Finite-time anti-interference control method and system for direct-current grid-connected system of doubly-fed wind generator

Abstract

The invention discloses a finite-time anti-interference control method and system for a doubly-fed wind generator direct-current grid-connected system. The finite-time anti-interference control method comprises the following steps: S1, constructing a direct rotating speed loop system model of a double-converter doubly-fed wind generator; s2, setting four concentrated disturbance terms based on the direct rotating speed loop system model of the double-converter doubly-fed wind generator; s3, constructing a finite time disturbance observer based on a super-distortion algorithm to observe the four concentrated disturbance items, and proving the convergence of the observer; and S4, performing real-time interference compensation on a disturbance estimation result while realizing tracking error finite time convergence by adopting an integral terminal sliding mode controller, thereby realizing finite time anti-interference control on the double-converter doubly-fed wind driven generator. Finally, through simulation and experiment verification, compared with a robust decoupling controller based on a disturbance observer, the method has more advantages in the aspects of suppressing buffeting and resisting various interferences.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind power generation, and in particular relates to a finite-time anti-interference control method and system for a double-fed induction generator DC grid-connected system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Doubly fed induction generator (DFIG) is widely used in wind farms due to its high efficiency and good adaptability. Especially with the development of high voltage direct current (HVDC), DC-based doubly fed induction generator has attracted more attention from scholars. Among them, double voltage source doubly fed induction generator (double-VSCDFIG), such as Figure 1 As shown in Figure 2, the stator and rotor of the dual voltage source doubly fed induction generator efficiently transmit electrical energy to the DC grid through the rotor side converter (RSC) and stator side converter (SSC). Figure 1 As shown in Figure 1, the system structure and application environment of this configuration are significantly different from those of an AC-based doubly fed induction generator. This patent focuses on the anti-interference control of a dual voltage source doubly fed induction generator, which can improve its steady-state and transient performance.

[0004] Traditional vector control schemes have been widely used in doubly-fed induction generator (DFIG) systems due to their simplicity and ease of implementation. However, in practical applications, DFIG wind turbines often face various internal and external disturbances and uncertainties, such as parameter variations, unmodeled dynamics, and external grid faults. Achieving high efficiency and fault ride-through (FRT) for DFIGs using only traditional linear control methods is challenging. Consequently, many nonlinear control algorithms have been successfully implemented in double-VSCDFIGs. A coordinated model predictive control (MPC) scheme based on a traditional dual-loop control scheme has been proposed to improve system efficiency. Single-loop model predictive control (SLMPC) has been proposed to improve dynamic response, but its interference rejection capability is insufficient and somewhat complex. To enhance the system's interference rejection capability, control strategies based on disturbance observers have been investigated, such as adaptive disturbance rejection and the extended state disturbance observer (based on sliding mode disturbance observer robust control (SPO)). However, adaptive disturbance rejection controllers can only handle single disturbances.

[0005] Sliding mode control (SMC) technology offers the advantages of strong robustness, ease of tuning, and implementation, ensuring satisfactory system performance. Therefore, it has been widely used in double-VSCDFIG systems. A coordinated sliding mode control strategy employing a traditional power-current dual-loop control structure has been applied to double-VSCDFIG systems. Single-loop sliding mode control has been designed using a feedback linearization algorithm. A damping observer has been used to reduce the sliding mode switching coefficient, thereby minimizing system chattering. However, these studies have not been able to effectively prevent the negative effects of chattering, which is detrimental to practical applications. Furthermore, from the perspective of control system time optimization, control methods that enable closed-loop systems to converge within finite time exhibit improved robustness and interference rejection. The integrated terminal sliding surface sliding mode controller (ITSMC) not only possesses these advantages but also exhibits nonsingularity. This sliding mode controller has been applied to AC-based doubly-fed induction generator (DFIG) systems to suppress chattering and achieve finite-time convergence. The ITSMC has been used to solve the finite-time tracking control problem of an incoming vehicle under input saturation and uncertainty. Therefore, in research practice, ITSMC has demonstrated the characteristics of fast convergence, excellent control performance and non-singularity.

[0006] The Double-VSCDFIG system is a highly nonlinear system. Due to its specific operating environment, it is often subject to non-negligible random wind forces, parameter uncertainties, grid faults, and other disturbances. Therefore, to enhance the system's robustness to disturbances, the switching gain must be increased when designing the sliding mode controller, which inevitably increases the probability of chattering. To further reduce chattering, adding a disturbance observer to the ITSMC can effectively estimate and compensate for multiple disturbances and reduce chattering by selecting a smaller switching gain. For example, prior art proposes a composite control scheme that aims to improve the stability of DC microgrids by combining an extended sliding mode observer with an ITSMC, and an ITSMC based on generalized disturbance estimation to effectively suppress chattering and improve the control performance of magnetic levitation systems under various disturbances. Among the many algorithms used for disturbance observers, the superwarp algorithm has been widely used in motors and other systems due to its effective ability to eliminate chattering and its finite-time convergence performance. Summary of the Invention

[0007] In summary, a hybrid control method based on ITSMC (Independent Steering System Control) (FT-SMC) is proposed for a double-VSC DFIG with external disturbances and parameter uncertainties. The ITSMC is used as the feedback regulation part to stabilize the system dynamics within a finite time, while the STO reduces system chattering by compensating for system disturbances and reducing the switching gain.

