WO2003106838A1 - Method of monitoring the power produced by aerogenerators - Google Patents

Method of monitoring the power produced by aerogenerators Download PDF

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Publication number
WO2003106838A1
WO2003106838A1 PCT/ES2003/000288 ES0300288W WO03106838A1 WO 2003106838 A1 WO2003106838 A1 WO 2003106838A1 ES 0300288 W ES0300288 W ES 0300288W WO 03106838 A1 WO03106838 A1 WO 03106838A1
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WO
WIPO (PCT)
Prior art keywords
wind
control
production
wind turbine
meteorological
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PCT/ES2003/000288
Other languages
Spanish (es)
French (fr)
Inventor
Mariano SANZ BADÍA
Francisco J. VAL TOMÁS
Andrés LLOMBART ESTOPIÑÁN
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Made Tecnologías Renovables, S.A. Unipersonal
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Publication date
Application filed by Made Tecnologías Renovables, S.A. Unipersonal filed Critical Made Tecnologías Renovables, S.A. Unipersonal
Priority to AU2003240859A priority Critical patent/AU2003240859A1/en
Publication of WO2003106838A1 publication Critical patent/WO2003106838A1/en

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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
    • 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 
    • 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
    • F03D7/028—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor controlling wind motor output power
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P5/00—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft
    • G01P5/02—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft by measuring forces exerted by the fluid on solid bodies, e.g. anemometer
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • 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
    • F05B2270/32—Wind speeds
    • 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
    • F05B2270/321—Wind directions
    • 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
    • F05B2270/335—Output power or torque
    • 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 new method for the productive control of electric wind turbines that are part of a wind farm, in order to detect any anomalous variation in production and, in addition, obtain information to perform proper maintenance.
  • the object of the invention is to achieve an automated control of the production of wind turbines, with a minimum number of meteorological towers (it is estimated that they may be of the order of a meteorological tower every 50 to 100 wind turbines).
  • the analysis of the performance of an electric wind turbine currently involves knowing exactly the density and wind speed that affects its blades. These data, together with the power curve of the machine, allow estimating the theoretical output that can be be compared with the measurement by the wind turbine wattmeter, and thus, perform a quality control of the production, or what is the same, a detection of anomalous production variations, or an evaluation of the machine's performance.
  • the first one consists in taking as valid wind speed data for each wind turbine the one that marks the gondola anemometer. With this data the production is calculated from the power curve and compared with the value received from production. This operation is carried out continuously taking the average of the values used every ten minutes.
  • the second is based on the realization of simulations with WASP-type programs, of wind production analysis, for monthly periods (the periodicity can change between the week or two months) and compare the data obtained with the actual production. This process cannot be automated and must be performed by a specialized technician.
  • the first of the methods takes as valid a data that due to the turbulence produced by the passage of the blades does not faithfully represent the wind speed at the entrance of the wind turbine, so its validity is very questionable.
  • the second is based on simulations carried out with programs for which it has been shown on numerous occasions that they are extremely inaccurate in their calculations when it comes to rough terrain, as in the vast majority of cases of parks located on mountainous terrain ( a type of site widely used for the location of wind farms).
  • This process value is usually “the maximum of the process value (maximum production)
  • This production reference value is usually referred to as a setpoint or reference.
  • the method for production control in electric wind turbines that the invention proposes solves in a fully satisfactory way the above-mentioned problem, simultaneously achieving two objectives: on the one hand it achieves automatic production quality detection and on the other it uses a minimum number of meteorological towers , with the consequent simplification that this implies for the installation.
  • the method consists in relating the power of each wind turbine with the speed and direction of the wind, as well as its temperature and atmospheric pressure, in a meteorological tower, more or less remote from the wind turbine.
  • control system continuously compares, during the operation of the park, the data of real production with the derivatives of the obtained relation, through a statistical quality control method.
  • control system If at any time an abnormal variation in the production of any of the wind turbines is detected, the control system generates the relevant alarms and warnings.
  • the method of the invention allows a rapid diagnosis of the modifications introduced in a given wind turbine model, reducing the time and costs of such a diagnostic process.
  • Figure 1 shows a scheme of fragmentation in sectors of a wind farm, which serves to exemplify the method but does not correspond to any real example.
  • Figure 2.- Shows an outline of the method learning process.
  • the method consists in relating the power produced by the wind turbine with the wind speed blowing at that moment, preferably measured in a meteorological tower (that of the wind farm) that is found in most of cases at a distance from the wind turbine (it is not a dedicated weather tower).
  • the data of the power produced will be corrected in density, for this the methods proposed by the IEC 61400-12 standard will be preferably used.
  • the data segmentation method in sectors works in such a way that a distribution function is calculated for each of the sectors.
  • the sectors are preferably defined by a partition of 5 or in the wind direction and 0.5 m / s in the same speed.
  • a meteorological tower will be used to determine the sectors of each wind turbine, although it is possible that depending on the layout of the park's elements, several meteorological towers can be used to optimize the control system.
