Network configuration type wind turbine control method based on adaptive power correction compensation

Abstract

The application belongs to the technical field of wind power generation, and discloses a network-constructing type wind turbine control method based on adaptive power correction compensation, and a network-constructing type wind turbine control system based on adaptive power correction compensation is constructed; an active-frequency control algorithm of the network-constructing type wind turbine control system based on adaptive power correction compensation is determined, a small disturbance equation is determined according to a virtual rotor motion equation; a reactive-voltage regulation equation of the network-constructing type wind turbine control system based on adaptive power correction compensation is determined, a compensation voltage drop of adaptive virtual impedance is substituted, a voltage target value of a wind turbine grid-connected point voltage when a short circuit occurs is corrected, a modulation signal of a grid-side converter is obtained, and active support to a virtual damping coefficient and a virtual damping power of a system is realized. The application is suitable for stability analysis of a grid-connected system control parameter of a network-constructing type wind turbine, the voltage target value of the wind turbine grid-connected point voltage is corrected, transient voltage is improved, and voltage support is provided when a short circuit occurs at the grid side.

Description

Technical Field

[0001] This invention belongs to the field of wind power generation technology and relates to a grid-type wind turbine control method, specifically a grid-type wind turbine control method based on adaptive power correction compensation. Background Technology

[0002] Energy is a crucial foundation for national economic development and a fundamental material guarantee for human production and life. In recent years, with the increasing prominence of energy and environmental problems caused by the large-scale combustion of fossil fuels, wind power has become an increasingly important component of the power system. While wind power, as a clean and renewable energy source, meets the requirements of environmental protection plans, its randomness and intermittency mean that as the proportion of wind power generation capacity in the power grid gradually increases, the impact of large-scale wind farms on system stability is also gradually intensifying. Furthermore, frequency variations caused by changes in system load are becoming more drastic, making the power grid more prone to instability.

[0003] Among existing control methods for improving the stability of wind turbine systems, based on whether or not a PLL is used to achieve synchronization with the grid, control strategies are divided into two categories: PLL-based droop control and virtual inertia control. Droop control enables wind power to achieve primary frequency regulation of the system, but lacks sufficient dynamic response characteristics to the grid. Virtual inertia control can reduce the control conflict with MPPT (Multi-Pulse Test-Pulse Control) and achieves inertial response capability to the system by releasing the wind turbine rotor energy during disturbances; however, its grid-synchronized phase-locked loop mechanism also carries the risk of system instability.

[0004] To address the aforementioned issues, scholars have proposed grid-connected wind power VSG (Virtual Synchronizer Generator) systems, which offer significant advantages in improving the stability of weak power grids. Existing research primarily focuses on analyzing the VSG grid structure and its own inertia and damping enhancement capabilities, neglecting the impact of the coupling relationship between the source-end wind turbine operating characteristics and the VSG power control loop on the stability of the wind power VSG system. Therefore, analyzing the impact of wind turbine grid-connected system control parameters on grid stability characteristics and constructing a grid-connected wind turbine control method based on adaptive power correction compensation is of great significance to researchers in this field. Summary of the Invention

[0005] The purpose of this invention is to provide a grid-connected wind turbine control method based on adaptive power correction compensation. By determining the active-frequency control algorithm and the reactive-voltage regulation equation of the grid-connected wind turbine control system based on adaptive power correction compensation, the method can achieve active support for the inertia and damping of the system and improve the stability of the wind power grid-connected system.

[0006] To achieve the above objectives, the technical solution adopted by this invention is as follows:

[0007] A grid-type wind turbine control method based on adaptive power correction compensation includes the following steps:

[0008] S1. Construct a VSG-based grid-type wind turbine control system;

[0009] S2. Introduce active-frequency and reactive-voltage links into the grid-side converter of the VSG-based grid-type wind turbine control system, and construct the active-frequency control loop and the reactive-voltage control loop of the VSG-based grid-type wind turbine control system.

[0010] S3. Adaptive correction and compensation control is introduced into the active-frequency control loop and the reactive-voltage control loop of the VSG-based grid-type wind turbine control system to construct a grid-type wind turbine control system based on adaptive power correction and compensation.

[0011] S4. Determine the active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation. Based on the virtual rotor motion equation of the permanent magnet direct-drive wind turbine, determine the small disturbance equation and obtain the VSG virtual phase angle and VSG voltage amplitude.

[0012] S5. Determine the reactive power-voltage regulation equation of the grid-type wind turbine control system based on adaptive power correction compensation. According to the adaptive virtual impedance equation, obtain the compensation voltage drop of the adaptive virtual impedance in the dq coordinate system. Substitute the compensation voltage drop of the adaptive virtual impedance into the reactive power-voltage regulation equation, and correct the voltage target value of the wind turbine grid connection point voltage when a short circuit occurs through the compensation voltage drop of the adaptive virtual impedance.

[0013] S6. By correcting the target voltage value of the grid connection point voltage of the wind turbine when a short circuit occurs, the modulation signal of the grid-side converter of the grid-type wind turbine control system based on adaptive power correction compensation is obtained, thereby realizing active support for the virtual damping coefficient and virtual damping power of the system.

