Method for determining wind speed in the rotor plane of a wind turbine

Abstract

The invention relates to a method for determining the wind speed in the plane (PR) of a rotor of a wind turbine (1) by measuring the rotational speed of the rotor, the angle of the blades and the power produced. The method according to the invention implements a dynamic wind turbine model, a dynamic wind model and an unscented Kalman filter.

Description

Technical Field

[0001] The present invention relates to the field of renewable energy and more particularly to wind turbines, wind resource measurement with wind forecasting, turbine control (orientation, torque and speed regulation) and / or diagnostics and / or monitoring objectives.

[0002] Wind turbines convert kinetic energy from wind into electrical or mechanical energy. For wind energy conversion, they consist of the following facilities:

[0003] - a tower that positions the rotor at a sufficient height to enable its movement (required for horizontal axis wind turbines) or at a height that allows it to be driven by stronger and more frequent winds than at ground level. The tower usually houses part of the electrical and electronic components (modulators, controllers, multipliers, generators, etc.),

[0004] - The nacelle, which is mounted at the top of the tower and houses the mechanical, pneumatic, and some electrical and electronic components needed to run the turbine. The nacelle can be rotated to orient the rotor in the correct direction.

[0005] - A rotor fastened to the nacelle, comprising several blades (usually three) and the hub of the wind turbine. The rotor is driven by wind energy and is connected by a mechanical shaft directly or indirectly (via a gearbox and a mechanical shaft system) to an electric motor (generator) or to any other type of converter that converts the recovered energy into electrical energy or any other type of energy. The rotor may be provided with control systems such as variable angle blades or aerodynamic brakes,

[0006] A transmission consisting of two shafts (the mechanical shaft of the rotor and the mechanical shaft of the converter) connected by a transmission (gearbox) so as to form a kinematic chain between the mechanical shafts of the rotor and the converter.

[0007] Since the beginning of the 1990s, there has been a renewed interest in wind power, particularly in the European Union, where annual growth rates are around 20%. This growth is attributed to the inherent possibility of generating electricity without carbon emissions. In order to sustain this growth, there remains a need to further increase the energy output of wind turbines. The prospect of increased wind power production requires the development of efficient production tools and advanced control tools to improve machine performance. Wind turbines are designed to generate power at the lowest possible cost. Therefore, they are usually built to reach their maximum performance at wind speeds of around 15 m / s. It is not common to design wind turbines that maximize their output at higher wind speeds. At wind speeds above 15 m / s, some of the extra energy contained in the wind must be lost to avoid damage to the wind turbine. Therefore, all wind turbines are designed with a power regulation system.

[0008] For this power regulation, controllers have been designed for variable speed wind turbines. The controllers aim to maximize the recovered power, minimize rotor speed fluctuations, and minimize fatigue and extreme moments in the structure (blades, tower, and platform). Background Art

[0009] For optimal control, it is important to know the wind speed at the rotor of a wind turbine. Various techniques have been developed for this purpose.

[0010] According to a first solution, the use of anemometers makes it possible to estimate the wind speed at one point, but this imprecise technique does not allow measurement of the entire wind field or knowledge of the three-dimensional components of the wind speed.

[0011] According to the second approach, LiDAR (Light Detection and Ranging) sensors can be used. LiDAR is a remote sensing or optical measurement technology based on analyzing the properties of a beam returning from a transmitter. This method is specifically used to determine the distance to an object using pulsed laser light. Unlike radar, which is based on similar principles, LiDAR sensors use visible or infrared light rather than radio waves. The distance to an object or surface is determined by measuring the delay between the pulse and the detection of the reflected signal.

[0012] In the field of wind turbines, LiDAR sensors are being declared essential for the proper operation of large wind turbines, especially as their size and power are increasing (currently 5 MW for offshore turbines, soon to be 12 MW). These sensors enable remote wind measurement, initially allowing the wind turbines to be calibrated so that they can deliver maximum power (power curve optimization). For this calibration phase, the sensor can be positioned on the ground and oriented vertically (profiler), allowing it to measure wind speed and direction, as well as the wind gradient depending on altitude. This application is particularly crucial because it allows the source of energy generation to be determined. This is important for wind turbine projects, as it determines their economic viability.

