Wind power modeling and performance evaluating method based on confidence equivalent power curve band

A technology of equivalent power and curve, which is used in electrical digital data processing, information technology support systems, instruments, etc.

Active Publication Date: 2018-04-06
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there is no suitable method for establishing fan data cleaning model and performance evaluation based on the confidence equivalent power curve.

Method used

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  • Wind power modeling and performance evaluating method based on confidence equivalent power curve band
  • Wind power modeling and performance evaluating method based on confidence equivalent power curve band
  • Wind power modeling and performance evaluating method based on confidence equivalent power curve band

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0104] A certain wind farm has 30 1.5MW wind turbines, the sampling period is 10min / point, and the research data are the wind turbine data collected from January 1, 2016 to December 31, 2016.

[0105] figure 1 It is a schematic diagram of the specific implementation steps of the embodiment of the present invention, figure 2 is the collected single-machine raw data sample,

[0106] Step 1: The smaller the proportion of abnormal data in the total data, the easier it is to gain insight into the correlation between wind speed and power in each operating area of ​​the fan through statistical analysis, and more accurate related structural characteristics can be obtained. Therefore, according to the operation mechanism of the fan, the operation of the fan is divided into the following five stages:

[0107] Cut-in stage: 0≤Vcut_in , P=0;

[0108] Maximum wind energy tracking phase:

[0109] transitional phase:

[0110] Rated power stage: V rated ≤Vcut_out , P=P rated max ;...

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Abstract

The invention relates to the field of data processing, in particular to a wind power modeling and performance evaluating method based on a confidence equivalent power curve band. The wind power modeling and performance evaluating method includes the steps that preliminary screening and rejection are conducted on an abnormal data sample; wind speed is divided into three regions, and a kernel density estimation method is used for obtaining wind speed and power probability distributions in each region through statistics to obtain the Copula function in each region; the maximum likelihood estimation method is adopted to obtain confidence equivalent power boundary model in the corresponding region; a piecewise cubic Hermite interpolating polynomial method is used for reconstructing missing datato complete original data sample cleaning; the average value of the confidence bandwidth ratio is used as the model performance evaluation index, a d-fold cross validation method is used for validating the upper and lower boundary models in different regions, when the index is basically stabilized at a certain constant value, the up and lower boundary models of the different regions are determined; a sliding time window method is adopted to updating data, the deviation degree of the confidence bandwidth ratio is used as a triggering condition, and the up and lower boundary models are updatedwhen the deviation degree exceeds a certain threshold value.

Description

technical field [0001] The invention relates to the field of wind power data processing, in particular to a wind power modeling and performance evaluation method based on a confidence equivalent power curve. Background technique [0002] With the rapid development of wind power grid-connected installed capacity, large-scale wind power is difficult to absorb, and the intermittent and random characteristics of wind resources have caused severe wind curtailment. In addition, errors are inevitable in the process of wind power data collection, transmission, and storage. The inclusion of a large amount of abnormal data will distort the probability distribution and make it difficult to correctly characterize the real operating characteristics of wind turbines, which will seriously affect the accuracy and accuracy of related application research based on wind turbine operating data. reliability. [0003] Therefore, it is necessary to preprocess wind turbine data through technical m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06Q50/06
CPCG06Q50/06G06F30/20Y02E40/70Y04S10/50
Inventor 胡阳乔依林朱红路
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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