  • a total of 720 x 42 30,240 control sectors results .
  • the tower delivers a data of (277 °, 7.3 m / s)
  • the data of the power measured in a wind turbine would be recorded in the sector defined by the interval (275 ° - 280 ° , 7 m / s - 7.5 m / s), although the intervals can be defined in any other way, such as (272.5 ° - 277.5 °;
  • the data obtained have a high statistical quality, and for this a method of statistical processing of the data is used, which consists in capturing the data, taking the average every determined time interval and working with the distribution of the data. Show stockings. Due to the wind turbine power curve test regulations, data capture systems in wind turbines and meteorological towers usually have a sampling frequency of 0.5 Hz (minimum) and a statistical summary of the data (or sample mean, or average of the samples) which will be carried out preferably every 10 minutes.
  • 0.5 Hz minimum
  • a statistical summary of the data or sample mean, or average of the samples
  • the process of calculating the distribution functions ends well by an external manual decision, either when a time limit has elapsed, or when the statistical parameters of each of the sectors have ceased to vary.
  • FIG. 2 shows the scheme corresponding to the learning process, in which the module (1) corresponds to the data capture of the wind turbine (2), data such as power, speed, pressure, etc., supplied to a file (3) with historical data, which after a calculation phase (4) pass to a file (5) with the power parameters, finally taking in the module (6), materialized in a computer, the end of learning decisions , the valuation of statistical parameters, etc. , requesting new data from the capture module (1) or establishing the end (7) of learning.
  • the module (1) corresponds to the data capture of the wind turbine (2), data such as power, speed, pressure, etc.
  • data such as power, speed, pressure, etc.
  • the way to control the quality of production is a multi-criteria decision, in order to distinguish between the different types of failures or drifts that may exist in a productive system.
  • a multi-criteria decision reference is made to the use of several statistical control methods in parallel so that alarms of different anomalous behaviors can be obtained at the same time.
  • control methods that can be used are all related to statistical quality control.
  • methods based on the cumulative sum of error method commonly known as CUSUM
  • SHEWART method will be used. Variants of these methods have been developed specifically for this invention and constitute an important novelty therein. These methods have been called respectively the CUSUM FRACTIONAL or F-CUSUM method and the SHEWART FRACTIONAL or F-SHEWART method. And they are exposed in the following section.

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  • Engineering & Computer Science (AREA)
  • Combustion & Propulsion (AREA)
  • Chemical & Material Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Wind Motors (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Feedback Control In General (AREA)

Abstract

The invention relates to a method of monitoring the electric power produced by aerogenerators. The inventive method consists in first collecting data relating to wind speed, wind direction and the electric power produced each aerogenerator. Next, the system is statistically modelled. Once the system is operating normally, each aerogenerator is monitored and the power produced is continuously compared with the power that should be produced according to the aforementioned model.

Description

MÉTODO PARA EL CONTROL DE PRODUCCIÓN EN AEROGENERADORES ELÉCTRICOS METHOD FOR PRODUCTION CONTROL IN ELECTRICAL AIRCRAFTERS
DESCRIPCIÓNDESCRIPTION
OBJETO DE LA INVENCIÓNOBJECT OF THE INVENTION
La presente invención se refiere a un nuevo método para el control productivo de los aerogeneradores eléctricos que forman parte de un parque eólico, en orden de detectar cualquier variación anómala de la producción y, además, obtener información para poder realizar un adecuado mantenimiento.The present invention relates to a new method for the productive control of electric wind turbines that are part of a wind farm, in order to detect any anomalous variation in production and, in addition, obtain information to perform proper maintenance.
El objeto de la invención es conseguir un control automatizado de la producción de los aerogeneradores, con un número mínimo de torres meteorológicas (se estima que pueden ser del orden de una torre meteorológica cada 50 a 100 aerogeneradores).The object of the invention is to achieve an automated control of the production of wind turbines, with a minimum number of meteorological towers (it is estimated that they may be of the order of a meteorological tower every 50 to 100 wind turbines).
ANTECEDENTES DE LA INVENCIÓNBACKGROUND OF THE INVENTION
Para medir el rendimiento de cualquier sistema de producción de energía eléctrica es necesario conocer, por un lado, la cantidad de energía primaria introducida en el sistema y, por otro, cuánta energía eléctrica se produce. En el caso de la energía hidráulica la energía de entrada viene determinada por el caudal y el salto hidráulico, en el de la energía de la biomasa por la cantidad de biomasa y su poder calorífico. Estas magnitudes se pueden medir con relativa facilidad, por lo que resulta sencillo determinar el rendimiento del sistema estudiado.To measure the performance of any electrical energy production system it is necessary to know, on the one hand, the amount of primary energy introduced into the system and, on the other, how much electrical energy is produced. In the case of hydraulic energy, the input energy is determined by the flow and the hydraulic jump, in the biomass energy by the amount of biomass and its calorific value. These quantities can be measured with relative ease, so it is easy to determine the performance of the system studied.