[0008] According to some embodiments, a first solution of the present invention provides a finite-time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system, which adopts the following technical solution:

[0009] A finite-time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system includes:

[0010] Construct a direct speed loop system model of a dual-converter doubly-fed wind turbine generator;

[0011] Based on the direct speed loop system model of the double-converter doubly-fed wind turbine generator, four concentrated disturbance terms are set;

[0012] A finite-time disturbance observer based on the hyperwarp algorithm is constructed to observe four concentrated disturbance terms, and the convergence of the observer is proved.

[0013] An integral terminal sliding mode controller is used to achieve finite-time convergence of the tracking error while performing real-time interference compensation on the disturbance estimation result, thereby realizing finite-time anti-interference control of the dual-converter doubly-fed wind turbine.

[0014] According to some embodiments, a second solution of the present invention provides a finite-time anti-interference control system for a doubly-fed wind turbine generator DC grid-connected system, which adopts the following technical solution:

[0015] The finite-time anti-interference control system of the doubly-fed wind turbine generator DC grid-connected system includes:

[0016] a dynamic model building module configured to build a dynamic model of a dual-converter doubly-fed wind turbine generator;

[0017] a control target determination module configured to determine a control target and a state variable of the control target of the dual-converter doubly-fed wind turbine generator based on a dynamic model of the dual-converter doubly-fed wind turbine generator;

[0018] The finite-time disturbance estimation module is configured to construct a finite-time disturbance observer for the super-warp algorithm and perform finite-time observations on the four concentrated disturbance terms set by the dual-converter doubly-fed wind turbine generator;

[0019] The finite-time anti-interference control module is configured to use an integral terminal sliding mode controller to achieve finite-time convergence of the tracking error while performing real-time interference compensation on the disturbance estimation result, thereby realizing finite-time anti-interference control of the dual-converter doubly-fed wind turbine generator.

[0020] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium.

[0021] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the finite-time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system as described in the first aspect above.

[0022] According to some embodiments, a fourth aspect of the present invention provides a computer device.

[0023] A computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system as described in the first aspect above are implemented.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The structure of a dual-converter doubly-fed wind turbine directly connected to the DC grid exhibits nonlinear and strongly coupled characteristics, making it difficult to improve the dynamic response speed of traditional dual-loop control strategies. To improve the transient and steady-state performance of the dual-converter doubly-fed wind turbine under multiple disturbances and suppress chattering, an integrating terminal sliding mode controller based on super-distorted disturbance estimation is proposed. First, a decoupled direct speed control system with multiple disturbances is proposed based on a mechanistic model, which breaks away from traditional dual-loop control and improves the system's response speed. However, this system is inevitably affected by strong disturbances, necessitating a large switching gain, which can lead to severe chattering. To address this issue, a super-distorted disturbance observer is proposed. This observer can effectively estimate and compensate for multiple disturbances within a finite time, significantly reducing the switching gain of the sliding mode controller. Furthermore, to ensure convergence of the tracking error within a finite time, the controller uses an integrating terminal sliding mode surface and introduces an exponential reaching law to mitigate the negative effects of large step responses. Simulations and experiments demonstrate the effectiveness and superiority of this strategy in suppressing chattering and resisting various types of disturbances, including grid sags. The strategy is compared with a robust decoupling controller based on a disturbance observer. Finally, an experimental platform is constructed to verify the feasibility of this approach. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0027] Figure 1 This is a schematic diagram of the configuration structure of a double-converter doubly-fed wind turbine generator in a DC power grid;

[0028] Figure 2 1 is a schematic diagram of the control logic of a finite time disturbance rejection controller (FT-SMC) in an embodiment of the present invention;

[0029] Figure 3 1 is a diagram showing the external wind disturbance experienced by the system in an embodiment of the present invention;

[0030] Figure 4 1 is a diagram showing the internal disturbance of the system in an embodiment of the present invention;

[0031] Figure 5 When the FT-SMC and the sliding mode disturbance observer (SPO) robust controller are used in the embodiment of the present invention, the rotor angular frequency ω of the system under multiple disturbances is r Tracking performance comparison chart;

[0032] Figure 6 When FT-SMC and SPO are used in the embodiment of the present invention, the system stator flux linkage ψ under multiple disturbances sd and ψ sq Tracking performance comparison chart;

[0033] Figure 7 When FT-SMC and SPO are used in the embodiment of the present invention, the rotor current i of the system under multiple disturbances is rd and i rq Operation status diagram;

[0034] Figure 8 1. This is a performance comparison diagram of the d-axis stator flux observation error when adding internal disturbance when using FT-SMC and SPO respectively in the embodiment of the present invention;

[0035] Figure 9 1. This is a performance comparison diagram of the q-axis stator flux observation error when adding internal disturbance when using FT-SMC and SPO respectively in the embodiment of the present invention;

