A method, system, medium, and processor for high voltage ride-through adaptive control of doubly-fed wind turbines.

Abstract

This application discloses a data-driven, active-reactive power coordinated adaptive control method, system, medium, and processor for high-voltage ride-through of doubly-fed induction generator (DFIG) wind turbines, belonging to the field of wind power control technology. Addressing the problems of traditional methods relying on precise turbine models and difficulty adapting to equipment diversity and parameter confidentiality, this invention constructs a dynamic linearized model of grid connection point voltage and reactive power using real-time data. It utilizes a pseudo-gradient estimation update law and a model-free adaptive control law to calculate reactive power reference values ​​online. During high-voltage ride-through, reactive power is preferentially adjusted to support voltage recovery, while active power output is coordinated and adjusted under converter capacity constraints, achieving adaptive voltage control without relying on precise models. This invention has advantages such as fast response, strong adaptability, and simple and reliable algorithm, effectively improving the high-voltage ride-through capability of DFIG wind turbines and grid voltage stability during grid faults.

Description

Technical Field

[0001] This invention relates to the field of wind power control technology, and in particular to a high-voltage ride-through adaptive control method, system, medium, and processor for doubly-fed wind turbines. Background Technology

[0002] Large-scale wind power bases are centrally transmitted via ultra-high-voltage direct current (UHVDC) transmission, which is the dominant form of wind power development and utilization in my country. Large-scale wind power is connected to the grid through power electronic interface equipment, resulting in a "dual-high" power system characteristic of a high proportion of new energy access and a high proportion of power electronic equipment in the sending-end AC grid. However, due to commutation failures or blocking faults in the DC system, near-field wind turbine overvoltage disconnection accidents can occur, seriously threatening the safe and stable operation of the sending-end grid. The national standard GB / T36995-2018, "Wind Turbine Generator Sets—Test Procedure for Fault Voltage Ride-Through Capability," clearly requires wind turbines to have fault ride-through capability under specified high-voltage scenarios, i.e., the high-voltage ride-through capability of the wind turbines.

[0003] Current high-voltage ride-through strategies for wind turbines include over-limit protection under high-voltage conditions, active turbine control (such as turbine reactive current / power support for the system), and coordinated control with external reactive power compensation equipment. Some researchers have focused on improving rotor-side crowbar resistance, connecting chopper unloading circuits to the DC bus side, and rotor current demagnetization to suppress rotor overcurrent and DC bus overvoltage. Others have studied the dynamics of rotor-side converters and grid-side converters during high-voltage processes, making full use of converter capacity to provide inductive reactive power support to the system.

[0004] However, the above strategies are all based on the premise of having detailed models and parameters of doubly fed wind turbines. However, the diversity of doubly fed wind turbine equipment structures and the confidentiality of parameter models by manufacturers pose challenges to traditional high voltage ride-through strategies based on accurate parameter models.

[0005] Therefore, there is a need for a high-voltage ride-through adaptive control method, system, medium, and processor for doubly-fed wind turbines. Summary of the Invention

[0006] To address the problem that existing high-voltage ride-through control strategies for doubly-fed induction generator (DFIG) wind turbines rely on precise physical models and parameters, while in practice, DFIG equipment structures are diverse and manufacturers keep their model parameters confidential, making traditional control methods based on accurate models difficult to apply, this invention provides an adaptive high-voltage ride-through control method, system, medium, and processor for DFIG wind turbines. This method is entirely data-driven, independent of traditional DFIG control models, and can quickly track the target voltage value, effectively reducing the grid connection point voltage. It features a simple algorithm structure, low computational load, and high adaptability. The specific technical solution is as follows: A high-voltage ride-through adaptive control method for doubly-fed wind turbines includes: S1: A linearized model is constructed based on the real-time operating data of the doubly fed wind turbine. The linearized model is based on the pseudo-gradient estimate and is used to reflect the dynamic relationship between the grid connection point voltage and the output reactive power. S2: Determine the update law for the pseudo-gradient estimate; S3: Combine the update law of the pseudo-gradient estimate and the linearized model to determine the model-free adaptive control law of the doubly fed wind turbine; S4: Determine the reference values ​​of active power and reactive power under high voltage ride-through state based on the model-free adaptive control law; S5: Design an active-reactive power coordination strategy for the output of the doubly-fed wind turbine under high-voltage ride-through conditions, and determine the final active power reference value and reactive power reference value used for feedback control based on the coordination strategy.

