Wind power station short-term power prediction method

Abstract

The invention provides a wind power station short-term power prediction method. The wind power station short-term power prediction method comprises the steps that 1 a BP neural network is used for establishing the historical data statistics relationship between forecasting factors of a mesoscale numerical value weather forecast and the actually-measured wind speed, at the position of the hub height, of a single fan to generate a wind speed statistics downscaling model of the single fan; 2 according to the forecasting factors of the mesoscale numerical value weather forecast of a wind power station in the following 48 hours and the statistics downscaling model of the single fan in the step 1, the predicted wind speed, at the position of the hub height, of the single fan is generated; 3 according to historical data of the actually-measured wind speed of the single fan and the actually-measured power of the single can, a speed-power characteristic curve of the single fan is fit and the short-term predicted power of the fan is obtained through the combination of the predicted wind speed, at the position of the hub height, of the single fan. Therefore, by means of the wind power station short-term power prediction method, the uncertainty caused by the fact that the mesoscale resolution ratio is insufficient is reduced, and the short-term powder prediction precision of the wind power station is obviously improved.

Description

technical field [0001] The invention relates to a short-term power prediction method of a wind farm. Background technique [0002] In recent years, with the adjustment of my country's energy policy, the installed capacity of grid-connected wind power has grown rapidly, and the centralized grid-connection of large-scale wind power has brought impact on the safe operation of the power grid. Improving the predictability of wind farm output can effectively reduce the impact of wind power on the power grid and reduce the pressure of power grid dispatching and peak regulation. This is of positive significance for making full use of wind energy resources and further increasing the proportion of grid-connected wind power installed capacity. According to the technical specifications of wind farm power forecasting promulgated and implemented in China, wind farms must upload the next day 0-24h output forecast curve to the power dispatching agency according to the prescribed time every ...

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Problems solved by technology

[0005] In view of this, the main purpose of the present invention is to provide a short-term power prediction method for wind farms, which solves the problem of large wind speed errors in mesoscale numerical weather forecasts based on statistical downscaling, and effectively reduces the problems caused by insufficient mesoscale resolution. Uncertainty, greatly improving the downscaling calculation efficiency of mesoscale numerical weather forecasting, and significantly improving the accuracy of short-term power prediction of wind farms

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