CN112228290A - Intelligent early warning method for faults of wind turbine variable pitch system - Google Patents

Intelligent early warning method for faults of wind turbine variable pitch system Download PDF

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CN112228290A
CN112228290A CN202011140230.XA CN202011140230A CN112228290A CN 112228290 A CN112228290 A CN 112228290A CN 202011140230 A CN202011140230 A CN 202011140230A CN 112228290 A CN112228290 A CN 112228290A
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variable pitch
blade
blades
early warning
following
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CN112228290B (en
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韩斌
甘勇
孙世辉
王忠杰
李颖峰
赵勇
郑新建
程方
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Hunan Clean Energy Branch Of Huaneng International Power Co ltd
Xian Thermal Power Research Institute Co Ltd
Huaneng Power International Inc
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Hunan Clean Energy Branch Of Huaneng International Power Co ltd
Xian Thermal Power Research Institute Co Ltd
Huaneng Power International Inc
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction

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  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Wind Motors (AREA)

Abstract

The invention discloses an intelligent fault early warning method for a wind turbine variable pitch system, which comprises the steps of obtaining a given variable pitch speed and a feedback variable pitch speed of each blade, and calculating a variable pitch following error and a variable pitch following error coefficient of each blade; when the following error coefficient does not exceed a specified value, the variable pitch system is considered to have no fault, when the following error coefficient exceeds the specified value, the pitch angles of the blades before and after variable pitch are read, and the variable pitch angle difference of the blades is calculated; and if the mutual difference of the variable pitch angles of the blades is not greater than a specified value, giving early warning information: following the blade number with the maximum variable pitch angle difference, if the number is larger than the maximum variable pitch angle difference, determining the blade number with the maximum variable pitch angle error according to the maximum variable pitch angle difference and the minimum variable pitch angle difference of each blade; and simultaneously calling and simultaneously acquiring vibration monitoring data of the main bearing at the moment, judging whether the vibration exceeds the limit, and giving out early warning information if the vibration does not exceed the limit: following the blade number that becomes oar angle error maximum, if transfinite, then give alarm information: numbering the blades with the largest pitch angle error; the invention provides three early warning results, and the early warning is more accurate.