[0014] As a limitation, in step S1, the VSG-based grid-type wind turbine control system includes:

[0015] Wind turbines, permanent magnet direct-drive wind turbines, machine-side converters, grid-side converters, and LC filters;

[0016] The grid-side converter controls the normal operation of the wind turbine speed and the balance of power according to the MPPT algorithm, and adopts the VSG control strategy to actively support the grid frequency and voltage.

[0017] The output end of the wind turbine is connected to the input end of the permanent magnet direct-drive wind turbine, the output end of the permanent magnet direct-drive wind turbine is connected to the input end of the turbine-side converter, the output end of the turbine-side converter is connected to the input end of the grid-side converter, the output end of the grid-side converter is connected to the input end of the LC filter, and the output end of the LC filter is connected to the input end of the power grid.

[0018] As a second limitation, in step S4, the active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation includes an outer loop output estimation algorithm based on iterative learning, a vector weighted partial derivative algorithm, an adaptive correction compensation control output power limiting constraint function, and a control adaptive virtual prediction criterion function.

[0019] The outer loop output estimation algorithm based on iterative learning is obtained by formula (1):

[0020]

[0021] In the formula, P ω (k) represents the active power output of VSG at time k, P ω (k)=-k ω Δδ s k ω This is the adjustment coefficient. P at time k ω The estimated value of the control output signal of (k), φ ω (k) represents the estimated derivative at time k, and γ is the error gain at (0,1). Let Δδ be the system control output power feedback value obtained at time k through amplitude limiting and compensation algorithms. s Let e0(k) be the virtual phase angle change of VSG, and e0(k) be the estimation error of the output at time k.

[0022]

[0023] In the formula, The output power is determined by adaptive correction and compensation control at time k.

[0024] The vector weighted partial derivative algorithm is obtained from formula (3):

[0025]

[0026] In the formula, Let ε be the vector weighted partial derivative at time k, e0(k+1) be the estimation error of the output at time k+1, ε be the vector coefficient in the interval (0,1), and ξ be the weighting coefficient of the step size change of the correction system.

[0027]

[0028] In the formula, α is the positive constant of the step size factor of the estimation algorithm, and β is... The penalty coefficient for the change is used to determine the constraint strength for the step size change;

[0029] By constructing an initial value reset mechanism based on a minimum constraint using vector weighted partial derivatives, we obtain:

[0030]

[0031] In the formula, μ is the algorithm reset factor, π is the mathematical constant pi, and when k... When μ is less than or equal to μ+π, the vector weighted partial derivative algorithm resets to the initial value at time zero.

[0032] The adaptive correction compensation control output power limiting constraint function is obtained from formula (6):

[0033]

[0034] In the formula, This is the system control output power feedback value. This represents the minimum value of the system control output power feedback. This represents the maximum value of the system control output power feedback value.

[0035] right Introducing the compensation signal ρ, we get:

[0036]

[0037] In the formula, ρ(k+1) is the compensation signal at time k+1, and ρ(k) is the compensation signal at time k. The output power is adaptively corrected and compensated at time k-1;

[0038] The adaptive virtual prediction criterion function is obtained from formula (8):

[0039]

[0040] In the formula, Γ(k) represents the network iteration rate of the error weight. This refers to the derivative tracking error.

[0041] Γ(k+1)=Γ(k)+Tglog ξ / α+β (9);

[0042] In the formula, Tg is a constant, ranging from 0.015 to 0.028;

[0043]

[0044] In the formula, i and t are variables varying in the intervals (1, m) and (1, n), respectively, λ is the momentum control factor, and e 0i (k) represents the estimation error of the i-th output. For the i-th control output signal, For the i-th estimated derivative, To control the average value of the output signal, To estimate the initial value of the derivative;

[0045] Substituting formula (1) into formula (8), for Taking the partial derivative and setting it to 0, we get:

[0046]

[0047] In the formula, To estimate the average value of the derivative, Γ is the network iteration rate with error weight, and e0 is the initial error value. for The partial derivative of , where T is the time constant.

[0048] As a further limitation, in step S4, the motion equation of the virtual rotor of the permanent magnet direct-drive fan is obtained from formula (12):

[0049]

[0050] In the formula, δ s For the VSG virtual phase angle, ω vsg p is the virtual angular velocity of the VSG. ref H is the reference input power for the VSG active power control loop of the wind turbine. v P is the virtual inertia coefficient, and P is the output active power of the permanent magnet direct-drive fan after VSG control. d For virtual damping power;

[0051]

[0052] In the formula, P is the system control output power feedback value. * The output power of the permanent magnet direct-drive fan following the MPPT curve;

[0053]

[0054] In the formula, ρ1 is the air density, R is the radius of the fan blade, and ω r Let λ be the angular velocity of the wind turbine. p For the tip speed ratio, C p This is a function for the wind energy utilization coefficient.

[0055] P d =D v (ωvsg +ω n (15);

[0056] In the formula, ω n D is the angular frequency of the grid connection point voltage. v This is the virtual damping coefficient;

[0057]

[0058] In the formula: E is the VSG voltage amplitude, U0 is the grid connection point voltage of the wind turbine, and X is the grid connection impedance.