[0013] A second application scenario involves placing the sensor on the nacelle of a wind turbine to measure the wind field in front of the turbine when oriented nearly horizontally. Measuring the wind field in front of the turbine provides a priori knowledge of the turbulence the wind turbine will soon encounter. However, current wind turbine control and monitoring technologies are unable to take into account the measurements performed by the LiDAR sensor by accurately estimating the wind speed at the rotor, i.e., in the rotor plane. This application scenario is notably described in patent application FR-3-013,777 (US-2015-145,253).

[0014] However, LiDAR sensors are expensive. Furthermore, since they are relatively recent, it remains difficult to understand how to utilize wind field characteristics such as wind speed, wind direction, wind shear, turbulence, and induction factors by converting the raw data from the LiDAR sensors. Consequently, such LiDAR sensors require complex implementations to determine the wind speed in the rotor plane. Therefore, there is a need for an inexpensive, reliable, and readily usable method for determining the wind speed in the rotor plane, for example, for controlling and / or diagnosing wind turbines. Summary of the Invention

[0015] The object of the present invention is to determine the wind speed in the rotor plane in an inexpensive and reliable manner in real time. The present invention therefore relates to a method for determining the wind speed in the rotor plane of a wind turbine by measuring the rotor's rotational speed, the blade angle, and the power generated. The method according to the invention implements a dynamic wind turbine model, a dynamic wind model, and an unscented Kalman filter. The dynamic model enables reliable determination of the wind speed in the rotor plane. The unscented Kalman filter provides for interference-free determination of the result. Furthermore, the method according to the invention does not use expensive sensors.

[0016] The present invention relates to a method for determining the wind speed in a rotor plane of a wind turbine, wherein the following steps are performed:

[0017] a) measuring the rotation speed of the rotor of the wind turbine, the pitch angle of the blades of the wind turbine and the power generated by the converter of the wind turbine,

[0018] b) constructing a dynamic model of the wind turbine, the dynamic model relating the rotational speed of the rotor of the wind turbine to the wind speed in the rotor plane, the pitch angles of the blades of the wind turbine and the power generated by the converter of the wind turbine,

[0019] c) constructing a dynamic wind model using a second-order random walk model, and

[0020] d) determining the wind speed in the plane of the rotor by means of an unscented Kalman filter, the unscented Kalman filter being applied to the dynamic model of the wind turbine, the dynamic wind model and the measured values ​​of the rotational speed of the rotor, the pitch angle of the turbine blades and the power produced by the converter of the wind turbine.

[0021] According to one embodiment, the dynamic wind model is written as:

[0022]

[0023] where v1(t) is the wind speed in the rotor plane, v2(t) is the wind speed derivative in the rotor plane, η(t) is white noise with zero mean, and v(t)=v1(t).

[0024] Advantageously, the dynamic model of the wind turbine is written as:

[0025]

[0026] where ω(t) is the rotational speed of the rotor, J is the moment of inertia of the kinematic chain of the wind turbine, ρ is the air density, R is the radius of the rotor, and C q is the power coefficient, β(t) is the pitch angle of the blade, λ(t) is the ratio of blade tip speed to the wind speed in the rotor plane, P g (t) is the power generated by the converter of the wind turbine, v(t) is the wind speed in the rotor plane, and T l (t) is the loss torque along the kinematic chain of the wind turbine.

[0027] Preferably, the loss torque T l (t) is considered as noise.

[0028] Advantageously, the power coefficient C q Obtained from the diagram of the wind turbine.

[0029] According to one aspect, the method determines the longitudinal component of the mean wind speed in the rotor plane.

[0030] According to one embodiment, the unscented Kalman filter is applied to the state equation:

[0031]

[0032] Among them, x1(t)=ω(t), x2(t)=v(t), ω(t) is the rotational speed of the rotor, J is the moment of inertia of the kinematic chain of the wind turbine, ρ is the air density, R is the radius of the rotor, C q is the power coefficient, β(t) is the pitch angle of the blade, P g (t) is the power generated by the converter of the wind turbine, v(t) is the wind speed in the rotor plane, μ1(t) and μ2(t) are independent white noises with zero mean, and y(t) is the measured output identified at the rotor speed ω(t) corrupted by the white noise ξ(t).

