Simulation method, device and equipment of wind driven generator and storage medium

Abstract

The invention discloses a simulation method and device of a wind driven generator, equipment and a storage medium. When the method provided by the embodiment of the invention is executed, firstly, a mathematical model of a target wind driven generator is established, and dynamic characteristics, including a transfer function and a control object transfer function, of a current loop controller and a speed loop controller in the mathematical model are defined; and then target closed-loop characteristics are determined, target parameters of a current loop controller and a speed loop controller are calculated according to the target closed-loop characteristics and dynamic characteristics of the controllers in combination with an H-infinity control method, and a transfer function of the controllers is adjusted based on the target parameters. And finally, performing simulation verification on the mathematical model of the wind driven generator by using the adjusted controller to verify the effect of the wind driven generator. By establishing the mathematical model and the H-infinity control method, the target parameters of the current loop controller and the speed loop controller can be rapidly calculated and adjusted, the robustness and the adaptive capacity of the controller are improved, and therefore the problems of uncertainty and external disturbance of a wind power generation system in practical application are effectively solved.

Description

Technical Field

[0001] The present application relates to the technical field of wind power generation simulation, and in particular to a simulation method, device, equipment and storage medium for a wind turbine. Background Art

[0002] With the rapid advancement of renewable energy technology, wind power generation has been increasingly widely used as a clean and sustainable form of energy. Variable speed operation has become a common operating mode in wind turbines of wind power generation systems. This variable speed operation can not only achieve higher energy conversion efficiency below rated power, but also effectively reduce the load of the transmission chain, thereby extending the service life of the equipment. In order to improve the conversion efficiency of wind turbines in wind power generation systems during variable speed operation, ensure the quality of power, and extend the overall service life of wind power generation systems, it is particularly important to develop and implement high-performance wind turbine controllers. These controllers play a key role in the variable speed operation of wind power generation systems, which directly affects the efficient and stable operation of wind power generation systems.

[0003] At present, the traditional proportional-integral-derivative (PID) control is often used to adjust the parameters of the wind turbine controller of the wind power generation system. However, the parameter adjustment of this method often needs to rely on trial and error, which is not only time-consuming and labor-intensive, but also requires a lot of experimental investment. In addition, the traditional PID control method often does not fully consider the uncertainties and external disturbances that may occur during the operation of the wind power generation system. This neglect leads to the lack of robustness and poor adaptability of the wind power generation system controller in practical applications.

[0004] Therefore, how to provide a wind turbine controller control strategy with faster parameter adjustment speed, higher robustness and stronger adaptability to cope with the uncertainty and external disturbances in practical applications of wind turbine controllers is a technical problem that technical personnel in this field urgently need to solve. Summary of the invention

[0005] Based on the above problems, the present application provides a simulation method, device, equipment and storage medium for a wind turbine, which can provide a wind turbine controller control strategy with faster parameter adjustment speed, higher robustness and stronger adaptability to cope with the uncertainty and external disturbances of the wind turbine controller in actual applications.

[0006] The embodiments of the present application disclose the following technical solutions:

[0007] A simulation method for a wind turbine generator, the method comprising:

[0008] Establish a mathematical model of the target wind turbine;

[0009] Define the dynamic characteristics of the current loop controller of the mathematical model and the dynamic characteristics of the speed loop controller of the mathematical model; the dynamic characteristics of the current loop controller include the current loop controller transfer function and the current loop controller controlled object transfer function; the dynamic characteristics of the speed loop controller include the speed loop controller transfer function of the mathematical model and the speed loop controller controlled object transfer function;

[0010] Determine target closed-loop characteristics;

[0011] Based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller, in combination with the H∞ control method, target parameters of the current loop controller transfer function and the speed loop controller transfer function are calculated respectively;

[0012] The transfer functions of the current loop controller and the speed loop controller are adjusted based on the target parameter, and the mathematical model of the target wind turbine generator is simulated based on the adjusted transfer functions of the current loop controller and the speed loop controller.

[0013] In a possible implementation, based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller, and the dynamic characteristics of the speed loop controller, in combination with the H∞ control method, the target parameters of the current loop controller transfer function and the speed loop controller transfer function are calculated respectively, including:

[0014] Setting preliminary parameters of the current loop controller and preliminary parameters of the speed loop controller;

[0015] Determine the target parameters of the current loop controller by using the H∞ control method in combination with the target closed-loop characteristics, the current loop controller transfer function, the preliminary parameters of the current loop controller, the parameter calculation formula, the restriction condition and the convergence condition;

[0016] The target parameters of the current loop controller are determined by utilizing the H∞ control method in combination with the target closed-loop characteristics, the speed loop controller transfer function, the preliminary parameters of the speed loop controller, the parameter calculation formula, the restriction conditions and the convergence conditions.

[0017] In a possible implementation, the H∞ control method is used to determine the target parameters of the current loop controller in combination with the target closed-loop characteristics, the current loop controller transfer function, preliminary parameters of the current loop controller, parameter calculation formulas, restriction conditions, and convergence conditions, including:

[0018] In the target angular frequency range of the current loop controller, an instantiated transfer function of the current loop controller is calculated based on preliminary parameters of the current loop controller; the instantiated transfer function is the transfer function of the current loop controller into which the preliminary parameters are substituted;

[0019] Calculating intermediate parameters of the current loop controller based on the constraint condition, the instantiated transfer function and a preset upper limit value;

[0020] Based on the intermediate parameters and the parameter calculation formula, the intermediate closed-loop characteristic is calculated; the intermediate closed-loop characteristic is the product of the intermediate transfer function and the control object transfer function of the current loop controller; the intermediate transfer function is the current loop controller transfer function into which the intermediate parameters are substituted; the parameter calculation formula is L=G·K, L is the intermediate closed-loop characteristic, G is the control object transfer function of the current loop controller or the control object transfer function of the speed loop controller, and K is the intermediate transfer function of the current loop controller or the intermediate transfer function of the speed loop controller;

[0021] Subtracting the intermediate closed-loop characteristic from the target closed-loop characteristic, and taking the modulus of the difference as a calculated difference;

[0022] Setting the intermediate transfer function as a new instantiated transfer function;

[0023] In combination with the H∞ control method, a new instantiated transfer function is used to replace the original instantiated transfer function, so as to repeat the above steps of intermediate parameter calculation, intermediate closed-loop characteristic calculation, calculation difference calculation and intermediate parameter substitution, and record the calculation difference obtained by each calculation;

[0024] Drawing a difference curve based on all the calculated differences of the current loop controller; the calculated differences of the current loop controller have a one-to-one correspondence with the intermediate parameters of the current loop controller;

[0025] If the difference curve satisfies the convergence condition, the intermediate parameter with the smallest corresponding calculated difference is used as the target parameter; the convergence condition includes that the difference curve converges to the preset upper limit value.

[0026] In a possible implementation, the restriction condition includes: a first restriction condition and a second restriction condition;

[0027] The first restriction condition is:

[0028] The second restriction condition is: (X+G·Y) * ·(Y c +G·X c )+(Y c+G·X c ) * (X+G·Y)>0;

[0029] Wherein, Y is the denominator of the current loop controller transfer function, or the denominator of the speed loop controller transfer function; Y * is the conjugate complex number of Y; c is the denominator of the instantiated transfer function; Y c * Y c The conjugate complex number of; G is the control object transfer function of the current loop controller or the control object transfer function of the speed loop controller; X is the numerator of the current loop controller transfer function or the numerator of the speed loop controller transfer function; Y and X are both in matrix form; L d is the target closed-loop characteristic; γ is the preset upper limit value; I is the unit matrix; X c is the numerator of the instantiated transfer function; (G·XL d ·Y) * (G XL d The conjugate complex number of (X+G·Y); * is the conjugate complex number of (X+G·Y); (Y c +G·X c ) * Y c +G·Xc) conjugate complex number; X=a2·S 2 +a1·S+a0; a2 is the coefficient of the preliminary numerator quadratic term; a1 is the coefficient of the preliminary numerator linear term; a0 is the coefficient of the preliminary numerator zero-order term; Y=b2·S2+b1·S+b0; b2 is the coefficient of the preliminary denominator quadratic term; b1 is the coefficient of the preliminary denominator linear term; b0 is the coefficient of the preliminary denominator zero-order term; S is the complex frequency variable in the Laplace transform, S=j*ω, j is the imaginary unit, ω is the target angular frequency.

