Wind speed prediction method and system based on long-term and short-term memory time neural network

A long-term and short-term memory, wind speed prediction technology, applied in the direction of biological neural network model, prediction, neural architecture, etc., can solve problems such as inability to effectively use historical information and large prediction errors of prediction models

Pending Publication Date: 2020-06-02
ZHEJIANG WINDEY +3
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AI Technical Summary

Problems solved by technology

[0005] The present invention aims to solve the problems of large prediction errors of traditional prediction models and the inability to effectively use historical information, and provides a wind speed prediction method and system based on long-short-term memory time neural network

Method used

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  • Wind speed prediction method and system based on long-term and short-term memory time neural network
  • Wind speed prediction method and system based on long-term and short-term memory time neural network
  • Wind speed prediction method and system based on long-term and short-term memory time neural network

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Embodiment 1

[0061] Embodiment one, a kind of wind speed prediction method based on long short-term memory temporal neural network, such as figure 1 shown, including:

[0062] A) Collect existing historical wind speed data and measured wind speed data, and use the radar anemometer installed on the wind turbine to collect wind speed every fixed time;

[0063] B) Analyzing bad data, performing data preprocessing, obtaining wind speed samples, and constructing a wind speed sample database, including:

[0064] Bad data in step B) includes wind speed data and incomplete data with large errors, and data preprocessing includes:

[0065] B1) Delete the wind speed data with large error. In order to ensure the continuity and consistency of the wind speed data, obtain the mean value of the two data adjacent to the bad data, and use the mean value to complement the bad data, and obtain the wind speed arranged in chronological order data sequence;

[0066] B2) set the truncation length to be 15 seco...

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Abstract

The invention relates to the field of wind power plant wind speed prediction, and discloses a wind speed prediction method and system based on a long-term and short-term memory time neural network, and the method comprises the steps: A) collecting existing historical wind speed data and actually measured wind speed data; b) analyzing the bad data, carrying out data preprocessing to obtain a wind speed sample, and constructing a wind speed sample database; c) dividing the wind speed sample database into a training sample database, a verification sample database and a detection sample database;d) constructing a long-term and short-term memory neural network model; and E) predicting the wind speed by using the trained long-short-term memory neural network model to obtain a wind speed prediction value. Under the condition of completely utilizing historical data, the wind energy prediction is realized by establishing the long-short-term memory time neural network model and optimizing parameters of the long-short-term memory neural network model, and the prediction precision is high.

Description

technical field [0001] The invention relates to the field of wind speed forecasting in wind farms, in particular to a wind speed forecasting method and system based on a long-short-term memory temporal neural network. Background technique [0002] The influence of wind energy by natural factors is relatively complex. Wind speed is an important parameter for wind turbine pitch control and torque control. Wind power is largely affected by the change of wind speed in the wind farm. The randomness of wind speed will have a great impact on wind power grid connection. Therefore, predicting the wind speed of the wind farm will greatly improve the utilization rate and stability of wind energy. [0003] At present, many scholars at home and abroad have studied the problem of wind speed prediction in wind farms, and have also proposed a variety of methods, such as Kalman filter method, wavelet analysis method, BP neural network and support vector machine. Among them, the Kalman filte...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/04
CPCG06Q10/04G06Q50/06G06N3/045
Inventor 陈棋肖威孙勇林勇刚马灵芝
Owner ZHEJIANG WINDEY
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