Authors: Manish Kumar; Cherian Samuel
Addresses: Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi – 221005, India ' Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi – 221005, India
Abstract: Integration of renewable distributed generation technology with radial power distribution system is rapidly growing. Among the number of available renewable energy sources, the role of wind energy in the power sector is very important. In this work, authors have estimated the wind energy potential at Banaras Hindu University (BHU), India. Estimation of wind energy potential depends on statistical analysis of wind speed distribution, which will give us the best-fitted probability density function of the desired location. For statistical analysis of wind speed distribution, authors have taken hourly data of BHU centre from the source of National Renewable Energy Laboratory (NREL), USA for the 12-month period. A statistical R-programming language tool has been used for the computational work. In this work, authors have considered Weibull, Gamma and Lognormal probability distributions for getting best-fitted distribution. After the analysis, result shows for the given wind speed data of BHU area, Weibull distribution is the best-fitted one.
Keywords: statistical analysis; wind speed; wind energy potential; renewable energy; renewable distributed generation; probability distribution; goodness-of-fit.
International Journal of Intelligent Systems Technologies and Applications, 2018 Vol.17 No.1/2, pp.19 - 41
Received: 11 Feb 2017
Accepted: 31 Mar 2017
Published online: 03 May 2018 *