[0033] According to one embodiment, the wind speed is determined by performing the following steps:

[0034] i) Initially k = 0, the state vector and the state of the covariance matrix P(0|0)=P0,

[0035] ii) at any time k different from 0, obtaining said measurement value y(k), and

[0036] iii) At any time k different from 0, the wind speed v(k) in the rotor plane is determined by the following equation:

[0037] K(k)=P(k|k-1)C T (CP(k|k-1)C T +R) -1

[0038]

[0039]

[0040] Where K is the Kalman filter gain, P is the covariance of the Gaussian noise μ, P(k|k-1) is the error variance of the measurement from the time k-1, P(k|k) is the error variance of the measurement from the time k, x(k|k) is an estimate of x(k) from the measurement at time k, x(k|k-1) is an estimate of x(k) from the measurement at time k-1, R is the covariance of the Gaussian noise ξ, C = [1 0 0], and l3 is the identity matrix of size 3.

[0041] The present invention also relates to a method for controlling a wind turbine. The method comprises the following steps:

[0042] a) determining the wind speed in the rotor plane of a wind turbine by means of a method according to one of the above features, and

[0043] b) controlling the wind turbine according to the wind speed in the rotor plane of the wind turbine.

[0044] Furthermore, the invention relates to a computer program product comprising code instructions designed to perform the steps of the method according to one of the above features when said program is executed on a control and / or diagnostic unit of the wind turbine.

[0045] Furthermore, the present invention relates to a wind turbine comprising means for measuring the rotational speed of the rotor, means for measuring the pitch angle of the wind turbine blades, means for measuring the power generated by the converter of the wind turbine, and means for determining the wind speed in the rotor plane of the wind turbine, capable of implementing a method according to any of the above-mentioned features.

[0046] According to an embodiment of the present invention, a wind turbine comprises a real-time control and data acquisition system comprising the device for measuring the rotational speed of the rotor, the device for measuring the pitch angle of the wind turbine blades and the device for measuring the power generated by the converter of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Other characteristics and advantages of the method according to the invention will become apparent from the following description of an embodiment given by way of non-limiting example, with reference to the accompanying drawings, in which:

[0048] - Figure 1 A wind turbine according to an embodiment of the present invention is shown.

[0049] - Figure 2 The steps of the method according to an embodiment of the present invention are shown.

[0050] - Figure 3 shows the power coefficient C q An example of a graph of

[0051] - Figure 4 shows a graph of the power produced by a (power) converter as a function of time, measured for an example application scenario,

[0052] - Figure 5 Shown for Figure 4 An example of a curve of the measured rotor rotation speed versus time,

[0053] - Figure 6 Shown for Figure 4 and 5 The measured curve of the blade pitch angle over time, and

[0054] - Figure 7 FIG shows a curve showing the wind speed in the rotor plane obtained by a LiDAR sensor using a method according to an embodiment of the present invention over time, for example Figures 4 to 6 . DETAILED DESCRIPTION

[0055] The invention relates to a method for determining the wind speed in a rotor plane of a wind turbine in real time.

[0056] As a non-limiting example, Figure 1 A horizontal axis wind turbine 1 according to an embodiment of the present invention is schematically shown. Generally, the wind turbine 1 is capable of converting the kinetic energy of wind into electrical energy or mechanical energy. For wind energy conversion, it is composed of the following facilities:

[0057] a tower 4 which positions the rotor (not shown) at a sufficient height to enable its movement (required for horizontal axis wind turbines) or at a height that allows it to be driven by stronger and more frequent winds than at ground level 6. The tower 4 generally houses part of the electrical and electronic components (modulators, controllers, multipliers, generators, etc.),

[0058] - a nacelle 3, mounted at the top of a tower 4, housing the mechanical components, pneumatic components and some electrical and electronic components (not shown) necessary to operate the converter. The nacelle 3 can be rotated to orient the machine in the correct direction,

[0059] - A rotor fastened to the nacelle, comprising a plurality of blades 7 (typically three) and the hub of the wind turbine. The rotor is driven by energy from the wind and is connected by a mechanical shaft directly or indirectly (via a gearbox and a mechanical shaft system) to an electric motor (generator) or to any other converter (e.g. a hydraulic machine or a starter) that converts the recovered energy into electrical energy or any type of energy (e.g. hydraulic energy or pneumatic energy). The rotor may be provided with control systems such as variable angle blades or aerodynamic brakes,

[0060] A transmission (not shown) consisting of two connected shafts (the mechanical shaft of the rotor and the mechanical shaft of the converter) thus forming a kinematic chain between the mechanical shafts of the rotor and the converter.