El análisis del rendimiento de un aerogenerador eléctrico actualmente pasa por conocer con exactitud la densidad y la velocidad del viento que incide sobre sus palas. Estos datos, junto con la curva de potencia de la máquina, permiten estimar la producción teórica que puede ser comparada con la medida por el vatímetro del aerogenerador, y así, realizar un control de calidad de la producción, o lo que es lo mismo, una detección de variaciones anómalas de la producción, o una valoración del rendimiento de la máquina.The analysis of the performance of an electric wind turbine currently involves knowing exactly the density and wind speed that affects its blades. These data, together with the power curve of the machine, allow estimating the theoretical output that can be be compared with the measurement by the wind turbine wattmeter, and thus, perform a quality control of the production, or what is the same, a detection of anomalous production variations, or an evaluation of the machine's performance.
Sin embargo, los datos de velocidad y densidad de viento incidente sobre las palas son imposibles de medir, por lo que se debe trabajar con diferentes métodos de estimación. El único método reconocido para realizar esta estimación es el recogido en la norma CEI 61400-12. Esta norma exige la utilización de una torre meteorológica para cada aerogenerador del parque, situada en los aledaños de éste (a una distancia entre 2 y 4 diámetros), lo que supone un grave inconveniente para realizar inspecciones de manera continua por el importante desembolso económico que esto supone. Además el método exige un periodo mínimo de toma de datos de seis meses lo que compromete el realizar un control continuo de la producción.However, the speed and wind density data incident on the blades are impossible to measure, so it is necessary to work with different estimation methods. The only recognized method to perform this estimate is that set out in IEC 61400-12. This rule requires the use of a meteorological tower for each wind turbine in the park, located in the vicinity of the park (at a distance between 2 and 4 diameters), which is a serious inconvenience to carry out inspections continuously due to the significant economic outlay that This supposes. In addition, the method requires a minimum period of data collection of six months, which compromises the continuous monitoring of production.
Descartado el único método de análisis de rendimiento que puede ser utilizado, con garantías en cuanto a la validez de resultados, existen otros dos métodos aproximados que se pueden utilizar para el propósito señalado.Discarded the only method of performance analysis that can be used, with guarantees as to the validity of results, there are two other approximate methods that can be used for the stated purpose.
El primero de ellos consiste en tomar como dato válido de velocidad de viento para cada aerogenerador el que marca el anemómetro de góndola. Con este dato se calcula la producción a partir de la curva de potencia y se compara con el valor recibido de producción. Esta operación se realiza de manera continua tomando la media de los valores utilizados cada diez minutos.The first one consists in taking as valid wind speed data for each wind turbine the one that marks the gondola anemometer. With this data the production is calculated from the power curve and compared with the value received from production. This operation is carried out continuously taking the average of the values used every ten minutes.
El segundo está basado en la realización de simulaciones con programas tipo WASP, de análisis de producción eólica, para periodos mensuales (la periodicidad puede cambiar entre la semana o los dos meses) y comparar el dato obtenido con la producción real. Este proceso no puede ser automatizado y lo debe realizar un técnico especializado. El primero de los métodos toma como válido un dato que debido a las turbulencias producidas por el paso de las palas no representa con fidelidad la velocidad del viento a la entrada del aerogenerador, por lo que la validez del mismo es muy cuestionable. El segundo está basado en simulaciones realizadas con programas para los que se ha demostrado en numerosas ocasiones que se muestran tremendamente inexactos en sus cálculos cuando se trata de terrenos abruptos, como sucede en la gran mayoría de los casos de los parques situados en terrenos montañosos (un tipo de emplazamiento muy utilizado para la ubicación de parques eólicos).The second is based on the realization of simulations with WASP-type programs, of wind production analysis, for monthly periods (the periodicity can change between the week or two months) and compare the data obtained with the actual production. This process cannot be automated and must be performed by a specialized technician. The first of the methods takes as valid a data that due to the turbulence produced by the passage of the blades does not faithfully represent the wind speed at the entrance of the wind turbine, so its validity is very questionable. The second is based on simulations carried out with programs for which it has been shown on numerous occasions that they are extremely inaccurate in their calculations when it comes to rough terrain, as in the vast majority of cases of parks located on mountainous terrain ( a type of site widely used for the location of wind farms).
Por otro lado, para realizar el control de un proceso hace falta tener un valor de referencia para las variables de control del mismo. Este valor del proceso suele ser « el máximo del valor del proceso (máxima producción)On the other hand, in order to control a process, it is necessary to have a reference value for its control variables. This process value is usually “the maximum of the process value (maximum production)
• el valor de proceso que corresponde al de máximo beneficio (el que maximiza beneficios = ingresos - gastos - impuestos)• the process value that corresponds to the maximum benefit (the one that maximizes benefits = income - expenses - taxes)
• cualquier otro valor de producción que interese por el motivo que sea• any other production value that interests you for whatever reason
A este valor de referencia de producción es usual referirse como consigna o referencia.This production reference value is usually referred to as a setpoint or reference.