[0007] Furthermore, in step S1, the linearized model is as follows: ; in, and These are the grid connection voltages of the doubly-fed wind turbines at times k+1 and k, respectively. and These represent the reactive power output of the doubly-fed wind turbine at times k and k-1, respectively. This is the pseudo gradient estimate at time k.

[0008] Furthermore, in step S2, determining the update law for the pseudo-gradient estimate includes the following steps: S21: The nonlinear dynamic relationship between the voltage change at the grid connection point of the doubly-fed wind turbine and the output reactive power change is locally linearized based on pseudo-gradient at each sampling time as follows: ; ; ; in, The gradient at time k is a pseudo gradient; This represents the change in grid connection voltage at time k+1. Let k be the change in reactive power at time k; S22: Pseudo-gradient analysis using real-time data To make an estimate, the following error function is defined. : ; in, As a penalty factor; S23: Regarding the error function Regarding pseudo-gradient estimates Taking the derivative and setting it to zero yields the pseudo gradient estimate. The update law is as follows: ; in, Let be the change in reactive power output of the doubly-fed wind turbine at time k-1; Let k be the voltage change at the grid connection point of the doubly-fed wind turbine; This is the step size factor.

[0009] Furthermore, in step S3, the determination of the model-free adaptive control law of the doubly-fed wind turbine by combining the update law of the pseudo-gradient estimate and the linearized model includes the following steps: S31: The prediction model for the grid connection point voltage of the doubly-fed wind turbine, obtained from the linearized model, is as follows: ; S32: Define the voltage tracking error at the grid connection point of the doubly-fed wind turbine at time k+1. for: ; S33: Constructing Control Performance Indicators as follows: ; in, To control the input weighting coefficients; S34: Combine prediction model and voltage tracking error Substitution Formula, and for reactive power After taking the derivative and setting it to zero, we obtain the model-free adaptive control law: ; in, Let k be the reference value of reactive power output from the doubly-fed wind turbine; The target voltage for the doubly fed wind turbine grid connection point; To control the step size.

[0010] Furthermore, in step S4, determining the active power reference value and reactive power reference value under high-voltage ride-through state based on the model-free adaptive control law includes the following steps: S41: Real-time monitoring of grid connection point voltage amplitude When the detected voltage exceeds the preset high voltage ride-through start threshold, the wind turbine is determined to have entered the high voltage ride-through state and is switched to the active-reactive coordinated control mode. S42: Calculate the current reactive power reference value using a model-free adaptive control law. The reactive power reference value is updated using the following formula: ; in This is the target voltage value during high-voltage ride-through.

[0011] S43: Under the condition of satisfying the converter capacity constraint Under the premise of reactive power reference value, calculate active power reference value based on reactive power reference value. The formula is as follows: ; Among them, the converter capacity constraint This refers to the instantaneous capacity at which the converter can be safely used under high voltage ride-through conditions.

[0012] Furthermore, in step S5, the active-reactive power coordination strategy refers to prioritizing the achievement of reactive power regulation targets to absorb inductive reactive power to support grid voltage recovery, and then adjusting the active power output in real time according to the capacity constraints of the wind turbine converter and reactive power to ensure that the wind turbine operates within safe limits.

[0013] Furthermore, step S5 also includes: S52: Calculate the corresponding active power and reactive power reference values. Shaft current reference value , And verify whether the rotor-side and grid-side converter current limits are met. .

[0014] A high-voltage ride-through adaptive control system for doubly-fed induction generator (DFIG) wind turbines, applied to the aforementioned DFIG high-voltage ride-through adaptive control method, includes: A linear module is used to construct a linearized model based on the real-time operating data of the doubly fed wind turbine. The linearized model is based on pseudo-gradient estimates and is used to reflect the dynamic relationship between the grid connection point voltage and the output reactive power. The update module is used to determine the update law for the pseudo-gradient estimate; The fusion module is used to combine the update law of the pseudo-gradient estimate and the linearized model to determine the model-free adaptive control law of the doubly fed wind turbine. The calculation module is used to determine the active power reference value and reactive power reference value under high voltage ride-through state based on the model-free adaptive control law; The control module is used to design the active and reactive power coordination strategy for the output of the doubly fed wind turbine under high voltage ride-through conditions, and to determine the final active power reference value and reactive power reference value used for feedback control based on the coordination strategy.

