Determination the wind energy potential of the Kırklareli University Kayalı campus

In this study, the wind energy potential of Kırklareli University Kayalı Campus between September 2018-April 2019 was determined based on raw wind speed data measured at 5 minutes intervals from the wind measurement station, which is mounted on 25 meters long lighting column that considered as the most suitable place in the campus. The statistical distributions which are Weibull, Rayleigh and Gamma were applied the data about to estimate the wind energy potential of the region. The parameters of these distributions were calculated with Moment and Maximum Likelihood (MLE) methods. Root Mean Square Error (RMSE), Chi-Square Test (χ^2) and Correlation Coefficient (R^2) approach methods are applied, in order to determine which distribution has statistically proper approach and more successful in modelling. The Hellmann coefficient formula was used to transport the wind speeds at the measured height to the selected turbine's hub height. With this formula; wind data speeds were transport to the turbine hub height at 50, 80 and 100 meters. For each considered height values, the shape (k) and scale (c) parameters, the mean wind speed obtained from the actual and the distributions, the standard deviation values obtained from the actual and the distributions, the power density values obtained from the actual and distributions were calculated for the selected region. Within the thesis study, it is planned to establish a wind turbine with 80 meters hub height to the region where statistical studies are performed and the energy production calculations for the region were made according to this acceptance. The WRPLOT program was used to generate the hourly speed, frequency and direction distributions of the 80 meters wind profile, which was planned as the height of the wind turbine hub. In addition, wind roses and wind charts that is satellite map of the region by months were obtained. According to the speed range hours and frequency distribution for each wind direction by months were examined. A total of 69860 data were analyzed in the region. According to the results obtained from the wind profile at the reference height (25 meters); the average speed value is 4.9076 m/s, the dominant direction of the wind datas range between at North and North-North-East, monthly average power density value is 76.98 W/m², monthly mean standard deviation is 3.0968 m/s and the monthly average turbulence density is 0.6270. Considering the topographic and ambient roughness conditions of the region, the Hellmann coefficient was determined as 0.1893. According to the results obtained from the wind profile at the 50 meters; the average speed value is 5.5957 m/s, the monthly average power density value is 109.498 W/m² and monthly mean standard deviation is 3.531 m/s. The wind speed profiles at 50 meters height of the region were estimated to be appropriate for the Rayleigh distribution obtained by the MLE method, as a result of the application of statistical distributions and error analyzes. According to the results obtained as a result of the application of statistical distributions, it was found that k parameter ranged between 1.33-3.51 and the c parameter ranged between 1.38-8.09, the monthly average power density value is 243.9458 W/m². According to the results obtained from the wind profile at the 80 meters; the average speed value is 6.1164 m/s, the monthly average power density value is 148.5534 W/m² and monthly mean standard deviation is 3.8596 m/s. The wind speed profiles at 80 meters height of the region were estimated to be appropriate for the Rayleigh distribution obtained by the MLE method, as a result of the application of statistical distributions and error analyzes. According to the results obtained as a result of the application of statistical distributions, it was found that k parameter ranged between 1.33-3.51 and the c parameter ranged between 1.51-8.84, the monthly average power density value is 330.573 W/m². According to the results obtained from the wind profile at the 100 meters; the average speed value is 6.3803 m/s, the monthly average power density value is 168.2951 W/m², and the monthly mean standard deviation is 4.026 m/s. The wind speed profiles at 100 meters height of the region were estimated to be appropriate for the Rayleigh distribution obtained by the MLE method, as a result of the application of statistical distributions and error analyzes. According to the results obtained as a result of the application of statistical distributions, it was found that k parameter ranged between 1.33-3.51 and the c parameter ranged between 1.58-9.22, the monthly average power density value is 375.3313 W/m². As a result of the comparison with number of hourly blowing wind speeds, the actual wind speed blowing ranges can be obtained from the distribution's wind speed blowing ranges; it was found that the highest energy production density of the region analyzed is between 3-6 m/s for 80 meters turbine hub height. As a result of the examination of turbine models with 80 meters turbine hub height on the market, it was decided that Gamesa G-97 turbine model; which has highest energy density value at wind speed profile range and closest to average power density, would be the most suitable model for the region. At the end of the 8 month period, approximately 1,290 MWh of electricity could be produced by the selected wind turbine. The turbin capacity factor value calculated as %11.1.