Low voltage ride through control method and system for grid-connected direct drive wind turbine

Abstract

The application provides a network-constructing type direct-drive wind turbine low-voltage ride-through control method and system, and belongs to the technical field of new energy power generation grid connection control. In view of the problems that the existing fault ride-through control is difficult to consider the DC voltage suppression and rotor operation safety, the lag of after-feedback regulation, and the lack of safety boundary in intelligent control, the application determines the minimum allowable output power of the generator side as a safety lower boundary based on the rotor overspeed power reduction capability, and generates a basic active reference value by taking the maximum value of the power balance target power and the lower boundary; a state evaluation quantity is constructed based on the short-time prediction of the DC voltage and the square-type energy margin of the rotor speed, and the power instruction is adaptively corrected in the safety interval through fuzzy reasoning. The application has mechanism explainability and adaptability, can effectively suppress the DC bus overvoltage and rotor overspeed, and improves the adaptability of the wind turbine to complex faults.

Description

Technical Field

[0001] This invention relates to the field of grid-connected control technology for new energy power generation, and in particular to a low-voltage ride-through control method and system for grid-connected direct-drive wind turbines. Background Technology

[0002] With the increasing proportion of renewable energy sources, the low-voltage ride-through capability of grid-connected direct-drive wind turbines under grid fault conditions has attracted widespread attention. During low-voltage faults, the wind turbine continues to draw mechanical energy from the wind farm, while the grid-side converter is constrained by the voltage drop at the grid connection point and current limiting, resulting in a significant decrease in its active power output. This leads to a mismatch between the turbine-side input power and the grid-side output power, with excess energy accumulating on the DC side, causing DC bus overvoltage and potentially triggering rotor overspeed.

[0003] Traditional fault ride-through control often employs fixed load reduction rates or simple post-fault feedback regulation. Fixed power reduction control struggles to adapt to varying fault depths and wind speeds, easily causing sudden power surges and mechanical load impacts under minor faults, while potentially leading to excessive speeds due to insufficient load reduction under severe faults. Post-fault feedback-based DC voltage regulation often only produces significant corrections after the voltage has already risen considerably, failing to fully leverage its early suppression capabilities. Furthermore, purely intelligent control methods suffer from weak interpretability, lack of guaranteed safety boundaries, and complex engineering implementation. Therefore, improving the turbine-side power control's ability to anticipate and adaptively adjust complex fault dynamics while ensuring rotor operational safety is a pressing technical challenge for fault ride-through control of grid-connected direct-drive wind turbines. Summary of the Invention

[0004] To address the shortcomings and deficiencies of existing technologies, this invention provides a low-voltage ride-through control method and system for grid-type direct-drive wind turbines. First, the maximum power reduction capability of the unit's rotor overspeed control is evaluated, and the minimum allowable output power on the turbine side under rotor energy storage constraints is determined as the safety lower boundary. The target power is determined by combining the DC-side power balance requirements, and the maximum value of both is used to generate a basic active power reference value. Second, short-time voltage prediction is performed based on the DC bus voltage change rate to construct a normalized DC voltage risk coefficient, and a normalized rotor energy margin is constructed using the square of the rotational speed. The effective energy absorption coefficient is obtained by combining this with the fault severity coefficient. Subsequently, using the DC voltage risk coefficient and the effective energy absorption coefficient as inputs, a power correction coefficient is obtained through fuzzy inference, and adaptive interpolation correction is performed within the adjustable range of the basic reference value and the safety lower boundary. Furthermore, under severe fault conditions, a multi-level priority system is used in conjunction with a DC unloading loop to consume the remaining surplus power, and after fault clearance, the recovery time constant is adaptively adjusted based on the rotational speed and voltage deviation to smoothly restore power. This invention achieves a fusion of physical safety boundaries and intelligent correction, balancing the predictive capability of the control strategy with the adaptive adjustment capability under all operating conditions.

[0005] The present invention specifically adopts the following technical solution:

[0006] To address the problems in existing low-voltage ride-through control of grid-type direct-drive wind turbines, such as the difficulty in adapting fixed power reduction strategies to different fault depths and wind speeds, the lag in post-event feedback adjustment, and the lack of reliable safety boundaries in purely intelligent control, this invention provides a low-voltage ride-through control method and system for grid-type direct-drive wind turbines. It constructs a two-layer control architecture that integrates analytical physical safety boundaries with lightweight intelligent correction. While ensuring rotor operating safety, it enhances the adaptive adjustment capability of turbine-side power control to complex fault dynamics, and achieves proactive suppression of DC bus overvoltage and rotor overspeed risks.

[0007] Firstly, this invention provides a low-voltage ride-through control method for grid-type direct-drive wind turbines. Based on the maximum power reduction capability of the unit's rotor overspeed control, the minimum allowable output power of the turbine side under rotor energy storage constraints is determined as the safe lower boundary for power regulation. The target power for power balance is determined according to the DC-side power balance requirements during low-voltage faults. The maximum value of the target power for power balance and the minimum allowable output power of the turbine side is taken to generate the basic active power reference value of the turbine side. This maximum value operation ensures that the basic power command simultaneously satisfies both the DC-side energy balance and rotor energy storage safety constraints: when the fault severity is minor, the target power for power balance is higher than the safe lower boundary, and the turbine side operates according to the DC balance requirements to smooth bus voltage fluctuations; when the fault severity is severe, the target power for power balance is lower than the safe lower boundary, and the turbine side output is clamped at the safe lower boundary to avoid excessive power reduction leading to rotor speed exceeding limits.