[0015] A computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the above-described doubly-fed wind turbine high-voltage ride-through adaptive control method.

[0016] A processor for running a program, wherein the program executes the above-described doubly-fed wind turbine high-voltage ride-through adaptive control method during operation.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. When faced with unknown parameters such as the equipment model of the doubly fed wind turbine, the active and reactive power output of the doubly fed wind turbine can be adjusted in real time according to the system operating status to quickly track the target voltage value and effectively reduce the voltage at the grid connection point. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0019] Figure 1 A schematic diagram of a high-voltage ride-through adaptive control method for a doubly-fed wind turbine; Figure 2 This is a schematic diagram of the power system structure including a doubly-fed wind turbine in the embodiment; Figure 3 This is a schematic diagram of the model-free control signal flow in the embodiment; Figure 4 The diagram shows the voltage changes at the grid connection point before and after a fault under different control strategies in the embodiment. Figure 5 This is a schematic diagram of a high-voltage ride-through adaptive control system for a doubly-fed wind turbine. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] It should be understood that, when used in this application, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof.

[0022] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0023] It should also be further understood that the term “and / or” as used in this application refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes such combinations.

[0024] Example 1 like Figures 1 to 4 As shown, a high-voltage ride-through adaptive control method for a doubly-fed induction generator (DFIG) wind turbine includes the following steps: S1: A linearized model is constructed based on the real-time operating data of the doubly fed wind turbine. The linearized model is based on pseudo-gradient estimates and is used to reflect the dynamic relationship between the grid connection point voltage and the output reactive power.

[0025] S11: Voltage and current sensors are installed at the grid connection point of the doubly-fed wind turbine and on the DC side of the converter to fix the sampling period. (Typical value is 1ms) Synchronously acquire the following physical quantities: Instantaneous three-phase voltage values ​​at the grid connection point: ; Instantaneous values ​​of three-phase current at grid connection point: ; DC bus voltage: ; Meanwhile, the rotor speed is obtained from the main controller of the doubly fed wind turbine. and propeller pitch angle .

[0026] S12: The three-phase voltage is acquired via a phase-locked loop (PLL). Extracting the power grid synchronization rotation angle .

[0027] S13: Using the Park transformation, the electrical quantities in the three-phase stationary coordinate system (abc) are converted to the two-phase synchronous rotating coordinate system. Electrical quantities under: ; ; in, This is the Park transformation matrix.

[0028] S14: Determine the voltage amplitude at the grid connection point of the doubly-fed wind turbine based on the converted electrical quantities. and the output reactive power Active power The formula is as follows: ; ; .

[0029] S14: Construct a linearized model based on pseudo-gradient estimates to reflect the dynamic relationship between the grid connection point voltage and the output reactive power of the doubly-fed induction generator (DFIG). The model is as follows: ; in, and These are the grid connection voltages of the doubly-fed wind turbines at times k+1 and k, respectively. and These represent the reactive power output of the doubly-fed wind turbine at times k and k-1, respectively. The pseudo-gradient estimate at time k reflects the sensitivity of the doubly-fed induction generator's reactive power output to its grid connection voltage in real time. This is achieved when the doubly-fed induction generator changes its reactive power output. At that time, the voltage at the grid connection point of the doubly fed wind turbine itself... The extent of the instantaneous impact.

[0030] Furthermore, The pseudo gradient estimate of the doubly fed wind turbine control closed-loop system at time k is given. Furthermore, the doubly fed wind turbine control closed-loop system refers to the physical system covered by the single-machine level control closed loop, which uses the rotor-side and grid-side converters of a single doubly fed wind turbine as the control execution terminals and its grid connection point (PoC) as the voltage observation and control feedback point.

[0031] S15: To ensure that the control strategy operates within the equipment safety boundary, the following key state variables need to be estimated in real time: 1. Rotor current estimation: Based on the equivalent circuit of a doubly-fed induction motor, using the measured stator current... and rotational speed Estimate rotor current components and Ensure that it meets the rotor-side converter current constraints. .