La problemática que surge a la hora de diseñar sistema de control de producción es doble, por un lado, hay que calcular dichos valores de referencia, y, por otro, hay que medir las variables del proceso que nos permitan realizar una comparación con dichas consignas. De este modo se puede decidir cuándo el proceso está fuera de control, es decir, cuándo el valor de la producción está fuera de los límites impuestos a la variabilidad natural del proceso.The problem that arises when designing production control system is twofold, on the one hand, we must calculate these reference values, and, on the other, we must measure the process variables that allow us to make a comparison with these slogans . In this way it can be decided when the process is out of control, that is, when the value of production is outside the limits imposed on the natural variability of the process.
Los métodos de control estadístico se diseñaron para decidir cuándo un sistema productivo cambia sus parámetros estadísticos de producción, alertando de ello, lo que posibilita la toma de acciones correctoras.Statistical control methods were designed to decide when a productive system changes its statistical parameters of production, warning of it, which makes it possible to take corrective actions.
DESCRIPCIÓN DE LA INVENCIÓNDESCRIPTION OF THE INVENTION
El método para control de producción en aerogeneradores eléctricos que la invención propone resuelve de forma plenamente satisfactoria la problemática anteriormente expuesta, alcanzando simultáneamente dos objetivos: por un lado consigue la detección automática de calidad de la producción y por otro utiliza un número mínimo de torres meteorológicas, con la consecuente simplificación que ello supone para la instalación.The method for production control in electric wind turbines that the invention proposes solves in a fully satisfactory way the above-mentioned problem, simultaneously achieving two objectives: on the one hand it achieves automatic production quality detection and on the other it uses a minimum number of meteorological towers , with the consequent simplification that this implies for the installation.
Para ello y de forma más concreta el método consiste en relacionar la potencia de cada aerogenerador con la velocidad y la dirección del viento, así como su temperatura y presión atmosférica, en una torre meteorológica, más o menos alejada del aerogenerador.For this, and more specifically, the method consists in relating the power of each wind turbine with the speed and direction of the wind, as well as its temperature and atmospheric pressure, in a meteorological tower, more or less remote from the wind turbine.
Esta relación se obtiene a partir de los datos enumerados en el párrafo anterior que han debido ser tomados durante un determinado periodo de tiempo de funcionamiento normal del aerogenerador. A la obtención de dicha relación se le denomina proceso de aprendizaje del funcionamiento de un aerogenerador.This relationship is obtained from the data listed in the previous paragraph that must have been taken during a certain period of normal operating time of the wind turbine. To obtain this relationship is called the process of learning the operation of a wind turbine.
Como ya se ha comentado, se ha conseguido caracterizar el funcionamiento de los aerogeneradores utilizando datos de torres meteorológicas alejadas varios kilómetros de los mismos, de manera que una misma torre meteorológica es válida para un determinado número de aerogeneradores (50 a 100) situados en un área de considerable amplitud, según una función de la velocidad y de la dirección del viento, de la temperatura y de la presión atmosférica medidos en dicha torre meteorológica.As already mentioned, it has been possible to characterize the operation of wind turbines using data from meteorological towers several kilometers away from them, so that the same meteorological tower is valid for a certain number of wind turbines (50 to 100) located in a area of considerable amplitude, according to a function of the speed and direction of the wind, the temperature and the atmospheric pressure measured in said meteorological tower.
Una vez conocida esta relación el sistema de control compara de manera continua, durante el funcionamiento del parque, los datos de producción reales con los derivados de la relación obtenida, a través de un método de control de calidad estadístico.Once this relationship is known, the control system continuously compares, during the operation of the park, the data of real production with the derivatives of the obtained relation, through a statistical quality control method.
Si en algún momento se detecta una variación anómala de la producción de cualquiera de los aerogeneradores el sistema de control genera las alarmas y avisos pertinentes.If at any time an abnormal variation in the production of any of the wind turbines is detected, the control system generates the relevant alarms and warnings.
Especialmente el método de la invención permite realizar un diagnóstico rápido de las modificaciones introducidas en un determinado modelo de aerogenerador en desarrollo, disminuyendo el tiempo y los costes de tal proceso de diagnóstico.Especially the method of the invention allows a rapid diagnosis of the modifications introduced in a given wind turbine model, reducing the time and costs of such a diagnostic process.
Debido a que los métodos de control de calidad estadísticos permiten detectar tanto disminuciones como aumentos anómalos de la producción se pueden determinar la bondad de las modificaciones realizadas en un prototipo utilizando el método de control descrito.Because the statistical quality control methods allow to detect both decreases and abnormal increases in production, the goodness of the modifications made to a prototype can be determined using the described control method.