[0008] The system collects real-time data on DC bus voltage, rotor speed, and grid connection point voltage. Short-time voltage prediction is performed based on the DC bus voltage change rate, constructing a normalized DC voltage risk coefficient. A fault severity coefficient is determined based on the degree of voltage drop at the grid connection point. A normalized rotor energy margin is constructed using the square of the rotational speed. Multiplying the fault severity coefficient by the normalized rotor energy margin yields the effective energy absorption coefficient. Specifically, the short-time voltage prediction based on the change rate can identify the rising trend of the DC bus voltage in advance, improving the control lag of purely reactive feedback. The rotor energy margin, using the square of the rotational speed, aligns with the physical law that rotor kinetic energy is proportional to the square of the rotational speed, more accurately reflecting the rotor's remaining energy storage capacity. Multiplying these two parameters integrates information on both fault severity and rotor energy absorption potential. The deeper the fault and the greater the rotor margin, the larger the available power reduction space. When the rotor approaches its maximum rotational speed, the power reduction amplitude automatically narrows.

[0009] Using the DC voltage risk coefficient and the effective energy absorption coefficient as inputs to the fuzzy controller, a power correction coefficient is obtained through fuzzy inference. The difference between the machine-side basic active power reference value and the machine-side minimum allowable output power is used as the adjustable power range. Based on the power correction coefficient within the adjustable power range, an additional power reduction is determined. The machine-side basic active power reference value is then subtracted from the additional power reduction, and the maximum value is taken from the minimum allowable output power to obtain the corrected machine-side active power reference value. This process is equivalent to state-driven adaptive interpolation between the basic power command and the safe lower boundary. The final maximum value operation forms a safety constraint on the output command, ensuring that the corrected power command is always no lower than the safe lower boundary, thus guaranteeing that the intelligent correction stage will not exceed the rotor safety limit.

[0010] The corrected active power reference value on the machine side is output to the machine side converter, and the active power output on the machine side is adjusted to achieve fault ride-through.

[0011] Furthermore, when evaluating the maximum power reduction capability of rotor overspeed control, the low-wind-speed operating zone and the high-wind-speed operating zone are divided by a critical wind speed. The critical wind speed is calculated based on the maximum allowable mechanical speed, the rotor radius, and the tip speed ratio corresponding to a zero wind energy utilization coefficient. When the current wind speed is less than or equal to the critical wind speed, the maximum power reduction capability is taken as the output power corresponding to the maximum power point tracking condition at the current wind speed; when the current wind speed is greater than the critical wind speed, the maximum power reduction capability is calculated based on the unit's equivalent moment of inertia, rated mechanical angular velocity, speed constraints, and maximum fault duration. This zoning characteristic matches the aerodynamic characteristics of the wind turbine: in the low-wind-speed zone, wind energy input is limited, and the rotor has sufficient overspeed space to absorb surplus energy; in the high-wind-speed zone, wind energy input is abundant, but the rotor overspeed space is constrained by the upper limit of the speed, and the upper limit of energy that can be safely absorbed needs to be quantified in conjunction with the fault duration.

[0012] Furthermore, the process of constructing the DC voltage risk coefficient includes: performing a first-order filter on the DC bus voltage change rate; making a one-step prediction of the DC bus voltage at the next moment based on the filtered voltage change rate; and constructing the DC voltage risk coefficient normalized by a saturation function based on the relative deviation between the predicted voltage and the DC bus reference voltage and the upper limit of the voltage allowable. First-order filtering can suppress the interference of measurement noise on the calculation of the change rate and improve the stability of the prediction results; saturation function normalization can constrain the risk coefficient within the range of 0 to 1, with the value closer to 1 indicating that the DC bus voltage is closer to the upper limit of the allowable voltage.

[0013] Furthermore, the process of obtaining the effective energy absorption coefficient includes: constructing a fault severity coefficient normalized by a saturation function based on the degree of voltage drop at the grid connection point; constructing a rotor energy margin normalized by a saturation function based on the squared difference relationship between the maximum allowable speed, the current speed, and the initial fault speed; and multiplying the fault severity coefficient by the rotor energy margin to obtain the effective energy absorption coefficient. The fault severity coefficient increases with the increase of the voltage drop depth at the grid connection point, while the rotor energy margin decreases with the decrease of the remaining overspeed space. Multiplying the two can achieve a coupling match between fault requirements and rotor capacity.

[0014] Furthermore, the fuzzy controller employs a zero-order Sugeno-type fuzzy inference system. Both the DC voltage risk coefficient and the effective energy absorption coefficient are divided into three fuzzy sets: small, medium, and large, using a piecewise linear normalized membership function. The output variable is divided into multiple correction levels, corresponding to different single-point output values. Inference is performed based on a preset IF-THEN fuzzy rule, and the power correction coefficient is obtained by defuzzifying using a weighted average method. This fuzzy inference structure has low computational complexity, making it easy to deploy in existing wind turbine digital controllers and meeting the computing power requirements for real-time control.