[0036] Figure 10 1 is a performance comparison diagram of rotor speed observation error with internal disturbance when FT-SMC and SPO are used in embodiments of the present invention;

[0037] Figure 11 1 is a performance comparison diagram of the q-axis rotor current observation error when adding internal disturbance when using FT-SMC and SPO respectively in an embodiment of the present invention;

[0038] Figure 12 is a performance diagram of estimating the disturbance term d1 using finite-time sliding mode control (FT-SMC) in an embodiment of the present invention;

[0039] Figure 13 is a performance diagram of estimating the disturbance term d2 using finite-time sliding mode control (FT-SMC) in an embodiment of the present invention;

[0040] Figure 14is a performance diagram of estimating the disturbance term d3 using finite-time sliding mode control (FT-SMC) in an embodiment of the present invention;

[0041] Figure 15 is a performance diagram of estimating the disturbance term d3 using finite-time sliding mode control (FT-SMC) in an embodiment of the present invention;

[0042] Figure 16 1 is a comparison diagram of the rotor current when the voltage of the system is reduced, respectively using FT-SMC and SPO in the embodiment of the present invention;

[0043] Figure 17 1 is a comparison diagram of the rotor angular velocity when the voltage of the system is reduced, respectively using FT-SMC and SPO in the embodiment of the present invention;

[0044] Figure 18 1 is a comparison diagram of active power when the voltage is reduced in the system using FT-SMC and SPO respectively in the embodiment of the present invention;

[0045] Figure 19 1 is a comparison diagram of the total harmonic distortion of the stator current when the system voltage is reduced using FT-SMC and SPO respectively in an embodiment of the present invention; Figure 20 This is a schematic diagram of an experimental platform in an embodiment of the present invention; Figure 21 is a graph showing a DFIG rotor speed of 1650 rpm when the wind speed is 11 m / s in an embodiment of the present invention; Figure 22 is a graph showing that the DFIG rotor speed decreases from 1650 rpm to 1350 rpm when the wind speed gradually decreases from 11 m / s to 9 m / s in an embodiment of the present invention; DETAILED DESCRIPTION

[0046] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0047] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0048] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0049] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0050] Example 1

[0051] like Figure 1 As shown, this embodiment provides a finite-time anti-interference control method for a dual-converter doubly-fed wind turbine generator DC grid-connected system. In this embodiment, the method includes the following steps:

[0052] Construct a dynamic model of a dual-converter doubly-fed wind turbine generator;

[0053] Construct a direct speed loop system model of a dual-converter doubly-fed wind turbine generator;

[0054] Construct four concentrated disturbance terms of dual-converter doubly-fed wind turbine;

[0055] An integral terminal sliding mode controller based on a sliding film state observer with a super-twisted algorithm is constructed, and the state of a dual-converter doubly-fed wind turbine generator subsystem is estimated using the super-twisted sliding film state observer.

[0056] An integral terminal sliding mode controller is constructed to achieve finite-time convergence of the system, and filtering technology is used to ensure smooth switching control and effectively reduce chattering.

[0057] The dynamic model of the doubly-fed wind turbine generator is specifically as follows:

[0058]

[0059] Among them, u sd 、u sq 、u rd 、u rq 、i rd 、i rq 、 are the voltage, current and magnetic flux of the stator and rotor in the dq coordinate system, R s 、R r are the stator and rotor winding resistances, L s , L r , L m They are the stator and rotor inductance and mutual inductance, ω r is the rotor angular velocity, ω1 is the synchronous angular velocity, n p , J are the number of pole pairs and moment of inertia of the motor respectively, T m is the mechanical torque; where the coefficient C b =L m / L s .

[0060] The dual-converter doubly-fed wind turbine system is analyzed based on the dynamic model of the dual-converter doubly-fed wind turbine. The stator and rotor of the dual-converter doubly-fed wind turbine are connected to the DC grid through the SSC and RSC, which generates four control inputs (u sd 、u sq 、u rd 、u rq ), in order to improve the dynamic response time, the power control loop is discarded and the required voltage is directly calculated based on the system state, thus realizing a single-loop control scheme.

[0061] Specifically, the rotor speed control loop is designed as follows.

[0062]

[0063] in:

[0064]

[0065] The method of using a sliding film state observer based on a super-twisted algorithm to perform disturbance estimation on a doubly-fed wind turbine generator system is as follows:

[0066] Taking into account the inevitable existence of modeling errors, parameter perturbations, internal dynamic perturbations, and external perturbations, which are unknown and unmeasurable, four parameters (d1, d2, d3, d4) are set to represent four concentrated disturbance terms, specifically:

[0067]

[0068] Where B0 is a constant matrix, Due to physical limitations, the control inputs of a dual-converter doubly-fed wind turbine are locally bounded. Furthermore, the locally bounded nature of the state variables is attributed to the fact that the effects of disturbances and control inputs are limited. In the most extreme disturbance scenarios, the rotor speed and reactive power output can drop from the setpoint to near zero within a short time interval Δt. Therefore, the bounds of the system state and disturbance can be calculated as follows:

[0069]

[0070] The four concentrated disturbance states are estimated using a synovial state observer based on the super-warp algorithm.

