
Li Li Song ◽  
Peng Qin
Keyword(s):  
Wind Speed ◽  
Doppler Radar ◽  
Probability Method ◽  
Wall Region ◽  
Wind Speed Profile ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
The Mean ◽  
The Times ◽  
Wind Profiles

The recent development of Doppler radar sensor has allowed to study the typhoon wind structure more accuracy and systematic. In order to obtain more wind data near typhoon eye-wall, vehicular Doppler radar emerge as the times require. Based on two typhoon observed results carried out by vehicular Doppler radar in category A terrain, firstly the 10min mean wind profiles under 1000m height in different regions of typhoon were analyzed. The typhoon mean wind speeds increase a logarithmic law with height at nearly lower two hundred meters in all regions of typhoons. Using the power law to fit wind profiles, the exponential index α in pre-eye-wall region is greater than it in post-eye-wall region, and it decreases with increasing the mean wind speed. Secondly, based on analyzing the relationship between mean wind speed and wind ratio, the calculation formula for nominal gradient height were established in category A terrain. Finally introducing the probability method to study the mean wind profile, the exponential index α was established in category A terrain.

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