WO2016166017A1 - Procédé de détermination d'une durée de vie restante d'une éolienne - Google Patents

Procédé de détermination d'une durée de vie restante d'une éolienne Download PDF

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Publication number
WO2016166017A1
WO2016166017A1 PCT/EP2016/057668 EP2016057668W WO2016166017A1 WO 2016166017 A1 WO2016166017 A1 WO 2016166017A1 EP 2016057668 W EP2016057668 W EP 2016057668W WO 2016166017 A1 WO2016166017 A1 WO 2016166017A1
Authority
WO
WIPO (PCT)
Prior art keywords
wind
data
wind turbine
distribution
determining
Prior art date
Application number
PCT/EP2016/057668
Other languages
German (de)
English (en)
Inventor
Jan Carsten Ziems
Original Assignee
Wobben Properties Gmbh
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Wobben Properties Gmbh filed Critical Wobben Properties Gmbh
Publication of WO2016166017A1 publication Critical patent/WO2016166017A1/fr

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Classifications

    • 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
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2260/00—Function
    • F05B2260/82—Forecasts
    • F05B2260/821—Parameter estimation or prediction
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/332—Maximum loads or fatigue criteria
    • 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

Definitions

  • the present invention relates to a method for determining a residual life of a wind turbine.
  • the respective components of the wind turbine are designed so that the wind turbine can have a lifetime of, for example, 20 or 25 years, that is, the respective components of the wind turbine are designed so that operation of the wind turbine for the scheduled life is possible ,
  • Every wind turbine is exposed to stationary and transient loads.
  • the transient loads can be caused for example by wind turbulence, oblique currents and a height profile of the wind speed.
  • the load spectrum which acts on the wind turbine, diverse and the respective load situations must be evaluated in their entirety. This is done by a load collective, which represents the sum of the load situations.
  • the transient loads acting on the wind turbine lead to fatigue of the components of the wind turbine.
  • Each component of the wind turbine is designed so that maximum fatigue should only be achieved when the life of the wind turbine is reached.
  • EP 1 674 724 B1 describes an apparatus and a method for determining fatigue loads of a wind energy plant.
  • a tower fatigue load analysis is performed based on measurements of sensors on the wind turbine.
  • the results of fatigue analysis are subjected to spectral frequency analysis to estimate damage to the foundation of the wind turbine.
  • Based on the tower fatigue analysis an estimate of lifetime information is provided.
  • German Patent and Trademark Office has searched the following documents: DE 10 2014 1 8 146 A1, US 2013/0035798 A1, SHUANGSHU, Tian, et al., Fault Diagnosis and Life Prediction of Wind Turbine Based on Site Monitoring Data ", Instrumentation, Measurement, Computational he, Communication and Control, 2013, Third International Conference on IEEE 2013, pp. 1185-1188 and EP 1 674 724 B1.
  • This object is achieved by a method for determining a remaining service life of a wind turbine according to claim 1.
  • the invention relates to the idea of a residual life of a wind turbine based on historical data of the wind turbine such as the total power generated, the power generation over time, the wind conditions at the wind turbine over time and / or site-specific information (eg mean wind distribution, mean wind turbulence distribution, etc.). ) to determine or estimate.
  • historical data of the wind turbine such as the total power generated, the power generation over time, the wind conditions at the wind turbine over time and / or site-specific information (eg mean wind distribution, mean wind turbulence distribution, etc.). ) to determine or estimate.
  • those data can be used to determine a residual service life of the wind energy plant, which are present, for example, from operating records.
  • This data may be the total energy generated, data on the performance curve, that is, the time course of the power generation, data concerning the wind field distribution and / or site-specific data (such as the wind distribution at the location of the wind turbine).
  • the wind conditions have the greatest influence on the loads of the wind energy plant.
  • the higher the wind speed the higher the load on the wind turbine.
  • wind turbulences also have a high impact on the load on the wind turbine.
  • the service life is the ratio of actual or actual load cycles to m allowable load cycles. This ratio between n and m can then be converted into years of operation.
  • the number of actual load cycles should not exceed the number of maximum load cycles. If the number of actual load cycles is less than the maximum number of Load cycles, then draw conclusions about the remaining life of the wind turbine based on the difference between the actual and the maximum load cycles.
