Statistical diagnosis of the best weibull methods for wind power assessment for agricultural applications
Article
Article Title | Statistical diagnosis of the best weibull methods for wind power assessment for agricultural applications |
---|---|
ERA Journal ID | 123161 |
Article Category | Article |
Authors | Azad, Abul Kalam (Author), Rasul, Mohammad Golam (Author) and Yusaf, Talal (Author) |
Journal Title | Energies |
Journal Citation | 7 (5), pp. 3056-3085 |
Number of Pages | 30 |
Year | 2014 |
Publisher | MDPI AG |
Place of Publication | Switzerland |
ISSN | 1996-1073 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/en7053056 |
Web Address (URL) | http://www.mdpi.com/1996-1073/7/5/3056 |
Abstract | The best Weibull distribution methods for the assessment of wind energy potential at different altitudes in desired locations are statistically diagnosed in this study. Seven different methods, namely graphical method (GM), method of moments (MOM), standard deviation method (STDM), maximum likelihood method (MLM), power density method (PDM), modified maximum likelihood method (MMLM) and equivalent energy method (EEM) were used to estimate the Weibull parameters and six statistical tools, namely relative percentage of error, root mean square error (RMSE), mean percentage of error, mean absolute percentage of error, chi-square error and analysis of variance were used to precisely rank the methods. The statistical fittings of the measured and calculated wind speed data are assessed for justifying the performance of the methods. The capacity factor and total energy generated by a small model wind turbine is calculated by numerical integration using Trapezoidal sums and Simpson's rules. The results show that MOM and MLM are the most efficient methods for determining the value of k and c to fit Weibull distribution curves. |
Keywords | Weibull shape factor; scale factor; probability density function; power density; statistical tools |
ANZSRC Field of Research 2020 | 401703. Energy generation, conversion and storage (excl. chemical and electrical) |
490506. Probability theory | |
400803. Electrical energy generation (incl. renewables, excl. photovoltaics) | |
Byline Affiliations | Central Queensland University |
National Centre for Engineering in Agriculture | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q26vv/statistical-diagnosis-of-the-best-weibull-methods-for-wind-power-assessment-for-agricultural-applications
Download files
1799
total views231
total downloads1
views this month0
downloads this month