[0032] 2. Apparent power monitoring: Real-time monitoring Ensure that it does not exceed the capacity of the wind turbine converter. .

[0033] Since φ(k) is unknown in the actual system, it needs to be estimated using real-time data, denoted as (as above). .

[0034] S2: Determine the update law for the pseudo-gradient estimate.

[0035] S21: Convert the grid connection voltage of the doubly fed wind turbine. Changes and output reactive power The nonlinear dynamic relationship between the changes is locally linearized based on pseudo-gradient at each sampling time as follows: ; ; ; in, It is a pseudo gradient, indicating that in Sensitivity of reactive power changes to grid connection point voltage.

[0036] S22: Due to pseudo-gradients in actual systems Unknown, pseudo gradient needs to be analyzed using real-time data. Make an estimate, denoted as The following error function is defined: ; ; ; in, , serving as a penalty factor to suppress abrupt changes in the estimated value; based on experimental fitting, the recommended values ​​for μ are as follows: Voltage change rate > 0.1 pu / 10 ms, μ ranges from 0.01 to 0.03; The voltage change rate is 0.05-0.1 pu / 10 ms, and μ is 0.03 ~ 0.07; Voltage change rate < 0.05 pu / 10 ms, μ is 0.07–0.15.

[0037] S23: Yes about Taking the derivative and setting it to zero, we obtain the recursive update law for the pseudo-gradient estimate: ; in, Let be the change in reactive power output of the doubly-fed wind turbine at time k-1; Let k be the voltage change at the grid connection point of the doubly-fed wind turbine; This is the step size factor, used to adjust the update rate. Recommended values ​​for typical scenarios are as follows: The pseudo-gradient rate of change |Δφ| > 0.05 / step. Take a value of 1.0 to 2; pseudo gradient rate of change |Δφ| 0.05 / step Take a value of 0.5 to 1.0; The pseudo-gradient rate of change |Δφ| < 0.01 / step. Take a value between 0 and 0.5.

[0038] Furthermore, , ; in, These are the minimum and maximum boundary values ​​of the pseudo-gradient, with a typical range of values: .

[0039] This update law dynamically corrects the pseudo-gradient estimate using real-time data, gradually bringing it closer to the true sensitivity. .

[0040] S3: Combine the update law of the pseudo-gradient estimate with the linearized model to determine the model-free adaptive control law of the doubly fed wind turbine.

[0041] S31: As can be seen from the linearized model, the prediction model for the grid connection point voltage of the doubly-fed wind turbine one step ahead is: ; S32: Further, define the voltage tracking error at the grid connection point of the doubly-fed wind turbine at time k+1. for: .

[0042] The control objective of the scheme is to minimize the voltage tracking error at time k+1.

[0043] S33: To minimize tracking error while avoiding reactive power in the control quantity. If the changes are too large, construct the following control performance indicators: ; in To control the input weighting coefficients, the recommended values ​​for typical scenarios are as follows: Voltage deviation | |>0.15 pu, Take a value between 0.01 and 0.05; Voltage deviation 0.05 <| | 0.15 pu, Take values ​​between 0.05 and 0.15; Voltage deviation | | 0.05 pu, Take 0.05–0.15.

[0044] S34: Substitute the prediction model and voltage tracking error formula into... and control quantity Take the derivative and set it to zero: S35: Will Substituting the expression and rearranging it, we can obtain the control law as follows: ; ; Introducing a control step size ρ to flexibly adjust the dynamic response yields a model-free adaptive control law: ; in, Let k be the reference value of reactive power output from the doubly-fed wind turbine; The target voltage for the doubly fed wind turbine grid connection point; To control the step size.

[0045] The function of model-free adaptive control law is to control the grid connection point voltage deviation in real time without requiring a precise mathematical model and internal parameters of the doubly-fed induction generator (DFIG). Based on the reactive power from the previous moment and the real-time updated pseudo-gradient estimate, the reactive power reference command to be issued at the current moment is calculated. This allows for rapid and smooth adjustment of the grid connection point voltage to the target value, thereby achieving high-voltage ride-through. This control law constitutes a closed-loop feedback controller, which does not rely on any physical equation parameters related to the wind turbine, converter, or power grid, but only on real-time measurable input / output data (V, Q) and their changing relationships. This allows for decision-making, thereby achieving the core features of "model-free" and "adaptive".