[0015] Furthermore, after obtaining the corrected active power reference value, the process also includes safety limiting and dynamic constraint processing: setting an event-triggered update mechanism, when the changes in the DC voltage risk coefficient and the effective energy absorption coefficient at adjacent sampling times are both less than the corresponding set thresholds, maintaining the power correction coefficient of the previous time moment to reduce frequent command jitter caused by measurement noise; applying bidirectional power change rate constraints to the corrected active power reference value, respectively limiting the power decrease rate and the power increase rate, reducing the transient impact of power mutations on the transmission chain and DC bus.

[0016] Furthermore, during low-voltage faults, control actions are executed according to a multi-level priority: the first priority is for the grid-side converter to prioritize meeting the dynamic reactive power support requirements for low-voltage ride-through; the second priority is for the generator-side converter to reduce active power input based on the aforementioned safety lower boundary; the third priority is to activate the DC unloading circuit to consume the remaining surplus power when the generator-side power has dropped to the minimum allowable output power, or when the predicted DC bus voltage reaches the unloading start threshold; the remaining surplus power is the difference between the corrected generator-side active power reference value and the grid-side maximum active power output capacity; the fourth priority is to enter the power limiting protection or shutdown protection logic when the DC bus voltage rises to the protection threshold. This multi-level priority ensures the orderly execution of control actions, prioritizing grid connection compliance within limited converter capacity, then exploring rotor energy storage potential, and finally providing a fallback for extreme operating conditions through the unloading circuit.

[0017] Furthermore, the DC unloading circuit adopts a joint triggering method, and the unloading power command employs a composite control structure of feedforward and feedback: the DC unloading circuit is activated when one of the following conditions is met: the DC bus voltage reaches the unloading start threshold; the predicted DC bus voltage reaches the unloading start threshold; or the corrected generator-side active power reference value equals the generator-side minimum allowable output power and the remaining surplus power meets the triggering condition. The unloading power command is composed of the feedforward component of the remaining surplus power, the DC voltage deviation feedback component, and the voltage change rate feedback component, and is subject to output upper limit saturation constraint. The joint triggering method balances operational reliability and response speed. The feedforward component is used to quickly offset the known surplus power, and the feedback component is used to smooth residual voltage fluctuations. The composite control structure can simultaneously ensure response speed and adjustment accuracy.

[0018] Furthermore, the fault clearance process includes an adaptive smooth recovery step: using the active power command on the machine side at the time of fault clearance as the initial value, exponential trajectory control is employed to smoothly restore the machine-side power to the maximum power point tracking operation state; the recovery time constant is adaptively adjusted based on the positive deviation of rotor speed and the positive deviation of DC bus voltage. The larger the positive deviation of rotor speed or the positive deviation of DC bus voltage, the larger the recovery time constant. Positive deviation means that adjustment is only involved when the speed and voltage are higher than the reference values; when they are lower than the reference values, no additional extension of the recovery time is required. This strategy can slow down the recovery speed when the system transient energy is high, avoiding secondary impacts; and accelerate the recovery pace when the system state is close to normal, reducing power loss.

[0019] Secondly, this invention provides a grid-type direct-drive wind turbine low-voltage ride-through control system.

[0020] The system includes a rotor boundary calculation module, a basic instruction generation module, a state feature evaluation module, a fuzzy adaptive correction module, and an output control module.

[0021] The rotor boundary calculation module is used to determine the minimum allowable output power on the machine side under rotor energy storage constraints based on the maximum power reduction capability of the unit rotor overspeed control, as the safe lower boundary of power regulation.

[0022] The basic instruction generation module is used to determine the target power for power balance based on the DC-side power balance requirements during low-voltage faults, and to generate the basic active power reference value for the generator side by taking the maximum value of the target power for power balance and the minimum allowable output power on the generator side.

[0023] The state characteristic assessment module is used to collect DC bus voltage, rotor speed and grid connection point voltage in real time, perform short-time voltage prediction based on DC bus voltage change rate, and construct a normalized DC voltage risk coefficient; at the same time, it determines the fault severity coefficient according to the degree of grid connection point voltage drop, constructs a normalized rotor energy margin using the square of speed, and multiplies the fault severity coefficient with the normalized rotor energy margin to obtain the effective energy absorption coefficient.

[0024] The fuzzy adaptive correction module is used to obtain a power correction coefficient through fuzzy inference by taking the DC voltage risk coefficient and the effective energy absorption coefficient as inputs, and then taking the difference between the machine-side basic active power reference value and the machine-side minimum allowable output power as the adjustable power range. Based on the power correction coefficient, an additional power reduction amount is determined within the adjustable power range. After subtracting the additional power reduction amount from the machine-side basic active power reference value, the maximum value is taken from the minimum allowable output power of the machine side to obtain the corrected machine-side active power reference value.

[0025] The output control module is used to output the corrected active power reference value to the machine-side converter and adjust the active power output to achieve fault ride-through.

