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dc.contributor.authorOyewole, J. A.-
dc.contributor.authorAweda, F. O.-
dc.contributor.authorOni, D.-
dc.date.accessioned2023-04-13T13:08:19Z-
dc.date.available2023-04-13T13:08:19Z-
dc.date.issued2019-01-30-
dc.identifier.citationOyewole, J. A., Aweda, F. O., & Oni, D. (2019). Comparison of three numerical methods for estimating weibull parameters using weibull distribution model in Nigeria. Nigerian Journal of Basic and Applied Science, 27(2), 8 – 15.en_US
dc.identifier.uriir.bowen.edu.ng:8080/jspui/handle/123456789/1023-
dc.description.abstractThere is a crucial need in Nigeria to enhance the development of wind technology in order to boost our energy supply. Adequate knowledge about the wind speed distribution becomes very essential in the establishment of Wind Energy Conversion Systems (WECS). Weibull Probability Density Function (PDF) with two parameters is widely accepted and is commonly used for modelling, characterizing and predicting wind resource and wind power, as well as assessing optimum performance of WECS. Therefore, it is paramount to precisely estimate the scale and shape parameters for all regions or sites of interest. Here, wind data from year 2000 to 2010 for four different locations (Port Harcourt, Ikeja, Kano and Jos) were analysed and the Weibull parameters was determined. The three methods employed are Mean Standard Deviation Method (MSDM), Energy Pattern Factor Method (EPFM) and Method of Moments (MOM) for estimating Weibull parameters. The method that gave the most accurate estimation of the wind speed was MSDM method, while Energy Pattern Factor Method (EPFM) is the most reliable and consistent method for estimating probability density function of wind.en_US
dc.language.isoenen_US
dc.publisherNigerian Journal of Basic and Applied Scienceen_US
dc.subjectWeibull distributionen_US
dc.subjectMethod of momenten_US
dc.subjectMean standard deviation methoden_US
dc.subjectEnergy pattern methoden_US
dc.titleComparison Of three numerical methods for estimating weibull parameters using weibull distribution model in Nigeriaen_US
dc.typeArticleen_US
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