[0059] As a further limitation, in step S4, the small perturbation equation is obtained from formula (17):

[0060]

[0061] In the formula, Δδ s Δω represents the virtual phase angle change of the VSG. vsg Let Δp be the virtual angular velocity change of the VSG. ref ΔP is the change in reference input power of the VSG active power control loop of the wind turbine, and δ is the change in output active power of the permanent magnet direct-drive wind turbine after adopting VSG control. s0 The initial value of the virtual phase angle of the VSG;

[0062] Ignoring the rate of change of the fan rotor angular velocity, the change in the reference input power of the fan VSG active power control loop is:

[0063]

[0064] In the formula, The change in the system control output power feedback value;

[0065] Combining formulas (17) and (18), we get:

[0066]

[0067] In the formula, k vsg For equivalent adaptive correction and compensation control parameters;

[0068]

[0069] Further resolution yields the second-order equations of motion for the system:

[0070]

[0071] As a third limitation, in step S5, the reactive power-voltage regulation equation of the grid-type wind turbine control system based on adaptive power correction compensation is obtained by formula (23):

[0072]

[0073] In the formula, K s The reactive equivalent inertia coefficient, ΔU ref Q is the reactive power-voltage regulation quantity. ref Q is the reference reactive power for the VSG system of a permanent magnet direct-drive wind turbine. e For the system to output reactive power, K v U is the reactive power-voltage regulation coefficient. d U represents the effective value of the d-axis voltage in the dq coordinate system. vd For the virtual internal potential, U ωd This is a virtual compensation voltage;

[0074]

[0075] In the formula, i d This represents the effective value of the d-axis current.

[0076]

[0077] In the formula, ΔU d This represents the voltage change at the wind turbine's grid connection point. When a short circuit occurs, U d The target voltage value.

[0078] As a further limitation, in step S5, the adaptive virtual impedance equation is obtained from formula (26):

[0079]

[0080] In the formula, Z v (s) is the adaptive virtual impedance, R s For virtual resistance, L s Let s be the damping inductance and s be the Laplace operator;

[0081] The compensation voltage drop of the adaptive virtual impedance is obtained by formula (27):

[0082]

[0083] In the formula, i q ω is the effective value of the q-axis current, and ω is the system angular frequency;

[0084] Substituting formula (27) into formula (23), we get:

[0085]

[0086] The present invention, by adopting the above-described technical solution, achieves the following technical advancements compared to existing technologies:

[0087] (1) The active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation and the reactive-voltage regulation equation of the grid-type wind turbine control system based on adaptive power correction compensation realize the active support capability of the system's inertia and damping, and improve the stability of the wind power grid-connected system.

[0088] (2) The active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation in this invention requires less computation time and cost, has high practicality and good practical prospects.

[0089] (3) In view of the fact that traditional VSG does not have low voltage ride-through capability, this invention introduces adaptive correction and compensation control into the active-frequency control loop and the reactive-voltage control loop of the VSG-based grid-type wind turbine control system. This can correct the voltage control input signal in real time and improve the system's transient voltage drop support capability.

[0090] (4) This invention introduces a current feedback loop in voltage control by compensating the voltage drop of the adaptive virtual impedance. The voltage drop of the output current on the virtual impedance is used to continuously correct the voltage target value of the wind turbine grid connection point when a short circuit occurs, thereby improving the transient voltage and thus playing a role in voltage support when a short circuit or asymmetrical short circuit occurs on the grid side.

[0091] In summary, this invention is applicable to the stability analysis of the grid connection of grid-connected wind turbine control parameters, and can provide engineering guidance for the formulation of stable control strategies for grid-connected wind turbine systems. Attached Figure Description

[0092] Figure 1 The diagram shown is a structural block diagram of the active-frequency link and the reactive-voltage link according to an embodiment of the present invention.

[0093] Figure 2 The diagram shown is a structural block diagram of a grid-type wind turbine control system based on adaptive power correction compensation according to an embodiment of the present invention.

[0094] Figure 3 The figure shown is a simulation model of a grid-connected wind turbine system based on adaptive power correction compensation according to an embodiment of the present invention.

[0095] Figure 4 The figure shows a comparison curve of the active power response of tie line B5-B6 between the embodiment of the present invention and the traditional grid-type wind turbine control method at a wind speed of 10 m / s.

[0096] Figure 5 The figure shows a comparison curve of the bus B2 voltage at a wind speed of 10 m / s between the embodiment of the present invention and the traditional grid-type wind turbine control method;

[0097] Figure 6The figure shows a comparison curve of the active power response of synchronous generator G2 at a wind speed of 10 m / s between the embodiment of the present invention and the traditional grid-type wind turbine control method.

[0098] Figure 7 The figure shows a comparison curve of the active power response of tie line B5-B6 under variable wind speed between the embodiment of the present invention and the traditional grid-type wind turbine control method.

[0099] Figure 8 The figure shows a comparison curve of the active power response of the 10m / s wind speed tie line B5-B6 between the embodiment of the present invention and the traditional grid-type wind turbine control method under variable wind speed control.

