Wind data analysis and accurate wind energy potential assessment are critical factors for suitable development of wind power application at a given location. This paper explores wind speed distribution to select the two-parameter Weibull methods that provide accurate and efficient estimation of energy output for Wind Energy Conversion Systems (WECS).The dimensionless shape parameter k and the scale parameter C are determined based on measured hourly mean wind speed data in times-series from 2007 to 2012, collected at the Garoua International Airport, main meteorological station, in Garoua, Cameroon. Six numerical methods, namely Empirical Method (EM), Energy Pattern Factor method (EPF), Graphical Method (GM), Maximum Likelihood Method (MLM), Moment Method (MM) and Modified Maximum Likelihood Method (MMLM) are examined to estimate the Weibull parameters. To analyze the efficiency of the methods and to ascertain how closely the measured data follow the Weibull methods, goodness of fit tests were performed using the chi-square test (X2), correlation coefficient (R2), root mean square error (RMSE) and Kolmogorov-Smirnov test (KOL). The results revealed that the EPF followed by the MM were the most accurate and efficient methods for determining the value of C and k to approximate wind speed distribution. The statistical tests rejected the GM as an adequate method and revealed as well that the EM, MLM and MMLM ranked respectively third, fourth and fifth. Furthermore, the potential for wind energy development in Garoua is not fitted for generating electricity and a very fruitful result would be achieved if windmills were installed for producing community water supply, livestock watering, and farm irrigation.
Statistical analysis of wind speed distribution based on sixWeibull Methods for wind power evaluation in Garoua, Cameroon
Dieudonné Kidmo Kaoga,R. Danwé,Serge Yamigno Doka,Noël Djongyang
Published 2015 in Journal of Renewable Energies
ABSTRACT
PUBLICATION RECORD
- Publication year
2015
- Venue
Journal of Renewable Energies
- Publication date
2015-03-31
- Fields of study
Geography, Engineering, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar
CITATION MAP
EXTRACTION MAP
CLAIMS
CONCEPTS
- chi-square test
A statistical goodness-of-fit test used to compare measured wind-speed frequencies with Weibull-model frequencies.
Aliases: X2
- correlation coefficient
A fit-quality measure used to quantify agreement between measured and modeled wind-speed distributions.
Aliases: R2
- energy pattern factor method
A Weibull-parameter estimation method that derives distribution parameters from the energy pattern factor of the wind-speed data.
Aliases: EPF
- garoua international airport
The meteorological station in Garoua, Cameroon that provided the hourly mean wind-speed measurements used in the analysis.
Aliases: Garoua
- graphical method
A graphical procedure used to estimate Weibull distribution parameters from the wind-speed data.
Aliases: GM
- kolmogorov-smirnov test
A nonparametric goodness-of-fit test used to assess how closely the measured data follow the Weibull distribution.
Aliases: KOL
- moment method
A Weibull-parameter estimation method based on matching sample moments to the Weibull distribution moments.
Aliases: MM
- root mean square error
An error metric used to measure the deviation between observed and Weibull-modeled wind-speed values.
Aliases: RMSE
- weibull distribution
The two-parameter probability distribution used here to model wind-speed frequency and derive wind-energy estimates.
Aliases: two-parameter Weibull
- weibull parameters
The shape parameter k and scale parameter C that characterize the fitted Weibull wind-speed distribution in this paper.
Aliases: shape parameter k, scale parameter C
- wind energy potential
The site-specific assessment of how much usable wind energy the Garoua wind record can support.
Aliases: wind power potential
REFERENCES
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