[0030] In a possible implementation, the method further includes:

[0031] If the difference curve does not meet the convergence condition, the latest instantiated transfer function is used to replace the original instantiated transfer function, so as to repeat the above steps of intermediate parameter calculation, intermediate closed-loop characteristic calculation, calculated difference calculation and intermediate parameter substitution, so as to obtain a new calculated difference of the current loop controller;

[0032] adjusting the difference curve based on the new calculated difference to obtain a new difference curve;

[0033] If the new difference curve still does not meet the convergence condition, the above steps of calculating a new difference and adjusting the difference curve are repeated based on the new difference curve until the latest difference curve meets the convergence condition.

[0034] A simulation device for a wind turbine generator, the device comprising:

[0035] A mathematical model building unit, used for building a mathematical model of a target wind turbine;

[0036] A definition unit, used to define the dynamic characteristics of the current loop controller of the mathematical model and the dynamic characteristics of the speed loop controller of the mathematical model; the dynamic characteristics of the current loop controller include the current loop controller transfer function and the current loop controller controlled object transfer function; the dynamic characteristics of the speed loop controller include the speed loop controller transfer function of the mathematical model and the speed loop controller controlled object transfer function;

[0037] A first determining unit, used to determine a target closed-loop characteristic;

[0038] A first calculation unit is used to calculate target parameters of the current loop controller transfer function and the speed loop controller transfer function respectively based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller in combination with the H∞ control method; the target parameters include a target numerator coefficient and a target denominator coefficient; the target numerator coefficient includes a target numerator quadratic term coefficient, a target numerator linear term coefficient and a target numerator zero-order term coefficient; the target denominator coefficient includes a target denominator quadratic term coefficient, a target denominator linear term coefficient and a target denominator zero-order term coefficient;

[0039] A transfer function adjustment unit, used for adjusting the transfer functions of the current loop controller and the speed loop controller based on the target parameter;

[0040] A simulation unit is used to simulate the mathematical model of the target wind turbine based on the adjusted transfer functions of the current loop controller and the speed loop controller.

[0041] In a possible implementation manner, the first computing unit specifically includes:

[0042] A first setting unit, used to set preliminary parameters of the current loop controller and preliminary parameters of the speed loop controller;

[0043] A second determination unit is used to determine the target parameters of the current loop controller by using the H∞ control method in combination with the target closed-loop characteristic, the current loop controller transfer function, the preliminary parameters of the current loop controller, the parameter calculation formula, the restriction condition and the convergence condition;

[0044] The third determination unit is used to determine the target parameters of the current loop controller by using the H∞ control method in combination with the target closed-loop characteristics, the speed loop controller transfer function, the preliminary parameters of the speed loop controller, the parameter calculation formula, the restriction conditions and the convergence conditions.

[0045] In a possible implementation manner, the second determining unit specifically includes:

[0046] a second calculation unit, configured to calculate an instantiation transfer function of the current loop controller based on preliminary parameters of the current loop controller within a target angular frequency range of the current loop controller; the instantiation transfer function is a transfer function of the current loop controller into which the preliminary parameters are substituted;

[0047] A third calculation unit, configured to calculate an intermediate parameter of the current loop controller based on the constraint condition, the instantiated transfer function and a preset upper limit value;

[0048] A fourth calculation unit is used to calculate an intermediate closed-loop characteristic based on the intermediate parameter and the parameter calculation formula; the intermediate closed-loop characteristic is the product of the intermediate transfer function and the transfer function of the object controlled by the current loop controller; the intermediate transfer function is the transfer function of the current loop controller into which the intermediate parameter is substituted; the parameter calculation formula is L=G·K, L is the intermediate closed-loop characteristic, G is the transfer function of the object controlled by the current loop controller or the transfer function of the object controlled by the speed loop controller, and K is the intermediate transfer function of the current loop controller or the intermediate transfer function of the speed loop controller;

[0049] a fifth calculation unit, configured to perform a subtraction between the intermediate closed-loop characteristic and the target closed-loop characteristic, and take a modulus value of the difference as a calculated difference;

[0050] The second setting unit is configured to set the intermediate transfer function as a new instantiated transfer function.

[0051] A synthesis unit, used to combine the H∞ control method, use a new instantiated transfer function to replace the original instantiated transfer function, repeat the above steps of intermediate parameter calculation, intermediate closed-loop characteristic calculation, calculation difference calculation and intermediate parameter substitution, and record the calculation difference obtained by each calculation;

[0052] A difference curve drawing unit, used for drawing a difference curve based on all the calculated differences of the current loop controller; the calculated differences of the current loop controller have a one-to-one correspondence with the intermediate parameters of the current loop controller;

[0053] A screening unit is used to use the intermediate parameter with the smallest corresponding calculated difference as the target parameter if the difference curve satisfies the convergence condition; the convergence condition includes that the difference curve converges to the preset upper limit value.

[0054] A wind turbine simulation device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the wind turbine simulation method as described above is implemented.

[0055] A computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes the above-mentioned wind turbine simulation method.

[0056] Compared with the prior art, this application has the following beneficial effects:

[0057] The present application provides a simulation method, device, equipment and storage medium for a wind turbine. Specifically, when executing the simulation method for a wind turbine provided in an embodiment of the present application, first, a mathematical model of a target wind turbine is established to accurately reflect the dynamic behavior of the generator and its components. Next, the dynamic characteristics of the current loop controller and the speed loop controller are defined respectively, which includes determining their respective transfer functions and the transfer functions of their controlled objects, providing an accurate theoretical basis for subsequent system control. Next, the optimization target is clarified by setting the target closed-loop characteristics. Based on this target, combined with the H∞ control method, the target parameters of the transfer functions of the current loop controller and the speed loop controller are calculated, and these parameters include the numerator coefficient and the denominator coefficient, as well as their quadratic term, linear term and zero-order term coefficients. Then, the existing controller transfer functions are adjusted using these target parameters so that they are consistent with the optimization target in the mathematical model. Finally, the adjusted controller is applied to the mathematical model of the target wind turbine for simulation, and the performance of the adjusted current loop and speed loop controllers is evaluated and verified to ensure stability and robustness under different operating conditions.

[0058] This application uses mathematical models and H∞ control theory to more accurately calculate the target parameters of the current loop and speed loop controllers, so that the performance of the control system can be predicted in the design stage, reducing the time and cost of experimental adjustments. At the same time, the H∞ control method can take into account the uncertainty and external disturbances during the operation of the wind turbine, making the wind turbine controller more robust and more adaptable, and maintaining stable performance even when environmental conditions change or the equipment ages.

[0059] In addition, by optimizing the control strategy, it helps to reduce the transmission chain load and thus extend the service life of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0061] Figure 1 A method flow chart of a simulation method of a wind turbine provided in an embodiment of the present application;

[0062] Figure 2 A method flow chart of a method for calculating a target parameter provided in an embodiment of the present application;

[0063] Figure 3 A method flow chart of a method for determining a target parameter provided in an embodiment of the present application;

[0064] Figure 4 A method flow chart of a difference curve optimization method provided in an embodiment of the present application;

[0065] Figure 5 A schematic structural diagram of a wind turbine simulation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0066] To facilitate understanding of the technical solutions provided by the embodiments of the present application, the background technology involved in the embodiments of the present application will be described below.

