Wind generating set transmission control method based on predictive control

Abstract

The invention relates to a wind generating set transmission control method, in particular to a wind generating set transmission control method based on predictive control, which can effectively reduce the torque fluctuation by predicting the future system state and adjusting the generator control pitch to enable the generator control pitch to better follow the change of the rotating speed of a wind wheel. The method comprises the following steps: calculating the maximum value of the wind energy utilization efficiency by using the Betz's law; applying a motion equation and considering a multi-degree-of-freedom coupling effect, and introducing a multi-modal coupling motion equation and a state vector to deduce a state equation; and performing optimization control on the system according to reality by predicting a control matrix and a performance index, continuously updating the state quantity at the next sampling moment, repeating the process and performing rolling optimization, and finally realizing control on the system. According to the method, predictive control can be carried out on torque fluctuation generated by frequent wind speed adaptation of the wind driven generator under the complex working condition, fluctuation is reduced, and the service life can be prolonged while steady-state operation of the wind driven generator is achieved.

Description

Technical Field

[0001] The invention relates to a wind power generation control method, and in particular to a wind power generator transmission control method based on predictive control. Background Art

[0002] With the continuous development of economy and the rapid growth of population, the global fossil energy storage is decreasing, so finding new energy alternatives is an indispensable part. Among them, wind energy has the characteristics of wide distribution, scale, renewable and clean, and is a renewable energy with extremely high cost performance. Therefore, vigorous development is considered to be an important way to solve today's energy problems. During the operation of the transmission system of the wind turbine, the frequent changes in wind force cause large torque fluctuations in the system, which causes large stress loads on the key components of the transmission system and greatly reduces the life of the components. The existing technology usually adopts proportional-integral (PI) control, but it is difficult to maintain the stability of the system when the wind speed changes rapidly. Therefore, a new control method is proposed, which adopts multi-input and multi-output model predictive control, which can effectively reduce torque fluctuations and extend the service life of the transmission system.

[0003] The predictive control method for the wind turbine transmission system refers to a method to prevent the wind turbine from frequently controlling the blade torque to adapt to wind changes, causing rapid attenuation of component life. It includes model predictive control, electronic control and automatic adjustment, etc., to ensure stable and normal operation of the wind turbine.

[0004] Wind turbines are large in size, and the amount of work required for both installation and maintenance is enormous. If component damage occurs frequently during operation, it will lead to high operating costs and be detrimental to future development. In particular, the variable pitch system, once a failure occurs, will be unable to perform the variable pitch action, which may lead to serious accidents such as runaway, thereby damaging the equipment and even endangering personnel safety. Summary of the invention

[0005] The purpose of the present invention is to provide a wind turbine transmission control method based on predictive control. The present invention maximizes the utilization rate of wind energy, determines the state equation, establishes a model according to the mechanism of the wind turbine, completes multi-input and multi-output model predictive control, achieves a reduction in the blade movement amplitude while stabilizing torque fluctuations, and extends service life.

[0006] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0007] A wind turbine generator transmission control method based on predictive control, the method comprising the following steps:

[0008] Step 1: Be familiar with the wind turbine blade torque control system and understand the relationship between process variables and quality variables.

[0009] Step 2: Use the kinetic energy formula to calculate the actual kinetic energy based on the mass of the wind passing through the blade with an area of ​​s and the speed difference after passing through, and then compare it with the maximum kinetic energy of the theoretical maximum efficiency to obtain the maximum value of wind energy utilization.

[0010] Step 3: Based on the motion equation in the case of no coupled modes and taking into account the vibration of the blades, it is necessary to introduce a multi-modal coupled motion equation to more accurately describe the vibration behavior of the blades, and then introduce the state vector x to finally derive the state equation.

[0011] Step 4: Determine the prediction model, implement optimization and feedback correction, optimize the system according to the actual situation through the prediction control matrix and performance indicators, continuously update the state quantity at the next sampling moment, repeat the process and perform rolling optimization, and finally achieve control of the system.

[0012] Step 5: Perform simulation verification through Simulink to prove the stability and effectiveness of this method under changing wind speed.

[0013] The wind turbine transmission control method based on predictive control, the familiarity with the wind turbine blade torque control system, includes being familiar with the wind turbine operation process, collecting blade information and control information.

[0014] In the wind turbine transmission control method based on predictive control, the area information s is the actual area of ​​the blade, the wind speed difference is obtained by actual measurement, and the maximum utilization rate of wind energy is obtained by actual calculation.

[0015] The wind turbine transmission control method based on predictive control obtains the state equation by actually quoting multi-modal coupled motion equations to describe the vibration behavior of the blades.

[0016] The wind turbine transmission control method based on predictive control, the prediction model is determined to achieve rolling optimization and feedback correction as follows:

[0017] (1) Determine the prediction model as a multi-input multi-output model.

[0018] (2) The control input sequence for a period of time in the future is determined by solving the optimization problem at the sampling time t, so that a certain performance indicator (such as tracking error, control energy, etc.) is minimized in the prediction time domain.

