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.

scholarly journals Mixture probability distribution functions using novel metaheuristic method in wind speed modeling

2021 ◽  
Author(s):  
Amr Khaled Khamees ◽  
Almoataz Y. Abdelaziz ◽  
Ziad M. Ali ◽  
Mosleh M. Alharthi ◽  
Sherif S.M. Ghoneim ◽  
...  
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Distribution Functions ◽  
Probability Distribution Functions

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 Global and Regional Comparison of Daily 2-m and 1000-hPa Maximum and Minimum Temperatures in Three Global Reanalyses

2009 ◽  
Vol 22 (17) ◽  
pp. 4667-4681 ◽  
Author(s):  
A. J. Pitman ◽  
S. E. Perkins
Keyword(s):  
Probability Distribution ◽  
Probability Density Functions ◽  
Distribution Functions ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
Density Functions ◽  
Regional Comparison ◽  
Probability Distribution Functions ◽  
Air Temperatures ◽  
The Mean

Abstract A comparison of three global reanalyses is conducted based on probability density functions of daily maximum and minimum temperature at 2-m and 1000-hPa levels. The three reanalyses compare very favorably in both maximum and minimum temperatures at 1000 hPa, in both the mean and the 99.7th and 0.3rd percentiles of both quantities in most regions. At 2 m, there are large and widespread differences in the mean and 99.7th percentiles in maximum temperature between the three reanalyses over land commonly exceeding ±5°C and regionally exceeding ±10°C. The 2-m minimum temperatures compare unfavorably between the three reanalyses over virtually all continental surfaces with differences exceeding ±10°C over widespread areas. It is concluded that the three reanalyses are generally interchangeable in 1000-hPa temperatures. The three reanalyses of 2-m temperatures are very different owing to the methods used to diagnose these quantities. At this time, the probability distribution functions of the 2-m temperatures from the three reanalyses are sufficiently different that either the 2-m air temperatures should not be used or all three products should be used independently in any application and the differences highlighted.

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.

On the conditional expected value of contributions from a renewal process

1966 ◽  
Vol 3 (2) ◽  
pp. 464-480 ◽  
Author(s):  
M. F. James
Keyword(s):  
Probability Distribution ◽  
Cross Sections ◽  
Renewal Process ◽  
Mean Value ◽  
Distribution Functions ◽  
Total Contribution ◽  
Probability Distribution Functions ◽  
General Terms ◽  
The Mean ◽  
Neutron Cross Sections

The problem discussed in this paper arose from the study of the effects of unresolved resonances on neutron cross-sections, but it is considered here in more general terms.Events in a modified renewal process occur at successive intervals x1, x2, …, and the ith event has associated with it a parameter Γi. The random variables xi and Γi are all independent, and their probability distribution functions are known. Each event contributes to two quantities F(u) and G(v) measured at u and v respectively. The value of the total contribution of all events to G(v) is assumed to be known from observation: this paper gives formulae for the mean value of F(u) conditional on this known value of G(v).

On the conditional expected value of contributions from a renewal process

1966 ◽  
Vol 3 (02) ◽  
pp. 464-480
Author(s):  
M. F. James
Keyword(s):  
Probability Distribution ◽  
Cross Sections ◽  
Renewal Process ◽  
Mean Value ◽  
Distribution Functions ◽  
Total Contribution ◽  
Probability Distribution Functions ◽  
General Terms ◽  
The Mean ◽  
Neutron Cross Sections

The problem discussed in this paper arose from the study of the effects of unresolved resonances on neutron cross-sections, but it is considered here in more general terms. Events in a modified renewal process occur at successive intervals x 1, x 2, …, and the ith event has associated with it a parameter Γ i . The random variables xi and Γ i are all independent, and their probability distribution functions are known. Each event contributes to two quantities F(u) and G(v) measured at u and v respectively. The value of the total contribution of all events to G(v) is assumed to be known from observation: this paper gives formulae for the mean value of F(u) conditional on this known value of G(v).

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.

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