[0061] The figure also shows the axes x, y, and z. The reference point of this coordinate system is the center of the rotor. Direction x is the longitudinal direction, corresponding to the direction of the rotor axis upstream of the wind turbine. Direction y, perpendicular to direction x, is a transverse direction lying in a horizontal plane (directions x and y form the horizontal plane). Direction z is a vertical direction pointing upward (essentially corresponding to the direction of tower 4), with axis z perpendicular to axes x and y. The rotor plane is represented by the rectangle indicated by the dashed line PR; for zero values ​​of x, it is defined by directions y and z.

[0062] According to the present invention, the method for determining wind speed comprises at least the following steps:

[0063] 1) Measurement,

[0064] 2) Construct a dynamic wind turbine model,

[0065] 3) Construct a dynamic wind model,

[0066] 4) Determine wind speed.

[0067] Steps 1) and 4) can be performed in real time. Steps 2) and 3) can be performed in advance and offline. These steps are described in detail below.

[0068] As a non-limiting example, Figure 2 The steps of a method for determining wind speed according to an embodiment of the present invention are schematically shown. A dynamic wind turbine generator model MEO can be pre-constructed to relate the rotational speed of the rotor to the wind speed in the rotor plane, the pitch angle of the blades, and the power generated by the converter. Furthermore, a dynamic wind model MVE can be pre-constructed. The method also involves measuring the rotational speed ω of the MES rotor, the pitch angle β of the blades, and the power P generated by the converter. g Then the unscented Kalman filter UKF is applied to the dynamic wind turbine model MEO, the dynamic wind model MVE and the measured ω, β, P g The unscented Kalman filter is implemented to determine the wind speed v in the rotor plane.

[0069] 1. Measurement

[0070] The following measurements are performed in this step:

[0071] - the rotational speed of the rotor,

[0072] - the pitch angle of the blades, and

[0073] - The power generated by the converter (in other words, the power generated by the wind turbine).

[0074] According to one embodiment of the present invention, at least one of the measurements (values) can be obtained from a real-time control and data acquisition system (SCADA). SCADA systems are large-scale remote management systems capable of processing a large number of remote measurements in real time and controlling technical equipment from a distance. It is an industrial technology in the field of instrumentation, and its implementation can be considered as an instrumentation structure including a middleware-type layer. Preferably, all measurements (values) can be obtained from the SCADA system, which facilitates the implementation of the method without specific instrumentation. In addition, the SCADA system may be able to take into account at least one other measurement to more accurately determine the wind speed in the rotor plane. These measurements (values) may be, in particular, temperature, electrical data, vibration, etc. Temperature can provide information on effective mechanical losses, and therefore they can improve the modeling of the wind turbine. Accelerometers, combined with a sufficiently detailed and relevant understanding of the structure's modal and vibration characteristics, can provide a return assessment of the wind and turbulence conditions affecting the wind turbine.

[0075] Alternatively, at least one of the measurements may be obtained by a dedicated sensor. For this embodiment:

[0076] - Rotor angle rotation sensor can be used to measure the rotation speed of the rotor, and / or

[0077] - Blade angle sensors can be used to measure the pitch angle of the blades, and / or

[0078] - A known and controlled voltage sensor can be used to measure the power produced by the converter, and an intensity sensor can be used to measure the current delivered by the generator.

[0079] 2. Construction of dynamic wind turbine model

[0080] This step involves constructing a dynamic wind turbine model that relates the rotational speed of the rotor to the wind speed in the rotor plane, the pitch angle of the wind turbine blades, and the power generated by the wind turbine's converter. A dynamic wind turbine model is understood to be a model obtained by applying the fundamental principles of dynamics to a wind turbine.

[0081] According to one embodiment of the present invention, the dynamic wind turbine model can be written as:

[0082]

[0083] where ω(t) is the rotational speed of the rotor, J is the moment of inertia of the kinematic chain of the wind turbine, ρ is the air density, R is the radius of the rotor, C q is the power coefficient, β(t) is the pitch angle of the blade, and λ(t) is the ratio of the blade tip speed to the wind speed in the rotor plane (i.e., ), P g (t) is the power generated by the turbine's converter, v(t) is the wind speed in the rotor plane, and T l (t) is the loss torque along the kinematic chain of the wind turbine. Preferably, for this embodiment, the loss torque T l (t) can be considered as noise. This simplifies the determination of the wind speed in the rotor plane. Alternatively, T can be measured l (t).

