STATISTICAL DISTRIBUTION ANALYSIS IMPLEMENTATION USING MATLAB FOR WIND ENERGY
K. MAHESH *
Department of CSE, Faculty at New Horizon, College of Engineering, JAIN University, Bangalore-560103, India.
M. V. VIJAYAKUMAR *
Department of Computer Science Engineering, Dr AIT, Visvesvaraya Technological University, India.
Y. H. GANGADHARAIAH *
Department of Mathematics, New Horizon College of Engineering, Visvesvaraya Technological University, India.
J. LITHESH *
Department of Electrical and Electronics Engineering, New Horizon College of Engineering, Visvesvaraya Technological University, India.
*Author to whom correspondence should be addressed.
This paper analyses wind speed characteristics and wind power potential of Naganur site using statistical probability parameters. A measured 10-minute time series average wind speed over a period of 4 years (2006- 2009) was obtained from Karnataka Renewable Energy Development Limited (KREDL). Weibull density distribution function is an analytical function which is found to fit the wind speed curve very well. To assess the wind power potentials, the Weibull two parameters (k and c) were computed in the analysis of wind speed data. The wind speed distributions were represented by Weibull distribution and related distribution. The data used were real time data and calculated by using the MATLAB programming to determine and generate the Weibull and Rayleigh distribution functions. The monthly values of k range from 2.21 to 8.64 and the values of c ranged from 2.28 to 6.80. The most probable wind speed and corresponding maximum energy are in the range of 2.45 to 6.52 and 3.10 to 6.26 respectively. The Weibull and Rayleigh distributions also revealed estimated wind power densities ranging between 7.30 W/m2 to 116.51 W/m2 and 9.71 W/m2 to 266.00 W/m2 respectively at 10 m height for the location under study. This paper is relevant to a decision-making process on significant investment in a wind power project.
Keywords: Statistical analysis, wind power density, wind speed, weibull parameters