[0071] The synovial state observer based on the super-twisted algorithm is specifically:

[0072] Substituting the disturbance term into the dynamic model of the dual-converter doubly-fed wind turbine generator, it is organized as follows:

[0073]

[0074] Therefore, a system dynamics equation including an internally coupled disturbance term is obtained, which allows the direct calculation of the required voltage without an additional power calculation loop.

[0075] The method of constructing an integral terminal sliding mode controller of a sliding film state observer based on a super-twisted algorithm and using the super-twisted sliding film state observer to perform state estimation on a dual-converter doubly-fed wind turbine generator subsystem includes:

[0076] The lemma required in designing the synovial state observer based on the super-warp algorithm is as follows:

[0077] Lemma 1: Consider the following scalar system:

[0078]

[0079] exist Under the condition of , r is a constant. The control rate u(t) is designed as:

[0080]

[0081] If satisfied And δ≥1.1r, then e and Converges to zero T in finite time e Establishment

[0082]

[0083] The design of the synovial state observer based on the super-twisted algorithm is as follows:

[0084]

[0085] The superscripts (∧) and (-) represent the state estimate and estimation error, respectively. Observer gain γ i >0,δ i >0(i=1,2..3).

[0086] The observer error obtained by subtracting the dynamic model of the dual-converter doubly-fed wind turbine generator with disturbance term from the sliding film state observer based on the super-twisted algorithm is as follows:

[0087]

[0088] According to Lemma 1, when and δ i ≥1.1r d (i=1,2..3), the estimation error and its derivative are in finite time Converges to 0. Therefore, when t≥T d hour, The perturbation d can be obtained as follows:

[0089]

[0090] The final integral terminal sliding mode controller is:

[0091]

[0092] in, A variable with a superscript “*” indicates that the value is the reference point of the original variable.

[0093] This embodiment proposes an integral terminal sliding mode controller based on super-distortion disturbance estimation for a doubly-fed induction generator DC grid-connected structure based on dual converters (Double-VSCDFIG) to improve the transient and steady-state performance of the Double-VSCDFIG under various disturbances and suppress chattering.

[0094] The innovations and contributions of this embodiment can be summarized as follows:

[0095] The proposed controller adopts an improved ITSMC strategy, which can achieve finite-time convergence of the system tracking error, effectively reduce the fluctuation during system operation, and ensure excellent transient and steady-state performance.

[0096] The FT-SMC system has a simpler structure and effectively reduces system chattering. Compared with high-gain disturbance observers and synovial disturbance observers, the observation error of the super-distorted disturbance observer can converge within a finite time, resulting in higher steady-state accuracy and stronger anti-interference capability.

[0097] This controller utilizes a novel direct speed loop system model with disturbances. Compared to high-gain disturbance observers and sliding film disturbance observers, this model reduces the system order and controller design complexity while achieving single-loop direct control. This order reduction significantly improves operability compared to single-loop model predictive control and damping observers.

[0098] The simulation records the parameter selection method of the integral terminal sliding mode controller based on super-distorted disturbance estimation. The transient characteristics and low voltage ride-through capability under multiple disturbances are compared with those of the classical feedback controller based on the sliding film disturbance observer (SPO). The improvement of the proposed controller in terms of transient characteristics and low voltage ride-through capability under multiple disturbances is evaluated.

[0099] ·An experimental platform was designed and built to determine the practical operability of the proposed controller.

[0100] 1. System mathematical model

[0101] Double-VSIDFIG (dynamic model of doubly-fed wind turbine)

[0102] Double-VSIDFIG dynamics can be described as:

[0103]

[0104] The coefficient C b =L m / L s .

[0105] 2. System analysis and problem description

[0106] The stator and rotor of the double-converter doubly-fed wind turbine are connected to the DC grid through the SSC and RSC, resulting in four control inputs (u sd 、u sq 、u rd 、u rq ), in order to improve the dynamic response time, the power control loop is abandoned, and the required voltage is directly based on the system state Calculated, thus realizing the single-loop control scheme.

[0107] Specifically, the rotor speed control loop is designed as follows.

[0108]

[0109] in:

[0110]

[0111] The method of using a sliding film state observer based on a super-twisted algorithm to perform disturbance estimation on a doubly-fed wind turbine generator system is as follows:

[0112] Taking into account the inevitable existence of modeling errors, parameter perturbations, internal dynamic perturbations, and external perturbations, which are unknown and unmeasurable, four parameters (d1, d2, d3, d4) are set to represent four concentrated disturbance terms, specifically:

[0113]

[0114] Where B0 is a constant matrix, Due to physical limitations, the control inputs of a dual-converter doubly-fed wind turbine are locally bounded. Furthermore, the locally bounded nature of the state variables is attributed to the fact that the effects of disturbances and control inputs are limited. In the most extreme disturbance scenarios, the rotor speed and reactive power output can drop from the setpoint to near zero within a short time interval Δt. Therefore, the bounds of the system state and disturbance can be calculated as follows:

[0115]

[0116] The four concentrated disturbance states are estimated using a synovial state observer based on the super-warp algorithm.