[0100] Figure 9 The figure shows a comparison curve of the active power response of the synchronous generator G3 under varying wind speeds between the embodiment of the present invention and the traditional grid-type wind turbine control method. Detailed Implementation

[0101] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0102] Example: A grid-type wind turbine control method based on adaptive power correction compensation

[0103] In practical applications, the use of VSG-based grid-connected wind turbine control systems carries the risk of reducing the stability of the power grid during small disturbances. A comprehensive evaluation of the stable operation capability of wind turbine grid-connected systems incorporating VSG control is crucial for perfecting the PMSG-friendly grid-connection function of permanent magnet direct-drive wind turbines. Therefore, this embodiment provides a grid-connected wind turbine control method based on adaptive power correction compensation, including the following steps:

[0104] S1. Construct a VSG-based grid-type wind turbine control system;

[0105] The VSG-based grid-connected wind turbine control system includes: a wind turbine, a permanent magnet direct-drive wind turbine, a turbine-side converter, a grid-side converter, and an LC filter. The grid-side converter controls the normal operation of the wind turbine speed and the balance of power according to the MPPT algorithm, and adopts the VSG control strategy to actively support the grid frequency and voltage.

[0106] The output end of the wind turbine is connected to the input end of the permanent magnet direct-drive wind turbine. The output end of the permanent magnet direct-drive wind turbine is connected to the input end of the turbine-side converter. The output end of the turbine-side converter is connected to the input end of the grid-side converter. The output end of the grid-side converter is connected to the input end of the LC filter. The output end of the LC filter is connected to the input end of the power grid.

[0107] S2, such as Figure 1As shown, active-frequency and reactive-voltage links are introduced into the grid-side converter of the VSG-based grid-type wind turbine control system to construct the active-frequency control loop and the reactive-voltage control loop of the VSG-based grid-type wind turbine control system.

[0108] The active-frequency component is used to simulate the inertia and primary frequency regulation characteristics of a permanent magnet direct-drive fan. Figure 1 In the middle, H v For virtual inertia coefficient, D v ω is the virtual damping coefficient. n ω is the grid connection point voltage angular frequency, and P is the output active power of the permanent magnet direct drive fan after VSG control.

[0109] S3. Adaptive correction and compensation control (denoted as ACCC) is introduced into the active-frequency control loop and the reactive-voltage control loop of the VSG-based grid-type wind turbine control system to construct a grid-type wind turbine control system based on adaptive power correction and compensation; such as Figure 2 As shown in the figure, P * U0 represents the output power of the permanent magnet direct-drive fan following the MPPT curve, L and C are the filter inductor and filter capacitor, respectively, and U0 is the voltage at the fan's grid connection point.

[0110] S4. Determine the active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation. Based on the virtual rotor motion equation of the permanent magnet direct-drive wind turbine, determine the small disturbance equation and obtain the VSG virtual phase angle and VSG voltage amplitude.

[0111] In this step, the active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation includes an outer-loop output estimation algorithm based on iterative learning, a vector weighted partial derivative algorithm, an adaptive correction compensation control output power limiting constraint function, and a control adaptive virtual prediction criterion function. By using the vector weighted partial derivative algorithm for derivative compensation control, the repetitive disturbances existing in the system are compensated. By increasing the number of downlinks, the output error of the system is continuously reduced until it completely tracks the expected output of the system.

[0112] I. The outer loop output estimation algorithm based on iterative learning is obtained from formula (1):

[0113]

[0114] In the formula, P ω (k) represents the active power output of VSG at time k, P ω (k)=-k ω Δδ s k ω This is the adjustment coefficient. P at time k ω The estimated value of the control output signal of (k), φ ω (k) represents the estimated derivative at time k, and γ is the error gain at (0,1). Let Δδ be the system control output power feedback value obtained at time k through amplitude limiting and compensation algorithms. s Let e0(k) be the virtual phase angle change of VSG, and e0(k) be the estimation error of the output at time k.

[0115]

[0116] In the formula, The output power is determined by adaptive correction and compensation control at time k.

[0117] 2. By optimizing and compensating the outer loop output estimation algorithm of iterative learning with lead-lag tracking, the vector weighted partial derivative algorithm is obtained by formula (3):

[0118]

[0119] In the formula, Let ε be the vector weighted partial derivative at time k, e0(k+1) be the estimation error of the output at time k+1, ε be the vector coefficient in the interval (0,1), and ξ be the weighting coefficient of the step size change of the correction system.

[0120]

[0121] In the formula, α is the positive constant of the step size factor of the estimation algorithm, and β is... The penalty coefficient for the change is used to determine the constraint strength for the step size change; where the larger ξ is, the greater the penalty coefficient. The faster the convergence speed, the better. If the value is too large, the system is prone to instability due to convergence overshoot;

[0122] Furthermore, to improve the ability to track time-varying parameters during the optimization and compensation process, an initial value reset mechanism based on minimum constraint is constructed for the vector weighted partial derivatives, resulting in:

[0123]

[0124] In the formula, μ is the algorithm reset factor, π is the mathematical constant pi, and when k... When μ is less than or equal to μ+π, the vector weighted partial derivative algorithm resets to the initial value at time zero.

[0125] Since the normal operation of the grid-type wind turbine control system based on adaptive power correction compensation is threatened by disturbances and serious faults, limiting the output of the adaptive correction compensation control within a certain range can prevent excessive control force and eliminate the adverse effects on the normal control function of the permanent magnet direct-drive wind turbine. The output power limiting constraint function of the adaptive correction compensation control is obtained by formula (6):

[0126]

[0127] In the formula, This is the system control output power feedback value. This represents the minimum value of the system control output power feedback. This represents the maximum value of the system control output power feedback value.