Description

Intelligent early warning method for faults of wind turbine variable pitch system
Technical Field
The invention relates to the technical field of fault early warning of a wind turbine variable pitch system, in particular to an intelligent early warning method for faults of the wind turbine variable pitch system.
Background
In recent years, intelligent operation and maintenance of wind power plants become development hotspots in the industry, but in the intelligent operation and maintenance process of the wind power plants, early warning of faults of all devices through various intelligent algorithms is particularly important. At present, SCADA system data and CMS system data in a wind power plant contain a large amount of equipment operation state information, and the information is to be fully mined. The variable pitch system is an important component of the wind turbine generator, and the operation state of the variable pitch system is directly related to the safety of the generator, so that the early warning of the variable pitch system is very important.
At present, early warning for a variable pitch system of a wind turbine in the industry is based on constant single threshold early warning or certain single parameter although a plurality of different methods are provided at home and abroad. The early warning scheme has certain defects, so that the early warning false alarm rate is high, and the early warning method cannot be effectively applied due to the high false alarm rate.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide an intelligent early warning method for the faults of the variable pitch system of the wind turbine, which provides three early warning results and has more accurate early warning.
In order to achieve the purpose, the invention adopts the following technical scheme:
an intelligent early warning method for faults of a wind turbine variable pitch system is characterized in that given variable pitch speeds V of 1#, 2#, and 3# blades are obtained from second-level data of a wind power plant data acquisition and monitoring control system10、V20、V30And 1#, 2#, 3# blade feedback variable pitch speed V11、V21、V31And calculating the 1#, 2#, 3# blade variable pitch following errors e1、e2、e3：
e1＝|V10-V11|
e2＝|V20-V21|
e3＝|V30-V31|
By comparing 1#, 2#, 3# blade variable pitch following error e1、e2、e3Determining the number of the blade with the largest pitch following error, and simultaneously calculating the average value E of the pitch following errors of the 3 blades:
Figure BDA0002738011280000021
and further calculating a variable pitch following error coefficient epsilon:
Figure BDA0002738011280000022
in order to eliminate the influence of discrete data on an analysis result, simultaneously calculating a plurality of groups of continuous data, then judging a following error coefficient epsilon, and when the following error coefficient epsilon does not exceed a specified value, determining that no fault exists in the variable pitch system; when the following error coefficient epsilon exceeds a specified value, the pitch angle A of 1#, 2#, 3# blades in the wind power plant data acquisition and monitoring control system needs to be read10、A20、A30And a pitch angle A after pitch variation11、A21、A31And calculating the blade pitch angle differences A of the 1#, 2#, and 3# blades12、A23、A31Wherein:
A12＝||A10-V11|-|A20-V21||
A23＝||A20-V21|-|A30-V31||
A31＝||A30-V31|-|A10-V11||
then, whether the difference of the variable pitch angles of the blades is larger than a specified value is judged, if not, early warning information is given out: numbering the blades with the largest following variable pitch angle difference; if the variable pitch angle difference of each blade is larger than a specified value, determining the blade number with the maximum variable pitch angle error according to the maximum value and the minimum value of the variable pitch angle difference of the 1#, 2#, and 3# blades; and simultaneously calling and simultaneously acquiring vibration monitoring data of the main bearing at the moment, judging whether the vibration exceeds the limit, and giving out early warning information if the vibration does not exceed the limit: following the blade number that becomes oar angle error maximum, if transfinite, then give alarm information: and numbering the blades with the largest pitch angle error.
Preferably, 20 sets of consecutive data are calculated simultaneously, and then the following error coefficient ε is determined.
Compared with the prior art, the invention has the following advantages:
(1) meanwhile, fault early warning is carried out on the variable pitch system by utilizing the variable pitch following error, the variable pitch angle error and the vibration data value, and the problem of high early warning false alarm rate caused by single parameter is avoided.
(2) The method of the invention simultaneously gives three early warning results, and the early warning is more accurate.
Drawings
FIG. 1 is a flow chart of the early warning method of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples.
As shown in FIG. 1, the intelligent early warning method for the fault of the variable pitch system of the wind turbine provided by the invention comprises the following steps ofAcquiring given variable pitch speed V of 1#, 2#, 3# blades from second-level data of a data acquisition and monitoring control system (SCADA system)10、V20、V30And 1#, 2#, 3# blade feedback variable pitch speed V11、V21、V31And calculating the 1#, 2#, 3# blade variable pitch following errors e1、e2、e3：
e1＝|V10-V11|
e2＝|V20-V21|
e3＝|V30-V31|
By comparing 1#, 2#, 3# blade variable pitch following error e1、e2、e3Determining the number of the blade with the largest pitch following error, and simultaneously calculating the average value E of the pitch following errors of the 3 blades:
Figure BDA0002738011280000041
and further calculating a variable pitch following error coefficient epsilon:
Figure BDA0002738011280000042
in order to eliminate the influence of discrete data on an analysis result, 20 groups of continuous data are calculated at the same time, then a following error coefficient epsilon is judged, and when the following error coefficient epsilon does not exceed a specified value, a fault does not exist in the variable pitch system; when the following error coefficient epsilon exceeds a specified value, the pitch angle A of 1#, 2#, 3# blades in the wind power plant data acquisition and monitoring control system needs to be read10、A20、A30And a pitch angle A after pitch variation11、A21、A31And calculating the blade pitch angle differences A of the 1#, 2#, and 3# blades12、A23、A31Wherein:
A12＝||A10-V11|-|A20-V21||
A23＝||A20-V21|-|A30-V31||
A31＝||A30-V31|-|A10-V11||
then, whether the difference of the variable pitch angles of the blades is larger than a specified value is judged, if not, early warning information is given out: numbering the blades with the largest following variable pitch angle difference; if the variable pitch angle difference of each blade is larger than a specified value, determining the blade number with the maximum variable pitch angle error according to the maximum value and the minimum value of the variable pitch angle difference of the 1#, 2#, and 3# blades; and simultaneously calling and simultaneously acquiring vibration monitoring data of the main bearing at the moment, judging whether the vibration exceeds the limit, and giving out early warning information if the vibration does not exceed the limit: following the blade number that becomes oar angle error maximum, if transfinite, then give alarm information: and numbering the blades with the largest pitch angle error.