[0019] (3) Apply the optimal control input u(t) at the current moment, then scroll through the time domain, reacquire the system at the next sampling moment t+1 and repeat the process.

[0020] The wind turbine generator transmission control method based on predictive control is verified by simulation using Simulink to prove the stability and effectiveness of the method.

[0021] (1) The NREL5MW wind turbine system is linearized at a wind speed of 13m / s. At this working point, the pitch angle requirement is 0.0551229 and the motor torque requirement is 13403.

[0022] (2) Using Bladed to model the aerodynamics of the fan system, the approximate state space model is:

[0023] (3) Based on the frequent changes in wind speed, simulink was used to perform a 600s simulation to obtain the response waveform of the generator speed and torque changes and draw the final conclusion.

[0024] The advantages of the present invention are:

[0025] The present invention uses a model predictive control strategy designed by a wind turbine to extend the service life of its transmission mechanism, and establishes a multi-input multi-output simulation model based on its mechanism. The model predictive control is used to solve the complex coupling problem of its multi-input multi-output, and simulink is used for simulation. The simulation results verify the good performance of the multi-input multi-output system of the wind turbine using predictive control, which can reduce the torque and the action amplitude of the actuator under the premise of stable operation of the generator, so that the controller can not only quickly stabilize the system, so that it can reach steady-state operation under different working conditions, but also extend the service life. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a predictive control structure diagram of the present invention;

[0027] Figure 2 This is a diagram of a wind turbine control system according to the present invention;

[0028] Figure 3 This is a wind speed variation diagram of the present invention;

[0029] Figure 4 This is a diagram showing the rotor changes of the present invention;

[0030] Figure 5 It is the torque variation diagram of the present invention;

[0031] Figure 6 This is the generator speed diagram of the present invention. DETAILED DESCRIPTION

[0032] The technical method of the present invention is further described in detail below in conjunction with the accompanying drawings. In this embodiment, simulink is used for simulation.

[0033] The present invention provides a wind turbine generator transmission control method based on predictive control, which specifically includes the following steps:

[0034] Step 1: Be familiar with the wind turbine blade torque control system and understand the relationship between process variables and quality variables.

[0035] It should be further explained that in this step, the blade area must be measured, wind speed information must be collected, and the effect of transmission control relationship and torque on component life must be clearly understood.

[0036] Step 2: Use the kinetic energy formula to calculate the actual kinetic energy based on the mass of the wind passing through the blade with an area of ​​s and the speed difference v after passing through, and then compare it with the maximum kinetic energy of the theoretical maximum efficiency to obtain the maximum value of the wind energy utilization rate.

[0037] It should be further explained that the kinetic energy calculation formula is:

[0038]

[0039] The formula for calculating the mass of wind is:

[0040]

[0041] The theoretical maximum efficiency of wind energy is:

[0042]

[0043] The actual efficiency compared with the maximum efficiency is:

[0044]

[0045] In formula 2, ρ is the air density

[0046] Step 3: Based on the motion equation in the case of no coupled modes and taking into account the vibration of the blades, it is necessary to introduce a multi-modal coupled motion equation to more accurately describe the vibration behavior of the blades, and then introduce the state vector x to finally derive the state equation.

[0047] It should be further explained that the uncoupled modal motion equation can be written as:

[0048]

[0049] The multi-modal motion equation after considering blade vibration is as follows:

[0050]

[0051] Introduce the state vector x:

[0052]

[0053] Derived state equation:

[0054]

[0055] In Formula 5, q is the modal displacement, M is the modal mass, and F is the modal force. In Formula 6, M represents the modal mass.

[0056] C represents damping, K represents the stiffness matrix, q represents the modal displacement vector, and F represents the modal force vector. In formula 7, q represents the first-order derivative of the modal displacement vector.

[0057] Step 4: Determine the prediction model, implement optimization and feedback correction, optimize the system according to the actual situation through the prediction control matrix and performance indicators, continuously update the state quantity at the next sampling moment, repeat the process and perform rolling optimization, and finally achieve control of the system.

[0058] It should be further explained that the prediction model is determined to achieve rolling optimization and feedback correction as follows:

[0059] (1) Determine that the prediction model is a multi-input multi-output model. The augmented matrix of the state equation is:

[0060]

[0061] X is converted to:

[0062]

[0063] (2) By solving the optimization problem at sampling time t, the control input sequence for a period of time in the future is determined so that a certain performance indicator (such as tracking error, control energy, etc.) is minimized in the prediction time domain. The minimum value solution formula is as follows:

[0064]

[0065] In formula 11, N is the length of the prediction time domain, y(t+k|t) is the prediction of time t+k in the future, and y ref (t+k) is the reference trajectory, Q and R are weight matrices.

[0066] (3) Apply the optimal control input u(t) at the current moment, then scroll the time domain, reacquire the system at the next sampling moment t+1 and repeat this process. The feedback correction structure diagram is shown in the attached manual. Figure 1 The wind turbine generator prediction control flow chart is shown in the attached manual. Figure 2 shown.

[0067] Step 5: Perform simulation verification through Simulink to prove the stability and effectiveness of this method under changing wind speed.

