Assessment of wind energy potential and optimal electricity generation in Borj-Cedria, Tunisia

Dahmouni, A. W.; Salah, M. Ben; Askri, Faouzi; Kerkeni, C.; Nasrallah, Sassi Ben

doi:10.1016/j.rser.2010.07.020

Cited by 86 publications

(40 citation statements)

References 19 publications

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“…Table 7 shows, for the whole year, the comparison between the mean wind speed standard deviation predicted by the Weibull methods and the measured wind speed data while table 8 gives an idea about the comparison between the mean wind speeds predicted by the Weibull methods and the measured wind speed data. …”

Section: Resultsmentioning

confidence: 99%

“…It is obvious that the more appropriate Weibull estimation method shall provide accurate and efficient evaluation of wind energy potential. In this regard, a number of studies have been carried out by various researchers in order to assess wind energy potential by using the Weibull PDF [6][7][8][9][10] .Various methods have been effectively experimented for estimating the shape and scale parameters and the precision of each method varied according to the sample data distribution, which is basically location specific. In the present study, five numerical methods, namely the maximum likelihood method, the modified maximum likelihood method, the energy pattern factor method, the graphical method, and the empirical method are explored and their accuracy compared for Banyo, Meiganga and Ngaoundéré in the Adamaoua region in Cameroon.…”

Section: Introductionmentioning

confidence: 99%

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Performance analysis of Weibull methods for estimation of wind speed distributions in the adamaoua region of Cameroon

Kaoga

Yamigno²,

Raïdandi³

et al. 2014

International Journal of Basic and Applied Sciences

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This paper explores the performance analysis of five Weibull distribution methods to select the more accurate estimation for the Weibull parameters using time-series of measured daily wind speed data collected in three localities in the Adamaoua region of Cameroon. The Weibull distribution with two parameters, the shape k, and the scale C, was specifically considered to be a good quality probabilistic model for wind speed distributions. The five Weibull distribution methods proved to be effective in evaluating the parameters of the Weibull distribution. This fact was supported by the values of the root mean square error, the Chi-square (χ²) and the correlation coefficient R² which showed magnitudes very close to each other. In addition, the comparison between wind speed distributions predicted by the Weibull methods and wind speed distributions measured locally, suggested that the most accurate two-parameter Weibull distribution method is the Energy Pattern Factor Method (EPF). As a result, to reduce uncertainties related to the wind energy output calculation, the EPF is recommended for estimating wind speed distributions.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance analysis of Weibull methods for estimation of wind speed distributions in the adamaoua region of Cameroon

Kaoga

Yamigno²,

Raïdandi³

et al. 2014

International Journal of Basic and Applied Sciences

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“…Dahmouni et al [13] assessed the wind power potential of Borj Cedria in Tunisia using measured wind speeds at 10-, 20-, and 30-m heights above the ground level. The author used the seven 1.5 MW rated capacity wind turbines for the wind power potential of site.…”

Section: Literature Reviewmentioning

confidence: 99%

Technical and economic assessment of wind power potential of Nooriabad, Pakistan

2017

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Background: Pakistan is a developing nation and heavily spends on the development of conventional power plants to meet the national energy demand. The objective of this paper is to investigate wind power potential of site using wind speed, wind direction, and other meteorological data collected over a period of 1 year. This type of detailed investigation provides information of wind characteristics of potential sites and helps in selecting suitable wind turbine. Methods: The site-specific air density, wind shear, wind power density, annual energy yield, and capacity factors have been calculated at 30 and 50 m above the ground level (AGL). The Weibull parameters have been calculated using empirical (EM), maximum likelihood (MLM), modified maximum likelihood (MMLM), energy pattern (EPFM), and graphical (GM) methods to determine the other dependent parameters. The accuracies of these methods are determined using correlation coefficient (R

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“…The data are obtained from a meteorological station in Tehran related to the Tehran Meteorological Organization (TMO). To convert the wind energy based on the height of the hub, the wind law is applied [31]. The aim is to improve the efficiency by optimal layout of 20 turbines and to decrease the wake effect to maximize the profit.…”

Section: An Application Of Ica To Solve the Quadratic Assignment Problemmentioning

confidence: 99%

Developing Realistic Designs for Wind Farms: Incorporation of an Imperialist Competitive Algorithm

Raahemifar

Rosen

Rahbari

et al. 2014

Proceedings of the 4th World Sustainability Forum

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Abstract:The optimal positioning of wind turbines plays an important role in acquiring the anticipated output power from wind farms. This paper addresses challenges related to typical restriction assumptions for turbine arrangements in wind farms with a candidate selection approach. A hybrid quadratic assignment problem-imperialist competitive algorithm (ICA-QAP) method with an initial candidate points' selection (ICPS) approach is applied to two case studies. This hybrid algorithm is used to obtain optimal layout designs in terms of maximum efficiency. The current study incorporates previously utilized indicators from the literature for wind farms, such as wake effects, turbine hub height, rotor diameter, and power losses, and proposes additional criteria such as load-bearing capacity of soil and its restrictions. This is done to make the method applicable for realistic cases, and to incorporate the comments of expert designers into the design process and results. The results indicate that the achieved optimal layout design provides superior performance of the farms compared to that provided in previous similar studies. An efficiency improvement of about OPEN ACCESS 2 5% is attained for the first considered case. In addition, a combination of Dijkstra's Minimum Spanning and K-means approaches is applied to reduce the length of cables in the farm by 664 m in the second studied case.

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Assessment of wind energy potential and optimal electricity generation in Borj-Cedria, Tunisia

Cited by 86 publications

References 19 publications

Performance analysis of Weibull methods for estimation of wind speed distributions in the adamaoua region of Cameroon

Performance analysis of Weibull methods for estimation of wind speed distributions in the adamaoua region of Cameroon

Technical and economic assessment of wind power potential of Nooriabad, Pakistan

Developing Realistic Designs for Wind Farms: Incorporation of an Imperialist Competitive Algorithm

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