Claims (2)

1. An intelligent early warning method for faults of a variable pitch system of a wind turbine is characterized by comprising the following steps: obtaining the given variable pitch speed V of 1#, 2#, 3# blades from the second-level data of the wind power plant data acquisition and monitoring control system10、V20、V30And 1#, 2#, 3# blade feedback variable pitch speed V11、V21、V31And calculating the 1#, 2#, 3# blade variable pitch following errors e1、e2、e3：
e1＝|V10-V11|
e2＝|V20-V21|
e3＝|V30-V31|
By comparing 1#, 2#, 3# blade variable pitch following error e1、e2、e3Determining the number of the blade with the largest pitch following error, and simultaneously calculating the average value E of the pitch following errors of the 3 blades:
Figure FDA0002738011270000011
and further calculating a variable pitch following error coefficient epsilon:
Figure FDA0002738011270000012
in order to eliminate the influence of discrete data on an analysis result, simultaneously calculating a plurality of groups of continuous data, then judging a following error coefficient epsilon, and when the following error coefficient epsilon does not exceed a specified value, determining that no fault exists in the variable pitch system; when the following error coefficient epsilon exceeds a specified value, the pitch angle A of 1#, 2#, 3# blades in the wind power plant data acquisition and monitoring control system needs to be read10、A20、A30And a pitch angle A after pitch variation11、A21、A31And calculating the blade pitch angle differences A of the 1#, 2#, and 3# blades12、A23、A31Wherein:
A12＝||A10-V11|-|A20-V21||
A23＝||A20-V21|-|A30-V31||
A31＝||A30-V31|-|A10-V11||
then, whether the difference of the variable pitch angles of the blades is larger than a specified value is judged, if not, early warning information is given out: numbering the blades with the largest following variable pitch angle difference; if the variable pitch angle difference of each blade is larger than a specified value, determining the blade number with the maximum variable pitch angle error according to the maximum value and the minimum value of the variable pitch angle difference of the 1#, 2#, and 3# blades; and simultaneously calling and simultaneously acquiring vibration monitoring data of the main bearing at the moment, judging whether the vibration exceeds the limit, and giving out early warning information if the vibration does not exceed the limit: following the blade number that becomes oar angle error maximum, if transfinite, then give alarm information: and numbering the blades with the largest pitch angle error.
2. The intelligent early warning method for the faults of the pitch system of the wind turbine as claimed in claim 1, wherein: 20 sets of continuous data are simultaneously calculated, and then the following error coefficient epsilon is judged.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113530763A (en) * 2021-06-10 2021-10-22 北京国电思达科技有限公司 Method and system for monitoring zero position abnormity of blades of wind turbine generator
CN113898528A (en) * 2021-09-30 2022-01-07 江苏金风软件技术有限公司 Abnormity detection method of fan variable pitch bearing, model training method and related device
WO2024045413A1 (en) * 2022-08-31 2024-03-07 北京金风慧能技术有限公司 Pitch fault prediction method and apparatus for wind turbine

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090243295A1 (en) * 2008-04-01 2009-10-01 General Electric Company System and method for reducing rotor loads in a wind turbine upon detection of blade-pitch failure and loss of counter-torque
US20110305568A1 (en) * 2008-12-15 2011-12-15 Per Brath Pitch control of a wind turbine
CN102418663A (en) * 2011-12-29 2012-04-18 一重集团大连设计研究院有限公司 Variable pitch system for offshore high-power wind driven generator group and control method for variable pitch system
US20150176570A1 (en) * 2013-12-20 2015-06-25 Siemens Aktiengesellschaft Detecting a pitch angle adjustment fault
US20150204208A1 (en) * 2014-01-21 2015-07-23 Ssb Wind Systems Gmbh & Co. Kg Pitch angle measuring system and method for wind turbines
CN104807644A (en) * 2015-04-14 2015-07-29 北京中恒博瑞数字电力科技有限公司 Fault early warning method and system for wind generation set variable-pitch system
CN105464912A (en) * 2016-01-27 2016-04-06 国电联合动力技术有限公司 Method and device for detecting freezing of wind generating set blades
CN207485607U (en) * 2017-11-09 2018-06-12 西安热工研究院有限公司 A kind of wind energy conversion system pitch variable bearings fault detection system
CN108760318A (en) * 2018-08-31 2018-11-06 西安热工研究院有限公司 A kind of wind energy conversion system pitch variable bearings fault detection method
CN108894913A (en) * 2018-06-27 2018-11-27 北京金风科创风电设备有限公司 Pitch control method and device and computer readable storage medium
CN109458295A (en) * 2018-12-29 2019-03-12 北京金风科创风电设备有限公司 Variable pitch control method and device for wind generating set, electronic equipment and medium
CN109723609A (en) * 2017-10-31 2019-05-07 中国电力科学研究院有限公司 A kind of fault early warning method and system of paddle change system of wind turbines
JP2019158577A (en) * 2018-03-13 2019-09-19 トヨタ自動車株式会社 Absolute encoder failure detection device