[0084] According to one implementation of this embodiment, the power coefficient C can be obtained by using a (mapping) diagram of the wind turbine. q Such a (mapping) diagram will be the power coefficient C q is related to the pitch angle β of the blades and the ratio λ of the blade tip speed to the wind speed in the rotor plane. According to a non-limiting example, a map may be pre-constructed (mapped) using an aerodynamic model of the wind turbine under consideration. Figure 3 An example of such a diagram is schematically shown as a non-limiting example, which plots the power coefficient C as a function of the pitch angle β (expressed in degrees) of the blades. q is related to the ratio λ of the blade tip speed relative to the wind speed in the rotor plane.

[0085] In fact, the dynamic wind turbine model according to this embodiment can be obtained from the equation of the basic principle of dynamics:

[0086]

[0087] Where, ω(t) is the rotational speed of the rotor, J is the moment of inertia of the kinematic chain of the wind turbine, T r (t) is the aerodynamic torque generated by the rotor, T g (t) the torque generated by the converter, and T l (t) is the loss torque along the kinematic chain of the wind turbine.

[0088] In this equation, the aerodynamic torque can be written as:

[0089]

[0090] Where ρ is the air density, R is the rotor radius, and C q is the power coefficient, β(t) is the pitch angle of the blade, and λ(t) is the ratio of the blade tip speed to the wind speed in the rotor plane (i.e., ), and v(t) is the wind speed in the rotor plane.

[0091] In addition, the torque T generated by the converter g Can be written as:

[0092]

[0093] Where, ω(t) is the rotation speed of the rotor, P g (t) is the power generated by the converter of the wind turbine.

[0094] The combination of these equations enables the above-mentioned dynamic wind turbine model to be obtained.

[0095] The method according to the invention is not limited to this dynamic model of a wind turbine, but can be implemented for any other dynamic model of a wind turbine.

[0096] 3. Construction of dynamic wind model

[0097] This step involves constructing a dynamic wind model using a second-order random walk model. A dynamic wind model represents wind changes over time. A random walk model is a model with discrete dynamics, consisting of a series of random time intervals. For this model, the future of the system depends on its current state, not its past. Using a random walk model provides good wind modeling and is suitable for representing smooth curves using squared second-order derivatives. Such a model does not require prior knowledge of wind characteristics such as average speed and turbulence.

[0098] According to one embodiment of the present invention, the dynamic wind model can be written as:

[0099]

[0100] where v1(t) is the wind speed in the rotor plane, v2(t) is the wind speed derivative in the rotor plane, and η(t) is white noise with zero mean.

[0101] 4. Determine wind speed

[0102] This step consists in determining the wind speed in the rotor plane of the wind turbine by means of an unscented Kalman filter (UKF). The unscented Kalman filter is applied to the dynamic wind turbine model constructed in step 2) and the dynamic wind model constructed in step 3), taking into account the measurements performed in step 1). The unscented Kalman filter is a filtering algorithm that uses a system model to estimate the current hidden state of the system and then corrects this estimate using available measurements. The principle of the UKF differs from that of the extended Kalman filter in that it uses an unscented transform to directly estimate the mean and covariance of the target distribution. The unscented Kalman filter can include the steps of state prediction and measurement correction, both of which are preceded by a prior step of calculating "sigma points". Sigma points are a set of samples calculated so that the mean and variance information is accurately propagated through the space of nonlinear functions.

[0103] This filter is therefore very suitable for quickly determining the wind speed in the rotor plane.

[0104] According to one embodiment of the present invention, the longitudinal component of the average wind speed in the rotor plane can be determined in this step. This component, denoted by REWS (Rotor Equivalent Wind Speed), corresponds to the operational and production status of the wind turbine at a given moment. This is the wind speed typically used for controlling and / or monitoring wind turbines.