[0067] With the rapid development of renewable energy technology, wind power generation has received increasing attention as a clean and sustainable form of energy. Variable speed operation has become a common mode for wind turbines in wind power generation systems. This mode not only improves the energy conversion efficiency, but also reduces the burden on the transmission chain and extends the service life of the wind power generation system. In order to improve the efficiency and power quality of wind power generation systems during variable speed operation, it is crucial to develop high-performance wind power generation system controllers (i.e., wind turbine controllers). These controllers directly affect the efficient and stable operation of wind power generation systems. At present, traditional PID control methods are widely used in the parameter adjustment process of wind power generation system controllers, but their parameter adjustment often relies on trial and error, which is time-consuming and laborious. In addition, PID control fails to fully consider the uncertainty and external disturbances in operation, resulting in its lack of robustness and adaptability.

[0068] In order to solve this problem, a simulation method, device, equipment and storage medium of a wind turbine are provided in an embodiment of the present application. A mathematical model of a target wind turbine is first established, and then the dynamic characteristics of the current loop controller and the speed loop controller in the mathematical model are defined, including the transfer function and the control object transfer function. Then the target closed-loop characteristics are determined, and the target parameters of the transfer functions of the current loop controller and the speed loop controller are calculated respectively in combination with the H∞ control method, considering the target closed-loop characteristics and the dynamic characteristics of the current loop controller and the speed loop controller, including the target numerator coefficient and the target denominator coefficient, and then the controller transfer function is adjusted. Finally, the mathematical model of the target wind turbine is simulated using the adjusted controller. Compared with the traditional PID controller debugging method, the present application can accurately simulate the operating state of the wind turbine by establishing a mathematical model and defining the dynamic characteristics of the controller, reducing the dependence on physical experiments, thereby saving time and resources. At the same time, by applying the H∞ control method, the uncertainty of the current loop and speed loop controller of the wind turbine can be effectively handled, the robustness of the current loop and speed loop controller can be enhanced, and its adaptability to external disturbances can be improved.

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0070] See also Figure 1 , which is a flow chart of a simulation method for a wind turbine provided in an embodiment of the present application, such as Figure 1 As shown, the simulation method of the wind turbine generator may include steps S101-S105:

[0071] S101: Establish a mathematical model of a target wind turbine.

[0072] Establishing a mathematical model of the target wind turbine means using mathematical equations and physical laws to describe the operating mechanism and characteristics of the wind turbine. This includes considering the interaction between wind mechanical components, electrical components, and the overall system, and describing the dynamic behavior of the wind turbine by establishing a mathematical model, which helps to further design, optimize, and simulate the control strategy. Through mathematical models, we can better understand the working principle of the wind turbine, predict its performance, and provide a basis for system control and improvement. The target wind turbine refers to the wind turbine to be modeled.

[0073] In a possible implementation, the mathematical model of the target wind turbine generator includes a mechanical dynamics model and an electrical model. The mathematical model of the target wind turbine generator can describe the relationship between the speed, torque, current and voltage of the wind turbine generator.

[0074] Under a certain power, the motor speed and torque are inversely proportional. The higher the speed, the lower the torque; the lower the speed, the higher the torque.

[0075] The speed T of the wind turbine can be calculated by the following formula:

[0076] T = 9550*P / n, where T is the torque of the wind turbine (unit: Newton meter, N·m); P is the actual output power of the wind turbine (unit: kilowatt, kW); n is the speed of the wind turbine (unit: revolutions per minute, r / min); the power of the wind turbine P = η*P e , η is the efficiency of the wind turbine, P e is the electromagnetic power of the wind turbine.

[0077] Wind turbine electromagnetic power P e It can be calculated by the following formula:

[0078] P e =V*I*cosφ, where V is the voltage of the wind turbine (unit: volt, V), I is the current of the wind turbine (unit: ampere, A), and cosφ is the power factor of the wind turbine. For a DC wind turbine, the speed is proportional to the armature voltage and inversely proportional to the excitation voltage, and the torque is proportional to the excitation flux and the armature current.

[0079] In practical applications, the mathematical model of wind turbines also needs to consider the aerodynamic model. The mechanical power P captured by the wind turbine from natural wind energy m It can be calculated by the following formula:

[0080] P m =1 / 2*ρ*A*v 3 *C p , where ρ is the air density (unit: kilograms per cubic meter, kg / m 3 ), A is the swept area of ​​the wind turbine (unit: square meters, m 2 ), v is the wind speed (unit: meters per second, m / s), Cp is the wind energy utilization coefficient of the wind system where the wind turbine is located, which represents the ability of the wind turbine to capture power from wind energy.

[0081] It should be noted that establishing a preliminary mathematical model of a target wind turbine usually includes the following steps: first, analyzing the structure and working principle of the wind turbine to determine the various physical quantities, parameters and variables involved in the wind power generation system where the target wind turbine is located; secondly, using Newtonian mechanics, fluid mechanics and other related knowledge to establish a dynamic model of the wind turbine blades under the action of wind; then, deriving the electrical part model of the wind turbine, including the equivalent circuit of the generator and the electrical characteristic equations; subsequently, combining the mechanical part model with the electrical part model to establish a complete mathematical model of the wind turbine, taking into account factors such as blade rotation, wind speed changes, and electromagnetic induction.

[0082] S102: defining the dynamic characteristics of the current loop controller of the mathematical model and the dynamic characteristics of the speed loop controller of the mathematical model.

[0083] Defining the dynamic characteristics of the current loop controller and the speed loop controller of the mathematical model means describing the behavioral characteristics of the current control and the speed controller in the wind turbine system where the target wind turbine is located. The dynamic characteristics of the current loop controller include the transfer function of the current loop controller and the control object transfer function. The transfer function describes the response of the controller to the input signal (for example, current error). The control object transfer function represents the response of the controlled object (current loop) to the control signal (controller output). Similarly, the dynamic characteristics of the speed loop controller include the transfer function of the speed loop controller and the control object transfer function, which are used to describe how the speed controller adjusts the generator speed to achieve the target closed-loop characteristics.

[0084] In a possible implementation, the transfer function of the current loop controller control object is: G i =(K s / R) / ((T1·S+1)·(T s ·S+1));

[0085] The transfer function of the speed loop controller control object is: G j =(K d ·R) / (C e ·T m ·S·(T·S+1));

[0086] The current loop controller transfer function is: K i (S)=(a i2 ·S 2 +a i1 ·S+a i0 ) / (b i2 ·S 2 +b i1 ·S+b i0 );

[0087] The transfer function of the speed loop controller is: K j (S)=(a j2 ·S 2 +a j1 ·S+a j0 ) / (b j2 ·S 2 +b j1 ·S+b j0 ).

[0088] Among them, K s K is the gain of the control system where the current loop controller is located, which indicates the response strength of the control system to the input signal (current error); d is the gain of the control system where the speed loop controller is located, indicating the response strength of the system to the input signal (speed error); R is the resistance value, which is the resistance parameter in the control system where the current loop and speed loop controller are located; T1, Ts and T are three different time constants, which affect the dynamic response speed of the system; C e is the electromotive force coefficient, a parameter representing the electromotive force of the target wind turbine generator; T m is the mechanical time constant, which affects the dynamic response capability of the mechanical part in the control system where the current loop and speed loop controller are located; S is the complex frequency variable in the Laplace transform, S = j*ω, which is an imaginary unit, and ω is the target angular frequency; a i2 , a i1 , a i0 are the numerator quadratic term coefficient, numerator linear term coefficient and numerator zero-order term coefficient of the current loop controller transfer function respectively; b i2 , b i1 , b i0 are the denominator quadratic term coefficient, the denominator linear term coefficient and the denominator zero-order term coefficient of the current loop controller transfer function respectively; a j2 , a j1 , a j0 are the numerator quadratic term coefficient, numerator linear term coefficient and numerator zero-order term coefficient of the speed loop controller transfer function respectively; b j2 , b j1 , b j0 They are respectively the denominator quadratic term coefficient, the denominator linear term coefficient and the denominator zero-order term coefficient of the speed loop controller transfer function.