[0117] The synovial state observer based on the super-twisted algorithm is specifically:

[0118] Substituting the disturbance term into the dynamic model of the dual-converter doubly-fed wind turbine generator, it is organized as follows:

[0119]

[0120] Therefore, a system dynamics equation including an internally coupled disturbance term is obtained, which allows the direct calculation of the required voltage without an additional power calculation loop.

[0121] Mathematical Preliminaries Lemma 1 Consider the following scalar system:

[0122]

[0123] exist Under the condition of , r is a constant. The control rate u(t) is designed

[0124]

[0125] If satisfied And δ≥1.1r, then e and In a finite time T e Converges to zero internally, Lemma 2 For nonlinear systems There exists a Lyapunov function V(x)>0 such that V(x)+λ1V(x)+λ2V σ (x)≤0,x∈D / {0}, where 0<σ<1,λ1>0,λ σ (x)>0. Then, the nonlinear system is finite-time stable. Convergence time T x satisfy:

[0126]

[0127] 3. The finite-time disturbance observer is designed as follows:

[0128] The super-warp algorithm is a second-order sliding mode algorithm based on finite-time convergence. It does not require derivative information of the sliding mode variable and the control law is continuous, thus reducing chattering. The sliding mode state observer based on the super-warp algorithm is designed as follows:

[0129]

[0130] The superscripts (∧) and (-) represent the state estimate and estimation error, respectively. γ i >0,δ i >0 (i=1,2..3) is the observer's gain.

[0131] The observer error obtained by subtracting the dynamic model of the double-converter doubly-fed wind turbine generator with disturbance term (4) from the sliding film state observer based on the super-twisted algorithm (5) is as follows:

[0132]

[0133] According to Lemma 1, when And δ i ≥1.1r d (i=1,2..3), the estimated error and its derivative are in finite time T d Converges to 0, that is Therefore, when t≥T d hour, and converges to zero, so the aggregate interference can be estimated by the following formula:

[0134]

[0135] Theorem 1 According to Lemma 1, if Converges to 0, then Also tends to 0, where

[0136] Proof: Design a Lyapunov function, Then find its derivative:

[0137]

[0138] Therefore, when t>T d When the estimated error

[0139] 4. Finite-time sliding film controller (FT-SMC) based on disturbance observer

[0140] The integral terminal sliding mode controller achieves finite-time convergence of the system while overcoming the singularity problem. By adopting filtering technology, it ensures smooth switching control and effectively mitigates chattering.

[0141] The tracking error of the dual-converter doubly-fed wind turbine generator system is expressed as:

[0142]

[0143] in, is the system tracking error.

[0144] The integral terminal sliding surface designed for the four error systems is shown below:

[0145]

[0146] in, c i >0,0<α i <1(i=1,2..5),

[0147] The system tracking reference value of the Double-VSC DFIG is determined using the stator flux orientation coordinate system, where the q-axis is parallel to the stator flux vector. The reference value of the stator flux is given as:

[0148]

[0149] Among them U s is the rated voltage amplitude of the generator. According to the above formula, the rotor current reference value can be obtained:

[0150]

[0151] The reference value of the system's optimal rotor angular frequency is determined based on the maximum mechanical energy captured by the wind turbine, assuming that β = β0 and the mechanical angular frequency ω m Equal to the rotor angular frequency ω of the doubly fed induction generator (DFIG) r , so the DFIG rotor speed reference value is given:

[0152]

[0153] The operating conditions in wind power generation systems are often complicated by the changing wind environment and potential grid failures, resulting in large step responses. Based on the operating characteristics of the Double-VSC DFIG system, this paper selects the exponential approach law, which is particularly suitable for solving large step response control problems. When the tracking error is large, it can ensure that the system approaches the sliding surface at an accelerated rate, thereby improving the response speed and robustness. In addition, by adjusting the control parameters, the chattering can be reduced, and the system stability and control accuracy can be improved. Then, an exponential control rate is designed. The FT-SMC controller is as follows:

[0154]

[0155] where ε i >0,k i >0, i=1,2..4. Figure 2The control scheme of FT-SMC is presented, which will set up two simulation scenarios and introduce three types of disturbances to verify its effectiveness.

[0156] Theorem 2: By choosing a switching gain ε, it exceeds the aggregate interference observation error The maximum absolute value of , the system state will converge to the designed sliding surface in a finite time. That is, when ε>λ, the system state will reach the sliding surface s=0 in a finite time and converge to zero along the sliding surface.

[0157] For ease of reading, this paper uses the third-order rotor angular frequency subsystem as an example to prove the proposed theorem. The proof process for the other three second-order subsystems is similar and will not be repeated here.

