Wind power prediction method based on wind resource correlation analysis

Abstract

The invention discloses a wind power prediction method based on wind resource correlation analysis. The wind power prediction method comprises the following steps that the wind speed linear correlation between all blowers is determined, and area division is performed on the blowers according to the linear correlation; the blower of the highest utilization rate of each area is selected to act as the representative blower, and the position of the representative blower acts as the forecast point of weather forecast of the area; the numerical weather forecast value of the representative blower of each area is acquired, the wind speed prediction value of the representative blower is determined according to the numerical weather forecast value and the wind speed prediction values of other blowers are acquired according to the wind speed prediction value of the representative blower and the linear correlation; and the power prediction value of each blower is determined and obtained according to the output power characteristic curve of each blower and the wind speed prediction value so that the power prediction value of the whole wind power plant is calculated. The wind speed prediction value is reasonable and effective.

Description

technical field [0001] The invention relates to a wind power prediction method based on wind resource correlation analysis. Background technique [0002] Wind energy is a clean, safe and efficient energy, which has important positive significance in protecting the ecological environment, delaying global warming, and promoting sustainable development. Therefore, wind energy can be used as a way to solve the increasingly tense problem of traditional energy supply. In recent years, my country's wind power industry has achieved large-scale and rapid development. [0003] However, wind energy has intermittent and volatile defects. In order to ensure the safe and stable operation of the power grid, it is necessary to predict the power generation of wind farms, so as to reasonably allocate various power sources and arrange power generation plans. For large-scale wind farms, power forecasting often adopts the method of regional forecasting, and the predicted wind speed of the repre...

AI Technical Summary

Problems solved by technology

In terms of regional division, this method is often roughly divided according to topography, wind turbine type, etc. This division relies too much on human factors and lacks theoretical guidance

On the other hand, there is also a lack of theoretical analysis as to whether the predicted wind speeds of representative wind turbines in each region can fully represent the predicted wind speeds of all wind turbines in the region, which is one of the important reasons for the formation of wind farm power prediction errors

Images