[0046] Furthermore, parameters and Design principles: 1. Stability condition: According to the theory of dynamic linearization of compact schemes, the following must be satisfied: ; 2. Robustness adjustment: parameters Recommended value for suppressing measurement noise: ; in, For voltage measurement noise variance, .

[0047] 3. Dynamic performance tuning: By simulating the voltage step response, the overshoot is... and adjustment time ms is an indicator, tuned within the following range: ; .

[0048] S4: Determine the active power reference value under high voltage ride-through condition based on the model-free adaptive control law. Reactive power reference value .

[0049] S41: Real-time monitoring of grid connection point voltage amplitude When the detected voltage exceeds the preset high voltage crossover start-up threshold (Typical value is 1.1 pu) consistently exceeding When the time is typically 10~20 ms, the wind turbine is determined to have entered the high voltage ride-through state and is switched to the active-reactive power coordinated control mode; furthermore, the threshold and target value can be set according to the technical specifications of different power grid operators.

[0050] S42: Calculate the current reactive power reference value using a model-free adaptive control law. The reactive power reference value is updated using the following formula: ; in This is the target voltage value during high-voltage ride-through, typically set to 1.0~1.1 pu.

[0051] S43: Under the condition of satisfying the converter capacity constraint Under the premise of current reactive power reference value, the active power reference value is calculated based on the current reactive power reference value, as follows: ; Converter capacity constraints It primarily serves the short-term fault process of high voltage ride-through, and is the (maximum) instantaneous capacity or short-term overload capacity that the converter can safely use under specific short-term high voltage ride-through conditions.

[0052] S5: Design an active-reactive power coordination strategy for the output of the doubly-fed induction generator (DFIG) under high-voltage ride-through conditions, and determine the final active power reference value used for feedback control based on the coordination strategy. Reactive power reference value .

[0053] S51: Design a strategy for coordinating active and reactive power output of a doubly-fed wind turbine under high-voltage ride-through conditions.

[0054] During high-voltage ride-through, the coordination strategy is as follows: prioritize achieving the reactive power regulation target to absorb inductive reactive power to support grid voltage recovery, and then adjust the active power output in real time according to the capacity constraints of the wind turbine converter and the reactive power to ensure that the wind turbine operates within safe limits.

[0055] That is, when the calculated active power reference value Even if it is lower than "the maximum active power that the doubly-fed wind turbine can generate using maximum power point tracking (MPPT) technology at the current wind speed", the active power reference value should still be used. This limits active power output by sacrificing a portion of power generation (active power) to ensure that reactive power generation is not affected and to prioritize reaching the reactive power reference value. The goal.

[0056] In an alternating current power system, reactive power is a scalar quantity, but it can be positive or negative, representing two opposite physical phenomena: Inductive reactive power (Q>0): Usually represented as positive, indicating that the load (or generator) needs to absorb lagging (inductive) reactive power from the grid to establish a magnetic field, which will cause the grid voltage to drop.

[0057] Capacitive reactive power (Q<0): Usually represented as negative, it indicates that the load (or generator) sends ahead (capacitive) reactive power to the grid, which will increase the grid voltage.

[0058] S52: Calculate the corresponding active power and reactive power reference values. Check the shaft current reference value and verify whether it meets the current limits of the rotor-side and grid-side converters. like Then reduce proportionally. and And recalculate according to the above formula. and .

[0059] S53: The calculated active power reference value Reactive power reference value The power outer loop controller, which supplies power to the rotor side of the doubly-fed induction generator and the grid-side converter, adjusts the inductive reactive power output of the doubly-fed induction generator to absorb the excess reactive power of the grid, thereby reducing the voltage and achieving active-reactive coordinated adaptive control during high-voltage ride-through.

[0060] The reason why adjusting the reactive power output of a doubly-fed induction generator (DFIG) can control the grid connection voltage is that the voltage amplitude of a local node in an AC power system is mainly determined by the reactive power balance of that node. When the grid voltage rises due to a fault, the DFIG quickly absorbs inductive reactive power through its converter, which is equivalent to removing the excess reactive power from the grid that caused the voltage rise. This directly adjusts the reactive power balance at the grid connection point, thereby reducing the voltage amplitude at that point.