DESCRIPCIÓN DE LOS ESQUEMASDESCRIPTION OF THE SCHEMES
Para complementar la descripción que se está realizando y con objeto de ayudar a una mejor comprensión de las características del invento, de acuerdo con un ejemplo preferente de realización práctica del mismo, se acompaña como parte integrante de dicha descripción, un juego de esquemas en donde con carácter ilustrativo y no limitativo, se ha representado lo siguiente:To complement the description that is being made and in order to help a better understanding of the characteristics of the invention, according to a preferred example of practical implementation thereof, a set of diagrams is attached as an integral part of said description where In an illustrative and non-limiting manner, the following has been represented:
La figura 1.- Muestra un esquema de la fragmentación en sectores de un parque eólico, que sirve para ejemplificar el método pero que no corresponde a ningún ejemplo real.Figure 1 shows a scheme of fragmentation in sectors of a wind farm, which serves to exemplify the method but does not correspond to any real example.
La figura 2.- Muestra un esquema del proceso de aprendizaje del método.Figure 2.- Shows an outline of the method learning process.
La figura 3.- Muestra, finalmente, un esquema del proceso de control. REALIZACIÓN PREFERENTE DE LA INVENCIÓNFigure 3.- Shows, finally, a scheme of the control process. PREFERRED EMBODIMENT OF THE INVENTION
A la vista de las figuras reseñadas puede observarse cómo el método consiste en relacionar la potencia producida por el aerogenerador con la velocidad del viento que sopla en ese instante, medida preferentemente en una torre meteorológica (la del parque eólico) que se encuentra en la mayoría de los casos a cierta distancia del aerogenerador (no es una torre meteorológica dedicada).In view of the figures outlined, it can be seen how the method consists in relating the power produced by the wind turbine with the wind speed blowing at that moment, preferably measured in a meteorological tower (that of the wind farm) that is found in most of cases at a distance from the wind turbine (it is not a dedicated weather tower).
Para el proceso de determinación de las funciones de ajuste en cada uno de los sectores, se parte de los siguientes datos:For the process of determining the adjustment functions in each of the sectors, it is based on the following data:
- P: potencia producida por el aerogenerador- P: power produced by the wind turbine
- v: módulo de la velocidad del aire, medido en la torre meteorológica- v: air velocity module, measured in the meteorological tower
- α: dirección del aire, medido en la torre meteorológica- α: air direction, measured in the meteorological tower
- B: presión del aire medido en la torre meteorológica - T: temperatura del aire medido en la torre meteorológica- B: air pressure measured in the weather tower - T: air temperature measured in the weather tower
Los datos de potencia producida serán corregidos en densidad, para ello se utilizarán preferentemente los métodos propuestos por la norma IEC 61400 - 12.The data of the power produced will be corrected in density, for this the methods proposed by the IEC 61400-12 standard will be preferably used.
A partir de este momento cada vez se haga referencia a la potencia generada se estará haciendo referencia a la potencia corregida. Los datos de temperatura y presión del aire se utilizan únicamente para realizar esta corrección.From this moment on, each time reference is made to the power generated, reference will be made to the corrected power. The temperature and air pressure data are used only to perform this correction.
Como el viento depende de la orografía y la rugosidad del terreno, no es lo mismo que sople en una dirección que en otra, así que no es suficiente con encontrar una función del tipo:As the wind depends on the orography and the roughness of the terrain, it is not the same as blowing in one direction than in another, so it is not enough to find a function of the type:
P = f(v) siendoP = f (v) being
- P: la potencia producida por el aerogenerador- P: the power produced by the wind turbine
- v: el módulo de la velocidad del viento sino que se debe tener en cuenta la dirección del viento. De esta forma el ajuste que se realizará será uno del tipo- v: the wind speed module but the wind direction must be taken into account. In this way the adjustment that will be made will be one of the type
P = f(v,α) siendoP = f (v, α) being
- P: potencia generada por el aerogenerador - v: el módulo de la velocidad del viento medido en la torre meteorológica- P: power generated by the wind turbine - v: the wind speed module measured in the meteorological tower
- α: la dirección de la velocidad del viento medida en la torre meteorológica- α: the direction of the wind speed measured in the meteorological tower
Además, se conoce por estudios estadísticos de series temporales del viento, que el viento viene en rachas, de forma que no está definido por una distribución temporal funcional (es decir matemáticamente v ≠ v(t)), sino que lo que define la serie temporal es una función de distribución de probabilidad. Para poder determinar dicha función de distribución de probabilidad, se va a usar un método de segmentación de datos por sectores, de modo que la función P = f(v,α) será una función a trozos, lo que se expresa comoIn addition, it is known by statistical studies of wind time series, that the wind comes in gusts, so that it is not defined by a functional time distribution (ie mathematically v ≠ v (t)), but what defines the series Temporal is a probability distribution function. In order to determine this probability distribution function, a segmentation method of data by sectors will be used, so that the function P = f (v, α) will be a piecewise function, which is expressed as
- P = U fm,n (V, tt) m,n- P = U fm, n (V, tt) m, n
El método de segmentación de datos en sectores funciona de tal forma que se calcula una función de distribución para cada uno de los sectores.The data segmentation method in sectors works in such a way that a distribution function is calculated for each of the sectors.