[0158] Proof: Design Lyapunov function Then the derivative is:

[0159]

[0160] Substituting (13) into (14), we can obtain

[0161]

[0162] where λ′=ε3-λ>0. Therefore, according to Lemma 2, the system (13) will reach the integral terminal sliding surface in a finite time and will remain on the sliding surface despite the presence of disturbances and uncertainties. The finite arrival time is:

[0163]

[0164] When the system state reaches the sliding surface, the system state will remain on this sliding surface due to the switching control. So we can get ω r The error dynamics subsystem can be rewritten as:

[0165]

[0166] Therefore, Theorem 2 proves that the tracking error e r1 Finally it converges to the origin. In short, the rotor angular frequency ω r Will track accurately within a limited time

[0167] The FT-SMC proposed in this paper is a two-degree-of-freedom controller that combines feedforward disturbance compensation with feedback sliding mode control. Compared with traditional single-feedback sliding mode controllers, it can simultaneously balance tracking performance and disturbance rejection, and has the advantages of finite-time convergence, no singularities, and a continuous control law.

[0168] 5. Simulation Results

[0169] In the simulation scenario design, in order to more clearly verify the effectiveness of the proposed controller FT-SMC in improving system tracking performance and resisting grid faults, it was compared with a classic feedback controller based on a sliding mode disturbance observer (SPO). Therefore, two simulation cases were designed: (1) verification of the system's transient tracking performance under multiple disturbances; (2) verification of the low voltage ride-through capability under the condition of a grid voltage sag fault.

[0170] Table 2 shows the design parameters of the two controllers. To ensure reasonable comparability of the simulation results, the parameters of the SPO are consistent with those in the original paper. The parameters of the DFIG are shown in Table 1. The physical unit used in the simulation system is per unit (pu).

[0171] Table 1: Parameters of a doubly-fed induction generator (DFIG)

[0172]

[0173]

[0174] Table 2: Controller parameters

[0175]

[0176] 5.1 Transient Characteristics under Multiple Interferences

[0177] The purpose of this simulation is to evaluate the transient performance of the proposed controller FT-SMC compared to the SPO controller under the same internal and external disturbance conditions. Figure 3 As shown in Figure 1, after 8 seconds, the wind speed gradually increases from 8 m / s to 12 m / s to simulate gusts. Internal interference is considered as unknown changes in system parameters, modeling uncertainty, etc. When the system runs for 5 seconds, an interference signal d = sin (50t) is superimposed on the stator resistance, as shown in Figure 1. Figure 4 shown.

[0178] Figure 5-Figure 7 The control performance of the system state using the proposed fault-tolerant sliding mode control (FT-SMC) and adaptive predictive observer (SPO) is demonstrated. Figure 5 The system's rotor angular frequency tracking performance is demonstrated. The detailed graph shows that during a wind speed step change, FT-SMC's tracking is largely unaffected, while SPO exhibits an overshoot of approximately 0.02 per unit. Because the dynamic characteristics of the rotor angular frequency are largely unaffected by stator resistance, the internal disturbance at 5 seconds has minimal impact on it.

[0179] stator flux ψ sd and ψ sqTracking performance such as Figure 6 As shown in the detailed diagram, it can be seen that the FT-SMC has a very strong anti-interference ability. rd and i rq The operation status of Figure 7 As shown. Since the d axis is the active power axis, i rd Affected by the change of angular frequency, the fluctuation is large. Figure 5-Figure 7 It can be seen that by using the FT-SMC method proposed in this paper, under double disturbances, the system state can converge to the reference data in a short time, with reasonable performance and small oscillation.

[0180] Figures 8-11 It is shown whether the state observation errors of the proposed super-twisted state observer (FT-SMC) and sliding mode state observer (SPO) can converge under double perturbations. Figure 8-11 The state observation errors are shown in They all converge to 0. But in Figure 8 It can be clearly seen that the addition of internal interference interferes with the observed value of SPO.

[0181] Figure 12-15 The performance of FT-SMC for estimating multiple disturbances (d1, d2, d3, d4) is demonstrated. Both the external wind disturbance and the internal disturbance (added at t = 8 seconds) are accurately estimated. These estimates are achieved without any prior knowledge of the upper limit of the disturbance.

[0182] Overall, compared with SPO, FT-SMC shows significantly stronger robustness to internal and external disturbances, faster convergence speed and more reasonable tracking performance.

[0183] In order to effectively quantify the performance difference between the proposed controller FT-SMC and SPO, the following performance indicators are introduced:

[0184] (1) Time multiplied by the integral of the absolute value of the error (ITAE):

[0185]

[0186] (2) Root mean square error (RMSE).

[0187]

[0188] Where T f represents the running time, e represents the tracking error, represents the observation error. ITAE characterizes the transient tracking performance of the error curve. RMSE measures the accuracy of the observer's prediction. Table 3 compares the performance metrics of FT-SMC and SPO. As can be seen from Table 3, the proposed FT-SMC achieves lower ITAE and RMSE values ​​than SPO. Therefore, the proposed FT-SMC method outperforms SPO on both performance metrics.

[0189] Table 3: Performance indicators of FT-SMC and SPO

[0190]

[0191] 5.2 Low Voltage Ride-Through Capability

[0192] Assuming a voltage dip fault occurs in the DC grid, the voltage drops from the rated value to 30% for a duration of 3 to 3.1 seconds. By analyzing and evaluating the response of the stator active power and rotor current during the grid fault, the low voltage ride-through capability of the Double-VSC DFIG with two controllers is evaluated. During this period (e.g. Figure 16-19 As shown), the angular frequency ω of DFIG r Stable operation at 1.1 times the rated value.