[0105] According to one embodiment of the present invention, the unscented Kalman filter can be applied to the following state equation:

[0106]

[0107] Among them, x1(t)=ω(t), x2(t)=v(t), ω(t) is the rotational speed of the rotor, J is the moment of inertia of the kinematic chain of the wind turbine, ρ is the air density, R is the radius of the rotor, C q is the power coefficient, β(t) is the blade pitch angle, P g(t) is the power produced by the converter of the wind turbine, v(t) is the wind speed in the rotor plane, μ1(t) and μ2(t) are independent white noises with zero mean, and y(t) is the measured output identified at the rotor speed ω(t) corrupted by the white noise ξ(t).

[0108] y(t)=ω(t)+ξ(t)

[0109] In other words:

[0110] The equation of state can be obtained by combining the dynamic models of the wind turbine and the wind, respectively, determined in the previous steps.

[0111] Using this state equation, the problem of estimating the wind speed in the rotor plane becomes a problem of estimating the state using this equation and the measured output y(t), i.e., the unknown state x(t) at each sampling instant is x(t) = [x1(r) x2(t) x3(t)] T problem.

[0112] The unscented Kalman filter can be implemented by discretizing the state equation using the Euler discretization method, which gives:

[0113]

[0114] in,

[0115] C=[1 0 0],

[0116] f(x(k),β(k),

[0117] Among them, T s is the sampling period.

[0118] In this discrete state model, μ(t) and ξ(t) can be assumed to be Gaussian noise with zero mean, with corresponding covariance matrices Q and R.

[0119] Notice

[0120] x(k|k-1))

[0121] It is the estimate of x(k) based on the measurement value at time k-1.

[0122] x(k|k)

[0123] It is the estimate of x(k) based on the measurement value at time k.

[0124] P(k|k-1)

[0125] is the error variance of the measurement from time k-1.

[0126] P(k|k)

[0127] is the error variance of the measurement from time k.

[0128] For a given state estimate x(k-1|k-1) and a given error variance estimate P(k-1|k-1) at time k-1, there are two steps in UKF: prediction and correction.

[0129] After the correction step at time k-1, the distribution of x(k-1) can be given as follows:

[0130]

[0131] in, Indicates a Gaussian distribution.

[0132] The sigma points associated with the mean x(k-1|k-1) and the covariance matrix P(k-1|k-1) can be calculated as follows:

[0133]

[0134] In this case, n=3, and Si is the i-th column of S, where:

[0135] SS T =P(k-1|k-1).

[0136] The sigma points are propagated in the equation of state as follows:

[0137] γ i (k) = f( i ,β(k-1),P g (k-1))

[0138] Among them, γ i is the realization of x(k|k-1) for any i in the range from 0 to 2n.

[0139] The next step involves calculating the predicted mean x(k|k-1) and the predicted covariance P(k|k-1) using the following equations:

[0140]

[0141] Considering that the output equation is linear, the correction steps are similar to those of the linear Kalman filter. The Kalman gain can be calculated as follows:

[0142] K(k)=P(k|k-1)C T (CP(k|k-1)C T +R) -1

[0143] The state estimate x(k|k) and covariance estimate P(k|k) at time k can then be calculated using the following equations:

[0144]

[0145] Here, l3 is the identity matrix of size 3.

[0146] Once the state estimate is determined , the wind speed in the rotor plane can be calculated by doing the following:

[0147] The present invention also relates to a method for controlling at least one wind turbine. The following steps may be performed for this method:

[0148] - determining the wind speed in the rotor plane of the wind turbine by means of a method for determining the wind speed according to any one of the above variants or combinations of variants, and

[0149] - Controlling the wind turbine according to the wind speed in the rotor plane of the wind turbine.

[0150] Precise and real-time prediction of the wind speed in the rotor plane of a wind turbine enables appropriate wind turbine control with minimal impact on the turbine structure and maximum power recovery. In practice, such control enables the turbine equipment to be adjusted so that it is in the optimal configuration for that wind.

[0151] According to embodiments of the present invention, the pitch angle of the blades and / or the electrical recovery torque of the wind turbine generator and / or the orientation of the nacelle can be controlled based on wind speed and direction. Preferably, the pitch angle of each blade can be controlled individually. Other types of adjustment devices can also be used. Controlling the pitch of the blades can optimize energy recovery based on the incident wind on the blades.

[0152] According to one embodiment of the present invention, the blade pitch angle and / or the electrical recovery torque can be determined by using a diagram of the wind speed at the rotor of the wind turbine. For example, the control method described in patent application FR-2,976,630A1 (US 2012-0,321,463) can be applied.