[0061] S54: When After recovering to the normal range (e.g., below 1.05 pu) and maintaining this level for a certain period of time, gradually restore to the normal MPPT operating mode.

[0062] Beneficial effects: The control objective of this application is to adjust the active and reactive power output of the doubly-fed induction generator (DFIG) in real time according to the system operating status, given the unknown equipment model and parameters, so as to maintain the grid connection voltage. Track the reference value as soon as possible to effectively reduce the voltage at the grid connection point.

[0063] Specific embodiments of the present invention are as follows: We use the proposed method to... Figure 2 The system shown was verified. Taking a doubly-fed induction generator (DFIG) system as an example, the DFIG uses classic dual-loop PI control with an outer power loop and an inner current loop. The reason for the voltage rise at the grid connection point in the system is... Figure 2 A large amount of reactive power surges into the system at node 3. The method proposed in this application can be verified by comparing the system frequency waveforms before and after implementing the proposed control strategy.

[0064] The simulation calculations of the embodiments were performed using the method of the present invention, and the results are as follows: Figure 4 The changes in the grid-connected voltage of the doubly-fed induction generator (DFIG) before and after a fault are presented under different control strategies. The "nostrategies" curve represents the high-voltage ride-through strategy without a high-voltage ride-through strategy; the "traditional" curve represents the traditional high-voltage ride-through strategy with a constant reactive current proportional gain; and the "MFAC" curve represents the high-voltage ride-through strategy using model-free adaptive control with coordinated active and reactive power, i.e., the method described in this application. As can be seen from the figures, the model-free adaptive control strategy with coordinated active and reactive power can quickly track the target voltage value and effectively reduce the grid-connected voltage to 1.1 pu.

[0065] Example 2 like Figure 5 As shown, a high-voltage ride-through adaptive control system for doubly-fed induction generator (DFIG) wind turbines, applied to the aforementioned DFIG high-voltage ride-through adaptive control method, includes: A linear module is used to construct a linearized model based on the real-time operating data of the doubly fed wind turbine. The linearized model is based on pseudo-gradient estimates and is used to reflect the dynamic relationship between the grid connection point voltage and the output reactive power. The update module is used to determine the update law for the pseudo-gradient estimate; The fusion module is used to combine the update law of the pseudo-gradient estimate and the linearized model to determine the model-free adaptive control law of the doubly fed wind turbine. The calculation module is used to determine the active power reference value and reactive power reference value under high voltage ride-through state based on the model-free adaptive control law; The control module is used to design the active and reactive power coordination strategy for the output of the doubly fed wind turbine under high voltage ride-through conditions, and to determine the final active power reference value and reactive power reference value used for feedback control based on the coordination strategy.

[0066] Example 3 A computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the above-described doubly-fed wind turbine high-voltage ride-through adaptive control method.

[0067] Example 4 A processor for running a program, wherein the program executes the above-described doubly-fed wind turbine high-voltage ride-through adaptive control method during operation.

[0068] Beneficial effects: 1. When faced with unknown parameters such as the equipment model of the doubly fed wind turbine, the active and reactive power output of the doubly fed wind turbine can be adjusted in real time according to the system operating status to quickly track the target voltage value and effectively reduce the voltage at the grid connection point.

[0069] 2. It does not rely on an exact model and has strong adaptability. No need for internal turbine parameters: It adopts model-free adaptive control (MFAC), which only relies on real-time measured voltage and current data. It does not require a detailed mathematical model of the doubly fed wind turbine, and can adapt to wind turbines of different manufacturers and models, solving the problems of parameter confidentiality and model diversity.

[0070] Applicable to "high-energy-consumption" power grids: In power grids with a high proportion of new energy sources and high power electronics, the system dynamics are complex and traditional models are difficult to accurately characterize. This method has stronger adaptability and robustness.

[0071] 3. Fast control response and excellent dynamic performance Real-time updates based on pseudo-gradients: Pseudo-gradient estimates can dynamically reflect system sensitivity, enabling the controller to respond quickly to voltage changes.