En el esquema de la figura 1 se ha representado un ejemplo ficticio de división de los datos en 16 sectores, en función de la velocidad y la dirección del viento.In the scheme of figure 1 a fictitious example of division of the data into 16 sectors, depending on the wind speed and direction, has been represented.
De dicha fragmentación resulta una expresión matemática para la función: P = f (v, α) = U fm,n (v, α) = fi,ι(v, α) U fi,2 (v, α) U ... U fm,n (v, α) m,nThis fragmentation results in a mathematical expression for the function: P = f (v, α) = U f m , n (v, α) = fi, ι (v, α) U fi, 2 (v, α) U ... U fm, n (v, α) m, n
Los sectores están definidos, preferentemente, por una partición de 5o en dirección de viento y 0.5 m/s en velocidad del mismo.The sectors are preferably defined by a partition of 5 or in the wind direction and 0.5 m / s in the same speed.
Preferentemente se utilizará una torre meteorológica para la determinación de los sectores de cada aerogenerador, aunque es posible que en función de la disposición de los elementos del parque puedan ser utilizadas varias torres meteorológicas para optimizar el sistema de control.Preferably, a meteorological tower will be used to determine the sectors of each wind turbine, although it is possible that depending on the layout of the park's elements, several meteorological towers can be used to optimize the control system.
Para un ejemplo de particionado en que los sectores vengan definidos por una partición de 5 o en dirección de viento y 0.5 m/s en velocidad entre 4 m/s y 25 m/s, resultan un total de 720 x 42 = 30.240 sectores de control. De esta manera si en un momento dado la torre entrega un dato de (277°, 7,3 m/s), el dato de la potencia medida en un aerogenerador quedaría registrado en el sector definido por el intervalo (275° - 280°, 7 m/s - 7,5 m/s), aunque los intervalos pueden ser definidos de cualquier otra manera, como por ejemplo (272,5° - 277,5° ;For an example of partitioning in which the sectors are defined by a partition of 5 or in the wind direction and 0.5 m / s in speed between 4 m / s and 25 m / s, a total of 720 x 42 = 30,240 control sectors results . In this way, if at any given time the tower delivers a data of (277 °, 7.3 m / s), the data of the power measured in a wind turbine would be recorded in the sector defined by the interval (275 ° - 280 ° , 7 m / s - 7.5 m / s), although the intervals can be defined in any other way, such as (272.5 ° - 277.5 °;
7,25 m/s - 7,75 m/s).7.25 m / s - 7.75 m / s).
En cada uno de los sectores de cada aerogenerador se determinará una función de distribución de probabilidad para los datos de potencia registrados.In each of the sectors of each wind turbine a probability distribution function will be determined for the recorded power data.
Resulta conveniente que los datos que se obtienen tengan una gran calidad estadística, y para ello se usa un método de procesado estadístico de los datos que consiste en ir capturando los datos, sacar la media cada determinado intervalo de tiempo y trabajar con la distribución de las medias muéstrales. Debido a la normativa de ensayo de curvas de potencia de aerogeneradores, los sistemas de captura de datos en aerogeneradores y torres meteorológicas suelen tener una frecuencia de muestreo de 0.5 Hz (mínimo) y un resumen estadístico de los datos (o media muestral, o media de las muestras) que se realizará preferentemente cada 10 minutos. De esta forma se anulan anómalos estadísticos, y se filtran las componentes de alta frecuencia de la señal (valores anormalmente altos, bien por situaciones atmosféricas extrañas, bien por picos de tensión, bien por defecto del sistema de toma de datos, bien por ruido inherente al sistema, bien por ruido estadístico de muestreo).It is convenient that the data obtained have a high statistical quality, and for this a method of statistical processing of the data is used, which consists in capturing the data, taking the average every determined time interval and working with the distribution of the data. Show stockings. Due to the wind turbine power curve test regulations, data capture systems in wind turbines and meteorological towers usually have a sampling frequency of 0.5 Hz (minimum) and a statistical summary of the data (or sample mean, or average of the samples) which will be carried out preferably every 10 minutes. In this way statistical anomalies are annulled, and the high frequency components of the signal are filtered (abnormally high values, either due to strange atmospheric situations, either due to voltage spikes, or by default of the data collection system, or by inherent noise to the system, either by statistical sampling noise).
Para el proceso de determinación de las funciones de distribución en cada uno de los sectores (denominado proceso de aprendizaje del funcionamiento del aerogenerador), se parte de los siguientes datos:For the process of determining the distribution functions in each of the sectors (called the process of learning the operation of the wind turbine), it is based on the following data:
- P: potencia producida por el aerogenerador- P: power produced by the wind turbine
- v: módulo de la velocidad del viento, medido en la torre meteorológica- v: wind speed module, measured in the meteorological tower
- α: dirección del viento, medido en la torre meteorológica- α: wind direction, measured in the meteorological tower
Cuando uno de los datos medidos y normalizados pertenece a uno de los sectores (vm'n, αm'n) del particionado imcial, lo que se hace es recalcular los parámetros estadísticos de la función de distribución de probabilidad de la potencia, para ese sector, teniendo en cuenta los valores de la nueva muestra.When one of the measured and normalized data belongs to one of the sectors (v m ' n , α m ' n ) of the imcial partitioning, what is done is to recalculate the statistical parameters of the power probability distribution function, to that sector, taking into account the values of the new sample.
