Evaluation of wind energy resource and wind turbine characteristics at two locations in China |
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| Affiliation: | 1. Department of Economics, San Jose State University, USA;2. Mercatus Center at George Mason University, USA;1. Fontys University of Applied Sciences, Fontys EGT – Centre for Healthcare and Technology, Dominee Theodor Fliednerstraat 2, 5631 BN Eindhoven, The Netherlands;2. Fontys University of Applied Sciences, Institute of Human Resource Management and Psychology, Emmasingel 28, 5611 AZ Eindhoven, The Netherlands;3. Fontys University of Applied Sciences, Institute of Allied Health Professions, Dominee Theodor Fliednerstraat 2, 5631 BN Eindhoven, The Netherlands;1. Central Business School, Central University, Accra, Ghana;2. Computer Science Department, Lancaster University Ghana, Accra, Ghana;1. Academy for Scientific and Innovative Research-AcSIR-AMPRI, Bhopal, India;2. Materials for Radiation Shielding and Cement Free Concrete Division, CSIR-AMPRI (Advanced Materials and Processes Research Institute), Hoshangabad Road, Bhopal, M.P., 462064, India;1. School of Computer Science and Technology, Tianjin University, Tianjin, 300072, China;2. School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China;3. School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, Gansu Province, China |
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| Abstract: | The ten-year monthly mean wind speed data at 10, 50,100, 150 and 300 m heights over a typical year were statistically analyzed in this study to determine the potential for wind power generation at two locations (Urumqi and Xining) in China, using the two-parameters Weibull distribution function. The shape factor k and scale factor c were estimated by the maximum likelihood method. Fourteen small to medium sized commercially available wind turbines were selected for the two regions, and their mean energy outputs and capacity factors were all analyzed. Results showed that the maximum monthly mean wind speeds at different heights in Urumqi and Xining occur in November and December, respectively; while the minimum values of the two locations occur in June and July, respectively. The wind power class and potential of Urumqi and Xining are “class 1” and “poor” and “class 2” and “Marginal”, respectively. Urumqi is not suitable for large-scale electric wind-power application; however, small-scale wind turbines or wind-hybrid power systems might be a reasonable option for this site for supplying power. Xining has a better wind resource than Urumqi, and medium-scale wind turbines might be a reasonable option in Xining for supplying more electric energy. The mean energy outputs for the selected wind turbines range from 491 kWh/yr to 87,333 kWh/yr in Urumqi, while the values range from 1,071 kWh/yr to 167,237 kWh/yr in Xining. The capacity factors for these wind turbines in Urumqi and Xining range from 4.3% to 19.5% and 10.4%–27.9%, respectively. The aim of this paper is to promote the development of wind power in China by contributing to scholarly understanding of its impact on the geographical regions studied. |
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| Keywords: | Wind energy resource Wind turbine Wind power density Capacity factor Weibull distribution |
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