Assessment of Wind Power Potential Based on Raleigh Distribution Model: An Experimental Investigation for Coastal Zone

Authors

  • B. Memon Department of Electrical Engineering, Mehran University of Engineering & Technology, Pakistan
  • M. H. Baloch Department of Electrical Engineering, Mehran University of Engineering & Technology, Pakistan
  • A. H. Memon Department of Electrical Engineering, Mehran University of Engineering & Technology, Pakistan
  • S. H. Qazi Department of Electrical Engineering, Mehran University of Engineering & Technology, Pakistan
  • R. Haider Electrical Engineering Department, Baluchistan University of Engineering & Technology, Pakistan
  • D. Ishak School of Electrical and Electronics Engineering, Universiti Sains Malaysia, Malaysia
Volume: 9 | Issue: 1 | Pages: 3721-3725 | February 2019 | https://doi.org/10.48084/etasr.2381

Abstract

When compared with other renewable energy resources (RER), the wind energy share in the global energy production is increasing rapidly. Currently, the Government of Pakistan (GoP) is moving towards RER, specifically wind and solar energy. In this paper, the wind energy potential of Tando Ghulam Ali, Sindh, Pakistan is explored. For this purpose, one-year wind speed data is considered at various heights through various probability distribution functions (PDFs). Statistical comparison of Rayleigh, gamma, generalized extreme value (GEV) and lognormal PDFs have been done with two methods, namely root mean square error and (R^2) in order to select the best PDF. Results showed that the Rayleigh distribution function is the best at the above mentioned area for finding various factors like site selection and wind power cost per kWh.

Keywords:

wind energy, wind probability distribution function, fitting tool

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How to Cite

[1]
B. Memon, M. H. Baloch, A. H. Memon, S. H. Qazi, R. Haider, and D. Ishak, “Assessment of Wind Power Potential Based on Raleigh Distribution Model: An Experimental Investigation for Coastal Zone”, Eng. Technol. Appl. Sci. Res., vol. 9, no. 1, pp. 3721–3725, Feb. 2019.

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