[0089] S103: Determine target closed-loop characteristics.

[0090] To determine the target closed-loop characteristic L of the target wind turbine d, it is necessary to clarify the main performance objectives of the wind turbine system where the target wind turbine is located, which include but are not limited to the stability of power output, response speed, anti-disturbance capability and operating efficiency, etc. Then these main performance objectives are converted into the closed-loop characteristics of the target wind turbine in the mathematical model.

[0091] It should be noted that the target closed-loop characteristics refer to the expected system response and performance parameters set in the control system where the current loop and speed loop controllers are located. These characteristics describe the closed-loop behavior of the system in actual operation, such as stability, response speed, accuracy, anti-interference ability, etc. By setting the target closed-loop characteristics, the performance indicators that the system should have can be clarified, which helps design the controller to meet the system's operating requirements and ensure that the system operates stably and reliably under different working conditions.

[0092] S104: Based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller, in combination with the H∞ control method, target parameters of the current loop controller transfer function and the speed loop controller transfer function are calculated respectively.

[0093] Combining the target closed-loop characteristics, the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller, the H∞ control method is used to calculate the target parameters of the current loop controller transfer function and the speed loop controller transfer function respectively. These target parameters include the target numerator coefficient and the target denominator coefficient, where the target numerator coefficient is composed of the target numerator quadratic term coefficient, the target numerator linear term coefficient and the target numerator zero-order term coefficient; the target denominator coefficient includes the target denominator quadratic term coefficient, the target denominator linear term coefficient and the target denominator zero-order term coefficient. By calculating and determining these target parameters, the controller design can be optimized to meet the required closed-loop characteristics and system performance indicators, ensuring that the current loop and speed loop controllers are stable and efficient during operation.

[0094] See also Figure 2 , Figure 2 A method flow chart of a method for calculating a target parameter provided in an embodiment of the present application. Accordingly, step S104 is based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller, and the dynamic characteristics of the speed loop controller, combined with the H∞ control method, to respectively calculate the target parameters of the current loop controller transfer function and the speed loop controller transfer function, which can be specifically achieved by the following steps:

[0095] A1: Set the initial parameters of the current loop controller and the initial parameters of the speed loop controller.

[0096] In order to calculate the target parameters of the current loop controller transfer function, it is necessary to first set the preliminary parameters of the current loop controller. That is, the current loop controller transfer function Ki (S)=(a i2 ·S 2 +a i1 ·S+a i0 ) / (b i2 ·S 2 +b i1 ·S+b i0 )Set a i2 , a i1 , a i0 , b i2 , b i1 , b i0 The initial value of .

[0097] It should be noted that a i2 , a i1 , a i0 , b i2 , b i1 , b i0 The initial value of can be set reasonably based on experience.

[0098] A21: Determine the target parameters of the current loop controller by utilizing the H∞ control method in combination with the target closed-loop characteristics, the current loop controller transfer function, the preliminary parameters of the current loop controller, the parameter calculation formula, the restriction conditions and the convergence conditions.

[0099] By utilizing the H∞ control method, combined with the target closed-loop characteristics, the current loop controller transfer function, preliminary parameters, parameter calculation formulas, constraints, and convergence conditions, the target parameters of the current loop controller can be determined. This means that when designing the current loop controller, the required closed-loop characteristics, controller transfer function, and initial parameters are considered comprehensively, and the H∞ control method is applied to optimize the parameter selection. At the same time, the set constraints and conditions to ensure convergence performance are followed to ensure that the current loop controller meets the design requirements and effectively controls the system. This process aims to improve the stability and robustness of the control system to meet the expected performance indicators and control requirements.

[0100] A22: Determine the target parameters of the current loop controller by utilizing the H∞ control method in combination with the target closed-loop characteristics, the transfer function of the speed loop controller, the preliminary parameters of the speed loop controller, the parameter calculation formula, the restriction conditions and the convergence conditions.

[0101] Similarly, by applying the H∞ control method, the target parameters of the current loop controller can be determined by combining the target closed-loop characteristics, the transfer function of the speed loop controller, the initial parameters of the speed loop controller, the parameter calculation formula, the constraints and the convergence conditions. This means that when designing the current loop controller, the required closed-loop characteristics, the transfer function of the speed loop controller, the preliminary parameters are considered, and the H∞ control method is used to optimize the parameter selection. At the same time, it is ensured that the set constraints and the convergence requirements for system stability are followed so that the appropriate current loop controller parameters are finally determined. This process aims to improve the performance, stability and robustness of the control system, thereby achieving effective control and optimized operation of the system.

[0102] In a possible implementation, the restriction condition includes: a first restriction condition and a second restriction condition;

[0103] The first restriction condition is:

[0104] The second restriction condition is: (X+G·Y) * ·(Y c +G·X c )+(Y c +G·X c ) * (X+G·Y)>0;

[0105] Wherein, Y is the denominator of the current loop controller transfer function, or the denominator of the speed loop controller transfer function; Y * is the conjugate complex number of Y; c is the denominator of the instantiated transfer function; Y c * Y c The conjugate complex number of; G is the control object transfer function of the current loop controller or the control object transfer function of the speed loop controller; X is the numerator of the current loop controller transfer function or the numerator of the speed loop controller transfer function; Y and X are both in matrix form; L d is the target closed-loop characteristic; γ is the preset upper limit value; I is the unit matrix; X c is the numerator of the instantiated transfer function; (G·XL d ·Y) * (G XL d The conjugate complex number of (X+G·Y); * is the conjugate complex number of (X+G·Y); (Y c +G·X c ) * Y c +G·Xc) conjugate complex number; X=a2·S 2+a1·S+a0; a2 is the coefficient of the initial numerator quadratic term; a1 is the coefficient of the initial numerator linear term; a0 is the coefficient of the initial numerator zero-order term; Y=b2·S 2 +b1·S+b0; b2 is the coefficient of the preliminary denominator quadratic term; b1 is the coefficient of the preliminary denominator linear term; b0 is the coefficient of the preliminary denominator zero-order term; S is the complex frequency variable in Laplace transform, S=j*ω, j is the imaginary unit, ω is the target angular frequency.

[0106] When Y is the denominator of the current loop controller transfer function, a2 = a i2 , a1=a i1 , a0=a i0 ;

[0107] When Y is the denominator of the speed loop controller transfer function, b2 = b i2 , b1=b i1 , b0=b i0 ;

[0108] When X is the numerator of the current loop controller transfer function, a2 = a j2 , a1=a j1 , a0=a j0 ;

[0109] When X is the numerator of the speed loop controller transfer function, b2 = b j2 , b1=b j1 , b0=b j0 .

[0110] See also Figure 3 , Figure 3 A method flow chart of a method for determining a target parameter provided in an embodiment of the present application. Accordingly, step A21 utilizes the H∞ control method, combined with the target closed-loop characteristics, the current loop controller transfer function, the preliminary parameters of the current loop controller, the parameter calculation formula, the restriction conditions and the convergence conditions, to determine the target parameters of the current loop controller, which can be specifically implemented by steps B1-B8:

[0111] B1: calculating an instantiation transfer function of the current loop controller based on preliminary parameters of the current loop controller within a target angular frequency range of the current loop controller.