[0072] Active and reactive power coordination optimization: During high-voltage ride-through, reactive power is adjusted first to support the voltage, and active power is adjusted in real time to maintain power generation capacity to the maximum extent while ensuring system stability.

[0073] 4. The algorithm has a simple structure and low computational burden. Linearized model + recursive update: avoids complex nonlinear optimization or large-scale state estimation, suitable for embedded systems or real-time control platforms.

[0074] Clear parameter tuning: It provides the stability domain and tuning suggestions for control parameters (such as ρ and λ), which facilitates engineering implementation and debugging.

[0075] 5. The system has high security and multiple protection mechanisms. Real-time constraint verification: When calculating active / reactive power reference values, the safety constraints such as converter capacity and current limits are verified in real time to ensure that the equipment operates within a safe range.

[0076] Smooth Fault Recovery: After voltage recovery, it can smoothly switch to maximum power point tracking (MPPT) mode to avoid secondary impact.

[0077] 6. It is beneficial to grid voltage stability and wind power absorption. Active voltage support: By absorbing inductive reactive power, it effectively suppresses the rise in grid connection voltage and improves the voltage stability of the power grid during faults.

[0078] Reduce grid disconnection risk: Improve the high voltage ride-through success rate of wind turbines, reduce wind turbine disconnection caused by voltage problems, and enhance the reliability of wind power grid connection and grid acceptance capacity.

[0079] This application discloses a data-driven, active-reactive power coordinated adaptive control method, system, medium, and processor for high-voltage ride-through of doubly-fed induction generator (DFIG) wind turbines, belonging to the field of wind power control technology. Addressing the problems of traditional methods relying on precise turbine models and difficulty adapting to equipment diversity and parameter confidentiality, this invention constructs a dynamic linearized model of grid connection point voltage and reactive power using real-time data. It utilizes a pseudo-gradient estimation update law and a model-free adaptive control law to calculate reactive power reference values ​​online. During high-voltage ride-through, reactive power is preferentially adjusted to support voltage recovery, while active power output is coordinated and adjusted under converter capacity constraints, achieving adaptive voltage control without relying on precise models. This invention has advantages such as fast response, strong adaptability, and simple and reliable algorithm, effectively improving the high-voltage ride-through capability of DFIG wind turbines and grid voltage stability during grid faults.

[0080] Those skilled in the art will recognize that the units of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of the invention.

[0081] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical functional division. In actual implementation, there may be other division methods, such as multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored.

[0082] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0083] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of this application.

Claims

1. A high-voltage ride-through adaptive control method for a doubly-fed induction generator (DFIG), characterized in that, include: S1: A linearized model is constructed based on the real-time operating data of the doubly fed wind turbine. The linearized model is based on the pseudo-gradient estimate and is used to reflect the dynamic relationship between the grid connection point voltage and the output reactive power. S2: Determine the update law for the pseudo-gradient estimate; S3: Combine the update law of the pseudo-gradient estimate and the linearized model to determine the model-free adaptive control law of the doubly fed wind turbine; S4: Determine the reference values ​​of active power and reactive power under high voltage ride-through state based on the model-free adaptive control law; S5: Design an active-reactive power coordination strategy for the output of the doubly-fed wind turbine under high-voltage ride-through conditions, and determine the final active power reference value and reactive power reference value used for feedback control based on the coordination strategy.

2. The high-voltage ride-through adaptive control method for doubly-fed wind turbines according to claim 1, characterized in that, In step S1, the linearized model is as follows: ； in, and These are the grid connection voltages of the doubly-fed wind turbines at times k+1 and k, respectively. and These represent the reactive power output of the doubly-fed wind turbine at times k and k-1, respectively. This is the pseudo gradient estimate at time k.

3. The high-voltage ride-through adaptive control method for doubly-fed wind turbines according to claim 2, characterized in that, In step S2, determining the update law for the pseudo-gradient estimate includes the following steps: S21: The nonlinear dynamic relationship between the voltage change at the grid connection point of the doubly-fed wind turbine and the output reactive power change is locally linearized based on pseudo-gradient at each sampling time as follows: ； ； ； in, The gradient at time k is a pseudo gradient; The change in grid connection voltage at time k+1; Let k be the change in reactive power at time k; S22: Pseudo-gradient analysis using real-time data To make an estimate, the following error function is defined. : ； in, As a penalty factor; S23: Regarding the error function Regarding pseudo-gradient estimates Taking the derivative and setting it to zero yields the pseudo gradient estimate. The update law is as follows: ； in, Let be the change in reactive power output of the doubly-fed wind turbine at time k-1; Let k be the voltage change at the grid connection point of the doubly-fed wind turbine; This is the step size factor.