El proceso de calculo de las funciones de distribución finaliza bien mediante una decisión manual externa, bien cuando ha transcurrido un tiempo límite, o bien cuando los parámetros estadísticos de cada uno de los sectores han dejado de variar.The process of calculating the distribution functions ends well by an external manual decision, either when a time limit has elapsed, or when the statistical parameters of each of the sectors have ceased to vary.
En la figura 2 se ha representado el esquema correspondiente al proceso de aprendizaje, en el que el módulo (1) corresponde a la captura de datos del aerogenerador (2), datos tales como potencia, velocidad, presión, etc., suministrados a un archivo (3) con datos históricos, que tras una fase de cálculo (4) pasan a un archivo (5) con los parámetros de potencia, tomándose finalmente en el módulo (6), materializado en un computador, las decisiones de fin de aprendizaje, la valoración de los parámetros estadísticos, etc. , solicitando nuevos datos del módulo de captura (1) o estableciendo el fin (7) del aprendizaje.Figure 2 shows the scheme corresponding to the learning process, in which the module (1) corresponds to the data capture of the wind turbine (2), data such as power, speed, pressure, etc., supplied to a file (3) with historical data, which after a calculation phase (4) pass to a file (5) with the power parameters, finally taking in the module (6), materialized in a computer, the end of learning decisions , the valuation of statistical parameters, etc. , requesting new data from the capture module (1) or establishing the end (7) of learning.
Por su parte en el esquema de la figura 3 se detalla el proceso de control basado en el aprendizaje de la figura anterior, en el que nuevamente se establece una fase (8) de captura de datos del aerogenerador (2), datos que son suministrados en un sistema (9) de control estadístico, que a su vez recibe información del archivo (5) con los parámetros de potencia, actuando dicho sistema de control (9) sobre los mecanismos de disparo (10) de alarmas por anomalías en la producción que servirán para que el operario correspondiente tome la adecuada decisión (11) al respecto.On the other hand, in the scheme of figure 3 the control process based on the learning of the previous figure is detailed, in which again a phase (8) of wind turbine data capture (2) is established, data that are supplied in a statistical control system (9), which in turn receives information from the file (5) with the power parameters, said control system acting (9) on the triggering mechanisms (10) of alarms due to production anomalies that will serve for the corresponding operator to make the appropriate decision (11) in this regard.
La forma de controlar la calidad de la producción, es una decisión multicriterio, para poder distinguir entre los diferentes tipos de fallo o derivas que pueden existir en un sistema productivo. Como decisión multicriterio se hace referencia a la utilización de varios métodos de control estadísticos en paralelo de modo que se pueden obtener alarmas de diferentes comportamientos anómalos al mismo tiempo.The way to control the quality of production is a multi-criteria decision, in order to distinguish between the different types of failures or drifts that may exist in a productive system. As a multi-criteria decision, reference is made to the use of several statistical control methods in parallel so that alarms of different anomalous behaviors can be obtained at the same time.
Los métodos de control que se pueden utilizar son todos los relacionados con control de calidad estadística. Preferentemente se utilizarán métodos basados en el método de sumas acumuladas del error (conocido comúnmente como CUSUM), y el método SHEWART. Se han desarrollado variantes de estos métodos expresamente para esta invención y constituyen una novedad importante en la misma. Estos métodos se han denominado respectivamente método de la CUSUM FRACCIONAL o F- CUSUM y método SHEWART FRACCIONAL o F-SHEWART. Y se exponen en el siguiente apartado. The control methods that can be used are all related to statistical quality control. Preferably, methods based on the cumulative sum of error method (commonly known as CUSUM), and the SHEWART method will be used. Variants of these methods have been developed specifically for this invention and constitute an important novelty therein. These methods have been called respectively the CUSUM FRACTIONAL or F-CUSUM method and the SHEWART FRACTIONAL or F-SHEWART method. And they are exposed in the following section.