[0112] Within the target angular frequency range of the current loop controller, the instantiation transfer function K of the current loop controller is determined based on the preliminary parameters of the current loop controller. c , which means that a specific transfer function (i.e., instantiated transfer function K) is determined according to the preset target angular frequency range and the initial parameters of the controller. c). The preliminary parameters include preliminary numerator coefficients and preliminary denominator coefficients. The preliminary numerator coefficients include preliminary numerator quadratic term coefficients, preliminary numerator linear term coefficients, and preliminary numerator zero-order term coefficients; the preliminary denominator coefficients include preliminary denominator quadratic term coefficients, preliminary denominator linear term coefficients, and preliminary denominator zero-order term coefficients.

[0113] Specifically, the instantiated transfer function is obtained by substituting the initial parameters of the current loop controller into the transfer function of the current loop controller. At the same time, the target angular frequency ω needs to be substituted into the complex frequency variable S=j*ω in the transfer function of the current loop controller.

[0114] Example 1: Assume that the coefficient of the quadratic term in the preliminary numerator in the preliminary parameters is a i2 =2, the coefficient of the first-order term in the initial numerator is a i1 =3, initial numerator zero-order coefficient a i0 =4, preliminary denominator quadratic term coefficient b i2 =5, the coefficient of the first-order term of the initial denominator is b i1 =6, initial denominator zero-order coefficient b i0 =7, target angular frequency ω = 1, then the instantiation transfer function K c =(2+3j) / (2+6j).

[0115] This process aims to comprehensively consider the impact of different parameters on the closed-loop control system, thereby optimizing the design of the current loop controller to better adapt it to the dynamic characteristics of the actual control object and improve the stability and performance of the system. Through this process, a specific current loop controller transfer function designed for the target angular frequency range can be obtained to further analyze and optimize the closed-loop performance of the control system.

[0116] It should be noted that the target angular frequency range refers to the desired or target frequency range set in the control system design where the current loop controller is located. In the control system where the current loop controller is located, the angular frequency is usually used to describe the frequency response characteristics of the signal or system. Therefore, the target angular frequency range can be understood as the specific frequency range within which the system needs to achieve the desired performance indicators or response characteristics. In the control system design, determining the target angular frequency range is crucial for setting controller parameters and optimizing system performance and stability.

[0117] B2: Calculating intermediate parameters of the current loop controller based on the constraint condition, the instantiated transfer function and a preset upper limit value.

[0118] In the calculation, the instantiation transfer function K c After that, we can instantiate the transfer function K cThe preset upper limit value γ is substituted into the first constraint condition and the second constraint condition to calculate the intermediate parameters of the current loop controller. The intermediate parameters include the intermediate numerator coefficient and the intermediate denominator coefficient. The intermediate numerator coefficient includes the intermediate numerator quadratic term coefficient, the intermediate numerator linear term coefficient and the intermediate numerator zero-order term coefficient; the intermediate denominator coefficient includes the intermediate denominator quadratic term coefficient, the intermediate denominator linear term coefficient and the intermediate denominator zero-order term coefficient.

[0119] It should be noted that the size of the preset upper limit value is generally set to a number close to 0.

[0120] Example 2: Taking Example 1 as an example, let’s assume that the upper bound γ is set to 0.001. Then, the instantiated transfer function K c =(2+3j) / (2+6j), γ=0.001 is substituted into the first constraint condition and the second constraint (X+G·Y) * ·(Y c +G·X c )+(Y c +G·X c ) * ·(X+G·Y)>0, thus obtaining the intermediate parameters of the current loop controller.

[0121] B3: Calculate the intermediate closed-loop characteristic based on the intermediate parameter and the parameter calculation formula.

[0122] Based on the intermediate parameters and parameter calculation formula, calculating the intermediate closed-loop characteristics means calculating by multiplying the intermediate transfer function by the transfer function of the object controlled by the current loop controller. The intermediate transfer function here refers to the new transfer function obtained by substituting the intermediate parameters into the transfer function of the current loop controller. According to the parameter calculation formula L=G·K, L represents the intermediate closed-loop characteristics, G can be the transfer function of the object controlled by the current loop controller or the transfer function of the object controlled by the speed loop controller, and K represents the intermediate transfer function of the current loop controller or the intermediate transfer function of the speed loop controller. By calculating the intermediate closed-loop characteristics, the feedback effect of the system can be analyzed, and the influence of different parameters on the system performance can be considered during the controller design process, thereby optimizing the stability and performance of the control system.

[0123] Exemplarily, assuming that the coefficient of the intermediate numerator quadratic term is 1, the coefficient of the intermediate numerator linear term is 1, the coefficient of the intermediate numerator zero-order term is 2, the coefficient of the intermediate denominator quadratic term is 3, the coefficient of the intermediate denominator linear term is 4, the coefficient of the intermediate denominator zero-order term is 2, and the target angular frequency is 1, then the intermediate transfer function of the current loop controller is K = (1+S) / (-1+4S).

[0124] B4: Subtract the intermediate closed-loop characteristic from the target closed-loop characteristic, and take the modulus of the difference as the calculated difference.

[0125] The intermediate closed-loop characteristic is subtracted from the target closed-loop characteristic, but since the result of the subtraction between the two may be a quantity with an imaginary unit, it is necessary to take the modulus of the subtraction result to obtain the calculated difference in order to evaluate the deviation between the intermediate closed-loop characteristic and the target expectation. This process helps quantify the degree of difference between the closed-loop characteristics of different parameter settings and the target requirements, thereby determining the most suitable parameter configuration or guiding further optimization of the controller design to achieve a system response that is closer to the ideal closed-loop characteristic.

[0126] B5: Setting the intermediate transfer function as a new instantiated transfer function.

[0127] In addition, the intermediate transfer function calculated in step B3 needs to be set as a new instantiated transfer function, so as to calculate other intermediate parameters of the current loop controller based on the restriction condition, the new instantiated transfer function and the preset upper limit value.

[0128] B6: In combination with the H∞ control method, a new instantiated transfer function is used to replace the original instantiated transfer function to repeat the above steps B2-B5, and the calculated difference obtained in each calculation is recorded.

[0129] By combining the H∞ control method, using a new instantiation transfer function to replace the original instantiation transfer function, the steps of intermediate parameter calculation in step B2, intermediate closed-loop characteristic calculation in step B3, difference calculation in step B4, and new instance parameter setting in step B5 can be performed. At the same time, in each repetition process, a calculation difference is obtained, which reflects the impact of using different instantiation transfer functions on system performance and control effect.

[0130] B7: Draw a difference curve based on the multiple calculated differences of the current loop controller.

[0131] There is a one-to-one correspondence between these calculated differences and each intermediate parameter, which means that each set of intermediate parameters will produce a corresponding calculated difference. At the same time, this series of calculated differences are plotted on a curve to form a difference curve. This curve provides an intuitive way to understand the degree of performance improvement or deviation from the target under different intermediate parameter combinations by observing the changing trend of the difference size. This method helps to identify which intermediate parameter combination is closest to or reaches the predetermined target performance standard, thereby guiding the selection or optimization direction of the final parameters. Overall, this difference curve-based method is an effective strategy for systematically evaluating and selecting the optimal control system parameters.

[0132] It should be noted that the intermediate parameter having a one-to-one correspondence with the calculated difference refers to the intermediate parameter substituted into the intermediate closed-loop characteristic used when calculating the calculated difference.

[0133] B8: If the difference curve meets the convergence condition, the intermediate parameter with the smallest corresponding calculated difference is used as the target parameter.