[0193] When the stator voltage drops significantly, the rotor increases its current to compensate. However, this can cause large inrush currents, which can damage power electronics and hinder wind energy system operation. To address the interference caused by the stator voltage drop, the controller increases the rotor speed, effectively limiting the rotor current.

[0194] Figure 16 is the amplitude of the rotor current, Figure 17 is the rotor angular frequency, Figure 18 is the active power output on the stator side. Figure 16-18 It shows that the proposed FT-SMC controller can effectively and quickly suppress the impact of grid disturbances on the system compared to SPO, and the rotor angular frequency does not increase significantly. Figure 17 The trajectory after 3.2 seconds shows that FT-SMC demonstrates superior control performance in suppressing chattering compared to SPO. When the power system experiences a disturbance at 3 seconds, the response speeds of the two controllers differ significantly: FT-SMC restores system stability in only about 0.2 seconds, while SPO takes 0.6 seconds, three times longer than FT-SMC.

[0195] The total harmonic distortion (THD) characteristics of the stator current are as follows: Figure 19The results, shown in Figure 2, intuitively reveal the impact of grid fault interference on the quality of the stator current waveform. The data shows that using FT-SMC control not only reduces the system's stabilization time to one-third of that under SPO, but more importantly, achieves smooth regulation with virtually no chattering.

[0196] 6. Experimental Verification

[0197] In order to verify the performance of the proposed control algorithm, a dSPACE-based experimental platform was designed. Figure 20 The induction motor (IM) is controlled by a dedicated driver to simulate the operating conditions of a wind turbine. The specific parameters of the DFIG are listed in Table 1. Its stator and rotor windings are connected to two independent IGBT converters, both powered by a 650V DC power supply. The rotor position is accurately measured by an incremental encoder. The designed controller is implemented on a dSPACE MicroLabBox platform with a sampling frequency of 10 kHz.

[0198] An experiment was designed to evaluate the operational stability of the system. Figure 21 As shown, the rotor speed n of the doubly fed induction generator (DFIG) r Maintained at a constant value of 1650 rpm. In addition, during the entire operation process, the stator voltage of the DFIG (u sa ), stator current (i sa ) and rotor current (i ra ) all show a stable sinusoidal waveform.

[0199] Another experiment was designed to evaluate the transient performance of the system. In this experiment, the wind speed was gradually reduced from 11 m / s to 9 m / s, and the rotor speed of the doubly fed induction generator (DFIG) was r Gradually reduce the speed from 1650 rpm to 1350 rpm. Figure 22 As shown in the figure, in this process, under the control of FT-SMC and SPO, the voltage and current (u sa ,i sa ,i ra ) are kept within the allowed fluctuation range. Figure 21 The rotor speed (n r ) It can be clearly seen from the enlarged figure that the transient performance of FT-SMC is better than that of SPO, and the tracking speed is faster.

[0200] 7. Conclusion

[0201] This paper proposes a novel FT-SMC controller to improve the anti-interference performance of a dual-VSC DFIG system. By constructing a single-loop, first-order decoupling system model, the control complexity is significantly reduced and the dynamic response speed is improved. The designed controller exhibits finite-time convergence stability. By introducing a super-distorted disturbance observer and an improved sliding surface design, the chattering problem present in traditional sliding mode control is effectively alleviated. Finally, simulation analysis and experimental verification confirm the superior performance of the proposed control scheme in terms of dynamic response, steady-state accuracy, and anti-interference capability. However, some areas for improvement remain in this study. The most significant issue is the presence of a certain degree of rotor current fluctuation, which may affect the long-term operational stability of the system. Future research will focus on optimizing the current control strategy to further suppress rotor current fluctuations and improve the overall system performance.

[0202] Example 2

[0203] This embodiment provides an anti-interference control system for a dual-converter doubly-fed wind turbine generator DC grid-connected system, including:

[0204] Construct a direct speed loop system model of a dual-converter doubly-fed wind turbine generator;

[0205] Based on the direct speed loop system model of the double-converter doubly-fed wind turbine generator, four concentrated disturbance terms are set;

[0206] A finite-time disturbance observer based on the hyperwarp algorithm is constructed to observe four concentrated disturbance terms, and the convergence of the observer is proved.

[0207] An integral terminal sliding mode controller is used to achieve finite-time convergence of the tracking error while performing real-time interference compensation on the disturbance estimation result, thereby realizing finite-time anti-interference control of the dual-converter doubly-fed wind turbine.

[0208] The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment 1. It should be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions. The description of each embodiment in the above embodiments has different emphases. For parts not detailed in one embodiment, please refer to the relevant description of other embodiments.

[0209] The proposed system can be implemented in other ways. For example, the system embodiment described above is merely illustrative. For example, the above module division is only a logical function division. In actual implementation, other division methods may be used. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not implemented.

[0210] Example 3

[0211] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of the anti-interference control method for the doubly-fed wind turbine generator DC grid-connected system as described in the first embodiment above are implemented.