[0128] right Introducing the compensation signal ρ, we get:

[0129]

[0130] In the formula, ρ(k+1) is the compensation signal at time k+1, and ρ(k) is the compensation signal at time k. The output power is adaptively corrected and compensated at time k-1;

[0131] IV. Obtaining the system control output power feedback value After the disturbance regulation of the grid-type wind turbine control system based on adaptive power correction compensation ends and the wind power system returns to steady-state operation, the system control output power feedback value based on adaptive correction compensation control needs to be adjusted. Reduced to 0 to ensure normal operation of wind power;

[0132] The adaptive virtual prediction is dynamically refreshed according to the negative gradient direction of the error weights to approximate the controlled target. The momentum factor in the negative gradient direction searches for extreme values ​​on the error surface to converge to local outliers, smoothing the learning trajectory of the negative gradient error weights and accelerating algorithm convergence. Therefore, the following adaptive virtual prediction criterion function is established.

[0133] The adaptive virtual prediction criterion function is obtained from formula (8):

[0134]

[0135] In the formula, Γ(k) represents the network iteration rate of the error weight. This refers to the derivative tracking error.

[0136] Γ(k+1)=Γ(k)+Tglog ξ / α+β (9);

[0137] In the formula, Tg is a constant, ranging from 0.015 to 0.028;

[0138]

[0139] In the formula, i and t are variables varying in the intervals (1, m) and (1, n), respectively, λ is the momentum control factor, and e 0i (k) represents the estimation error of the i-th output. For the i-th control output signal, For the i-th estimated derivative, To control the average value of the output signal, To estimate the initial value of the derivative;

[0140] Substituting formula (1) into formula (8), for Taking the partial derivative and setting it to 0, we get:

[0141]

[0142] In the formula, To estimate the average value of the derivative, Γ is the network iteration rate with error weight, and e0 is the initial error value. for The partial derivatives, where T is the time constant;

[0143] The active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation consists of formulas (1) to (11). The driving data required for adaptive correction compensation control is only obtained by iteratively obtaining its input and output data. The active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation requires less computation time and cost, thus it has high practicality and good practical prospects.

[0144] In this step, the motion equation of the virtual rotor of the permanent magnet direct-drive fan is obtained from formula (12):

[0145]

[0146] In the formula, δ s For the VSG virtual phase angle, ω vsg p is the virtual angular velocity of the VSG. ref H is the reference input power for the VSG active power control loop of the wind turbine. v P is the virtual inertia coefficient, and P is the output active power of the permanent magnet direct-drive fan after VSG control. d For virtual damping power;

[0147]

[0148] In the formula, P is the system control output power feedback value. * The output power of the permanent magnet direct-drive fan following the MPPT curve;

[0149]

[0150] In the formula, ρ1 is the air density, R is the radius of the fan blade, and ω r Let λ be the angular velocity of the wind turbine. p For the tip speed ratio, C p This is a function for the wind energy utilization coefficient.

[0151] P d =D v (ω vsg +ω n (15);

[0152] In the formula, ω n D is the angular frequency of the grid connection point voltage. v This is the virtual damping coefficient;

[0153] The active power P output of the permanent magnet direct-drive fan after adopting VSG control is:

[0154]

[0155] In the formula: E is the VSG voltage amplitude, U0 is the grid connection point voltage of the wind turbine, and X is the grid connection impedance;

[0156] Linearizing the virtual rotor motion equation of the permanent magnet direct-drive fan in equation (12) at the equilibrium point, we obtain the small perturbation equation, which is derived from equation (17):

[0157]

[0158] In the formula, Δδ s Δω represents the virtual phase angle change of the VSG. vsg Let Δp be the virtual angular velocity change of the VSG. ref ΔP is the change in reference input power of the VSG active power control loop of the wind turbine, and δ is the change in output active power of the permanent magnet direct-drive wind turbine after adopting VSG control. s0 The initial value of the virtual phase angle of the VSG;

[0159] Ignoring the rate of change of the fan rotor angular velocity, the change in the reference input power of the fan VSG active power control loop is:

[0160]

[0161] In the formula, The change in the system control output power feedback value;

[0162] Combining formulas (17) and (18), we get:

[0163]

[0164] In the formula, k vsg For equivalent adaptive correction and compensation control parameters;

[0165]

[0166] Further resolution yields the second-order equations of motion for the system:

[0167]

[0168] Analysis of formula (21) shows that k vsg Since the active power-frequency control loop of the VSG-based grid-type wind turbine control system is always greater than zero, the introduction of adaptive correction compensation control enhances the system's stability. Setting parameters such as the network iteration rate Γ of the error weight and the weighting coefficient ξ of the step size change in the correction system ensures a leftward shift of the system's characteristic roots, further enhancing stability. Simultaneously, increasing control parameters such as the positive constant α of the step size factor in the estimation algorithm and the error gain γ located at (0,1) smooths out transient frequency fluctuations and reduces frequency overshoot after disturbances. Therefore, the grid-type wind turbine control system based on adaptive power correction compensation can significantly improve the system's stability characteristics and anti-interference capability.