[0026] Compared to existing technologies, this invention and its preferred solutions can adapt to different fault depths and wind speeds while ensuring the rotor does not exceed limits. This avoids the problems of excessive power surges under mild faults and insufficient load reduction under severe faults caused by fixed power reduction strategies, while balancing DC voltage suppression and unit mechanical safety. Risk assessment is performed in advance based on voltage change trends, allowing for early adjustment of power commands before a significant rise in DC bus voltage, improving the lag of traditional post-event feedback control. An architecture combining mechanistic safety boundaries and lightweight intelligent correction is adopted, preserving the physical interpretability and reliability of analytical models while possessing adaptive adjustment capabilities for intelligent control. The overall computational complexity is low, facilitating engineering implementation in existing wind turbine digital controllers. Covering the entire lifecycle control process from fault occurrence and duration to fault clearance, and coupled with a load-bearing fallback mechanism under extreme faults, stable fault ride-through under all operating conditions is achieved. Attached Figure Description

[0027] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0028] Figure 1 This is a schematic diagram showing the relationship between the wind energy utilization coefficient and the tip speed ratio and the pitch angle in an embodiment of the present invention; in the figure, (a) is a three-dimensional characteristic surface, and (b) is a two-dimensional characteristic curve when the pitch angle is 0.

[0029] Figure 2 This is a surface diagram showing the relationship between the rotor storage ratio coefficient and the rated power and equivalent moment of inertia of the unit in an embodiment of the present invention.

[0030] Figure 3 This is a schematic diagram illustrating the principle of selecting active power reference power on the machine side in an embodiment of the present invention;

[0031] Figure 4 This is a block diagram illustrating the adaptive fault ride-through control principle of a grid-type direct-drive wind turbine according to an embodiment of the present invention.

[0032] Figure 5 This is a waveform diagram of the three-phase voltage at the grid connection point under a mild low-voltage fault, according to an embodiment of the present invention.

[0033] Figure 6 This is a comparison chart of the machine-side input power of different control methods under a mild low-voltage fault according to an embodiment of the present invention;

[0034] Figure 7 This is a comparison diagram of the power waveforms on the machine side and the grid side under the control method of the present invention in an embodiment of the present invention;

[0035] Figure 8 This is a comparison chart of DC bus voltages under different control methods during a mild low-voltage fault according to an embodiment of the present invention.

[0036] Figure 9 This is a comparison chart of rotor speeds under different control methods in the case of a mild low-voltage fault according to an embodiment of the present invention. Detailed Implementation

[0037] To make the features and advantages of the present invention more apparent and understandable, specific embodiments are described below in conjunction with the accompanying drawings:

[0038] This invention provides an adaptive fault ride-through control method for grid-type direct-drive wind turbines based on voltage trend prediction and rotor energy margin. This method constructs a two-layer control architecture that integrates analytical physical safety boundaries with lightweight intelligent correction, forming a closed-loop control link covering all fault levels (light, medium, and heavy). While ensuring that the rotor energy storage safety lower limit is not exceeded, it achieves highly adaptive ride-through control for complex low-voltage fault processes.

[0039] like Figure 4 As shown, the main circuit for implementing the present invention consists of a wind turbine, a permanent magnet synchronous generator, a machine-side converter, a DC bus, a grid-side converter, a filter inductor, and a grid connection point. During normal operation, the mechanical energy captured by the wind turbine is transferred to the DC side via the permanent magnet synchronous generator and the machine-side converter, and then fed into the power grid by the grid-side converter.

[0040] When a low-voltage fault occurs at the grid connection point, this invention generates a base power command on the generator side, constrained by the lower limit of the safe power calculated from the rotor energy storage boundary. Simultaneously, through state feature extraction and risk assessment, it collects real-time data on the DC bus voltage, rotor speed, and grid connection point voltage status, outputting this data to a fuzzy adaptive power correction stage for online fine-tuning of the base power command. The corrected power command, after safety limiting and dynamic constraints, is then output to the generator-side converter as a reference value for active power. After the fault is cleared, an adaptive smooth recovery stage controls the generator-side power to gradually return to normal operating conditions. If necessary, a DC unloading circuit can be used to consume remaining surplus energy, achieving closed-loop control across all operating conditions.

[0041] In the maximum power reduction capability assessment and safety boundary calculation stages, the power reduction capability of grid-connected wind turbines based on rotor overspeed control is closely related to wind speed. The mechanical input power of the wind turbine can be expressed as:

[0042]

[0043] In the formula, For mechanical input power, air density, Where is the radius of the wind turbine. For wind speed, The wind energy utilization coefficient, For the tip speed ratio, It is the propeller pitch angle.

[0044] Under maximum power point tracking conditions, the wind turbine meets the requirements. , and The optimal input power can be expressed in terms of rotational speed:

[0045]

[0046] In the formula, For MPPT optimal power, The maximum wind energy utilization factor, To achieve the optimal tip speed ratio, This refers to the mechanical speed of the fan.

[0047] After a fault occurs, the unbalanced power applied to the DC side can be expressed as: In the formula, For unbalanced power, Injecting DC power into the machine side, This is the grid-side output power. When... At this time, there is a power surplus on the DC side, and the active power input on the generator side needs to be reduced to maintain the power balance on the DC side. The load shedding rate is defined as follows: The wind energy utilization coefficient at the operating point after load reduction meets the requirements. .

