GOODNESS OF FIT TEST FOR WIND ENERGY POTENTIAL USING FIVE PROBABILITY DENSITY FUNCTIONS FOR SOME SELECTED CITIES IN NIGERIA

Authors

Keywords:

Goodness of fit test; A-D test; K-S Test; Wind Power Potential and Probability distribution functions

Abstract

This research gives a better understanding on wind energy availability for some selected cities in Nigeria, such as Katsina, Sokoto, Bauchi, Maiduguri, Abuja, Jos, Abeokuta, Lagos, Enugu, Owerri, Calabar and Benin City respectively. Twenty Years (2000-2020) average wind speed data obtained from NIMET Headquarters Abuja, were analysed and fitted with five probability density functions such as normal, Weibull, Rayleigh, lognormal and Gamma Function with fixed shape parameter (K), but different scale parameters (C) in the model. The results of goodness of fit test based on Kolmogorov-Smirnov and Anderson – Darling shows that all the  probability distribution functions are accepted at maximum difference,   less than their critical values,  (= 0.0853 and 0.0855). While in the A-D tests, all the distribution functions hold except lognormal distribution function which is satisfactory for Jos and Abuja with an observed significant level (OSL) ranging from (0.7497 - 0.7497). Therefore, this results can be used for investors on wind power and also improve wind farm project for surface wind electrification

Dimensions

Aidan J. & Ododo J. C. (2010). Wind speed distributions and power densities of some cities in Northern Nigeria, Journal of engineering and applied sciences, 5(6), 420-426

Aidan J. (2011). Turbine Selection and Estimates of Unit Cost of Wind Generated Electricity in Kano, Nigeria, Journal of Engineering and Applied Sciences 6 (4):227-230

Aidan J. (2015). Wind Energy. A lecture outline presented in a classroom lecture at Moddibbo Adama University of technology Yola, Adamawa State, Nigeria.

Ajayi, O.O. (2009) Assessment of utilization of wind energy resources in Nigeria. Energy Policy , 3(10), 720–723.

Akaike, H. (2011). Akaike’s information criterion. In: International Encyclopedia of Statistical Science. Berlin, Heidelberg: 25-25. https:/doi.org/10.1007/978-3-642-04898-2_110

American Wind Energy Association (AWEA) (2013). 10 Steps in Building a Wind Farm. Wind Energy Fact Sheet (2013). http://www.awea.org

Asiegbu, A.D. Iwuoha, G.S. (2007). Studies of wind resources in Umudike, South East Nigeria—An assessment of economic viability. Journal of. Engineering and Applied Science, 2,(3) 1539–1541.

Bajic, A. and Peros, B. (2005), “Meteorological basis for wind loads calculation in Croatiaâ€, Wind Struct., 8(6), 389-406. https://doi.org/10.12989/was.2005.8.6.389.

Chang, T.J., Tu, Y.L. (2007). Evaluation of monthly capacity factor of WECS using chronological and probabilistic wind speed data: A case study of Taiwan. Renewable Energy 32, 1999-2000

Clean Development Mechanism (CDM) and Baseline-Assessments for wind Energy Projects (2014). The webpage was last modified on 29 August, at 13:45. Retrieved from https://energypedia.info/index.php?title=Clean_Development_Mechanism_(CDM) BaselineAssessments_for_Wind_Energy_Projects&oldid=83438 on 12/12/2014

ECN-UNDP (Energy Commission of Nigeria-United Nations Development of Nigeria). Renewable energy master plan: Final draft report, 2005. Available online: http://www.iceednigeria.org/ REMP%20Final%20Report.pdf (accessed on 17 June 2007).

Elshaer, A., Bitsuamlak, G. and Abdallah, H. (2019), “Variation in wind load and flow of a low-rise building during progressive damage scenarioâ€, Wind Struct., 28(6), 389-404. https://doi.org/10.12989/was.2019.28.6.389.

Eskin, N., Artar, H. and Tolun, S. (2008), “Wind energy potential of Gokceada Island in Turkeyâ€, Renew. Sustain. Energy Rev., 12(3), 839-851. https://doi.org/10.1016/j.rser.2006.05.016.

Fadare, D.A. (2010). The application of artificial neural networks to mapping of wind speed profile for energy application in Nigeria. Applied Energy,87, 934–942.

Fadare, D.A. (2008). Statistical analysis of wind energy potential in Ibadan, Nigeria, based on Weibull distribution function. Journal of Science and Technology, 9,110–19.

Genç, M.S. (2011), “Economic viability of water pumping systems supplied by wind energy conversion and diesel generator systems in North Central Anatolia, Turkeyâ€, J. Energy Eng., 137(1), 21-35. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000033.

Genç, M.S. and Gökçek, M. (2009), “Evaluation of wind characteristics and energy potential in Kayseri, Turkeyâ€, J. Energy Eng., 135(2), 33-43. https://doi.org/10.1061/(ASCE)0733- 9402(2009)135:2(33)

Global Environment Facility (GEF) (2012). United Nation Industrial Development Organization (UNIDO), ECOWAS Centre for Renewable Energy and Energy Efficiency (ECREEE). Promoting Market Based Development of Small to Medium Scale Renewable Energy Systems in Cape Verde.

Gupta, A. K. (1997). Power Generation from Renewables in India, Ministry of Non-Conventional Energy Sources, New Delhi, India.