[0153] The present invention further relates to a method for monitoring at least one wind turbine and / or diagnosing at least one wind turbine. The following steps may be performed for this method:

[0154] - determining the wind speed in the rotor plane of the wind turbine by means of a method for determining the wind speed according to any one of the above variants or combinations of variants, and

[0155] - Monitoring and / or diagnosing the operation of a wind turbine as a function of the wind speed in the rotor plane.

[0156] The monitoring and / or diagnosis may for example correspond to the mechanical strains experienced by the structure of the wind turbine as a function of the wind speed in the rotor plane of the wind turbine.

[0157] Furthermore, the present invention relates to a computer program product comprising code instructions designed to perform the steps of one of the above-described methods (method for determining wind speed, control method, diagnostic method). The program is executed on a wind turbine control and / or diagnostic unit.

[0158] The present invention also relates to a wind turbine, in particular an offshore wind turbine or an onshore wind turbine. The wind turbine is equipped with a device for measuring the rotational speed of the rotor, a device for measuring the pitch angle of the blades, and a device for measuring the power generated by the converter. In addition, the wind turbine comprises a device capable of determining the wind speed in the rotor plane according to any of the above-mentioned variants or combinations of variants. According to one embodiment, the wind turbine can be similar to Figure 1 The wind turbine shown in .

[0159] According to one embodiment of the present invention, the wind turbine may include a real-time control and data acquisition (SCADA) system comprising at least one of a device for measuring rotor rotation, a device for measuring blade pitch angle, and a device for measuring power generated by the converter. Preferably, the SCADA system includes all of these measurement devices. Furthermore, the SCADA system may include other measurement devices (e.g., temperature, electrical data, etc.) to more accurately determine the wind speed in the rotor plane.

[0160] Alternatively, the wind turbine may comprise at least one sensor for performing at least one of these measurements, such as:

[0161] - a rotor angle rotation sensor for measuring the rotational speed of the rotor, and / or

[0162] - a blade angle sensor to measure the pitch angle of the blade, and / or

[0163] - a known and controlled voltage sensor for measuring the power generated by the converter, and an intensity sensor for measuring the current delivered by the generator.

[0164] For an embodiment of the control method, the wind turbine may include a control device, for example for controlling the tilt angle (or pitch angle) of at least one blade of the wind turbine or for controlling the electric torque, for implementing the control method according to the present invention.

[0165] It is clear that the present invention is not limited to the embodiments of the methods given above as examples, but it includes any variant embodiments.

[0166] Example

[0167] The characteristics and advantages of the method according to the invention will become more apparent from the following examples of application scenarios.

[0168] This example involves determining the wind speed REWS (Rotor Equivalent Wind Speed) in the rotor plane of a wind turbine, which corresponds to the operational and production status of the wind turbine at a given moment. The wind turbine is equipped with a SCADA system that measures the rotation of the rotor, the power generated by the converter, and the pitch angle of each blade.

[0169] Figure 4 shows the power P generated by the converter (in this example, the motor) as a function of time T (seconds). g (W) measured value.

[0170] Figure 5 Measured values ​​of the rotational speed ω (radians / second) of the rotor are shown as a function of time T (seconds).

[0171] Figure 6 The measured values ​​of the pitch angle β of the blades expressed in degrees are shown as a function of time T (seconds).

[0172] Applying a method according to an embodiment of the invention enables the determination of the wind speed REWS in the rotor plane. This speed determined by the invention is compared with the wind speed REWS in the rotor plane obtained by a four-beam LiDAR sensor positioned on the nacelle of the wind turbine.

[0173] Figure 7 Two wind speed curves REWS obtained by two methods are shown as a function of time T (seconds), where the present invention is denoted by INV and the LiDAR sensor curve is denoted by LID. Note that the two curves are nearly overlapping, demonstrating that the present invention can accurately determine the wind speed in the rotor plane of a wind turbine, despite not using expensive sensors.