  • data with regard to the wind speed or wind field distribution are necessary in order to estimate or determine the load cycles of the wind energy plant and thus the fatigue of the wind energy plant. If these data are not immediately available, then they can be derived or estimated, for example, based on the total generated power and location-specific data. The more detailed the available data, in particular with regard to their temporal distribution, the more accurate the estimate of the fatigue of the wind turbine and thus the remaining service life of the wind turbine can be estimated or determined.
  • Fig. 1 shows a schematic representation of a wind turbine according to the invention
  • FIG. 2 shows a flowchart of a method for determining a remaining service life of a wind energy plant.
  • 1 shows a wind energy plant 100 with a tower 102 and a nacelle 104.
  • a rotor 106 with three rotor blades 108 and a spinner 110 is arranged on the nacelle 104.
  • the rotor 106 is set in rotation by the wind in rotation and thereby drives a generator in the nacelle 104 at.
  • the wind energy plant 100 is coupled to a central control system, for example via a SCADA connection and transmits data to the central control system. These data can represent the wind speed, the power generated, etc. In the central control system, this data of the wind turbine can be detected and stored.
  • step S200 the available determined or analyzed the historical data of the wind turbine.
  • This data includes at least the total generated power, ie the power that has generated the wind turbine during its lifetime.
  • the historical data may also contain time-resolved performance data of the wind energy plant or time-resolved information with regard to the wind distribution at the wind energy plant.
  • step S300 wind distribution data are derived from the determined historical data of the wind turbine, if they are not yet available.
  • location-specific wind distribution data i.e., a statistical distribution of the wind conditions at the wind turbine sites
  • site-specific wind distribution data may include statistical wind distribution as well as, for example, statistical turbulence analysis.
  • step S400 a derivation or estimation of load collective data of the wind turbine is performed based on the wind distribution data derived in step S300.
  • step S500 a comparison is made with load spectrum data which corresponds to the maximum load collective data and thus the service life of the wind energy plant.
  • step S600 a remaining life or a life consumption is output.
  • the remaining life of a wind turbine is determined based on historical data (output power, wind data or wind distribution data).
  • the life of the wind turbine is assumed to be a number of cycles or revolution. Since this number of cycles or revolutions represents only an assumption, the actual life may differ from the designed life. It depends in particular on how many cycles or revolutions at a corresponding wind distribution has experienced the wind turbine. If the number of actual cycles or revolutions is less than the designed number of cycles, then the actual life may not correspond to the designed life. If the wind turbine has not yet reached the maximum permitted load capacity or the maximum permitted load spectrum, then it can continue to operate, even if the previously defined service life is exceeded.
  • historical data such as generated power and wind data may be used to determine remaining life. If there is no time-resolved wind distribution data, then site-specific wind distribution data (that is, a statistical distribution of the wind distribution data) can be used. This site specific data may include turbulence analysis.
  • a statistical distribution of the generated power of the wind turbine can be used.
  • This statistical distribution of the generated electrical power of the wind turbine can also be determined from a statistical distribution of the generated power of other wind turbines of the same type under similar site conditions. Based on these statistical analyzes, it can be assumed that a certain percentage of the time the wind turbine is operated at full load. From the statistical distribution of the generated power of the wind energy plant and from site-specific wind field data, a time-resolved load or a load spectrum of the wind energy plant can be determined.
  • An improved solution can be achieved if the wind speed and the generated electrical power are stored time-resolved. These data as well as site-specific data can then be used for a more accurate determination of the remaining service life.
  • the mean wind speed acting on the wind energy installation for example 10 minutes averages
  • the wind energy plant can be regarded as a wind mast, which logs the wind speeds and thus the wind distribution for this location. If there are no turbulence intensity values of the site, these can be estimated by additional measurements or standard assumptions according to regulations. From the wind distribution data for the specific location, load spectra for the previous runtime can be determined. According to the invention, the maximum sustainable load spectra can be calculated for the relevant components of the wind energy plant.
  • a determination of the remaining service life of a wind energy plant can be carried out retrospectively based on historical data.

