In the present study, wind speed data of Jumla, Nepal have been statistically analyzed. For this purpose, the daily averaged wind speed data for 10 year period (2004-2014: 2012 excluded) provided by Department of Hydrology and Meteorology (DHM) was analyzed to estimate wind power density. Wind speed as high as 18 m/s was recorded at height of 10 m. Annual mean wind speed was ascertained to be decreasing from 7.35 m/s in 2004 to 5.13 m/s in 2014 as a consequence of Global Climate Change. This is a subject of concern looking at government’s plan to harness wind energy. Monthly wind speed plot shows that the fastest wind speed is generally in month of June (Monsoon Season) and slowest in December/January (Winter Season). Results presented Weibull distribution to fit measured probability distribution better than the Rayleigh distribution for whole years in High altitude region of Nepal. Average value of wind power density based on mean and root mean cube seed approaches were 131.31 W/m 2 /year and 184.93 W/m 2 /year respectively indicating that Jumla stands in class III. Weibull distribution shows a good approximation for estimation of power density with maximum error of 3.68% when root mean cube speed is taken as reference.
KeywordsMean Wind SpeedRayleigh DistributionWeibull DistributionWind Power Density
Albuhairi, M.H. (2006) Assessment and Analysis of Wind Power Density in Taiz—Republic of Yemen. Assiut University Bulletin for Environmental Researches, 9, 13-21.
Ramachandra, T. and Shruthi, B. (2005) Wind Energy Potential Mapping in Karnataka, India, Using GIS. Energy Conversion and Management, 46, 1561-1578. http://dx.doi.org/10.1016/j.enconman.2004.07.009
Hernandez-Escobedo, Q., Manzano-Agugliaro, F., Gazquez-Parra, J.A. and Zapata-Sierra, A. (2011) Is the Wind a Periodical Phenomenon? The Case of Mexico. Renewable and Sustainable Energy Reviews, 15, 721-728. http://dx.doi.org/10.1016/j.rser.2010.09.023
Wentink Jr., T.W. (1976) Study of Alaskan Wind Power and Its Possible Applications. Final Report, 1 May 1974-30 Jan 1976, Geophysical Institute, Alaska University, Fairbanks.
Justus, C.G., Hargreaves, W.R. and Yalcin, A. (1976) Nationwide Assessment of Potential Output from Wind-Powered Generators. Journal of Applied Meteorology, 5, 673-678.
Baynes, C. and Davenport, A. (1975) Some Statistical Models for Wind Climate Prediction. Preprints Fourth Conference Probability and Statistics in the Atmospheric Sciences, Tallahassee, 18-21 November 1975, 1-7.
Rehman, S., Halawani, T.O. and Husain, T. (1994) Weibull Parameters for Wind Speed Distribution in Saudi Arabia. Solar Energy, 53, 473-479. http://dx.doi.org/10.1016/0038-092X(94)90126-M
Fyrippis, I., Axaopoulos, P.J. and Panayiotou, G. (2010) Wind Energy Potential Assessment in Naxos Island, Greece. Applied Energy, 87, 577-586. http://dx.doi.org/10.1016/j.apenergy.2009.05.031
Oner, Y., Ozcira, S., Bekiroglu, N. and Senol, I. (2013) A Comparative Analysis of Wind Power Density Prediction Methods for Çanakkale, Intepe Region, Turkey. Renewable and Sustainable Energy Reviews, 23, 491-502. http://dx.doi.org/10.1016/j.rser.2013.01.052
Odo, F.C., Offiah, S.U. and Ugwuoke, P.E. (2012) Weibull Distribution-Based Model for Prediction of Wind Potential in Enugu, Nigeria. Advances in Applied Science Research, 3, 1202-1208.
Ahmed, S.A. (2013) Comparative Study of Four Methods for Estimating Weibull Parameters for Halabja, Iraq. International Journal of Physical Sciences, 8, 186-192.
Islam, M.R., Saidur, R. and Rahim, N.A. (2011) Assessment of Wind Energy Potentiality at Kudat and Labuan, Malaysia Using Weibull Distribution Function. Energy, 36, 985-992. http://dx.doi.org/10.1016/j.energy.2010.12.011
Safari, B. and Gasore, J. (2010) A Statistical Investigation of Wind Characteristics and Wind Energy Potential Based on the Weibull and Rayleigh Models in Rwanda. Renewable Energy, 35, 2874-2880. http://dx.doi.org/10.1016/j.renene.2010.04.032
Oyedepo, S.O., Adaramola, M.S. and Paul, S.S. (2012) Analysis of Wind Speed Data and Wind Energy Potential in Three Selected Locations in South-East Nigeria. International Journal of Energy and Environmental Engineering, 3, 7. http://dx.doi.org/10.1186/2251-6832-3-7
Abbas, K., Alamgir, K., Ali, A., Khan, D. and Khalil, U. (2012) Statistical Analysis of Wind Speed Data in Pakistan. World Applied Sciences Journal, 18, 1533-1539.
WECS (2008) Energy Sector Synopsis Report.
