Wind speed prediction method and wind speed prediction system

Abstract

The invention discloses a wind speed prediction method and prediction system. The prediction method comprises the following steps: acquiring an original wind speed sequence; performing empirical modedecomposition on the wind speed sequence, and obtaining a plurality of inherent modal functions and residual items; classifying all inherent modal functions according to the instantaneous frequency mean value of each inherent modal function, obtaining a plurality of high-frequency modal functions and a plurality of low-frequency modal functions; training the least square support vector machine byadopting the training sample data of each high-frequency modal function to obtain a high-frequency prediction model; training a BP neural network through the training sample data of each low-frequencymode function to obtain a low-frequency prediction model; training the BP neural network through the training sample data of the residual items to obtain a residual prediction model; predicting the wind speed by utilizing all the high-frequency prediction models, the low-frequency prediction models and the residual prediction models. A prediction model is built on the basis of fluctuation characteristics of different components, the random fluctuation of the wind speed sequence can be effectively weakened, and the wind speed can be accurately predicted.

Description

technical field [0001] The invention relates to the field of renewable energy, in particular to a wind speed prediction method and a wind speed prediction system. Background technique [0002] Wind energy, as a clean and non-polluting new energy source, has been widely concerned by countries all over the world. However, due to problems such as the mismatch between the distribution of wind energy resources and the power load and the insufficient capacity of the power grid, there have been many "wind curtailment" phenomena. The intensification of wind curtailment has not only caused immeasurable economic losses, but also greatly weakened the market competitiveness of wind power. Reliable wind power forecasting is helpful for the power dispatching department to adjust the overall dispatching plan, allocate reasonable output of wind turbines, and save conventional energy generation. At the same time, in the electricity market, the accuracy of wind power forecast is also a key ...

AI Technical Summary

Problems solved by technology

[0003] However, the existing wind speed prediction methods are all models that directly fit the wind speed sequence and influencing factors, and do not dig into the characteristics of the wind speed sequence itself. The prediction effect is overly dependent on the prediction performance of the model, and the prediction accuracy is low.

Images