| Recent years, as the environment problems arousing public’s attention, government gives great policy support on the development of new energy. The wind farms rise up. Wind power capacity and proportion keep increasing. But, because of the difficulty of power prediction and distinct way of running, the wind power makes significant impact on the controllability, stability and safety of the power grid. It’s increasingly important that find a balance between the safety of power grid and the consumption of new energy.Under this circumstance, the positive and effective prediction of wind power plays an important role in the balance between the safety of power grid and the consumption of new energy. The article analyzed the principle of wind energy transformation and the regular prediction approaches, then, developed an improved wind power prediction method which is named "regional combined wind power generation prediction". Base on these, the author built a wind power prediction system.By studying the transformation between wind energy and electrical energy, we found the factors which influence the transform efficiency include wind speed, Atmospheric Density, land surface roughness, etc.The article discussed the popular prediction approaches, studied the categories of the approaches and generalized the principle and features of the widely used methods, such as "Neural Networks". On these bases, it carried out a deeper study in regional combined wind power generation prediction, provided the selection principle for some typical wind farms, gave the way to calculate the correlation and proportion between the wind power and grid power.The article analyzed the wind power prediction system in aspects of functional requirement, hard/soft ware framework and sub-systems. Then, we discussed the implementation of this prediction system in Huabei grid. It can make short or ultra-short term prediction which provides great technical support for the control and running of power grid. |
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