Harris, R.I. (2006), “Errors in GEV analysis of wind epoch maxima from Weibull parentsâ€, Wind Struct., 9(3), 179-191. https://doi.org/10.12989/was.2006.9.3.179.

Jensson, P. (2006). Profitability Assesment Model, Reykjavik University.

Jowder, F.A.L. (2009), “Wind power analysis and site matching of wind turbine generators in Kingdom of Bahrainâ€, Appl. Energy, 86(4), 538-545. https://doi.org/10.1016/j.apenergy.2008.08.006.

Ke, S.T., Wang, X.H. and Ge, Y.J. (2019), “Wind load and windinduced effect of the large wind turbine tower-blade system considering blade yaw and interferenceâ€. Wind Struct., 28(2) Energy, 86(10), 1864- 1872 https://doi.org/10.1016/j.apenergy.2008.12.016.

Lagomarsino, S., Piccardo, G. and Solari, G. (1999), “Probabilistic analysis of ltalian extreme winds: Reference velocity and return criterionâ€, Wind Struct., 2(1), 51-68. https://doi.org/10.12989/was.1999.2.1.051.

Lahmeyer (International) Consultants. (2005) Report on Nigeria Wind Power Mapping Projects; Federal Ministry Science Technology: Abuja, Nigeria, Pp37–51.

Leadership Newspaper (2014). Work Resumes on Katsina 10MW Wind Farm. Available online at http://leadership.ng/news/391965/work-resumes-katsina-10mw-wind- farm

Lu, W., & Tsai, T. R. (2009). Interval Censored Sampling Plans for the Gamma Life Model. European Journal of Operational Research, 192(1), 116-124

Ngala, G.M., Alkali, B., Aji, M.A. (2007). Viability of wind energy as a power generation source in maiduguri, Borno state, Nigeria. Renewable Energy, 32, Pp. 2242–2246.

Ogbonnaya, I.O., Chikuni, E., & Govender, P. (2009). Prospect of wind energy in Nigeria. Available online; http://active.cput.ac.za/energy/web/due/papers/2007/023O_Okoro.pdf (accessed on 16 July 2009).

Ozgener, L. (2010), “Investigation of wind energy potential of Muradiye in Manisaâ€, Renew. Sustain. Energy Rev., 14(9), 3232-3236. https://doi.org/10.1016/j.rser.2010.06.004.

Quan, Y., Hou, F. and Gu, M. (2017), “Effects of vertical ribs protruding from facades on the wind loads of super high-rise buildingsâ€, Wind Struct., 24(2), 145-169. https://doi.org/10.12989/was.2017.24.2.145.

Ramirez, P., & Carta, J. A. (2005). Influence of the Data Sampling Interval in the Estimation of the Parameters of the Weibull Wind Speed Probability Density Distribution. Energy Conversion and Management, 46(15-16), Pp. 2419-2438

Reliasoft, RBDs and Analytical System Reliability. [Online]. Available: http//reliawiki.com/index.php/RBDs_and_Analytical_System_Reliability. [Accessed:10-January-2019].

Wind Speed Database programs (2015). Wind statistics and the Weibull distribution. http://www.wind-power-program.com/wind_statistics.htm

Appl.Vanguard Newspaper (2015). Katsina 10 MW Wind Farm Achieves 98 % completion FG. Available online at http://www.vanguardngr.com/2015/05/katsina-10mw-wind-farm-attains-98-completion-fg/

Vestas-American Wind Technology, Inc. Key Aspects in Developing a Wind Power Project.https://www1.eere.energy.gov/tribalenergy/guide/pdfs/developingwindpower. Pdf

Weibull, W. (1951). A Statistical Distribution Function of Wide Applicability. J. Appl. Mech-Trans, ASME, 18(3), 293-297

Wide Energy The Facts: (2009) . A Guide to the Technology, Economics and Future of Wind Power: European Wind Energy Association (EWEA). Earthscan Publications Ltd.

Ye, X.W., Ding, Y. and Wan, H.P. (2019), “Machine learning approaches for wind speed forecasting using long-term monitoring data: a comparative studyâ€, Smart Struct. Syst., 24(6), 733-744. https://doi.org/10.12989/.2019.24.6.733.

Zidong, X., Hao, W., Teng, W., Tianyou, T. and Jianxiao, M. (2017), “Wind characteristics at Sutong Bridge site using 8-year field measurement dataâ€, Wind Struct., 25(2), 195-214. https://doi.org/10.12989/was.2017.25.2.195.

Published

31-03-2022

How to Cite

GOODNESS OF FIT TEST FOR WIND ENERGY POTENTIAL USING FIVE PROBABILITY DENSITY FUNCTIONS FOR SOME SELECTED CITIES IN NIGERIA. (2022). FUDMA JOURNAL OF SCIENCES, 6(1), 81-92. https://doi.org/10.33003/fjs-2022-0601-882

Issue

Vol. 6 No. 1 (2022): FUDMA Journal of Sciences - Vol. 6 No. 1

Section

Research Articles
Copyright & Licensing

FUDMA Journal of Sciences

How to Cite

GOODNESS OF FIT TEST FOR WIND ENERGY POTENTIAL USING FIVE PROBABILITY DENSITY FUNCTIONS FOR SOME SELECTED CITIES IN NIGERIA. (2022). FUDMA JOURNAL OF SCIENCES, 6(1), 81-92. https://doi.org/10.33003/fjs-2022-0601-882

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