Wind power forecasting method dividing based on weather process

Abstract

The invention provides a wind power forecasting method dividing based on weather process. The wind power forecasting method comprises the following steps of: determining a numerical weather prediction matrix M and a numerical weather prediction standard matrix X; analyzing principle components of the numerical weather prediction standard matrix X; clustering a matrix Y composed of the first m-th principle components in the numerical weather prediction standard matrix X which is subjected to the principle component analysis; and establishing a wind power forecasting model, and forecasting wind power. According to the wind power forecasting method dividing based on weather process, based on the wind speed, wind direction and diurnal variation of pressure in NWP data, a sample is subjected to dimension reduction process by the principle component analysis, weather processes are classified by a clustering analysis method, weather types are divided into a high pressure stable type, a low pressure unstable type and the like according to the size and stability of control air pressure and the variation characteristics of wind speed and wind direction, and a forecasting model is established by adopting a BP neural network with respect to each weather process, and thereby the forecasting accuracy is effectively improved.

Description

technical field [0001] The invention belongs to the technical field of wind power generation and distribution, and in particular relates to a wind power prediction method based on weather process division. Background technique [0002] With the increasingly serious problems of global energy security and environmental pollution, wind power has become a fast-growing new energy due to its outstanding advantages such as cleanliness, safety, and simplicity. However, due to its own randomness, volatility and intermittency, the centralized connection of large-scale wind power will have a great impact on the stability and balance of the power system. The power is incorporated into the power generation plan and participates in real-time scheduling, in order to provide technical support for the safe and stable operation of the power system. [0003] Foreign countries such as Germany, Denmark, Spain, and the United States have mature wind power forecasting systems. According to differ...

AI Technical Summary

Problems solved by technology

[0005] Conventional forecasting methods all use a single model for forecasting, mainly focusing on improving the forecasting accuracy by improving the forecasting model, without considering the difference in the forecasting ability of NWP data for different weather processes, but in fact the performance of NWP under different weather processes is quite different , leading to high prediction accuracy of the prediction model under some weather processes, but relatively low prediction accuracy for other weather processes

In addition, the single model forecasting method does not distinguish between weather processes and adopts centralized modeling, which leads to the introduction of large noise in the training samples, which limits the improvement of forecasting accuracy

Images