4. The high-voltage ride-through adaptive control method for doubly-fed wind turbines according to claim 3, characterized in that, In step S3, the determination of the model-free adaptive control law for the doubly-fed wind turbine by combining the update law of the pseudo-gradient estimate and the linearized model includes the following steps: S31: The prediction model for the grid connection point voltage of the doubly-fed wind turbine, obtained from the linearized model, is as follows: ； S32: Define the voltage tracking error at the grid connection point of the doubly-fed wind turbine at time k+1. for: ； S33: Constructing Control Performance Indicators as follows: ； in, To control the input weighting coefficients; S34: Combine prediction model and voltage tracking error Substitution Formula, and for reactive power After taking the derivative and setting it to zero, we obtain the model-free adaptive control law: ； in, Let k be the reference value of reactive power output from the doubly-fed wind turbine; The target voltage for the doubly fed wind turbine grid connection point; To control the step size.

5. The high-voltage ride-through adaptive control method for doubly-fed wind turbines according to claim 4, characterized in that, In step S4, determining the active power reference value and reactive power reference value under high-voltage ride-through state based on the model-free adaptive control law includes the following steps: S41: Real-time monitoring of grid connection point voltage amplitude When the detected voltage exceeds the preset high voltage ride-through start threshold, the wind turbine is determined to have entered the high voltage ride-through state and is switched to the active-reactive coordinated control mode. S42: Calculate the current reactive power reference value using a model-free adaptive control law. The reactive power reference value is updated using the following formula: ； in The target voltage value during high-voltage ride-through; S43: Under the condition of satisfying the converter capacity constraint Under the premise of reactive power reference value, calculate active power reference value based on reactive power reference value. The formula is as follows: ； Among them, the converter capacity constraint This refers to the instantaneous capacity at which the converter can be safely used under high voltage ride-through conditions.

6. The high-voltage ride-through adaptive control method for doubly-fed wind turbines according to claim 1, characterized in that, In step S5, the active-reactive power coordination strategy refers to prioritizing the achievement of reactive power regulation targets to absorb inductive reactive power to support grid voltage recovery, and then adjusting the active power output in real time according to the capacity constraints of the wind turbine converter and reactive power to ensure that the wind turbine operates within safe limits.

7. The high-voltage ride-through adaptive control method for doubly-fed wind turbines according to claim 1, characterized in that, Step S5 also includes: S52: Calculate the corresponding active power and reactive power reference values. Shaft current reference value , And verify whether the rotor-side and grid-side converter current limits are met. .

8. A high-voltage ride-through adaptive control system for a doubly-fed wind turbine, characterized in that, The high-voltage ride-through adaptive control method for doubly-fed wind turbines according to any one of claims 1 to 7 includes: A linear module is used to construct a linearized model based on the real-time operating data of the doubly fed wind turbine. The linearized model is based on pseudo-gradient estimates and is used to reflect the dynamic relationship between the grid connection point voltage and the output reactive power. The update module is used to determine the update law for the pseudo-gradient estimate; The fusion module is used to combine the update law of the pseudo-gradient estimate and the linearized model to determine the model-free adaptive control law of the doubly fed wind turbine. The calculation module is used to determine the active power reference value and reactive power reference value under high voltage ride-through state based on the model-free adaptive control law; The control module is used to design the active and reactive power coordination strategy for the output of the doubly fed wind turbine under high voltage ride-through conditions, and to determine the final active power reference value and reactive power reference value used for feedback control based on the coordination strategy.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the high-voltage ride-through adaptive control method for doubly-fed wind turbines as described in any one of claims 1 to 7.

10. A processor, characterized in that, The processor is used to run a program, wherein the program executes the high-voltage ride-through adaptive control method for doubly-fed wind turbines according to any one of claims 1 to 7.

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