STATISTICAL ANALYSIS OF WIND SPEED FOR ELECTRICAL POWER GENERATION IN SOME SELECTED SITES IN NORTHERN NIGERIA

Authors

  • A Abdulkarim DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING, UNIVERSITY OF ILORIN, KWARA STATE, NIGERIA
  • SM Abdelkader DEPARTMENT OF ELECTRICAL ENGINEERING, FACULTY OF ENGINEERING, MANSOURA UNIVERSITY, EGYPT
  • DJ Morrow SCHOOL OF ELECTRONICS, ELECTRICAL ENGR. AND COMPUTER SCI., QUEEN’S UNIV. BELFAST, UNITED KINGDOM
  • AJ Falade DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING, UNIVERSITY OF ILORIN, KWARA STATE, NIGERIA
  • YA Adediran DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING, UNIVERSITY OF ILORIN, KWARA STATE, NIGERIA

DOI:

https://doi.org/10.4314/njt.364.1499

Keywords:

Wind speed - probability - density function – wind energy conversion system- statistical analyses

Abstract

In this paper, statistical analysis is carried out to determine the accurate frequency distribution that fits wind speed data. The frequency distributions used include Weibull, Rayleigh and Gamma distribution functions. The performances of the probability distributions are based on the error evaluations between the predicted and the theoretical wind power densities of the site. The Results show that Weibull distribution modelled the wind speed better compared to other distribution functions. According to the European Wind Energy Association, most of the sites are suitable for the generation of electrical energy. Also, the results have shown that Jos, Kano and Minna fall in class 4 and therefore suitable for both off grid and grid connected modes. In addition, the effects of c and k parameters on the probability distribution functions have been presented.

 

http://dx.doi.org/10.4314/njt.v36i4.35

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Published

2017-09-29

Issue

Section

Computer, Telecommunications, Software, Electrical & Electronics Engineering

How to Cite

STATISTICAL ANALYSIS OF WIND SPEED FOR ELECTRICAL POWER GENERATION IN SOME SELECTED SITES IN NORTHERN NIGERIA. (2017). Nigerian Journal of Technology, 36(4), 1249-1257. https://doi.org/10.4314/njt.364.1499