Assessment of Wind Power Potential Based on Raleigh Distribution Model: An Experimental Investigation for Coastal Zone
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
M. H. Baloch, G. S. Kaloi, J. Wang, “Feasible Wind Power Potential from Costal Line of Sindh Pakistan”, Research Journal of Applied Sciences, Engineering and Technology, Vol. 10, No. 4, pp. 393-400, 2015 DOI: https://doi.org/10.19026/rjaset.10.2504
V. Sohoni, S. Gupta, R. Nema, “A comparative analysis of wind speed probability distributions for wind power assessment of four sites”, Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 24, No. 6, pp. 4724-4735, 2016 DOI: https://doi.org/10.3906/elk-1412-207
K. W. G. D. H. Rajapaksha, K. Perera, “Wind speed analysis and energy calculation based on mixture distributions in Narak kalliya, Sri Lanka”, Journal of the National Science Foundation of Sri Lanka Vol. 44, No. 4, pp. 409-416, 2016 DOI: https://doi.org/10.4038/jnsfsr.v44i4.8023
A. Parajuli, “A statistical analysis of wind speed and power density based on Weibull and Rayleigh models of Jumla, Nepal”, Energy and Power Engineering, Vol. 8, No. 7, pp. 271-271, 2016 DOI: https://doi.org/10.4236/epe.2016.87026
A. K. Azad, M. G. Rasul, T. Yusaf, “Statistical diagnosis of the best weibull methods for wind power assessment for agricultural applications”, Energies, Vol. 7, No. 5, pp. 3056-3085, 2014
S. F. Khahro, K. Tabbassum, A. M. Soomro, L. Dong, X. Liao, “Evaluation of wind power production prospective and Weibull parameter estimation methods for Babaurband, Sindh Pakistan”, Energy conversion and Management, Vol. 78, pp. 956-967, 2014 DOI: https://doi.org/10.1016/j.enconman.2013.06.062
A. Zaharim, A. M. Razali, R. Z. Abidin, K. Sopian, “Fitting of statistical distributions to wind speed data in Malaysia”, European Journal of Scientific Research, Vol. 26, No. 1, pp. 6-12, 2009
Y. Q. Xiao, Q. S. Li, Z. N. Li, Y. W. Chow, G. Q. Li, “Probability distributions of extreme wind speed and its occurrence interval”, Engineering Structures, Vol. 28, No. 8, pp. 1173-1181, 2006 DOI: https://doi.org/10.1016/j.engstruct.2006.01.001
S. H. Pishgar-Komleh, A. Keyhani, P. Sefeedpari, “Wind Speed and Power Density Analysis Based on Weibull and Rayleigh Distributions (A Case Study: Firouzkooh County of Iran)”, Renewable and Sustainable Energy Reviews, Vol. 42, pp. 313-322, 2015 DOI: https://doi.org/10.1016/j.rser.2014.10.028
T. B. Ouarda, C. Charron, J. Y. Shin, P. R., Marpu, A. H. Al-Mandoos, M. H. Al-Tamimi, H. Ghedira, T. N. Al Hosary, “Probability distributions of wind speed in the UAE. Energy Conversion and Management, Vol. 93, pp. 414-434, 2015 DOI: https://doi.org/10.1016/j.enconman.2015.01.036
P. A. C. Rocha, R. C. de Sousa, C. F. de Andrade, M. E. V. da Silva, “Comparison of seven numerical methods for determining Weibull parameters for wind energy generation in the northeast region of Brazil”, Applied Energy, Vol. 89, No. 1, pp. 395-400, 2012 DOI: https://doi.org/10.1016/j.apenergy.2011.08.003
Z. Olaofe, K. Folly, “Statistical Analysis of the Wind Resources at Darling for Energy Production”, International Journal of Renewable Energy Research, Vol. 2, pp. 250-261, 2012
C. Tian Pau, “Estimation of wind energy potential using different probability density functions”, Applied Energy, Vol. 88, No. 5, pp. 1848-1856, 2011 DOI: https://doi.org/10.1016/j.apenergy.2010.11.010
V. T. Morgan, “Statistical distributions of wind parameters at Sydney, Australia”, Renewable Energy, Vol. 6, No. 1, pp. 39-47, 1995 DOI: https://doi.org/10.1016/0960-1481(94)E0017-Y
Y. An, M. D. Pandey, “The r largest order statistics model for extreme windspeed estimation”, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 95, No. 3, pp. 165-182, 2007 DOI: https://doi.org/10.1016/j.jweia.2006.05.008
A. Azad, M. Rasul, T. Yusaf, “Statistical Diagnosis of the Best Weibull Methods for Wind Power Assess-ment for Agricultural Applications”, Energies, Vol. 7, pp. 3056-3085, 2014 DOI: https://doi.org/10.3390/en7053056
S. A. Akdag, A. Dinler, “A new method to estimate Weibull parameters for wind energy applications”, Energy Conversion and Management, Vol. 50, No. 7, pp. 1761-1766, 2009 DOI: https://doi.org/10.1016/j.enconman.2009.03.020
T. Soukissian, “Use of multi-parameter distributions for offshore wind speed modelling: the Johnson S E distribution”, Applied Energy, Vol. 111, pp. 982-1000, 2013 DOI: https://doi.org/10.1016/j.apenergy.2013.06.050
A. Mostafaeipour, A. Sedaghat, A. A. Dehgan-Niri, V. Kalantar, “Wind energy feasibility study for city of Shahr babak in Iran”, Renewable Sustainable Energy Reviews, Vol. 15, No. 6, pp. 2545-2556, 2011 DOI: https://doi.org/10.1016/j.rser.2011.02.030
M. H. Baloch, S. A. Abro, G. S. Kaloi, N. H. Mirjat, S. Tahir, M. H. Nadeem, M. Gul, Z. A. Memon, M. Kumar, “A Research on Electricity Generation from Wind Corridors of Pakistan (Two Provinces): A Technical Proposal for Remote Zones”, Sustainability, Vol. 9, No. 9, 2017 DOI: https://doi.org/10.3390/su9091611
M. H. Baloch, G. S. Kaloi, Z. A. Memon, “Current scenario of the wind energy in Pakistan challenges and future perspectives: A case study”, Energy Reports, Vol. 2, pp. 201-210, 2016 DOI: https://doi.org/10.1016/j.egyr.2016.08.002
G. S. Kaloi, J. Wang, M. H. Baloch, S. Tahir, “Wind Energy Potential at Badin and Pasni Costal Line of Pakistan”, International Journal of Renewable Energy Development, Vol. 6, No. 2, pp. 103-110, 2017 DOI: https://doi.org/10.14710/ijred.6.2.103-110
M. H. Baloch, J. Wang, G. S. Kaloi, “A Point of View: Analysis and Investigation of Wind Power from Southern Region of Pakistan”, International Journal of Energy Conversion, Vol. 3, No. 3, pp. 103-110, 2015
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