Landscapes

  • 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

L'invention concerne un procédé servant à déterminer une durée de vie restante d'une éolienne. Ledit procédé consiste à déterminer des données historiques disponibles de l'éolienne et à déduire, à partir des données historiques déterminées de l'éolienne, des données de distribution du vent si ces dernières ne sont pas encore disponibles. Des données collectives de charge de l'éolienne sont en outre déduites ou évaluées sur la base des données déduites de distribution du vent. De plus, une comparaison est effectuée entre les données collectives de charge déduites ou évaluées et les données collectives de charge, qui correspondent aux données collectives de charge maximales et, ce faisant, à la durée de vie de l'éolienne. Dès lors, la durée de vie restante de l'éolienne est déterminée sur la base de la comparaison entre les données collectives de charge déduites ou évaluées et les données collectives de charge maximales.
PCT/EP2016/057668 2015-04-13 2016-04-07 Procédé de détermination d'une durée de vie restante d'une éolienne WO2016166017A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102015206539.1 2015-04-13
DE102015206539.1A DE102015206539A1 (de) 2015-04-13 2015-04-13 Verfahren zum Bestimmen einer Restlebensdauer einer Windenergieanlage

Publications (1)

Publication Number Publication Date
WO2016166017A1 true WO2016166017A1 (fr) 2016-10-20

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PCT/EP2016/057668 WO2016166017A1 (fr) 2015-04-13 2016-04-07 Procédé de détermination d'une durée de vie restante d'une éolienne

Country Status (2)

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DE (1) DE102015206539A1 (fr)
WO (1) WO2016166017A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110259646A (zh) * 2019-05-06 2019-09-20 明阳智慧能源集团股份公司 一种基于历史数据的风力发电机组部件状态预警方法
CN113623142A (zh) * 2021-09-15 2021-11-09 中国船舶重工集团海装风电股份有限公司 风力发电机组变桨轴承齿寿命评估方法

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102006014121A1 (de) * 2005-06-03 2006-12-07 General Electric Co. System und Verfahren zum Betrieb eines Windparks bei hohen Windgeschwindigkeiten
US20130035798A1 (en) 2010-02-05 2013-02-07 Yu Zhou Method of operating a wind power plant
WO2013104930A1 (fr) * 2012-01-12 2013-07-18 Romax Technology Limited Procédé pour utiliser une génératrice de turbine éolienne
EP1674724B1 (fr) 2004-12-23 2014-04-02 General Electric Company Méthodes et dispositif pour la mesure des charges de fatigue d'une éolienne
WO2015014368A1 (fr) * 2013-07-29 2015-02-05 Vestas Wind Systems A/S Simulation d'une sortie de puissance maximale d'une turbine éolienne
DE102014118146A1 (de) 2013-12-12 2015-06-18 General Electric Company System und Verfahren zum Betreiben einer Windkraftanlage

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1674724B1 (fr) 2004-12-23 2014-04-02 General Electric Company Méthodes et dispositif pour la mesure des charges de fatigue d'une éolienne
DE102006014121A1 (de) * 2005-06-03 2006-12-07 General Electric Co. System und Verfahren zum Betrieb eines Windparks bei hohen Windgeschwindigkeiten
US20130035798A1 (en) 2010-02-05 2013-02-07 Yu Zhou Method of operating a wind power plant
WO2013104930A1 (fr) * 2012-01-12 2013-07-18 Romax Technology Limited Procédé pour utiliser une génératrice de turbine éolienne
WO2015014368A1 (fr) * 2013-07-29 2015-02-05 Vestas Wind Systems A/S Simulation d'une sortie de puissance maximale d'une turbine éolienne
DE102014118146A1 (de) 2013-12-12 2015-06-18 General Electric Company System und Verfahren zum Betreiben einer Windkraftanlage

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
SHUANGSHU, TIAN ET AL.: "Fault Diagnosis and Life Prediction of Wind Turbine Based on Site Monitoring Data", INSTRUMENTATION, MEASUREMENT, COMPUT ER, COMMUNICATION AND CONTROL, 2013, THIRD INTERNATIONAL CONFERENCE ON IEEE, 2013, pages 1185 - 1188, XP032609780, DOI: doi:10.1109/IMCCC.2013.263

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110259646A (zh) * 2019-05-06 2019-09-20 明阳智慧能源集团股份公司 一种基于历史数据的风力发电机组部件状态预警方法
CN113623142A (zh) * 2021-09-15 2021-11-09 中国船舶重工集团海装风电股份有限公司 风力发电机组变桨轴承齿寿命评估方法
CN113623142B (zh) * 2021-09-15 2023-01-24 中国船舶重工集团海装风电股份有限公司 风力发电机组变桨轴承齿寿命评估方法

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