<p class="MsoNormal" style="text-align: justify; line-height: 20.0pt">Fiji needs to invest in renewable energy sources to meet its energy needs as this will reduce the country’s dependence on imported fossil fuels and will help in the fight against climate change. For investing in wind energy projects, a detailed assessment of wind energy resource is required for the site chosen to ensure that it has good wind potential. In this work, a 34 m tall NRG systems tower was installed to measure the wind speed and wind direction. A detailed statistical analysis of the 10-minute average data was carried out for estimating the wind characteristics for a site in Suva, Fiji. Three years of recently measured wind data were used to estimate the Weibull parameters, the daily, monthly, yearly and seasonal averages. The site’s average turbulence intensities at 34 m and 20 m above ground level as well as those for typical windy and low-wind days were estimated. The plotted wind rose showed predominantly easterly winds. The Weibull parameters, average wind speed and the wind power density were estimated by using eleven frequentist methods and a Bayesian technique. These twelve methods were compared against each other for their performance using five goodness of fit and &nbsp;error measures. The methods were ranked according to their performance and the Weibull parameters from the best method was used to estimate the accurate wind power density. A horizontal axis wind turbine of 30 kW capacity was designed and optimized using Harp_Opt software which works on a multi-objective genetic algorithm. The blade sections (airfoils) &nbsp;were designed using a multi-objective genetic algorithm code by mathematically parametrized 7<sup>th</sup> order Bezier curve using an in-house software, coupled with &nbsp;XFOIL software. The lift and drag values were interpolated using AirfoilPrep to get the data in the required format as needed by the Harp_Opt GUI. The Weibull parameters from the statistical analysis of the measured data were used to optimize the performance characteristics of the small wind turbine. The output power curve shows a cut in speeds of about 3 m/s whereas the rated wind speed of the wind turbine was 12 m/s the designed turbine. The annual energy production was optimized by several iterations of the genetic code. Smaller wind turbines are suitable for installation in Fiji and other Pacific Island Countries, since there are frequent cyclones which can cause damage to the structure. Larger turbines are expensive in terms of operational and maintenance costs and have the risk of damage in the face of strong winds.</p>

Wind Energy Resource Assessment for Suva, Fiji and Design of a 30 kW Wind Turbine

Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2021/volume/85543

ASME 2021 International Mechanical Engineering Congress and Exposition (IMECE2021)

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