[0212] Example 4

[0213] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the finite-time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system as described in the first embodiment above are implemented.

[0214] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage and optical storage, etc.) containing computer-usable program code.

[0215] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0216] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0217] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0218] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware through a computer program. The program can be stored in a computer-readable storage medium, and when executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0219] Although the above describes the specific embodiments of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without any creative work are still within the scope of protection of the present invention.

Claims

1. A finite-time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system, characterized in that ,, including the following steps: Step S1, constructing a direct speed loop system model of a dual-converter doubly-fed wind turbine generator; Step S2, based on the direct speed loop system model of the dual-converter doubly-fed wind turbine generator, four concentrated disturbance terms are set; Step S3, constructing a finite-time disturbance observer based on the hyperwarp algorithm to observe the four concentrated disturbance terms, and proving the convergence of the observer; Step S4, using an integral terminal sliding mode controller to achieve finite time convergence of the tracking error while performing real-time interference compensation on the disturbance estimation result, thereby achieving finite time anti-interference control of the dual-converter doubly-fed wind turbine generator.

2. The finite time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system according to claim 1, characterized in that: The dynamic model of the dual-converter doubly-fed wind turbine generator is specifically as follows: Among them, u sd 、u sq 、u rd 、u rq 、i rd 、i rq , ψ sd , ψ sq are the voltage, current and magnetic flux of the stator and rotor in the dq coordinate system, R s 、R r are the stator and rotor winding resistances, L s , L r , L m They are the stator and rotor inductance and mutual inductance, ω r is the rotor angular velocity, ω1 is the synchronous angular velocity, n p , J are the number of pole pairs and moment of inertia T of the motor respectively m is the mechanical torque; where the coefficient C a =(L r L s -L m 2 ) / L s 、C b =L m / L s .

3. The finite time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system according to claim 2, characterized in that: Based on the dynamic model of the dual-converter doubly-fed wind turbine generator, the direct speed loop system model of the dual-converter doubly-fed wind turbine generator is determined, and four concentrated disturbance terms are set, specifically: The rotor speed control loop is designed as follows: in: The method of using a sliding film state observer based on a super-twisted algorithm to perform disturbance estimation on a doubly-fed wind turbine generator system is as follows: Taking into account the inevitable existence of modeling errors, parameter perturbations, internal dynamic perturbations, and external perturbations, which are unknown and unmeasurable, four parameters (d1, d2, d3, d4) are set to represent four concentrated disturbance terms, specifically: Where B0 is a constant matrix, Due to physical limitations, the control inputs of a double-converter doubly-fed wind turbine are locally bounded; and the local boundedness of the state variables is attributed to the fact that the effects of disturbances and control inputs are limited. In the most extreme disturbance cases, the rotor speed and reactive power output may drop from the set value to near zero within a short time interval Δt; therefore, the bounds of the system state and disturbance can be calculated as follows: Substituting the disturbance term into the dynamic model of the dual-converter doubly-fed wind turbine generator, it is organized as follows:

4. The anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system according to claim 3, characterized in that: The design of the sliding mode state observer based on the super-twisted algorithm is as follows: The superscripts (∧) and (-) represent the state estimate and estimation error, respectively. γ i >0,δ i >0 (i=1,2..3) is the observer’s gain; The observer error obtained by subtracting the dynamic model of the dual-converter doubly-fed wind turbine generator with disturbance term from the sliding film state observer based on the super-twisted algorithm is as follows: According to Lemma 1, when And δ i ≥1.1r d (i=1,2..3), the estimated error and its derivative are in finite time T d Converges to 0, that is Therefore, when t≥T d hour, and converges to zero, so the aggregate interference can be estimated by the following formula:

5. The finite time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system according to claim 4, characterized in that: The integral terminal sliding mode controller based on the super-twisted algorithm state observer is as follows: The tracking error of the dual-converter doubly-fed wind turbine generator system is expressed as: in, is the system tracking error; The integral terminal sliding surface designed for the four error systems is shown below: in, c i >0,0<α i <1(i=1,2..5), Based on the operating characteristics of the Double-VSC DFIG system, this paper adopts the exponential control rate The FT-SMC controller is as follows: among them i >0,k i >0, i=1,2..

4.

6. A finite-time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system, characterized in that: include: A dynamic model building module is configured as a direct speed loop system model of a dual-converter doubly-fed wind turbine generator; The disturbance term determination module is configured to set four concentrated disturbance terms based on the direct speed loop system model of the double-fed wind turbine generator with dual converters; The state estimation module is configured to construct a finite-time disturbance observer based on the hyperwarp algorithm to observe the four concentrated disturbance terms and prove the convergence of the observer; The anti-interference control module is configured to use an integral terminal sliding mode controller to achieve finite-time convergence of the tracking error while performing real-time interference compensation on the disturbance estimation result, thereby realizing finite-time anti-interference control of the dual-converter doubly-fed wind turbine generator.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the finite-time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system according to any one of claims 1 to 7 are implemented.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the finite-time anti-interference control method for a doubly-fed wind turbine generator DC grid-connected system are implemented as described in any one of claims 1 to 5.

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