[0048] In this embodiment, the wind energy utilization coefficient Speed ​​ratio with leaf tip Pitch angle Relationship such as Figure 1 As shown. Among them, Figure 1 (a) is a three-dimensional characteristic surface, and the cutting plane corresponds to... Under the operating conditions, the intersection of the curve with the three-dimensional surface is the wind energy utilization coefficient characteristic curve at that pitch angle. Figure 1 (b) A two-dimensional representation of this cross-section is further provided. During normal operation, the fan operates at... The maximum power point A on the cross section. After the fault occurs, under the condition that the wind speed and blade pitch angle remain unchanged for a short period of time, the rotor accelerates due to the imbalance between mechanical power and electromagnetic power, the tip speed ratio increases, and the operating point moves along... As the cross-sectional curve shifts from A to B, the wind energy utilization coefficient... The power decreases accordingly; at the same time, the transient unbalanced power is converted into rotor mechanical kinetic energy and stored in the rotor and transmission chain.

[0049] During the fault ride-through phase, under constant pitch control conditions, the least squares method can be used to... The inverse function is fitted with a cubic polynomial to obtain... .

[0050] When the fan speed reaches the maximum allowable value At that time, the critical wind speed for low and high wind speed zones is defined as follows: In the formula, This is the critical wind speed for low to high wind speeds. For the maximum permissible mechanical speed, for The corresponding tip speed ratio.

[0051] When wind speed At that time, the wind turbine can reduce its output power to zero through overspeed unloading; when the wind speed... At this time, the power reduction capability on the turbine side is constrained by the maximum permissible speed and the duration of the fault. The per-unit form of the rotor motion equation of the wind turbine can be written as:

[0052]

[0053] In the formula, This is the per-unit value of the mechanical input power. This is the per-unit value of electromagnetic output power. This is the per-unit value of the rotational speed. The equivalent moment of inertia of the unit. For the rated mechanical angular velocity, This is the rated power.

[0054] Based on the low voltage ride-through requirements, the maximum fault duration corresponding to different voltage sags can be expressed as:

[0055]

[0056] In the formula, For the maximum duration of the fault, This represents the voltage sag (the per-unit value of the voltage drop at the grid connection point). Integrating the rotor motion equations yields the expression for the maximum power reduction increment: In the formula, For the maximum power reduction increment, This is the per-unit value of the maximum permissible speed. This is the initial speed per unit value at the time of the fault.

[0057] The maximum power reduction capability of grid-connected wind turbines based on rotor overspeed control exhibits zonal characteristics. In low-wind-speed zones, the turbine can reduce its output power to zero through overspeed unloading, with its maximum power reduction capability determined by the MPPT output power under the current operating conditions. In high-wind-speed zones, it is mainly constrained by the unit's inertia, fault duration, and maximum permissible speed, which can be uniformly expressed as:

[0058]

[0059] In the formula, To standardize the maximum power reduction capability, This represents the output power corresponding to the MPPT operating condition at the current wind speed. The minimum allowable output power on the turbine side is... In the formula, This is the minimum permissible output power on the machine side.

[0060] In the basic power command generation stage, a reference value for the generator-side active power, constrained by the rotor energy storage capacity, is constructed by combining the dynamic reactive power support requirements during low-voltage ride-through, the active power output capacity of the grid-side converter, and the DC-side power balance. According to wind power grid connection standards, the dynamic reactive current injected into the grid during low-voltage ride-through must meet the following requirements: .

[0061] In the formula, For dynamic reactive current, This is the per-unit value of the grid connection point voltage. This is the rated current of the fan.

[0062] The failure was divided into two phases. The first phase was... Within seconds, the grid connection point voltage remained at 0.2 per unit, and all grid-side converter current was used for reactive power support, with zero active current. The second stage... Within seconds, the grid connection point voltage linearly recovered from 0.2 per unit value to 0.9 per unit value, voltage trajectory and active current Represented as:

[0063]

[0064]

[0065] In the formula, For the voltage recovery trajectory at the grid connection point, This represents the instantaneous value of the grid-side active current. The instantaneous active current output on the grid side is... Under rated wind speed conditions, the mechanical power is approximately equal to the rated power, i.e. The total mismatch energy within the system during low-voltage ride-through is defined as:

[0066]

[0067] In the formula, This represents the total mismatched energy. For a 3MW unit, the calculation yields... The equivalent average unbalanced power is ,Right now In the formula, For equivalent average unbalanced power, This is the fault analysis period. The rotor storage ratio is defined as... In the formula, This is the rotor storage ratio coefficient. Taking a 3MW unit as an example, the calculation yields... This indicates that the rotor can handle up to 34% of the low-level average unbalanced power.

[0068] Storage ratio coefficient in this embodiment With the rated power of the unit Equivalent moment of inertia The relationship of change is as follows Figure 2 As shown, The coefficient increases with increasing moment of inertia and decreases with increasing rated power of the rotor, directly reflecting the variation of the rotor's ability to share unbalanced power with parameters. The normalized lower boundary coefficient is... In the formula, This is the normalized lower boundary coefficient.

[0069] The target output power during a fault, determined by the DC-side power balance requirement, can be expressed as: In the formula, To balance the target power on the DC side, The target coefficient. Considering both DC-side power balance constraints and rotor energy storage constraints, the active power reference value selection command for the base unit side can be uniformly expressed as:

[0070]

[0071] In the formula, Based on the reference power, To meet the target power requirements for DC-side power balance. When the fault is minor, the generator side is set according to... Running; when the severity of the fault increases and At that time, the output of the machine side is limited by the maximum power reduction capacity that the rotor can withstand, and the output of the machine side is taken as follows: This is to prevent the engine speed from exceeding the limit during a fault.

