WO2012079699A1 - Dispositif d'entraînement - Google Patents

Dispositif d'entraînement Download PDF

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Publication number
WO2012079699A1
WO2012079699A1 PCT/EP2011/005933 EP2011005933W WO2012079699A1 WO 2012079699 A1 WO2012079699 A1 WO 2012079699A1 EP 2011005933 W EP2011005933 W EP 2011005933W WO 2012079699 A1 WO2012079699 A1 WO 2012079699A1
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WO
WIPO (PCT)
Prior art keywords
control loop
error
control
drive
fault
Prior art date
Application number
PCT/EP2011/005933
Other languages
German (de)
English (en)
Inventor
Markus Gottfried
Original Assignee
Robert Bosch 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 Robert Bosch Gmbh filed Critical Robert Bosch Gmbh
Publication of WO2012079699A1 publication Critical patent/WO2012079699A1/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
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/043—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
    • F03D7/045—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic with model-based controls
    • 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
    • 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
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/043—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
    • F03D7/046—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic with learning or adaptive control, e.g. self-tuning, fuzzy logic or neural network
    • 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 drive device and to a method for controlling a drive device.
  • Page 1 of 17 DE 103 41 504 A1 "Method for controlling the currents to be fed into a network in wind power plants and circuit operating according to this method"
  • [DE] 10 30 339 A1 "Method and device for improving the degree of utilization and the reliability of a power plant"
  • the operational management of the plant includes monitoring, with which the relevant subsystems are constantly monitored, and faults and emergency situations are identified.
  • the system is currently shut down (fail-passive) when an error is detected (lockout) or an emergency situation is detected (emergency shutdown) (see, e.g., [13], [14]).
  • Wind turbines are subject to variation in primary energy supply due to location and weather conditions (e.g., gusts). As a result, the system components are heavily loaded, and there are fluctuations in the electrical output variables (power, frequency, voltage) in appearance. To influence this is the task of the plant by means of suitable actuators, controls and regulations.
  • the numerous control circuits e.g. for the blade adjustment, turret adjustment, the generator, the aeroelasticity etc. (see eg [4-16], [22], [25]), the system can be realized with different control methods (see eg [3], [14]) ,
  • the present invention provides an improved drive device according to the features of patent claim 1 and an improved method for controlling a drive device according to the features of patent claim 6, in particular for use as / in an actuator in wind power plants,
  • Page 5 of 17 Tolerant systems are usually redundant systems. To achieve fault tolerant behavior, two tasks often need to be accomplished:
  • a faultless condition is established, i. a bug fix - forward or backward
  • Page 6 of 17 exhibit.
  • the method proposed here is characterized by a corresponding behavior in the event of a fault and has a modular structure.
  • the proposed method should use models, including physical quantities, which describe the dynamic behavior of the system, its subsystems and components, e.g. serve to observe these dynamics.
  • the models are described using finite state machines, mathematical functions and primarily differential equations. The description can be made in the time or frequency domain, time-continuous, time-discrete and event-discrete. In [13-15], [22],
  • [23], [26] give examples of suitable models of the mechanical structures of wind turbines.
  • Examples of suitable models of the subsystems can be [13-15],
  • FIG. 1 shows a block diagram of a fault-tolerant control
  • Figure 2 is a block diagram of the observer.
  • Figure 3 is a block diagram of the fault tolerant controller.
  • FIG. 4 shows a block diagram of the error accomodator.
  • FIG. 5 is a block diagram of the controller
  • FIG. 6 is a block diagram of the signal consolidation
  • FIG. 7 shows an example of a signal consolidation in the case of triplex redundancy
  • control loop sizes are used here:
  • Figure 1 the closed loop of the proposed method is shown in the form of a block diagram. In doing so, one recognizes the real system consisting of actuator system, process and sensor system as controlled system. Furthermore, one recognizes the observer, the error detection and fault diagnosis. In addition, error classification and fault-tolerant controller are shown.
  • FIG. 2 shows the block diagram of the observer with the gain matrix K, which uses the models of the actuators, the process and the sensors to estimate from the input vector and the output vector, the vector variables: parameters, states, outputs and residuals.
  • FIG. 3 shows, in the form of a block diagram, the fault-tolerant controller, which is composed of an error adjuster and a controller.
  • FIG. 4 illustrates the error accomodator in block diagram form, which consists of an arbitrator and a reconfigurator.
  • FIG. 5 shows in block diagram form the structure-variable, adaptive controller with the adaptation device. If, as shown here, more than one controller used, then a device is used, which serves for bounce-free switching or cross-fading between the individual controllers.
  • FIG. 6 shows a block diagram of the consolidation of redundant signals using the voting and monitoring methods.
  • FIG. 7 shows by way of example a possibility of the consolidation of the signals, as can be realized in the case of assumed triplex redundancy.
  • Proposed is a method for fault-tolerant control of wind turbines. As shown in the structure indicated in FIG. 1, observers, error detection, fault diagnosis, fault classification and fault-tolerant controllers are used.
