Analysis of wind power potential by the three-parameter Weibull distribution to install a wind turbine

Sukkiramathi, K.; Seshaiah, C. V.

doi:10.1177/0144598719871628

Cited by 26 publications

(17 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For each time series obtained, the frequency distribution of the wind intensity and the probability density function (PDF), f ( v ), 33,35,36 are calculated using the following equation:

f ((), v) = \frac{k}{c} {(\frac{v}{c})}^{k - 1} {e^{([], \frac{v}{c})}}^{k}

where v is the wind speed in m/s and the parameters k > 0 and c > 1 are the scale factor and the shape factor, respectively 37 …”

Section: Methodsmentioning

confidence: 99%

Analysis of solar and wind energy installations at electric vehicle charging stations in a region in Brazil and their impact on pricing using an optimized sale price model

et al. 2020

View full text Add to dashboard Cite

Electric vehicles are becoming more popular in the automobile sector since questions about the environment and quality of life have become increasingly important. New ways of commercializing energy should be regulated, like the sale prices applied to service stations for electric vehicles. This study adopted a model for calculating tariffs at a charging station using the optimized tariff methodology-Tarot, a new application for this method. The charging station proposed uses an alternative energy generation system comprised of photovoltaic panels and wind turbines. We evaluated four regions in Brazil with different solar and wind potentials. This is done to see how the tariff can be impacted by the use of natural resources. As a result, we indicate that the application of the Tarot methodology adapted to the concept of charging electric vehicles from the use of renewable sources becomes an opportunity for the sector to apply a tariff adjusted to national regulatory guidelines and to provide a better cost/benefit for the consumer. Of the four regions analyzed, Region 2 proved to be the best region for the implementation of this type of enterprise with the use of a wind and solar distributed generator. The difference in billing value with the average tariff applied with the aid of the distributed system and purely energy network reaches 6% in Region 2. If the photovoltaic generation is added in 30% in this location, it can cause a reduction of up to 7% in the tariff for the sale of energy to vehicles.

show abstract

“…For each time series obtained, the frequency distribution of the wind intensity and the probability density function (PDF), f ( v ), 33,35,36 are calculated using the following equation:

f ((), v) = \frac{k}{c} {(\frac{v}{c})}^{k - 1} {e^{([], \frac{v}{c})}}^{k}

where v is the wind speed in m/s and the parameters k > 0 and c > 1 are the scale factor and the shape factor, respectively 37 …”

Section: Methodsmentioning

confidence: 99%

Analysis of solar and wind energy installations at electric vehicle charging stations in a region in Brazil and their impact on pricing using an optimized sale price model

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The parameters k and c depend on the location of the wind source. Several methodologies using the available wind speed data such as least-squares fit methods, maximum likelihood method, and method of moments [56] have been proposed to estimate k and c. Moreover, many computer modelling packages, such as HOMER and WASP, have been used in several works for estimating these parameters [57]. In [1], it is suggested that [1.0-3.0] and [5.0-20.0] are suitable ranges for the shape and scale factors, respectively.…”

Section: Equivalent Deterministic Model For the Eed Problem Includingmentioning

confidence: 99%

Chaotic sine–cosine algorithm for chance‐constrained economic emission dispatch problem including wind energy

Guesmi

Farah

Ismail

et al. 2020

IET Renewable Power Generation

View full text Add to dashboard Cite

One of the most effective approaches to reduce carbon emissions is the integration of renewable energy sources into electrical power networks. Currently, wind turbines are the fastest growing among all renewable sources. With the integration of wind farms into electrical grids, the economic emission dispatch (EED) problem is becoming more complicated due to the stochastic availability of wind energy. In this study, a new approach is proposed to solve the EED problem incorporating wind farms. The problem is formulated as a chance-constrained problem to deal with the stochastic characteristic of wind power. A novel chaotic sine-cosine algorithm (CSCA) is proposed to provide the optimal generation schedule to minimise simultaneously the generation cost and emission. Some weakness has been encountered in exploitation and exploration capabilities in standard sine cosine algorithm (SCA). Hence, the chaos is integrated into the original SCA to improve its performance. In addition, a new mutation strategy is added to the SCA. In this study, the new algorithm is based on three mutually exclusive equations. The new technique is applied on the 69-bus ten-unit and 40-unit test systems with and without wind energy. The results performed by CSCA are compared with those generated by other recent techniques.

show abstract

“…Therefore, its usage cannot be generalized. To minimize errors, a suitable probability density function must be carefully selected for different wind regimes (Carta et al 2009;Sukkiramathi and Seshaiah, 2020). Tuller and Brett (1984) proposed a three-parameter Weibull function in wind analysis and found that it showed better fitness and flexibility than the two-parameter Weibull function.…”

Section: Introductionmentioning

confidence: 99%

“…The author compared the wind speeds for three different sites and found that the threeparameter Weibull distribution performed best when there was a greater frequency of lower wind speeds. Sukkiramathi and Seshaiah (2020) also utilized the three-parameter Weibull distribution for analyzing wind power potential. However, to date, only limited research has been carried out on wind analysis using the three-parameter Weibull distribution.…”

Section: Introductionmentioning

confidence: 99%

Bayesian method for estimating Weibull parameters for wind resource assessment in the Equatorial region: a comparison between two-parameter and three-parameter Weibull distributions

Khan¹,

Ahmed²

2022

Preprint

View full text Add to dashboard Cite

The two-parameter Weibull distribution has garnered much attention in the assessment of windenergy potential. The estimation of the shape and scale parameters of the distribution has broughtforth a successful tool for the wind energy industry. However, it may be inappropriate to use thetwo-parameter Weibull distribution to assess energy at every location, especially at sites wherelow wind speeds are frequent, such as the Equatorial region. In this work, a robust technique inwind resource assessment using a Bayesian approach for estimating Weibull parameters is firstproposed. Secondly, the wind resource assessment techniques using a two-parameter Weibulldistribution and a three-parameter Weibull distribution which is a generalized form of twoparameterWeibull distribution are compared. Simulation studies confirm that the Bayesianapproach seems a more robust technique for accurate estimation of Weibull parameters. Theresearch is conducted using data from seven sites in Equatorial region from 1o N of Equator to 19oSouth of Equator. Results reveal that a three-parameter Weibull distribution with non-zero shiftparameter is a better fit for wind data having a higher percentage of low wind speeds (0-1 m/s) andlow skewness. However, wind data with a smaller percentage of low wind speeds and highskewness showed better results with a two-parameter distribution that is a special case of threeparameterWeibull distribution with zero shift parameter. The results also demonstrate that theproposed Bayesian approach and application of a three-parameter Weibull distribution areextremely useful in accurate estimate of wind power and annual energy production.

show abstract

Analysis of wind power potential by the three-parameter Weibull distribution to install a wind turbine

Cited by 26 publications

References 16 publications

Analysis of solar and wind energy installations at electric vehicle charging stations in a region in Brazil and their impact on pricing using an optimized sale price model

Analysis of solar and wind energy installations at electric vehicle charging stations in a region in Brazil and their impact on pricing using an optimized sale price model

Chaotic sine–cosine algorithm for chance‐constrained economic emission dispatch problem including wind energy

Bayesian method for estimating Weibull parameters for wind resource assessment in the Equatorial region: a comparison between two-parameter and three-parameter Weibull distributions

Contact Info

Product

Resources

About