Claims

1. A method for determining the wind speed in the rotor plane (PR) of a wind turbine (1), characterized in that Perform the following steps: a) measuring (MES) the rotational speed of the rotor of the wind turbine, the pitch angle of the blades of the wind turbine and the power generated by the converter of the wind turbine, b) constructing a dynamic model (MEO) of the wind turbine, the dynamic model of the wind turbine relating the rotational speed of the rotor of the wind turbine to the wind speed in the rotor plane, the pitch angles of the blades of the wind turbine and the power produced by the converter of the wind turbine, c) constructing a dynamic wind model (MVE) using a second-order random walk model, and d) determining the wind speed in the plane (PR) of the rotor by means of an unscented Kalman filter, the unscented Kalman filter being applied to the dynamic model of the wind turbine (MEO), the dynamic wind model (MVE) and the rotational speed of the rotor, the pitch angles of the blades of the wind turbine and the measurement of the power produced by the converter of the wind turbine (MES).

2. The method for determining wind speed according to claim 1, wherein: The dynamic wind model (MVE) is written as: where v1(t) is the wind speed in the rotor plane, v2(t) is the wind speed derivative in the rotor plane, η(t) is white noise with zero mean, and v(t)=v1(t).

3. The method for determining wind speed according to claim 1, wherein: The dynamic model (MEO) of the wind turbine is written as: Where, ω(t) is the rotational speed of the rotor, J is the moment of inertia of the kinematic chain of the wind turbine, ρ is the air density, R is the radius of the rotor, C q is the power coefficient, β(t) is the pitch angle of the blade, λ(t) is the ratio of blade tip speed to the wind speed in the rotor plane, P g (t) is the power generated by the converter of the wind turbine, v(t) is the wind speed in the rotor plane, and T l (t) is the loss torque along the kinematic chain of the wind turbine.

4. The method for determining wind speed according to claim 3, wherein: The loss torque T l (t) can be considered as noise.

5. The method according to claim 3 or 4, wherein: The power coefficient C q Obtained from the diagram of the wind turbine.

6. The method for determining wind speed according to claim 1, wherein: The method determines the longitudinal component of the average wind speed in the rotor plane.

7. The method for determining wind speed according to claim 1, wherein: The unscented Kalman filter is applied to the following state equation: Among them, x1(t)=ω(t), x2(t)=v(t), ω(t) is the rotational speed of the rotor, J is the moment of inertia of the kinematic chain of the wind turbine, ρ is the air density, R is the radius of the rotor, C q is the power coefficient, β(t) is the pitch angle of the blade, P g (t) is the power generated by the converter of the wind turbine, v(t) is the wind speed in the rotor plane, μ1(t) and μ2(t) are independent white noises with zero mean, and y(t) is the measured output identified at the rotor speed ω(t) corrupted by the white noise ξ(t).

8. The method for determining wind speed according to claim 1, wherein: Determine the wind speed by performing the following steps: i) Initialize k = 0, the state vector and the state of the covariance matrix P(0|0)=P0, ii) at any time k different from 0, obtain a measurement y(k), and iii) At any time k different from 0, determine the wind speed v(k) in the rotor plane by the following equation: K(k)=P(k|k-1)C T (CP(k|k-1)C T +R) -1 Where K is the Kalman filter gain, P is the covariance of the Gaussian noise μ, P(k|k-1) is the error variance of the measurement from the time k-1, P(k|k) is the error variance of the measurement from the time k, x(k|k) is an estimate of x(k) from the measurement at time k, x(k|k-1) is an estimate of x(k) from the measurement at time k-1, R is the covariance of the Gaussian noise ξ, C = [1 0 0], and 13 is the identity matrix of size 3.

9. A method for controlling a wind turbine (1), characterized in that Perform the following steps: a) determining the wind speed in the rotor plane (PR) of a wind turbine (1) by means of a method according to any one of the preceding claims, and b) controlling the wind turbine (1) according to the wind speed in the rotor plane of the wind turbine (1).

10. A computer program product, characterized in that The computer program product comprises code instructions designed to perform the steps of the method according to any one of the preceding claims when the program is executed on a control and / or diagnostic unit of a wind turbine (1).

11. A wind turbine (1), characterized in that: The wind turbine comprises a device for measuring the rotational speed of the rotor, a device for measuring the pitch angle of the wind turbine blades, a device for measuring the power generated by the converter of the wind turbine, and a device for determining the wind speed in the rotor plane of the wind turbine, capable of implementing the method according to any one of claims 1 to 8.

12. The wind turbine according to claim 11, wherein: A real-time control and data acquisition system is included, comprising the device for measuring the rotational speed of the rotor, the device for measuring the pitch angle of the wind turbine blades and the device for measuring the power generated by the converter of the wind turbine.

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