[0134] When the difference curve shows a certain stability or stops changing significantly, it reaches a preset upper limit value (that is, the difference curve meets the convergence condition). Convergence means that the optimization strategy may have approached or reached the optimal solution.

[0135] On this basis, "the convergence condition includes the difference curve converging to a preset upper limit value", which means that this condition will be met only when the difference curve does reach a preset upper limit value. This upper limit represents the limit of the performance improvement that can be brought by the intermediate parameters. In this case, from the current set of intermediate parameters, the intermediate parameter corresponding to the minimum calculated difference (i.e., the closest to the target performance) is selected as the target parameter in the subsequent analysis or design process, thus ensuring that the performance of the control system where the current loop controller is located reaches the expected target or is close to the optimal state.

[0136] It should be noted that the specific implementation process of step A21 is shown in steps B1-B8, and the specific implementation process of step A22 is similar to the specific implementation process of step A21. You can refer to steps B1-B8 to implement the content described in step A22, and the specific implementation process of A21 will not be repeated here.

[0137] See also Figure 4 , Figure 4 A method flow chart of a difference curve optimization method provided in an embodiment of the present application can be implemented through steps C1-C3:

[0138] C1: If the difference curve does not meet the convergence condition, the latest instantiated transfer function is used to replace the original instantiated transfer function to repeat the above steps B2-B5, so as to obtain a new calculated difference of the current loop controller.

[0139] First, check whether the difference curve has reached the convergence condition, that is, whether the difference curve has a stable upper boundary value. If not, repeat the above steps of B2 intermediate parameter calculation, B3 intermediate closed-loop characteristic calculation, B4 difference calculation and B5 new instance parameter setting to obtain a new calculated difference of the current loop controller.

[0140] C2: adjusting the difference curve based on the new calculated difference to obtain a new difference curve.

[0141] After a new calculated difference is obtained by calculation, it is necessary to add the new calculated difference to the difference curve to obtain a new difference curve, so as to further observe whether the new difference curve meets the convergence condition.

[0142] C3: If the new difference curve still does not meet the convergence condition, then repeat the above steps C1 and C2 based on the new difference curve until the latest difference curve meets the convergence condition.

[0143] If the new difference curve still does not meet the set convergence condition, then the following steps are performed according to the new difference curve: First, repeat step C1 to calculate new calculated differences, and then continue to perform step C2 to adjust the difference curve according to these new calculated differences. Repeat these steps until the latest difference curve meets the set convergence condition. Through this iterative process, parameter settings or control strategies can be continuously optimized to ensure that system stability and performance meet expected requirements.

[0144] It should be noted that steps C1-C3 are optimization methods for the difference curve of the current loop controller, and this method is also applicable to the optimization of the difference curve of the speed loop controller. Therefore, the specific implementation steps of the speed loop controller difference curve optimization are not repeated here.

[0145] S105: adjusting the transfer functions of the current loop controller and the speed loop controller based on the target parameter, and simulating the mathematical model of the target wind turbine based on the adjusted transfer functions of the current loop controller and the speed loop controller.

[0146] The transfer functions of the current loop controller and the speed loop controller are adjusted based on the target parameters, and the mathematical model of the target wind turbine generator is simulated by the adjusted controllers.

[0147] Specifically, the transfer functions of the current loop and speed loop controllers can be combined with the mathematical model of the wind turbine to form a closed-loop control system, and then a simulation tool is selected to write the code that implements the current loop controller, speed loop controller, and the mathematical model of the target wind turbine in the selected simulation tool. The simulation code is then executed and the system response is observed. In addition, the output results can be analyzed by drawing graphs and other methods to evaluate the performance of the current loop and speed loop controllers.

[0148] Through the simulation process, the performance of these adjusted controllers in actual systems can be evaluated, including stability, dynamic response, and control effect. This simulation method helps to verify the effectiveness of parameter adjustment, optimize closed-loop control systems, and provide guidance and improvement directions for system design and practical applications.

[0149] Based on the contents of S101-S105, it can be known that the mathematical model of the target wind turbine is first established, and then the dynamic characteristics of the current loop controller and the speed loop controller are clearly defined, including the transfer function and the control object transfer function. After setting the target closed-loop characteristics, the H∞ control method is adopted, and the target closed-loop characteristics and the dynamic characteristics of the current loop controller and the speed loop controller are considered. On this basis, the target parameters of the transfer functions of the current loop controller and the speed loop controller are calculated respectively, including the target numerator coefficient and the target denominator coefficient, and then the controller transfer function is adjusted. Finally, the mathematical model of the target wind turbine is simulated and verified by applying the adjusted controller. Compared with traditional PID adjustment, this application realizes fast parameter calculation and adjustment by establishing a mathematical model and the H∞ control method, improves the robustness and adaptability of the controller, and effectively solves the uncertainty and external disturbance problems of the current loop and speed loop controllers in actual operation.

[0150] See also Figure 5 , Figure 5 The following is a schematic diagram of the structure of a wind turbine simulation device provided in an embodiment of the present application. Figure 5 As shown, the simulation device of the wind turbine generator comprises:

[0151] A mathematical model building unit 501 is used to build a mathematical model of a target wind turbine;

[0152] A definition unit 502 is used to define the dynamic characteristics of the current loop controller of the mathematical model and the dynamic characteristics of the speed loop controller of the mathematical model; the dynamic characteristics of the current loop controller include the current loop controller transfer function and the current loop controller control object transfer function; the dynamic characteristics of the speed loop controller include the speed loop controller transfer function of the mathematical model and the speed loop controller control object transfer function;

[0153] A first determining unit 503, configured to determine a target closed-loop characteristic;

[0154] The first calculation unit 504 is used to calculate the target parameters of the current loop controller transfer function and the speed loop controller transfer function respectively based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller in combination with the H∞ control method; the target parameters include a target numerator coefficient and a target denominator coefficient; the target numerator coefficient includes a target numerator quadratic term coefficient, a target numerator linear term coefficient and a target numerator zero-order term coefficient; the target denominator coefficient includes a target denominator quadratic term coefficient, a target denominator linear term coefficient and a target denominator zero-order term coefficient;

[0155] A transfer function adjustment unit 505, configured to adjust the transfer functions of the current loop controller and the speed loop controller based on the target parameter;

[0156] The simulation unit 506 is used to simulate the mathematical model of the target wind turbine based on the adjusted transfer functions of the current loop controller and the speed loop controller.

[0157] In a possible implementation, the first calculating unit 504 specifically includes:

[0158] A first setting unit, used to set preliminary parameters of the current loop controller and preliminary parameters of the speed loop controller;

[0159] A second determination unit is used to determine the target parameters of the current loop controller by using the H∞ control method in combination with the target closed-loop characteristic, the current loop controller transfer function, the preliminary parameters of the current loop controller, the parameter calculation formula, the restriction condition and the convergence condition;

[0160] The third determination unit is used to determine the target parameters of the current loop controller by using the H∞ control method in combination with the target closed-loop characteristics, the speed loop controller transfer function, the preliminary parameters of the speed loop controller, the parameter calculation formula, the restriction conditions and the convergence conditions.

[0161] In a possible implementation manner, the second determining unit specifically includes:

[0162] a second calculation unit, configured to calculate an instantiation transfer function of the current loop controller based on preliminary parameters of the current loop controller within a target angular frequency range of the current loop controller; the instantiation transfer function is a transfer function of the current loop controller into which the preliminary parameters are substituted;

[0163] A third calculation unit, configured to calculate an intermediate parameter of the current loop controller based on the constraint condition, the instantiated transfer function and a preset upper limit value;

[0164] A fourth calculation unit is used to calculate an intermediate closed-loop characteristic based on the intermediate parameter and the parameter calculation formula; the intermediate closed-loop characteristic is the product of the intermediate transfer function and the transfer function of the object controlled by the current loop controller; the intermediate transfer function is the transfer function of the current loop controller into which the intermediate parameter is substituted; the parameter calculation formula is L=G·K, L is the intermediate closed-loop characteristic, G is the transfer function of the object controlled by the current loop controller or the transfer function of the object controlled by the speed loop controller, and K is the intermediate transfer function of the current loop controller or the intermediate transfer function of the speed loop controller;

[0165] a fifth calculation unit, configured to perform a subtraction between the intermediate closed-loop characteristic and the target closed-loop characteristic, and take a modulus value of the difference as a calculated difference;

[0166] The second setting unit is configured to set the intermediate transfer function as a new instantiated transfer function.