[0169] S5. Determine the reactive power-voltage regulation equation of the grid-type wind turbine control system based on adaptive power correction compensation. According to the adaptive virtual impedance equation, obtain the compensation voltage drop of the adaptive virtual impedance in the dq coordinate system. Substitute the compensation voltage drop of the adaptive virtual impedance into the reactive power-voltage regulation equation, and correct the voltage target value of the wind turbine grid connection point voltage when a short circuit occurs through the compensation voltage drop of the adaptive virtual impedance.

[0170] The reactive power-voltage control link of the VSG-based grid-type wind turbine control system is used to simulate the excitation current control mode of a synchronous generator (traditional thermal power unit) to achieve voltage amplitude regulation. It has excitation regulation inertia. Therefore, the reactive power-voltage regulation equation of the VSG-based grid-type wind turbine control system is:

[0171]

[0172] Among them, K s K is the reactive equivalent inertia coefficient. v The reactive power-voltage regulation coefficient, ΔU ref Q is the reactive power-voltage regulation quantity. ref Q is the reference reactive power for the direct-drive wind turbine VSG system. e For the system to output reactive power, Ud U represents the effective value of the d-axis voltage in the dq coordinate system. vd This represents the virtual internal potential.

[0173] In this step, adaptive correction compensation control is introduced into the reactive power-voltage control loop of the VSG-based grid-type wind turbine control system. Compensation is achieved through additional virtual voltage control of the adaptive correction compensation control algorithm. Therefore, the reactive power-voltage regulation equation of the grid-type wind turbine control system based on adaptive power correction compensation is obtained by formula (23):

[0174]

[0175] In the formula, U ωd This is a virtual compensation voltage;

[0176]

[0177] In the formula, i d This represents the effective value of the d-axis current.

[0178] When the VSG-based grid-connected wind turbine control system is operating normally, the VSG output voltage tracks the grid-side voltage in real time. When a short circuit or asymmetrical short circuit occurs on the grid side, i.e., a single-phase, two-phase, or three-phase short-circuit ground fault, the impedance of the external line decreases, the voltage drops significantly, and the voltage change at the wind turbine grid connection point ΔU d for:

[0179]

[0180] In the formula, ΔU d This represents the voltage change at the wind turbine's grid connection point. When a short circuit occurs, U d The target voltage value.

[0181] Adaptive virtual impedance is used to compensate for ΔU d The voltage support capability of the VSG-based grid-type wind turbine control system is obtained by the adaptive virtual impedance equation from formula (26):

[0182] Z v (s)=-R s +sL s (26);

[0183] In the formula, Z v (s) is the adaptive virtual impedance, R s For virtual resistance, L s Let s be the damping inductance and s be the Laplace operator;

[0184] The compensation voltage drop of the adaptive virtual impedance is obtained in the dq coordinate system. The compensation voltage drop of the adaptive virtual impedance is obtained by formula (27):

[0185]

[0186] In the formula, i q ω is the effective value of the q-axis current, and ω is the system angular frequency;

[0187] Substituting formula (27) into formula (23), we get:

[0188]

[0189] S6. By correcting the target voltage value of the grid connection point voltage of the wind turbine when a short circuit occurs, the modulation signal of the grid-side converter of the grid-type wind turbine control system based on adaptive power correction compensation is obtained, so as to realize active support for the virtual damping coefficient and virtual damping power of the system.

[0190] The essence of adaptive virtual impedance compensation voltage drop is to introduce a current feedback loop into the voltage control, and use the voltage drop of the output current on the virtual impedance to continuously correct the voltage target value of the wind turbine grid connection point when a short circuit occurs, thereby improving the transient voltage and thus playing a voltage support role when a short circuit or asymmetrical short circuit occurs on the grid side.

[0191] The following is a calculation example analysis of this embodiment:

[0192] This embodiment is built based on MATLAB / Simulink. Figure 3 The simulation model shown contains three synchronous generators, each with a rated capacity of 600MW, and a wind farm connected in parallel by 120 PMSGs, each with a rated capacity of 1.5MW. The wind farm is connected to the system via bus B2, with load L1 of 156MW and load L2 of 98MW.

[0193] ① Control effect under constant wind speed

[0194] The wind turbine generators, namely three synchronous generators each with a rated capacity of 600MW, are operated at a wind speed of 10m / s. A fault is set in one circuit between bus B5 and bus B6 after 2 seconds, and the fault is cleared after 2.5 seconds. To verify the effectiveness of this embodiment, it is compared with a traditional grid-type wind turbine control method, such as... Figure 4 The figure shows the active power response comparison curves of tie lines B5-B6; as shown. Figure 5 The figure shows the voltage comparison curve of bus B2, as follows: Figure 6 The figure shows the active power response comparison curves of synchronous generator G2. Here, ACCC-VSG represents the grid-type wind turbine control method based on adaptive power correction compensation in this embodiment, and VSG represents the traditional grid-type wind turbine control method.

[0195] Depend on Figures 4-6As can be seen, under the two control methods mentioned above, the ACCC-VSG control method for grid-type wind turbines, based on adaptive power correction compensation, significantly dampes power oscillations compared to the traditional VSG control method, thus improving system damping. Simultaneously, ACCC-VSG greatly reduces interference with voltage control, allowing the voltage to stabilize more quickly and ensuring voltage stability. Therefore, the grid-type wind turbine control method based on adaptive power correction compensation proposed in this embodiment effectively improves voltage stability while damping oscillations.