[0072] The selection logic for the active power reference on the machine side in this embodiment is as follows: Figure 3 As shown in the figure. The horizontal axis represents the DC-side power balance target coefficient. The vertical axis represents the active power reference power on the machine side; this selection characteristic is segmented: when the DC side power balance target coefficient Less than the normalized lower boundary coefficient At that time, the active power reference value on the machine side is clamped at the minimum allowable output power constrained by the rotor energy storage. To avoid excessive power reduction leading to rotor speed exceeding limits when the fault depth is too deep; when In When the value reaches range 1, the active power reference value on the generator side follows the DC side power balance target. Linear variation prioritizes matching the DC-side power balance requirements to suppress bus voltage fluctuations; when When =1, the unit operates in normal operation and outputs rated power. This segmentation selection essentially performs a maximum operation between the DC-side power balance target and the rotor safety lower limit, and can automatically coordinate the constraint relationship between DC voltage suppression and rotor operating safety as the fault depth increases.

[0073] In the state feature extraction and risk assessment stages, to overcome the problem of insufficient response of the basic power command to dynamic changes in the system, this embodiment introduces a lightweight intelligent correction method. First, a first-order filter is applied to the DC bus voltage change rate:

[0074]

[0075] In the formula, The rate of change of the filtered voltage. These are the filter coefficients. To control the sampling period, This represents the DC bus voltage. A one-step prediction of the short-time DC bus voltage is performed based on the filtered voltage change rate:

[0076]

[0077] In the formula, To predict the voltage at the next moment, To predict the time scale, a normalized DC voltage risk coefficient is constructed:

[0078]

[0079] In the formula, DC voltage risk factor. This is the DC bus reference voltage. This is the upper limit allowed for the DC bus. To limit the output to The saturation function within. When A value close to 1 indicates that the predicted voltage is near its upper limit. Considering the voltage drop at the grid connection point, the fault severity coefficient is defined as... .

[0080] In the formula, This represents the severity coefficient of the fault. This is the per-unit value of the grid connection point voltage. The minimum fault voltage set for the controller. The rotor's remaining energy margin is constructed using the square of the rotational speed, consistent with the kinetic energy expression:

[0081]

[0082] In the formula, To normalize the rotor energy margin, For the maximum permissible speed, The current rotational speed, The initial rotational speed at which the fault occurred. Considering both the severity of the fault and the rotor's energy storage state, the effective energy absorption coefficient is defined as... In the formula, This is the effective energy absorption coefficient. When the fault is deep and the rotor still has a large energy margin, The value is relatively large; when the rotor approaches the upper speed limit, It automatically reduces power to avoid excessive power reduction that could cause the rotor to exceed its limits.

[0083] In the fuzzy adaptive power correction stage, with and As input to the fuzzy controller, with power correction coefficient As output, the input variables are divided into three fuzzy sets: small, medium, and large, denoted as S, M, and L, respectively. Both input variables use the same normalized membership function. For any input variable... Small membership function exist When the value is 1, The time value is ,exist The value is 0 when the membership function is in use. exist When the value is 0, The time value is ,exist The time value is ,exist The value is 0; large membership function exist When the value is 0, The time value is ,exist The value is 1.

[0084] The output variables adopt a zero-order Sugeno type single-point output format, divided into four levels: zero correction, small correction, medium correction, and large correction, with their single-point values... The values ​​are 0, 0.25, 0.55, and 0.85 respectively. The following nine basic rules are established:

[0085] Rule 1: IF (If) For small AND (and) For small, THEN (then) Zero correction;

[0086] Rule 2: IF For small AND For the middle, THEN Zero correction;

[0087] Rule 3: IF For small AND For the great, THEEN Minor corrections;

[0088] Rule 4: IF For Middle AND For small, THEN Minor corrections;

[0089] Rule 5: IF For Middle AND For the middle, THEN For correction;

[0090] Rule 6: IF For Middle AND For the great, THEEN For correction;

[0091] Rule 7: IF For big AND For small, THEN Minor corrections;

[0092] Rule 8: IF For big AND For the middle, THEN For correction;

[0093] Rule 9: IF For big AND For the great, THEEN This is a major revision.

[0094] No. The activation strength of a rule is defined as follows: .

[0095] In the formula, For the first The activation strength of the rule, for The membership degree corresponding to a fuzzy set. for The membership degree of the corresponding fuzzy set. The power correction coefficient is obtained by defuzzifying using the weighted average method.

[0096]

[0097] In the formula, This is the power correction factor. For the first The output single-point value corresponding to each rule. To prevent small positive numbers with a denominator of zero, the adjustable range between the base reference power and the minimum permissible power is: In the formula, The range is adjustable. The additional power reduction caused by fuzzy correction is... In the formula, This includes the additional power reduction. The corrected turbine-side active power reference value is:

[0098]

[0099] In the formula, To correct the active power reference value on the rear side, this control law is essentially a state-driven adaptive interpolation between the base power command and the rotor safety lower boundary. Since the final output always satisfies... Even if there are parameter deviations, the fuzzy rules will not break the rotor safety constraints established by the original method.