[0167] A synthesis unit, used to combine the H∞ control method, use a new instantiated transfer function to replace the original instantiated transfer function, repeat the above steps of intermediate parameter calculation, intermediate closed-loop characteristic calculation, calculation difference calculation and intermediate parameter substitution, and record the calculation difference obtained by each calculation;

[0168] A difference curve drawing unit, used for drawing a difference curve based on all the calculated differences of the current loop controller; the calculated differences of the current loop controller have a one-to-one correspondence with the intermediate parameters of the current loop controller;

[0169] A screening unit is used to use the intermediate parameter with the smallest corresponding calculated difference as the target parameter if the difference curve satisfies the convergence condition; the convergence condition includes that the difference curve converges to the preset upper limit value.

[0170] In a possible implementation, the restriction condition includes: a first restriction condition and a second restriction condition;

[0171] The first restriction condition is:

[0172] The second restriction condition is: (X+G·Y) * ·(Y c +G·X c )+(Y c +G·X c ) * (X+G·Y)>0;

[0173] Wherein, Y is the denominator of the current loop controller transfer function, or the denominator of the speed loop controller transfer function; Y * is the conjugate complex number of Y; c is the denominator of the instantiated transfer function; Y c * Y c The conjugate complex number of; G is the control object transfer function of the current loop controller or the control object transfer function of the speed loop controller; X is the numerator of the current loop controller transfer function or the numerator of the speed loop controller transfer function; Y and X are both in matrix form; L d is the target closed-loop characteristic; γ is the preset upper limit value; I is the unit matrix; X c is the numerator of the instantiated transfer function; (G·XL d ·Y) * (G XL dThe conjugate complex number of (X+G·Y); * is the conjugate complex number of (X+G·Y); (Y c +G·X c ) * Y c +G·Xc) conjugate complex number; X=a2·S 2 +a1·S+a0; a2 is the coefficient of the preliminary numerator quadratic term; a1 is the coefficient of the preliminary numerator linear term; a0 is the coefficient of the preliminary numerator zero-order term; Y=b2·S2+b1·S+b0; b2 is the coefficient of the preliminary denominator quadratic term; b1 is the coefficient of the preliminary denominator linear term; b0 is the coefficient of the preliminary denominator zero-order term; S is the complex frequency variable in the Laplace transform, S=j*ω, j is the imaginary unit, ω is the target angular frequency.

[0174] In a possible implementation manner, the device further includes:

[0175] A first repetitive execution unit, if the difference curve does not meet the convergence condition, is used to replace the original instantiated transfer function with the latest instantiated transfer function to repeat the above steps of intermediate parameter calculation, intermediate closed-loop characteristic calculation, calculated difference calculation and intermediate parameter substitution, so as to obtain a new calculated difference of the current loop controller;

[0176] A difference curve adjustment unit, configured to adjust the difference curve based on the new calculated difference to obtain a new difference curve;

[0177] The second repetitive execution unit is used to repeat the above steps of calculating a new calculated difference and adjusting the difference curve based on the new difference curve if the new difference curve still does not meet the convergence condition, until the latest difference curve meets the convergence condition.

[0178] In addition, an embodiment of the present application also provides a simulation device for a wind turbine, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the simulation method for the wind turbine as described above is implemented.

[0179] In addition, an embodiment of the present application further provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes the simulation method of the wind turbine as described above.

[0180] The embodiment of the present application provides a simulation device for a wind turbine generator, first using a mathematical model establishment unit mathematical model establishment unit 501, and using a definition unit 502 to define the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller of the mathematical model. The first determination unit 503 determines the target closed-loop characteristics. Then, the first calculation unit 504 is used to calculate the target parameters of the current loop controller transfer function and the speed loop controller transfer function based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller, combined with the H∞ control method. Finally, the transfer function adjustment unit 505 adjusts the transfer functions of the current loop controller and the speed loop controller based on the target parameters, so that the simulation unit 506 can simulate the mathematical model of the target wind turbine generator based on the adjusted transfer functions of the current loop controller and the speed loop controller. By integrating the mathematical model and the H∞ control theory, the present application can accurately calculate the target parameters of the current loop and the speed loop controller in the design stage, thereby predicting the performance of the wind turbine control system and significantly reducing the time and cost of experimental adjustment. At the same time, based on the strong robustness of the H∞ control method, this application can adapt to uncertainties and external disturbances during operation, ensuring stable and efficient performance even when environmental conditions change or equipment ages.

[0181] The above is a detailed introduction to a simulation method, device, equipment and storage medium for a wind turbine provided by the present application. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the embodiments can be referenced to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of the present application.

[0182] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0183] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

Claims

1. A simulation method for a wind turbine, characterized in that: The method comprises: Establish a mathematical model of the target wind turbine; Define the dynamic characteristics of the current loop controller of the mathematical model and the dynamic characteristics of the speed loop controller of the mathematical model; the dynamic characteristics of the current loop controller include the current loop controller transfer function and the current loop controller controlled object transfer function; the dynamic characteristics of the speed loop controller include the speed loop controller transfer function of the mathematical model and the speed loop controller controlled object transfer function; Determine target closed-loop characteristics; Based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller, in combination with the H∞ control method, target parameters of the current loop controller transfer function and the speed loop controller transfer function are calculated respectively; The transfer functions of the current loop controller and the speed loop controller are adjusted based on the target parameter, and the mathematical model of the target wind turbine generator is simulated based on the adjusted transfer functions of the current loop controller and the speed loop controller.

2. The method according to claim 1, characterized in that The target closed-loop characteristic, the dynamic characteristic of the current loop controller and the dynamic characteristic of the speed loop controller are calculated based on the H∞ control method, and the target parameters of the current loop controller transfer function and the speed loop controller transfer function are calculated respectively, including: Setting preliminary parameters of the current loop controller and preliminary parameters of the speed loop controller; Determine the target parameters of the current loop controller by using the H∞ control method in combination with the target closed-loop characteristic, the current loop controller transfer function, the preliminary parameters of the current loop controller, the parameter calculation formula, the restriction condition and the convergence condition; The target parameters of the current loop controller are determined by utilizing the H∞ control method in combination with the target closed-loop characteristics, the speed loop controller transfer function, the preliminary parameters of the speed loop controller, the parameter calculation formula, the restriction conditions and the convergence conditions.

