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Wind Turbine Power Prediction Method Based on Wake Deflection Effect and 2djensen Model

A power prediction and wind turbine technology, applied in the field of wind turbine power prediction, can solve the problems of mutual influence between wind turbines in large wind farms, complex and changeable internal wind fields, etc.

Active Publication Date: 2022-06-21
NANJING UNIV OF SCI & TECH
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  • Application Information

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Problems solved by technology

Due to factors such as cost and site, large-scale wind farms will have interactions between wind turbines, complex and changeable internal wind farms, etc.

Method used

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  • Wind Turbine Power Prediction Method Based on Wake Deflection Effect and 2djensen Model
  • Wind Turbine Power Prediction Method Based on Wake Deflection Effect and 2djensen Model
  • Wind Turbine Power Prediction Method Based on Wake Deflection Effect and 2djensen Model

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Embodiment Construction

[0022] In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

[0023] like figure 1 As shown, the wind turbine power prediction method based on the wake deflection effect and the 2DJensen model, the specific steps are as follows:

[0024] Step 1. Collect and preprocess the data of wind turbines in the wind farm;

[0025] Collect the inflow wind speed, inflow wind direction, pitch angle, yaw error angle and output power of each wind turbine in the SCADA system of the wind turbine. Preprocess the collected data, remove all the data at the time of missing values ​​in the data, remove all the data at the time of the power outage in ...

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Abstract

The invention discloses a wind turbine power prediction method based on the wake deflection effect and the 2D Jensen model, which collects and preprocesses the SCADA data of the wind turbines in the wind field; Relative position coordinates; determine the node set and global attributes of the wind turbines in the wind field; determine the edge set and adjacency matrix between the wind turbines in the wind field; construct the input vector map set; Graph neural network model; optimize parameters based on the preprocessed SCADA data set and input vector diagram, determine the wind turbine power prediction model in the wind field, and determine the predicted power of all wind turbine nodes in the wind field. The invention can accurately predict the power output value of the wind turbine with yaw error angle in the whole wind field under different wind conditions.

Description

technical field [0001] The invention belongs to the field of wind turbine power prediction, and in particular relates to a wind turbine power prediction method based on wake deflection effect and 2DJensen model. Background technique [0002] my country is vigorously developing the new energy industry, and wind energy has become one of the more promising new energy sources because of its wide distribution and no pollution. With the continuous development of wind power generation technology, more and more large-scale wind farms have appeared. Due to factors such as cost and site, large-scale wind farms may experience mutual influence between wind turbines and complex and changeable internal wind farms. By predicting the power, not only the power loss of the wind farm can be analyzed, but also the power generation efficiency of the wind farm can be effectively improved by combining the predicted power with the field control system. Therefore, it is of great significance to ac...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06N3/04G06N3/08G06Q50/06H02J3/00
CPCG06Q10/04G06Q50/06G06N3/04G06N3/08H02J3/003Y04S10/50
Inventor 邱颖宁柳靖冯延晖
Owner NANJING UNIV OF SCI & TECH
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