Fan power curve data preprocessing method based on outlier detection

A technology of outlier detection and data preprocessing, applied in data processing applications, computer components, instruments, etc., can solve the inaccurate data analysis results, the influence of potential failures that cannot be ruled out, and the failure to form fan operation data data cleaning specifications Process and other issues

Inactive Publication Date: 2018-06-15
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] (1) The traditional power curve acquisition method has not formed a data cleaning specification process for the fan operation data;
[0005] (2) All data under different working conditions were directly analyzed during the research process, resulting in inaccurate subsequent data analysis results;
[0006] (3) Only rely on the feedback of the fault

Method used

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  • Fan power curve data preprocessing method based on outlier detection
  • Fan power curve data preprocessing method based on outlier detection
  • Fan power curve data preprocessing method based on outlier detection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0061] In this embodiment, the data collected by the SCADA system of a certain wind power generator in a certain wind farm in 2014 is preprocessed for fan power curve data, wherein the data sampling interval of the wind power generator SCADA system is 10 minutes, and the data information is for a period of 1 year. The time range is from 2014.01.01 00:00:00 to 2014.12.31 23:50:00. The specific variables and related data information included in the data set are shown in Table 5 and Table 6:

[0062] Table 5 Partial data of the SCADA system data set of a fan in a wind farm

[0063]

[0064]

[0065] Table 6. Data set variable information of a fan SCADA system in a wind farm

[0066] variable name

variable meaning

variable unit

timestamp

Data collection time

Year-Month-Day Hour:Minute:Second

pitch angle β

Current fan pitch angle

deg

wind speed v

Current fan nacelle wind speed

m / s

Active power P

Current...

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Abstract

The invention discloses a fan power curve data preprocessing method based on outlier detection. According to the method, based on collected fan data comprising wind speed, active power, environment temperature, a pitch angle, etc. and real-time operating data obtained through a supervisory control (SCADA) system, outlier detection criteria are used to perform abnormal data cleaning, air density obtained through calculation is utilized to correct wind speed data, an outlier detection algorithm is used to detect and eliminate outliers in fan power curve data. According to the data preprocessingmethod, the outlier detection criteria guarantee the effectiveness of fan data information; wind speed correction guarantees the comparability of the fan data; and the outlier detection algorithm guarantees the reliability of final power curve data. The method is based on data driving, does not have a special requirement on data and is high in universality. Compared with the prior art, data credibility is higher, the process is more standard, and a high theoretical property and practicability are achieved.

Description

technical field [0001] The invention relates to a fan power curve data preprocessing method, in particular to a fan power curve data preprocessing method based on abnormal point and outlier point detection. Background technique [0002] In a modern society where traditional fossil energy resources are scarce and seriously polluted, wind energy is widely favored by the public as a pollution-free and renewable new energy source, and the wind power industry has thus become one of the new renewable energy industries that are vigorously developed at home and abroad. . In my country, the construction of wind farms and related research work have significantly improved both in terms of quantity and quality in the past ten years. a series of negative factors. During the use of wind turbines today, due to the intermittent and highly uncertain characteristics of wind speed, it has a great impact on the performance evaluation of wind turbines themselves, and the correct performance and...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06K9/62
CPCG06Q10/0635G06F18/22G06F18/2433
Inventor 杨秦敏鲍雨浓王旭东林巍陈积明
Owner ZHEJIANG UNIV
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