  • the diagnosis should primarily be model-based and preferably based on analytical methods.
  • a technical diagnosis describes the analysis of the actual state.
  • the fault diagnosis assigns a cause of error to the deviation of the setpoint behavior detected in an error detection.
  • the diagnosis that implies a previous error detection can be broken down into the following steps:
  • the first two points describe the error detection, which allows a statement about the presence of an error.
  • the error diagnosis identifies the detected errors (the size of the error, the type of error, the cause of the error and the location of the error are determined).
  • Page 9 of 17 The observer serves, as can be seen in FIG. 2, to determine parameters, states and residuals.
  • various embodiments of the observers are suitable, of which are to be given as an example:
  • the basis for the use of the observers are appropriate models, as stated in section 3. This allows model-based identification of parameters and states, as well as the generation of residuals that can be used for error detection and fault diagnosis.
  • the basis of the parameter identification is the assumption that the physical parameters and their changes are mapped in the model parameters.
  • the fault diagnosis requires error detection and assesses the errors that have occurred in order to determine the cause of an error that has occurred.
  • Suitable methods include, for example:
  • Page 10 of 17 The error classifier selects the errors that have occurred from a set of possible errors based on characteristics, features and symptoms. Procedures that are useful for classifying errors include:
  • the fault-tolerant control uses the vector variables: commanded command values, output variables, estimated states, estimated control variables, error signals, additional signals.
  • the fault-tolerant control can be activated and deactivated.
  • the fault-tolerant controller consists of two parts on the first sublevel, as FIG. 3 shows. These are the error accomodator and the controller described in the following sections.
  • the error accomodator is composed of the portions of arbitrator and reconfigurator, as illustrated in FIG.
  • the task of the Arbitrators is to make an appropriate error handling using the information supplied to him. For this purpose, a decision is made as to how the controller, the actuators and the sensors should behave during further operation in the present fault situation and under the prevailing operating conditions. In this case, an appropriately suitable error exclusion, error correction or error compensation must be made. The appropriate information is passed to the reconfigurator. Applicable methods of arbitration may be, for example:
  • the task of the reconfigurator is to select the appropriate fallback level based on the information supplied to it by the arbitrator as required and to outsource, integrate and relocate the subsystems and the corresponding replacement systems on the basis of the requirements. If necessary, adjustments in structure and parameterization are necessary.
  • the reconfigurator passes on suitable information to the controller, the actuators and the sensors.
  • For reconfiguration for example:
  • the controller has, as seen in Figure 5, a general structure. Depending on the requirements, it is composed of individual multivariable regulators (see, for example, [28]), which can be adapted as required by structure and parameterization by means of an adaptation mechanism.
  • the individual multivariable controllers can also be equipped with anti-reset windup measures to prevent an integrator windup caused by manipulated variable limits (saturations).
  • the controller outputs can be proportionately taken into account when using several individual controllers, e.g. by using fuzzy logic, artificial neural networks, etc. It is also possible to switch between the individual controller outputs, e.g. by bounce-free switches, etc. make.
  • the individual controllers can be based, for example, on stability concepts, such as e.g. Hyperstability, dissipativity, etc., or methods based on differential algebraic methods, such as feedback linearization, backstepping, flatness, etc.
  • stability concepts such as e.g. Hyperstability, dissipativity, etc.
  • methods based on differential algebraic methods such as feedback linearization, backstepping, flatness, etc.
  • methods such as gain scheduling, model reference adaptive control, seif tuning control, model predictive methods, State regulations (eg LQR, Riccati etc.) are suitable.
  • PIDTV controls robust control methods (e.g., ⁇ -synthesis, Hoo method), hybrid controllers, finite state machines, artificial neural networks, and fuzzy logic.
  • the consolidation of redundant signals may be done using methods such as voting (see, e.g., [34]) and monitoring, as shown in Figure 6 as a block diagram.
  • voting see, e.g., [34]
  • monitoring as shown in Figure 6 as a block diagram.
  • Figure 7 As an example of a possibility for the case of a signal consolidation in Triplex redundancy serves Figure 7.
  • the method can have effects on the layout of the wind turbine.
  • actuators, sensors, control units etc. are available redundantly in order to be able to operate the plant in a fault-tolerant manner. This suggests the use of the described method.
  • the error classification provides information about the current error case, which results from the system control or the
  • Page 13 of 17 Data transfers of remote monitoring can be read out. These are indications for the use of the described method of fault-tolerant control.
  • the error acceptor with Arbitrator and Reconfigurator provide in case of reconfiguration of the system for the adjustments of regulation, actuators and sensors. Corresponding disconnection and connection of subsystems can be determined, which also points to a fault-tolerant operation of the system and thus to the method described.
  • the direct detectability of the competitor product is a challenge.
  • stimulation with appropriate test signals and appropriate recording of system responses during tests may give indications of the use of the method described.