[0068] Embodiment 1

[0069] The NREL5MW wind turbine system with a wind speed of 13m / s is used for linearization. At this working point, the pitch angle requirement is 0.0551229, and the motor torque requirement is 13403. Bladed is used to model the aerodynamics of the wind turbine system, and the approximate state space model is obtained as follows:

[0070]

[0071] A is a 25*25 matrix, B is a 25*3 matrix, C is a 7*25 matrix, and D is a 7*3 matrix. Solving the characteristic roots, we can get a 25*1 matrix, which corresponds to the flapping plane of the impeller, the swing plane, the yaw distance of the cabin, the front and rear left and right modal displacements of the tower, the rotor speed increment, and the generator speed increment. It can be found that all its characteristic roots have negative real parts, so it is basically stable, but the speed regulation ability is relatively poor, the cabin yaw response is sensitive, and the frequency of some modal oscillations is high. Therefore, this aspect of the design is considered when designing the controller to establish predictive control.

[0072] Based on the frequent changes in wind speed, simulink was used to perform a 600s simulation, where the wind speed changes are shown in the attached manual. Figure 3 As shown in the figure, the hub wind speed is constantly changing from 13m / s to 25m / s, but the changes in horizontal wind shear and vertical wind shear are ignored and regarded as a constant. The simulation data from 50s to 400s are compared, and the comparison data is the speed of the generator. From the results, it is equivalent to the original PID control. Predictive control can improve the stability of the system, make the system have good robustness, and maintain its generator speed at a relatively stable level, thereby stabilizing its power generation and improving power generation efficiency.

[0073] Instructions attached Figures 4 to 6 The following is a response waveform of the rotor speed, generator speed and torque of the wind turbine under the drastic change of wind speed. We can find that under the adjustment of the predictive controller, the generator speed and rotor speed have a clear stable trend, and there will not be too large errors under the frequent changes of external wind speed. The generator speed and rotor speed directly affect the torque of the actuator. Figure 5 It can be seen that the torque of the generator is relatively more stable, the action amplitude of the actuator is smaller, the service life can be extended, and the expected effect can be achieved.

[0074] The above is only a specific embodiment of the present application, so that those skilled in the art can understand or implement the present application. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the application will not be limited to these embodiments shown in this article, and specific related details.

Claims

1. A wind turbine transmission control method based on predictive control, characterized in that: The method comprises the following steps: Step 1: Be familiar with the wind turbine blade torque control system and understand the relationship between process variables and quality variables; Step 2: Use the kinetic energy formula to calculate the actual kinetic energy based on the mass of the wind passing through the blade with an area of ​​s and the speed difference after passing through, and then compare it with the maximum kinetic energy of the theoretical maximum efficiency to obtain the maximum value of wind energy utilization; Step 3: Based on the motion equation without coupled modes and considering the vibration of the blades, it is necessary to introduce the multi-mode coupled motion equation to more accurately describe the vibration behavior of the blades, and then introduce the state vector x to finally derive the state equation; Step 4: Determine the prediction model, implement optimization and feedback correction, optimize the system according to the actual situation through the prediction control matrix and performance indicators, continuously update the state quantity at the next sampling moment, repeat the process and perform rolling optimization, and finally achieve control of the system; Step 5: Perform simulation verification through Simulink to prove the stability and effectiveness of this method under changing wind speed.

2. A wind turbine generator transmission control method based on predictive control according to claim 1, characterized in that: In step one, you will be familiar with the wind turbine blade torque control system, including being familiar with the wind turbine operation process, collecting blade information and control information.

3. The wind turbine generator transmission control method based on predictive control according to claim 1, characterized in that: The area information s in step 2 is the actual area of ​​the blade, and the maximum utilization rate of wind energy is obtained by actual calculation.

4. A wind turbine generator transmission control method based on predictive control according to claim 3, characterized in that: The actual area of ​​the blade and its state equation are actually based on the multi-modal coupled motion equation to describe the vibration behavior of the blade.

5. The wind turbine generator transmission control method based on predictive control according to claim 1, characterized in that: Determine the prediction model as described in step 4 to achieve rolling optimization and feedback correction: (1) Determine that the prediction model is a multi-input multi-output model; (2) Determine the control input sequence for a period of time in the future by solving the optimization problem at sampling time t, so as to minimize a certain performance indicator (such as tracking error, control energy, etc.) in the prediction time domain; (3) Apply the optimal control input u(t) at the current moment, then scroll through the time domain, reacquire the system at the next sampling moment t+1 and repeat the process.

6. A wind turbine generator transmission control method based on predictive control according to claim 1, characterized in that: The verification described in step 5 uses Simulink for simulation verification to prove the stability and effectiveness of the method; (1) Linearize the NREL5MW wind turbine system at a wind speed of 13m / s. At this operating point, the pitch angle requirement is 0.0551229 and the motor torque requirement is 13403; (2) Using Bladed to model the aerodynamics of the fan system, the approximate state space model is obtained; (3) Based on the frequent changes in wind speed, simulink was used to perform a 600s simulation to obtain the response waveform of the generator speed and torque changes and draw the final conclusion.

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