A railway and wind power plant environment wind speed machine learning prediction method

A technology for wind speed prediction and wind farms, which is applied in the field of wind speed machine learning prediction for railways and wind farms, and can solve problems such as the inability to predict wind speed and the difficulty in accurately finding out the characteristics of wind speed changes.
CN109726802AActive Publication Date: 2019-05-07CENT SOUTH UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
CENT SOUTH UNIV
Publication Date
2019-05-07

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Abstract

The invention discloses a railway and wind power plant environment wind speed machine learning prediction method. The method includes: selecting various neural network models; establishing 100 wind speed prediction characteristic pre-selection models for each wind speed; carrying out mean square error analysis and correlation analysis; selecting 10 models with good performance and strong feature independence; establishing a plurality of wind speed prediction integrated models; integrating the wind speed prediction characteristics; finally, establishing a wind speed prediction normalization model; carrying out Normalization processing on the wind speed integrated value, calculating the correlation between the predicted wind speed vector and the wind speed vector of the training sample, restoring and predicting the wind speed value through wind speed noise at the corresponding moment with high correlation. The method can effectively predict the non-stable wind speed and has the accurateprediction effect on complex and non-linear wind speed values.
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Description

technical field

[0001] The invention belongs to the field of wind speed prediction, in particular to a machine learning prediction method for wind speed in railway and wind farm environments. Background technique

[0002] In recent years, wind speed prediction has received more and more attention from railway-related safety departments and wind farm fields. The wind speed has the characteristics of randomness, changeability, complex nonlinearity, etc. Realizing super-step and ultra-accurate prediction of wind speed can provide more early warning processing time for train operation in harsh windy environments and ensure driving safety; at the same time, accurate wind speed prediction can provide The wind farm execution scheduling plan provides strong data support to stabilize power generation and ensure power generation safety.

[0003] Many scholars have invested a lot of energy in studying the law of wind speed change. Due to its complex and nonlinear characteristics, trad...

Claims

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