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Method and system for predicting yaw static deviation angle of wind turbine scada data

A technology of static deviation and yaw angle, which is applied in the control of wind turbines, wind turbines, neural learning methods, etc., can solve the problem of high system erection cost, achieve high accuracy, is suitable for promotion, and is conducive to predicting fan failures.

Active Publication Date: 2021-06-29
武汉展盛科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, in a wind turbine yaw control method disclosed in a Chinese invention patent (patent number CN109989884), it obtains wind direction data through laser radar, and then deduces the current wind information of the wind turbine to improve the yaw stability of the wind turbine; but in these technologies, It needs to rely on other equipment such as lidar, and the cost of system installation is high

Method used

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  • Method and system for predicting yaw static deviation angle of wind turbine scada data
  • Method and system for predicting yaw static deviation angle of wind turbine scada data
  • Method and system for predicting yaw static deviation angle of wind turbine scada data

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Embodiment 1

[0044] Such as figure 1 As shown, a yaw static deviation angle prediction method of wind turbine SCADA data, including:

[0045] S1. Obtain the wind speed, yaw angle and power generation power of different wind turbines within a time period, and construct a data matrix;

[0046] S2. Obtain the static yaw error according to the data matrix mark;

[0047] S3. Based on the neural network, train the neural network learning model about the wind speed, yaw angle, power generation and static yaw error;

[0048] S4. Obtain the current wind speed, yaw angle and power generation data of the target wind turbine, input them into the trained neural network learning model, and predict the deviation angle of the target wind turbine for output.

[0049] The method of the present invention is a static yaw error calculation method based on a neural network genetic algorithm, which is mainly aimed at the SCADA system of a wind power generator, that is, the data in the data acquisition and moni...

Embodiment 2

[0064] Such as Figure 4 As shown, the present invention also provides a yaw static deviation angle prediction system of SCADA yaw data of wind power generator, comprising

[0065] Data acquisition module: used to obtain the wind speed, yaw angle and power generation of different wind turbines within a time period, and construct a data matrix;

[0066] Data processing module: used to obtain the static yaw error according to the data matrix mark;

[0067] Parameter training module: used to train the neural network learning model about the wind speed, yaw angle, power generation and static yaw error based on the neural network;

[0068] Data prediction module: used to obtain the current wind speed, yaw angle and power generation data of the target wind turbine, input them into the trained neural network learning model, and predict the deviation angle of the target wind turbine for output.

[0069] The system of the present invention is used to implement the forecasting method ...

Embodiment 3

[0085] Such as Figure 5-6 As shown, the present invention also provides an intelligent diagnosis system, including a prediction system, a file management system and a version management system;

[0086] Prediction system for training the neural network learning model on wind speed, yaw angle, power generation and static yaw error of wind turbines;

[0087] A file management system for storing the neural network learning model trained by the prediction system, and providing TensorFlow services to the version management system;

[0088]The version management system is used to save and manage the version data information of the neural network learning model in the file management system, so that the client can access and obtain the corresponding neural network learning model through the service handle to perform prediction tasks.

[0089] Specifically, the neural network learning model trained by the prediction system provides TensorFlow services to the version management syste...

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Abstract

The invention discloses a yaw static deviation angle prediction method of wind turbine SCADA data, comprising: S1. Obtaining wind speed, yaw angle and power generation power of different wind turbines within a time period, and constructing a data matrix; S2. Marking according to the data matrix Obtain the static yaw error; S3. Based on the neural network, train the neural network learning model about the wind speed, yaw angle, power generation and static yaw error; S4. Obtain the current wind speed, yaw angle and power generation of the target fan The data is input to the trained neural network learning model, and the deviation angle of the target wind turbine is predicted for output; the present invention is based on a neural network algorithm to predict the static yaw error of the wind turbine, with high accuracy and without the need for external airborne Type laser radar and other equipment can reduce the cost of introducing other equipment and the data error caused by the performance of the equipment itself. That is, compared with the traditional technology, the method of the present invention can achieve the purpose of reducing cost and increasing efficiency, and is suitable for promotion.

Description

technical field [0001] The invention relates to the technical field of rectifying the yaw static deviation angle of a wind power generator, in particular to a method and system for predicting the yaw static deviation angle of wind turbine SCADA data. Background technique [0002] A wind turbine (hereinafter referred to as a fan) refers to a machine that can absorb wind energy and convert wind energy into electrical energy. Wind turbine yaw means that the wind turbine rotates the nacelle to change the windward side of the wind turbine to adjust the effect of the wind energy absorbed by the wind turbine. If the yaw angle is greater than the threshold for a certain period of time, the control system of the wind turbine adjusts the axis of the wind rotor by controlling the yaw motor. To be basically consistent with the wind direction. The yaw angle of the wind turbine, in °, is the angle between the wind direction and the axis of the wind rotor, and the second average yaw angle...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): F03D7/04G06N3/08
CPCF03D7/04F03D7/045F03D7/046G06N3/08Y02E10/72
Inventor 江魁何鑫曹辉杨家伟
Owner 武汉展盛科技有限公司
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