@article{MAKHILLRJAS2007298816,
    title = {Determination of Annual Energy Capture Potential for Wind Power System: A Case Study},
    journal = {Research Journal of Applied Sciences},
    volume = {2},
    number = {9},
    pages = {927-930},
    year = {2007},
    issn = {1815-932x},
    doi = {rjasci.2007.927.930},
    url = {https://makhillpublications.co/view-article.php?issn=1815-932x&doi=rjasci.2007.927.930},
    author = {J.A. Amusan,Y.K. Sanusi and},
    keywords = {Renewable energy,wind turbine,wind speed,conventional energy,power potential,digital data logger},
    abstract = {Annual mean wind speed in Ogbomoso was calculated to be 127.517ms <SUP>1</SUP> through the monthly wind speed and direction data collected for 5 years from Nigeria Meteorological Agency (NIMET), Ilorin. The data were collected from Ilorin (Lattitude 8<SUP>0</SUP>32<SUP>1 </SUP>N and Longitude 4<SUP>0</SUP>34<SUP>1</SUP>E), which is very close to Ogbomoso (Latitude 8<SUP>0</SUP>05<SUP>1 </SUP>S and Longitude 4<SUP>0</SUP>12<SUP>1 </SUP>W). The determined annual mean wind speed was then applied in the Weibull Probability  distribution  function using c<SUP>++</SUP> Programming Language. Weibull Probability distribution of 1.3030×10<SUP>-54</SUP> at sea level is obtained which shows the wind speed variation over the period and thus indicates the probability distribution of annual mean wind speed being 127.517ms <SUP>1</SUP>. Digital Data Logger is employed to compute the power potential for wind turbine. The annual energy capture potential of 5562.69MJ is obtained for wind power system. The obtained equivalent power potential of 635.01kW is a considerable amount when compared with power consumption of 956.25kW utilized in Ladoke Akintola University of Technology, Ogbomoso. We then realize that the annual energy capture potential for a single wind turbine is 66.4% of the power consumption in LAUTECH through conventional energy source.}
    }