Wind turbine generator system state prediction method for carrying out similarity search on basis of history data

A technology for wind turbines and historical data, used in forecasting, data processing applications, instruments, etc., to solve problems such as identification of fans, end temperature, solar radiation, rainfall, snow, salt fog, sand, and terrain profile fans.

Inactive Publication Date: 2017-05-31
NORTHEASTERN UNIV
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Problems solved by technology

The main problem in this patent is that wind turbines work in harsh natural environments for a long time, and are affected by factors such as normal and extreme extreme temperatures, solar radiation, rainfall, snow, salt fog, sand and dust, and terrain contours. There are certain fluctuations in the operating state of the wind turbine, and the generated hea

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  • Wind turbine generator system state prediction method for carrying out similarity search on basis of history data
  • Wind turbine generator system state prediction method for carrying out similarity search on basis of history data
  • Wind turbine generator system state prediction method for carrying out similarity search on basis of history data

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[0039] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0040] like figure 1 As shown, this embodiment provides a method for predicting the state of a wind turbine based on a similar search in historical data, including the following steps.

[0041] Step 1. Obtain sufficiently long historical operation data of the wind turbine sensor to ensure that the historical operation data includes various meteorological conditions, data of seasonal changes, and can include all possible states of the wind turbine.

[0042] Step 2. Clean and preprocess the historical wind turbine operation data collected by the existing data acquisition and monitoring control system, delete useless variables and erroneous data, and complete missing data. ...

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Abstract

The invention provides a wind turbine generation system state prediction method for carrying out similarity search on basis of history data, and relates to the technical field of wind turbine generation system state monitoring. The method comprises the following steps of: carrying out fan attribute selection and dimensionality reduction after preprocessing history data; carrying out clustering analysis on the dimensionality reduced data through an improved K-mean clustering algorithm; and carrying out history data similarity query to predict a fan operation state. According to the wind turbine generation system state prediction method for carrying out similarity search on basis of history data, a database can be established through history operation data of the wind turbine generator system, and the operation data can be compared with the history data of the fan and similar fans in real time so as to assess the state of the wind turbine generator system.

Description

technical field [0001] The invention relates to the technical field of wind turbine state monitoring, in particular to a wind turbine state prediction method based on similar search in historical data. Background technique [0002] At present, the research in the field of condition monitoring and fault diagnosis of wind turbines is in its infancy. Among the existing research results, the research on the whole machine focuses on the state evaluation and fault prediction, and the research on the key components of the wind turbine focuses on fault diagnosis. In wind turbine state assessment, it is mainly the residual analysis. The monitoring data of SCADA (Supervisory Control And Data Acquisition, that is, data acquisition and monitoring control system) is used as the input of the prediction model, and the prediction model such as artificial neural network or support vector machine is established. Obtain the predicted value, and then combine the actual monitoring value with the...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y04S10/50
Inventor 朱志良杜海涛石凯宋航刘国奇于海
Owner NORTHEASTERN UNIV
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