Surendra, K.C., Khanal, S.K., Shrestha, P. and Lamsal, B. (2011) Current Status of Renewable Energy in Nepal: Opportunities and Challenges. Renewable and Sustainable Energy Reviews, 15, 4107-4117. http://dx.doi.org/10.1016/j.rser.2011.07.022
Ghimire, M., Poudel, R.C., Bhattarai, N. and Luintel, M.C. (n.d.) Wind Energy Resource Assessment and Feasibility Study of Wind Farm in Mustang. Journal of Institute of Engineering, 8, 93-106. http://dx.doi.org/10.3126/jie.v8i1-2.5099
Pishgar-Komleh, S.H., Keyhani, A. and Sefeedpari, P. (2015) Wind Speed and Power Density Analysis Based on Weibull and Rayleigh Distributions (A Case Study: Firouzkooh County of Iran). Renewable and Sustainable Energy Reviews, 42, 313-322. http://dx.doi.org/10.1016/j.rser.2014.10.028
Buenestado-Caballero, P., Jarauta-Bragulat, E. and Hervada-Sala, C. (2006) Weibull Parameters Distribution Fitting in the Surface Wind Layer. International Association for Mathematical Geology 11th International Congress, Liège, 3-8 September 2006, 6-9.
Simiu, E. and Heckert, N.A. (1996) Extreme Wind Distribution Tails: A “Peaks over Threshold” Approach. 539-547.
Ouarda, T.B.M.J., Charron, C., Shin, J.-Y., Marpu, P.R., Al-Mandoos, A.H., Al-Tamimi, M.H., et al. (2015) Probability Distributions of Wind Speed in the UAE. Energy Conversion and Management, 93, 414-434. http://dx.doi.org/10.1016/j.enconman.2015.01.036
Weibull, W. (1951) A Statistical Distribution Function of Wide Applicability. Journal of Applied Mechanics, 103, 293-297.
Akdag, S.A. and Dinler, A. (2009) A New Method to Estimate Weibull Parameters for Wind Energy Applications. Energy Conversion and Management, 50, 1761-1766. http://dx.doi.org/10.1016/j.enconman.2009.03.020
Azad, A., Rasul, M. and Yusaf, T. (2014) Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications. Energies, 7, 3056-3085. http://dx.doi.org/10.3390/en7053056
Chang, T.P. (2010) Wind Speed and Power Density Analyses Based on Mixture Weibull and Maximum Entropy Distributions. International Journal of Applied Science and Engineering Research, 8, 39-46.
Carlin, P.W. (1997) Analytical Expressions for Maximum Wind Turbine Average Power in a Rayleigh Wind Regime. ASME Wind Energy Symposium, Reno, 6-9 January 1997, 1-9.
Patel, M. (2005) Wind and Solar Power Systems: Design, Analysis, and Operation. CRC Press, Boca Raton. http://dx.doi.org/10.1201/9781420039924
Keyhani, A., Ghasemi-Varnamkhasti, M., Khanali, M. and Abbaszadeh, R. (2010) An Assessment of Wind Energy Potential as a Power Generation Source in the Capital of Iran, Tehran. Energy, 35, 188-201. http://dx.doi.org/10.1016/j.energy.2009.09.009
Caretto, L. (2010) Use of Probability Distribution Functions for Wind. California State University Northridge, Calif.
Crutcher, H.L. (1957) On the Standard Vector-Deviation Wind Rose. Journal of Meteorology, 14, 28-33. http://dx.doi.org/10.1175/0095-9634-14.1.28
Dore, A.J., Vieno, M., Fournier, N., Weston, K.J. and Sutton, M.A. (2006) Development of a New Wind-Rose for the British Isles Using Radiosonde Data, and Application to an Atmospheric Transport Model. Quarterly Journal of the Royal Meteorological Society, 132, 2769-2784. http://dx.doi.org/10.1256/qj.05.198
Iacono, M.J. (2009) Why Is the Wind Speed Decreasing? Journal of Geophysical Research: Atmospheres, 114, 1-3.
Yin, J.H. (2005) A Consistent Poleward Shift of the Storm Tracks in Simulations of 21st Century Climate. Geophysical Research Letters, 32, L18701. http://dx.doi.org/10.1029/2005GL023684
Leibensperger, E.M., Mickley, L.J. and Jacob, D.J. (2008) Sensitivity of US Air Quality to Mid-Latitude Cyclone Frequency and Implications of 1980-2006 Climate Change. Atmospheric Chemistry and Physics, 8, 7075-7086. http://dx.doi.org/10.5194/acpd-8-12253-2008
Wang, X.L., Wan, H. and Swail, V.R. (2006) Observed Changes in Cyclone Activity in Canada and Their Relationships to Major Circulation Regimes. Journal of Climate, 19, 896-915. http://dx.doi.org/10.1175/JCLI3664.1
Kaldellis, J.K. (1999) Wind Energy Management. Stomoullis, Athens.
Dhunny, A.Z., Lollchund, M.R., Boojhawon, R. and Rughooputh, S.D.D.V. (2014) Statistical Modelling of Wind Speed Data for Mauritius. International Journal of Renewable Energy Research, 4, 1056-1064.
Mohammadi, K. and Mostafaeipour, A. (2013) Using Different Methods for Comprehensive Study of Wind Turbine Utilization in Zarrineh, Iran. Energy Conversion and Management, 65, 463-470. http://dx.doi.org/10.1016/j.enconman.2012.09.004
Elliott, D. and Holladay, C. (1987) Wind Energy Resource Atlas of the United States. NASA STI/Recon Technical Report N, 87, 24819.