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Wind Motors (AREA)

Abstract

L'invention porte sur un dispositif d'entraînement, en particulier sur un entraînement de réglage compris dans une éolienne, pouvant être utilisé en particulier comme entraînement de pas, ou entraînement azimutal, et qui comprend : un circuit de régulation dans lequel sont agencés, comme éléments de circuit de régulation, au moins une électronique de régulation, un dispositif de réglage - en particulier un actionneur électromécanique ou un actionneur hydraulique - ainsi qu'un détecteur pour la grandeur réglée, un dispositif d'observation qui est conçu pour exécuter un modèle du circuit de régulation sur la base de signaux de consigne, de signaux de réglage et des signaux de détecteurs du circuit de régulation qui lui sont envoyés, un dispositif de reconnaissance des défauts qui est conçu pour identifier un défaut en se basant sur des écarts entre le modèle et le circuit de régulation, et un circuit d'adaptation qui, en présence d'un défaut, est conçu pour adapter le comportement du circuit de régulation dans le sens tendant vers un comportement sans défaut.
PCT/EP2011/005933 2010-12-15 2011-11-25 Dispositif d'entraînement WO2012079699A1 (fr)

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DE102010054631A DE102010054631A1 (de) 2010-12-15 2010-12-15 Antriebseinrichtung
DE102010054631.3 2010-12-15

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CN103344914A (zh) * 2013-06-26 2013-10-09 中能电力科技开发有限公司 基于归一化的风电机组故障预警方法
WO2014202079A1 (fr) * 2013-06-21 2014-12-24 Kk Wind Solutions A/S Système de commande de turbine éolienne
EP3133282A1 (fr) 2015-08-19 2017-02-22 Senvion GmbH Procede et systeme de surveillance d'un dispositif de reglage de pale individuelle d'une eolienne
CN109340048A (zh) * 2018-09-14 2019-02-15 北京金风科创风电设备有限公司 风力发电机组运行控制方法和装置、存储介质
CN110821759A (zh) * 2019-12-13 2020-02-21 北京三力新能科技有限公司 一种液压变桨故障快速定位和安全停机方法
CN113007021A (zh) * 2021-03-18 2021-06-22 上海第二工业大学 用于变速风力发电机的命令滤波反步控制方法及控制器
CN115234448A (zh) * 2022-07-25 2022-10-25 东方电气新能科技(成都)有限公司 一种预防双馈风机快速收桨失败的监控方法及装置

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WO2017108044A1 (fr) * 2015-12-23 2017-06-29 Vestas Wind Systems A/S Commande de turbines éoliennes en fonction d'estimations de fiabilité
EP3842635A1 (fr) * 2019-12-23 2021-06-30 Vestas Wind Systems A/S Fonctionnement d'une éolienne avec des capteurs mis en oeuvre à l'aide d'un modèle d'apprentissage automatique

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