3. The method according to claim 2, characterized in that The method of using the H∞ control method, in combination with the target closed-loop characteristic, the current loop controller transfer function, the preliminary parameters of the current loop controller, the parameter calculation formula, the restriction condition and the convergence condition, to determine the target parameters of the current loop controller includes: In the target angular frequency range of the current loop controller, an instantiated transfer function of the current loop controller is calculated based on preliminary parameters of the current loop controller; the instantiated transfer function is the transfer function of the current loop controller into which the preliminary parameters are substituted; Calculating intermediate parameters of the current loop controller based on the constraint condition, the instantiated transfer function and a preset upper limit value; Based on the intermediate parameters and the parameter calculation formula, the intermediate closed-loop characteristic is calculated; the intermediate closed-loop characteristic is the product of the intermediate transfer function and the control object transfer function of the current loop controller; the intermediate transfer function is the current loop controller transfer function into which the intermediate parameters are substituted; the parameter calculation formula is L=G·K, L is the intermediate closed-loop characteristic, G is the control object transfer function of the current loop controller or the control object transfer function of the speed loop controller, and K is the intermediate transfer function of the current loop controller or the intermediate transfer function of the speed loop controller; Subtracting the intermediate closed-loop characteristic from the target closed-loop characteristic, and taking the modulus of the difference as a calculated difference; Setting the intermediate transfer function as a new instantiated transfer function; In combination with the H∞ control method, a new instantiated transfer function is used to replace the original instantiated transfer function, so as to repeat the above steps of intermediate parameter calculation, intermediate closed-loop characteristic calculation, calculation difference calculation and intermediate parameter substitution, and record the calculation difference obtained by each calculation; Drawing a difference curve based on all the calculated differences of the current loop controller; the calculated differences of the current loop controller have a one-to-one correspondence with the intermediate parameters of the current loop controller; If the difference curve satisfies the convergence condition, the intermediate parameter with the smallest corresponding calculated difference is used as the target parameter; the convergence condition includes that the difference curve converges to the preset upper limit value.

4. The method according to claim 2 or 3, characterized in that: The restriction conditions include: a first restriction condition and a second restriction condition; The first restriction condition is: The second restriction condition is: (X+G·Y) * ·(Y c +G·X c )+(Y c +G·X c ) * (X+G·Y)>0; Wherein, Y is the denominator of the current loop controller transfer function, or the denominator of the speed loop controller transfer function; Y * is the conjugate complex number of Y; c is the denominator of the instantiated transfer function; Y c * Y c The conjugate complex number of; G is the control object transfer function of the current loop controller or the control object transfer function of the speed loop controller; X is the numerator of the current loop controller transfer function or the numerator of the speed loop controller transfer function; Y and X are both in matrix form; L d is the target closed-loop characteristic; γ is the preset upper limit value; I is the unit matrix; X c is the numerator of the instantiated transfer function; (G·XL d ·Y) * (G XL d The conjugate complex number of (X+G·Y); * is the conjugate complex number of (X+G·Y); (Y c +G·X c ) * Y c +G·Xc)'s conjugate complex number; X=a2·S2+a1·S+a0; a2 is the coefficient of the preliminary numerator quadratic term; a1 is the coefficient of the preliminary numerator linear term; a0 is the coefficient of the preliminary numerator zero-order term; Y=b2·S2+b1·S+b0; b2 is the coefficient of the preliminary denominator quadratic term; b1 is the coefficient of the preliminary denominator linear term; b0 is the coefficient of the preliminary denominator zero-order term; S is the complex frequency variable in Laplace transform, S=j*ω, j is the imaginary unit, ω is the target angular frequency.

5. The method according to claim 3, characterized in that: The method further comprises: If the difference curve does not meet the convergence condition, the latest instantiated transfer function is used to replace the original instantiated transfer function, so as to repeat the above steps of intermediate parameter calculation, intermediate closed-loop characteristic calculation, calculated difference calculation and intermediate parameter substitution, so as to obtain a new calculated difference of the current loop controller; adjusting the difference curve based on the new calculated difference to obtain a new difference curve; If the new difference curve still does not meet the convergence condition, the above steps of calculating a new difference and adjusting the difference curve are repeated based on the new difference curve until the latest difference curve meets the convergence condition.

6. A simulation device for a wind turbine, characterized in that: The device comprises: A mathematical model building unit, used for building a mathematical model of a target wind turbine; A definition unit, used to define the dynamic characteristics of the current loop controller of the mathematical model and the dynamic characteristics of the speed loop controller of the mathematical model; the dynamic characteristics of the current loop controller include the current loop controller transfer function and the current loop controller controlled object transfer function; the dynamic characteristics of the speed loop controller include the speed loop controller transfer function of the mathematical model and the speed loop controller controlled object transfer function; A first determining unit, used to determine a target closed-loop characteristic; A first calculation unit is used to calculate target parameters of the current loop controller transfer function and the speed loop controller transfer function respectively based on the target closed-loop characteristics, the dynamic characteristics of the current loop controller and the dynamic characteristics of the speed loop controller in combination with the H∞ control method; the target parameters include a target numerator coefficient and a target denominator coefficient; the target numerator coefficient includes a target numerator quadratic term coefficient, a target numerator linear term coefficient and a target numerator zero-order term coefficient; the target denominator coefficient includes a target denominator quadratic term coefficient, a target denominator linear term coefficient and a target denominator zero-order term coefficient; A transfer function adjustment unit, used for adjusting the transfer functions of the current loop controller and the speed loop controller based on the target parameter; A simulation unit is used to simulate the mathematical model of the target wind turbine based on the adjusted transfer functions of the current loop controller and the speed loop controller.

7. The device according to claim 6 is characterized in that The first calculation unit specifically includes: A first setting unit, used to set preliminary parameters of the current loop controller and preliminary parameters of the speed loop controller; A second determination unit is used to determine the target parameters of the current loop controller by using the H∞ control method in combination with the target closed-loop characteristic, the current loop controller transfer function, the preliminary parameters of the current loop controller, the parameter calculation formula, the restriction condition and the convergence condition; The third determination unit is used to determine the target parameters of the current loop controller by using the H∞ control method in combination with the target closed-loop characteristics, the speed loop controller transfer function, the preliminary parameters of the speed loop controller, the parameter calculation formula, the restriction conditions and the convergence conditions.

8. The device according to claim 7, characterized in that The second determining unit specifically includes: a second calculation unit, configured to calculate an instantiation transfer function of the current loop controller based on preliminary parameters of the current loop controller within a target angular frequency range of the current loop controller; the instantiation transfer function is a transfer function of the current loop controller into which the preliminary parameters are substituted; A third calculation unit, configured to calculate an intermediate parameter of the current loop controller based on the constraint condition, the instantiated transfer function and a preset upper limit value; A fourth calculation unit is used to calculate an intermediate closed-loop characteristic based on the intermediate parameter and the parameter calculation formula; the intermediate closed-loop characteristic is the product of the intermediate transfer function and the transfer function of the object controlled by the current loop controller; the intermediate transfer function is the transfer function of the current loop controller into which the intermediate parameter is substituted; the parameter calculation formula is L=G·K, L is the intermediate closed-loop characteristic, G is the transfer function of the object controlled by the current loop controller or the transfer function of the object controlled by the speed loop controller, and K is the intermediate transfer function of the current loop controller or the intermediate transfer function of the speed loop controller; a fifth calculation unit, configured to perform a subtraction between the intermediate closed-loop characteristic and the target closed-loop characteristic, and take a modulus value of the difference as a calculated difference; A second setting unit, configured to set the intermediate transfer function to a new instantiated transfer function; A synthesis unit, used to combine the H∞ control method, use a new instantiated transfer function to replace the original instantiated transfer function, repeat the above steps of intermediate parameter calculation, intermediate closed-loop characteristic calculation, calculation difference calculation and intermediate parameter substitution, and record the calculation difference obtained by each calculation; A difference curve drawing unit, used for drawing a difference curve based on all the calculated differences of the current loop controller; the calculated differences of the current loop controller have a one-to-one correspondence with the intermediate parameters of the current loop controller; A screening unit is used to use the intermediate parameter with the smallest corresponding calculated difference as the target parameter if the difference curve satisfies the convergence condition; the convergence condition includes that the difference curve converges to the preset upper limit value.

9. A simulation device for a wind turbine, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the simulation method for a wind turbine as described in any one of claims 1 to 5 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes the wind turbine simulation method according to any one of claims 1 to 5.

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