| In the 21st century, energy has become the foundation for survival and development.With the increasing demand for electricity from global economy, the coal, oil and other fossil energy are running out, the wind power has become one of the most promising sustainable energy in the world. Although China's installed wind capacity has been increasing sharply in recent years, but the proportion of wind power in the energy consumption structure is low. This is largely due to the randomness and volatility of wind, which can have great influence on electric power system operation. In order to increase the wind power penetration, accurate and stable wind power forecasting is needed. Traditional statistic forecasting models cannot deliver accurate results when it comes to extreme weathers, and the physical models need advanced computer and the more accurate the outcomes are, the more resources and time the computation is needed.As a result, a quick short-term forecasting model based on real-time meteorological data is needed.In this paper, the POD was used to reconstruct the velocity distribution of the wind field, and the effectiveness is evaluated by simulation. The wind velocity distribution around the three-dimensional model of hills and real topography were computed and compared with the reconstructed results. The relative error is low which demonstrated that the application of POD method into wind velocity distribution can obtain good results.The content of the paper mainly includes the CFD numerical simulation and an introduction to verify experiment.In the CFD numerical simulation, the sensitivity and accuracy of the reconstruction results versus the numbers of measured data are analyzed. The simulation results show that by using the dominant POD modes and a limited number of sensors, the reconstruction can yield reasonably accurate velocity distribution results. A wind tunnel experiment was carried out to verify the effectiveness of the POD method in wind field reconstruction. |
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