Research In Wake Model On The Large-scale Wind Farm And Its Application

By the end of 2014, there are around 4% of the electricity comes from wind power. It is expected that wind power generating capacity will be doubled in 2020, and by 2030, wind power is expected to break through to 20%. With the rapid development of wind power, reduce the power loss in the process of wind electric power generation has become particularly important.Wake effect is a very important factor of wind power energy loss, has occupied a large proportion. To reduce the power losses in the wake effects of wind power plant, has been the concern issue.In the field of wind power generation micro siting process, arrangement of wind turbines will directly affect the wind flow characteristics of each turbine. The natural flow of airflow through the wind wheel is acting upstream, downstream of the fan after the arrival of wind speed and work ability will decline, produce wake effect, therefore, the study and selection of reasonable arrangement for the wind turbines takes a significant role in improving the generation efficiency of wind farm wind power unit. At present, at home and abroad for wind turbine layout optimizingwake model are mainly one-dimensional linear, nonlinear model and its superposition model.In order to improve the accuracy and meet the actual situation, we use the theorem of kinetic energy, momentum-blade element theory and Gaussian distribution and Eulerian transport equations derived combination to derive complete three dimensional nonlinear wake model and its superposition model.We use the complete model in the calculation and study of wind wake and its related problems. Based on the analysis of income related conclusions, we take them as guidance for the wind farm micro location selection work and for the wind turbines arrangement in the corresponding optimization, to improve the overall economic benefits of wind power. In this paper, we use the MATLAB software in the calculation and study of the wind wake, the results are compared with the tunnel test, wind field numerical operation data and otherl kinds of simulation results. The conclusion shows that Gaussian and its superposition model are more reliable and reasonable, which can be applied to the actual engineering calculation, guiding wind farm micrositing and optimized arrangement of work, thus improving the overall economic benefits of wind power plant.