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090243295A1 (en) * 2008-04-01 2009-10-01 General Electric Company System and method for reducing rotor loads in a wind turbine upon detection of blade-pitch failure and loss of counter-torque
US20110305568A1 (en) * 2008-12-15 2011-12-15 Per Brath Pitch control of a wind turbine
CN102418663A (en) * 2011-12-29 2012-04-18 一重集团大连设计研究院有限公司 Variable pitch system for offshore high-power wind driven generator group and control method for variable pitch system
US20150176570A1 (en) * 2013-12-20 2015-06-25 Siemens Aktiengesellschaft Detecting a pitch angle adjustment fault
US20150204208A1 (en) * 2014-01-21 2015-07-23 Ssb Wind Systems Gmbh & Co. Kg Pitch angle measuring system and method for wind turbines
CN104807644A (en) * 2015-04-14 2015-07-29 北京中恒博瑞数字电力科技有限公司 Fault early warning method and system for wind generation set variable-pitch system
CN105464912A (en) * 2016-01-27 2016-04-06 国电联合动力技术有限公司 Method and device for detecting freezing of wind generating set blades
CN109723609A (en) * 2017-10-31 2019-05-07 中国电力科学研究院有限公司 A kind of fault early warning method and system of paddle change system of wind turbines
CN207485607U (en) * 2017-11-09 2018-06-12 西安热工研究院有限公司 A kind of wind energy conversion system pitch variable bearings fault detection system
JP2019158577A (en) * 2018-03-13 2019-09-19 トヨタ自動車株式会社 Absolute encoder failure detection device
CN108894913A (en) * 2018-06-27 2018-11-27 北京金风科创风电设备有限公司 Pitch control method and device and computer readable storage medium
CN108760318A (en) * 2018-08-31 2018-11-06 西安热工研究院有限公司 A kind of wind energy conversion system pitch variable bearings fault detection method
CN109458295A (en) * 2018-12-29 2019-03-12 北京金风科创风电设备有限公司 Variable pitch control method and device for wind generating set, electronic equipment and medium

Non-Patent Citations (7)

* Cited by examiner, † Cited by third party
Title
崔天依;褚孝国;: "大转动惯量风电机组变桨控制技术研究", 热力发电 *
张轶东;童博;邓巍;董国伟;张军;李顺民;: "风电机组叶片改造后的检测评估方法", 船舶工程 *
王晓兰;吴姣;马玲;: "基于动态补偿和逆系统方法的有功功率平滑控制", 兰州理工大学学报 *
秦斌;周浩;杜康;王欣;: "基于RBF网络的风电机组变桨距滑模控制", 电工技术学报 *
肖成;刘作军;张磊;: "基于SCADA系统的风电变桨故障预测方法研究", 可再生能源 *
蒋说东;刘军;: "额定风速附近变速变桨风力发电机组功率优化控制", 太阳能学报 *
陈茜;李录平;刘瑞;杨波;李重桂;邓子豪;: "大功率风电机组变桨系统故障诊断方法与技术研究进展", 电站系统工程 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113530763A (en) * 2021-06-10 2021-10-22 北京国电思达科技有限公司 Method and system for monitoring zero position abnormity of blades of wind turbine generator
CN113898528A (en) * 2021-09-30 2022-01-07 江苏金风软件技术有限公司 Abnormity detection method of fan variable pitch bearing, model training method and related device
WO2024045413A1 (en) * 2022-08-31 2024-03-07 北京金风慧能技术有限公司 Pitch fault prediction method and apparatus for wind turbine

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