Claims

R E I V I N D I C A C I O N E S R E I V I N D I C A C I O N E S
I a.- Método para el control de producción en aerogeneradores eléctricos, que teniendo por finalidad la detección automática de variaciones anómalas de producción de los aerogeneradores de un parque eólico, con un número mínimo de torres meteorológicas, se caracteriza porque consiste en relacionar la potencia de cada aerogenerador con la velocidad y la dirección del viento en una torre meteorológica, que puede estar alejada varios kilómetros del aerogenerador, según una función a trozos:I a .- Method for the control of production in electric wind turbines, whose purpose is the automatic detection of anomalous production variations of wind turbines of a wind farm, with a minimum number of meteorological towers, is characterized in that it consists in relating the power of each wind turbine with the speed and direction of the wind in a meteorological tower, which may be several kilometers away from the wind turbine, according to a piecewise function:
P = f (v, ) = U fm,n (v, ) = fi,ι(v, α) U f (v, α) U ... U fm,n (v, α) m,nP = f (v,) = U fm, n (v,) = fi, ι (v, α) U f (v, α) U ... U fm, n (v, α) m, n
donde P es la potencia generada por el aerogenerador que ha sido corregida en densidad, v el módulo de velocidad del viento medido en la torre meteorológica y α la dirección del viento en dicha torre meteorológica, y a partir de estas relaciones aplicar métodos de control de calidad estadísticos.where P is the power generated by the wind turbine that has been corrected in density, v the wind speed module measured in the meteorological tower and α the wind direction in said meteorological tower, and from these relationships apply quality control methods Statisticians
2 a.- Método para el control de producción en aerogeneradores eléctricos, según reivindicación Ia, caracterizado porque se determina una función de distribución de probabilidad para cada aerogenerador, mediante la segmentación de datos por sectores, calculando una función de distribución para cada uno de tales sectores de trabajo, función que relaciona la potencia P generada por el aerogenerador, que es corregida en densidad utilizando los datos de temperatura y presión atmosférica tomados en la torre meteorológica con la velocidad y dirección del viento tomadas también en la torre meteorológica.2 .- Method for production control electric turbines, according to claim I, characterized in that a probability distribution function for each turbine is determined by segmenting data by sector, calculating a distribution function for each of such work sectors, a function that relates the power P generated by the wind turbine, which is corrected in density using the temperature and atmospheric pressure data taken in the meteorological tower with the wind speed and direction also taken in the meteorological tower.
3 a.- Método para el control de producción en aerogeneradores eléctricos, según reivindicación 2a, caracterizado porque para cada aerogenerador se consideran varios sectores de control que vienen definidos preferentemente por una partición de 5° en dirección del viento y 0.5 m/s en velocidad del viento. 4 a.- Método para el control de producción en aerogeneradores eléctricos, según reivindicaciones Ia, 2a y 3a, caracterizado porque se determinan funciones de ajuste, para cada aerogenerador en cada uno de sus sectores de control definidos a partir de:3 .- Method for production control electric turbines, according to claim 2, characterized in that for each wind turbine considering several sectors control are preferably defined by a partition of 5 ° in the direction of the wind and 0.5 m / s in wind speed. 4 .- Method for production control electric turbines, according to claims I, 2 and 3, characterized in that adjustment functions are determined for each wind turbine in each of its control sectors defined from:
- P: potencia producida por el aerogenerador- P: power produced by the wind turbine
- v: módulo de la velocidad del aire, medido en la torre meteorológica - α: dirección del aire, medido en la torre meteorológica- v: air velocity module, measured in the meteorological tower - α: air direction, measured in the meteorological tower
- B: presión del aire medido en la torre meteorológica- B: air pressure measured in the weather tower
- T: temperatura del aire medido en la torre meteorológica- T: temperature of the air measured in the meteorological tower
5 a.- Método para el control de producción en aerogeneradores eléctricos, según reivindicaciones I a, 2a y 3a, caracterizado porque las funciones de ajuste de los sectores de control son de tipo estadístico, y para su determinación se utilizan datos reales del funcionamiento de cada aerogenerador, es decir el modelado del aerogenerador está basado en datos históricos meteorológicos y de producción del aerogenerador.5 a. - Method for the control of production in electric wind turbines, according to claims I a , 2 a and 3 a , characterized in that the adjustment functions of the control sectors are of statistical type, and for their determination real data of the operation of each wind turbine, that is, the modeling of the wind turbine is based on historical meteorological and production data of the wind turbine.
6 a.- Método para el control de producción en aerogeneradores eléctricos, según reivindicaciones anteriores, caracterizado porque los datos serán normalizados en densidad, y para ello se utilizarán preferentemente los métodos marcados por la norma6 a. - Method for the control of production in electric wind turbines, according to previous claims, characterized in that the data will be normalized in density, and for this purpose the methods marked by the standard will be preferably used
IEC 61400-12.IEC 61400-12.
7 a.- Método para el control de producción en aerogeneradores eléctricos, según reivindicaciones anteriores, caracterizado porque el control propiamente dicho se realiza mediante un método estadístico multicriterio, en el que se utilizan preferentemente los métodos F-CUSUM y F-SHEWART especialmente desarrollados para implementar esta invención que permiten detectar con gran rapidez distintos tipos de fallos en los aerogeneradores eléctricos. 7 a. - Method for the control of production in electric wind turbines, according to previous claims, characterized in that the control itself is carried out by means of a multicriteria statistical method, in which the F-CUSUM and F-SHEWART methods specially developed are preferably used for Implement this invention that allows to detect very quickly different types of failures in electric wind turbines.
PCT/ES2003/000288 2002-06-14 2003-06-11 Method of monitoring the power produced by aerogenerators WO2003106838A1 (en)

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