[0100] To reduce frequent adjustments caused by measurement noise, an event triggering mechanism is set up when... and The changes at adjacent sampling times are each less than a set threshold. and At the same time, maintain the correction factor from the previous moment. Simultaneously, apply a rate-of-change constraint to the machine-side active power reference value:

[0101]

[0102] In the formula, For the maximum allowable power descent rate, This represents the maximum permissible power rise rate. It can be appropriately increased during the fault occurrence phase. To quickly suppress the rise in DC bus voltage, a smaller [scale / method] is used during the fault clearing phase. To avoid secondary impact caused by a sudden increase in power on the machine side.

[0103] During the severe fault unloading coordination phase, when the generator-side converter has reduced the active power reference value to the level specified by the rotor energy storage boundary... Even then, there may still be residual surplus energy that the rotor cannot absorb. The DC-side power balance relationship is expressed as:

[0104]

[0105] In the formula, This is the equivalent capacitance of the DC bus. This consumes power for the DC unloading circuit. During low-voltage faults, grid-side grid-type converters prioritize meeting dynamic reactive power support requirements; their active current capacity is expressed as... The maximum active power output capacity on the grid side is In the formula, This is the maximum active current on the grid side. For converter current limits, This is a reactive power support current command. This represents the maximum active power output capacity on the grid side. This is the per-unit value of the grid connection point voltage. The remaining surplus power is defined as:

[0106]

[0107] In the formula, This represents the remaining surplus power. During severe faults, a multi-level priority coordination logic is employed: the first priority is for the grid-side converter to meet the low-voltage ride-through reactive power support requirements; the second priority is for the generator-side converter to reduce active power input based on the rotor energy storage boundary; the third priority is when the generator-side power has decreased to... If it is predicted that the DC bus voltage will still exceed the unloading threshold, the DC unloading circuit will be started to consume the remaining surplus energy; the fourth priority is that if the DC bus voltage continues to rise to the protection threshold, the power limiting protection or shutdown protection logic will be entered.

[0108] The DC unloading circuit employs a combined triggering method based on voltage threshold, predicted risk, and remaining power. When the following conditions are met... ,or ,or and At that time, the DC unloading circuit is activated. Where, The unloading start-up voltage threshold, To predict the DC bus voltage, This is the remaining power trigger coefficient. The exit condition is... and continued Time. In the formula, The unloading exit threshold, This is the exit coefficient. The dwell time. The unloading power command is composed of residual power feedforward and DC voltage feedback:

[0109]

[0110] In the formula, For unloading power command, This represents the maximum power consumption of the DC unloading circuit. This is the DC voltage deviation feedback coefficient. This is the DC voltage rise rate feedback coefficient. This is the filtered DC bus voltage. This corresponds to the rate of change of the DC bus voltage after filtering. The corresponding PWM duty cycle can be expressed as:

[0111]

[0112] In the formula, To unload the PWM duty cycle, This is the upper limit of the duty cycle. This is the unloading resistor.

[0113] In the adaptive smooth recovery phase after a fault, the engine-side power should not immediately recover to the MPPT power after the fault is cleared; instead, exponential trajectory smooth recovery is adopted.

[0114]

[0115] In the formula, This is the power recovery trajectory on the engine side after the fault. This refers to the active power command on the machine side at the moment of fault clearance. Power under MPPT conditions. This is the time to clear the fault. The recovery time constant is adaptively adjusted based on the positive deviations of the rotor speed and the DC bus voltage.

[0116]

[0117] in, , In the formula, To recover the lower limit of the time constant, To restore the upper limit of the time constant, Based on the recovery time constant, This is the speed correction factor. For positive deviation of rotor speed, This is the DC voltage recovery correction factor. This indicates a positive deviation in DC bus voltage. When both the rotational speed and DC bus voltage remain too high... Automatically increasing power slows down power recovery; when the system state approaches normal operating point... Reduce the load so that the unit can quickly return to MPPT status.

[0118] As a preferred implementation, this invention provides a set of typical engineering tuning parameters adapted to a 3MW grid-connected direct-drive wind turbine. Rated power Take 3MW, rated speed Take 15 r / min, equivalent moment of inertia Take 2.5 × 10 6 kg·m 2 Maximum permissible speed Use a per-unit value of 1.20 to control the sampling period. Take 1ms, voltage change rate filter coefficient Set the value to 0.90 for the DC voltage prediction time scale. Take 10ms. DC bus reference voltage. Take a per-unit value of 1.00, the maximum allowable value for the DC bus. Take a per-unit value of 1.15 as the unloading start threshold. Take a per-unit value of 1.10, and set the unloading exit threshold. Take a per-unit value of 1.05 for DC bus protection threshold. Use a per-unit value of 1.20. Event trigger threshold. Set the threshold to 0.02. Take 0.03, residual power triggering coefficient Take 0.03. Maximum power decrease rate. Take 5 per unit value per second, maximum power rise rate Take 1 unit value per second. Basic recovery time constant. Take 0.25s as the lower limit of the recovery time constant. Set the time constant to 0.25s, which is the upper limit of the recovery time constant. Take 1.00s as the speed recovery correction factor. Set to 4, DC voltage recovery correction factor Take 3. Maximum DC unloading power. Use 0.6 to 0.8 times the rated power, and set the upper limit of the unloading duty cycle. Set the value to 0.95. Exit coefficient. Take 0.01, duration Take 10ms.