[0196] ② Control effect under variable wind speed

[0197] Under wind speed variations ranging from 5 m / s to 15 m / s, the parameters of the adaptive correction compensation control remain unchanged in the grid-type wind turbine control method based on adaptive power correction compensation, which operates under the same fault conditions as under constant wind speed control. To verify the effectiveness of this embodiment, it is compared with the traditional grid-type wind turbine control method. Figure 7 The figure shows the active power response comparison curves of tie lines B5-B6 under varying wind speeds, as shown below. Figure 8 The comparison curves of the active power response of tie lines B5-B6 at a wind speed of 10 m / s are shown below. Figure 9 The figure shows the active power response curves of synchronous generator G3 under varying wind speeds.

[0198] Depend on Figures 7-9 It can be seen that under variable wind speed conditions, the ACCC-VSG grid-connected wind turbine control method, based on adaptive power correction compensation, effectively mitigates power oscillations through its excellent self-disruption and anti-interference capabilities. The power of tie lines B5-B6 and the synchronous generator recovers to stability within a short effective time. Both the ACCC-VSG and traditional grid-connected wind turbine control methods provide positive damping for the system; however, compared to the traditional VSG method, the ACCC-VSG method significantly improves the suppression of tie line power oscillations and can restore the system to a stable state more quickly. In contrast, the traditional VSG method takes 16 seconds to stabilize. Therefore, the adaptive power correction compensation-based grid-connected wind turbine control method in this embodiment is superior to the traditional method, rapidly suppressing low-frequency oscillations. Thus, the adaptive power correction compensation-based grid-connected wind turbine control method in this embodiment can effectively improve the stability of the wind power grid-connected system.

[0199] It should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A control method for grid-type wind turbines based on adaptive power correction compensation, characterized in that, Includes the following steps: S1. Construct a VSG-based grid-type wind turbine control system; S2. Introduce active-frequency and reactive-voltage links into the grid-side converter of the VSG-based grid-type wind turbine control system, and construct the active-frequency control loop and the reactive-voltage control loop of the VSG-based grid-type wind turbine control system. S3. Adaptive correction and compensation control is introduced into the active-frequency control loop and the reactive-voltage control loop of the VSG-based grid-type wind turbine control system to construct a grid-type wind turbine control system based on adaptive power correction and compensation. S4. Determine the active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation. Based on the virtual rotor motion equation of the permanent magnet direct-drive wind turbine, determine the small disturbance equation and obtain the VSG virtual phase angle and VSG voltage amplitude. S5. Determine the reactive power-voltage regulation equation of the grid-type wind turbine control system based on adaptive power correction compensation. According to the adaptive virtual impedance equation, obtain the compensation voltage drop of the adaptive virtual impedance in the dq coordinate system. Substitute the compensation voltage drop of the adaptive virtual impedance into the reactive power-voltage regulation equation, and correct the voltage target value of the wind turbine grid connection point voltage when a short circuit occurs through the compensation voltage drop of the adaptive virtual impedance. S6. By correcting the target voltage value of the grid connection point voltage of the wind turbine when a short circuit occurs, the modulation signal of the grid-side converter of the grid-type wind turbine control system based on adaptive power correction compensation is obtained, thereby realizing active support for the virtual damping coefficient and virtual damping power of the system.

2. The grid-type wind turbine control method based on adaptive power correction compensation according to claim 1, characterized in that, In step S1, the VSG-based grid-type wind turbine control system includes: Wind turbines, permanent magnet direct-drive wind turbines, machine-side converters, grid-side converters, and LC filters; The grid-side converter controls the normal operation of the wind turbine speed and the balance of power according to the MPPT algorithm, and adopts the VSG control strategy to actively support the grid frequency and voltage. The output end of the wind turbine is connected to the input end of the permanent magnet direct-drive wind turbine, the output end of the permanent magnet direct-drive wind turbine is connected to the input end of the turbine-side converter, the output end of the turbine-side converter is connected to the input end of the grid-side converter, the output end of the grid-side converter is connected to the input end of the LC filter, and the output end of the LC filter is connected to the input end of the power grid.

