Estimation of Probability Distribution Function and Wind Energy Potential for Higher Heights

M.S.Nidhya, Associate Professor, Department of Computer Science and Information Technology, Jain (Deemed to be University), Email Id-ms.nidhya@jainuniversity.ac.in, Bangalore, India .
Dr. Ramakant Upadhyay, Assistant Professor, Department of Computer Science Engineering, Sanskriti University, Email Id-ramakantupadhyay@sanskriti.edu.in, Mathura, Uttar Pradesh, India .
Dr. Intekhab Alam, Assistant Professor, Maharishi School of Engineering & Technology, Maharishi University of Information Technology, Email Id-intekhab@muit.in, Uttar Pradesh, India .
Kuldeep Singh Kulhar, Professor, Civil Engineering, Vivekananda Global University, Email Id-k.singh@vgu.ac.in, Jaipur, India .

^* Corresponding Author: ms.nidhya@jainuniversity.ac.in

Abstract

This paper focuses on analyzing wind characteristics at Maulana Azad National Institute of Technology. Wind characteristics are site dependents, so it is reasonable that different wind regimes may have different wind speed distributions. Distributions appeared in the literature are revisited and a comparison between these distributions is carried out. Modified maximum likelihood method in Weibull distribution has shown better results over other. Justus and Mikhail method is used for vertical extrapolation of wind power density for higher heights. As a conclusion, the highest wind energy potential value was found in the month of June while the lowest value was encountered in November.