3. The grid-type wind turbine control method based on adaptive power correction compensation according to claim 1, characterized in that, In step S4, the active-frequency control algorithm of the grid-type wind turbine control system based on adaptive power correction compensation includes an outer loop output estimation algorithm based on iterative learning, a vector weighted partial derivative algorithm, an adaptive correction compensation control output power limiting constraint function, and a control adaptive virtual prediction criterion function. The outer loop output estimation algorithm based on iterative learning is obtained by formula (1): In the formula, P ω (k) represents the active power output of VSG at time k, P ω (k)=-k ω Δδ s k ω This is the adjustment coefficient. P at time k ω The estimated value of the control output signal of (k), φ ω (k) represents the estimated derivative at time k, and γ is the error gain at (0,1). Let Δδ be the system control output power feedback value obtained at time k through amplitude limiting and compensation algorithms. s Let e0(k) be the virtual phase angle change of VSG, and e0(k) be the estimation error of the output at time k. In the formula, The output power is determined by adaptive correction and compensation control at time k. The vector weighted partial derivative algorithm is obtained from formula (3): In the formula, Let ε be the vector weighted partial derivative at time k, e0(k+1) be the estimation error of the output at time k+1, ε be the vector coefficient in the interval (0,1), and ξ be the weighting coefficient of the step size change of the correction system. In the formula, α is the positive constant of the step size factor of the estimation algorithm, and β is... The penalty coefficient for the change is used to determine the constraint strength for the step size change; By constructing an initial value reset mechanism based on a minimum constraint using vector weighted partial derivatives, we obtain: In the formula, μ is the algorithm reset factor, π is the mathematical constant pi, and when k... When μ is less than or equal to μ+π, the vector weighted partial derivative algorithm resets to the initial value at time zero. The adaptive correction compensation control output power limiting constraint function is obtained from formula (6): In the formula, This is the system control output power feedback value. This represents the minimum value of the system control output power feedback. This represents the maximum value of the system control output power feedback value. right Introducing the compensation signal ρ, we get: In the formula, ρ(k+1) is the compensation signal at time k+1, and ρ(k) is the compensation signal at time k. The output power is adaptively corrected and compensated at time k-1; The adaptive virtual prediction criterion function is obtained from formula (8): In the formula, Γ(k) represents the network iteration rate of the error weight. This refers to the derivative tracking error; Γ(k+1)=Γ(k)+Tglog ξ / α+β (9); In the formula, Tg is a constant, ranging from 0.015 to 0.028; In the formula, i and t are variables varying in the intervals (1, m) and (1, n), respectively, λ is the momentum control factor, and e 0i (k) represents the estimation error of the i-th output. For the i-th control output signal, For the i-th estimated derivative, To control the average value of the output signal, To estimate the initial value of the derivative; Substituting formula (1) into formula (8), for Taking the partial derivative and setting it to 0, we get: In the formula, To estimate the average value of the derivative, Γ is the network iteration rate with error weight, and e0 is the initial error value. for The partial derivative of , where T is the time constant.

4. The grid-type wind turbine control method based on adaptive power correction compensation according to claim 3, characterized in that, In step S4, the motion equation of the virtual rotor of the permanent magnet direct-drive fan is obtained from formula (12): In the formula, δ s For the VSG virtual phase angle, ω vsg p is the virtual angular velocity of the VSG. ref H is the reference input power for the VSG active power control loop of the wind turbine. v P is the virtual inertia coefficient, and P is the output active power of the permanent magnet direct-drive fan after VSG control. d For virtual damping power; In the formula, P is the system control output power feedback value. * The output power of the permanent magnet direct-drive fan following the MPPT curve; In the formula, ρ1 is the air density, R is the radius of the fan blade, and ω r Let λ be the angular velocity of the wind turbine. p For the tip speed ratio, C p This is a function for the wind energy utilization coefficient. P d =D v (oh vsg +oh n ) (15); In the formula, ω n D is the angular frequency of the grid connection point voltage. v This is the virtual damping coefficient; In the formula: E is the VSG voltage amplitude, U0 is the grid connection point voltage of the wind turbine, and X is the grid connection impedance.

5. The grid-type wind turbine control method based on adaptive power correction compensation according to claim 4, characterized in that, In step S4, the small perturbation equation is obtained from formula (17): In the formula, Δδ s Δω represents the virtual phase angle change of the VSG. vsg Let Δp be the virtual angular velocity change of the VSG. ref ΔP is the change in reference input power of the VSG active power control loop of the wind turbine, and δ is the change in output active power of the permanent magnet direct-drive wind turbine after adopting VSG control. s0 The initial value of the virtual phase angle of the VSG; Ignoring the rate of change of the fan rotor angular velocity, the change in the reference input power of the fan VSG active power control loop is: In the formula, The change in the system control output power feedback value; Combining formulas (17) and (18), we get: In the formula, k vsg For equivalent adaptive correction and compensation control parameters; Further resolution yields the second-order equations of motion for the system:

6. The grid-type wind turbine control method based on adaptive power correction compensation according to claim 1, characterized in that, In step S5, the reactive power-voltage regulation equation of the grid-type wind turbine control system based on adaptive power correction compensation is obtained by formula (23): In the formula, K s The reactive equivalent inertia coefficient, ΔU ref Q is the reactive power-voltage regulation quantity. ref Q is the reference reactive power for the VSG system of a permanent magnet direct-drive wind turbine. e For the system to output reactive power, K v U is the reactive power-voltage regulation coefficient. d U represents the effective value of the d-axis voltage in the dq coordinate system. vd For the virtual internal potential, U ωd This is a virtual compensation voltage; In the formula, i d This represents the effective value of the d-axis current. In the formula, ΔU d This represents the voltage change at the wind turbine's grid connection point. When a short circuit occurs, U d The target voltage value.

7. The grid-type wind turbine control method based on adaptive power correction compensation according to claim 6, characterized in that, In step S5, the adaptive virtual impedance equation is obtained from formula (26): Z v (s)=-R s +sL s (26); In the formula, Z v (s) is the adaptive virtual impedance, R s For virtual resistance, L s Let s be the damping inductance and s be the Laplace operator; The compensation voltage drop of the adaptive virtual impedance is obtained by formula (27): In the formula, i q ω is the effective value of the q-axis current, and ω is the system angular frequency; Substituting formula (27) into formula (23), we get:

Images