[0119] To verify the effectiveness of the proposed control method, a 3MW grid-connected direct-drive wind turbine was used as the research object for simulation verification. A low-voltage fault case was set up, with the fault occurring at 0.5s, lasting for 0.625s, and cleared at 1.125s, for a simulation duration of 2s. Comparison methods included traditional grid-connected control, turbine-side fixed power reduction control, and the control proposed in this invention. Under the low-voltage fault condition, the grid connection point voltage dropped to 0.78 per unit, representing a voltage drop depth of 22%.

[0120] Table 1 summarizes the key performance indicators of each method under mild undervoltage faults. Regarding DC bus voltage, compared to traditional grid-based control and fixed power reduction control only at the generator side, the method of this invention reduces the peak voltage deviation by approximately 86.9% and 73.5%, respectively. Regarding rotor speed, the method of this invention reduces the peak speed from 1.14 pu under generator-side power reduction control only to 1.08 pu, reduces the speed rise by approximately 41.4%, and shortens the speed recovery time to 1.27 s. These results demonstrate that under mild undervoltage faults, the method of this invention can simultaneously improve DC bus voltage stability and rotor speed dynamic response with a relatively small generator-side power adjustment range.

[0121] Table 1 Performance Comparison of Different Control Methods

[0122]

[0123] The system dynamic response under a mild low-voltage fault in this embodiment is as follows: Figures 5 to 9 As shown. Among them, Figure 5 The three-phase voltage waveform at the grid connection point reflects the voltage drop and recovery characteristics during the fault occurrence and clearing process. Figure 6 A comparison of the machine-side input power under the three control methods shows that the reduction in machine-side input power under the method of this invention is approximately 0.09 per unit, which is about 35.7% lower than the fixed power reduction control on the machine side, and can effectively reduce the sudden change in machine-side power. Figure 7 The waveforms of the generator-side power and grid-side power under the proposed control method are shown, demonstrating the transient power coordination effect during the fault period; Figure 8 A comparison of DC bus voltage using three control methods shows that the method of this invention reduces peak voltage deviation by approximately 86.9% and 73.5% compared to traditional grid-based control and fixed power reduction control at the generator side. Figure 9For the comparison of rotor speeds of the three control methods, the method of the present invention reduces the peak speed from 1.14 per unit under the fixed power reduction control on the machine side to 1.08 per unit, reduces the speed increase by about 41.4%, and shortens the speed recovery time to 1.27s.

[0124] The above-described solutions in this invention form a complete fault ride-through control framework for grid-connected direct-drive wind turbines through steps such as maximum power reduction capability assessment, turbine-side safe power boundary construction, DC-side power coordination, state trend prediction, fuzzy adaptive correction, and smooth recovery after a fault. This framework balances the physical interpretability of the mechanistic model with the dynamic adaptability of the intelligent correction mechanism. While suppressing DC bus energy accumulation, limiting rotor overspeed, and reducing turbine-side power surges, it significantly improves the control strategy's adaptability to wind speed fluctuations, parameter deviations, and non-preset voltage recovery processes. The required calculations mainly involve state filtering, normalization operations, and two-dimensional rule lookup tables, resulting in low computational complexity. It is feasible to further implement this framework in existing wind turbine digital controllers and can provide theoretical and control method references for the safe and stable operation of grid-connected wind turbines under complex low-voltage fault conditions.

[0125] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A low-voltage ride-through control method for a grid-type direct-drive wind turbine, characterized in that, include: Based on the maximum power reduction capability of the unit's rotor overspeed control, the minimum allowable output power on the generator side under rotor energy storage constraints is determined as the safe lower boundary for power regulation. The target power for power balance is determined based on the DC-side power balance requirement during low-voltage faults. The maximum value of the target power for power balance and the minimum allowable output power on the generator side is taken to generate the basic active power reference value on the generator side. The DC bus voltage, rotor speed, and grid connection point voltage are collected in real time. Short-time voltage prediction is performed based on the DC bus voltage change rate, and a normalized DC voltage risk coefficient is constructed. The fault severity coefficient is determined according to the degree of grid connection point voltage drop. A normalized rotor energy margin is constructed using the square of the speed. The effective energy absorption coefficient is obtained by multiplying the fault severity coefficient and the normalized rotor energy margin. Using the DC voltage risk coefficient and the effective energy absorption coefficient as inputs to the fuzzy controller, a power correction coefficient is obtained through fuzzy inference; using the difference between the base active power reference value and the minimum allowable output power of the machine side as the adjustable power range, an additional power reduction amount is determined within the adjustable power range according to the power correction coefficient, and the base active power reference value of the machine side is subtracted from the additional power reduction amount, and the maximum value is taken with the minimum allowable output power of the machine side to obtain the corrected base active power reference value of the machine side; The corrected active power reference value on the machine side is output to the machine side converter, and the active power output on the machine side is adjusted to achieve fault ride-through.

2. The low voltage ride-through control method for grid-type direct-drive wind turbines according to claim 1, characterized in that: The process of evaluating the maximum power reduction capability includes: The low-wind-speed operating zone and the high-wind-speed operating zone are divided by the critical wind speed. The critical wind speed is calculated based on the maximum allowable mechanical speed, the wind turbine radius, and the tip speed ratio corresponding to the wind energy utilization coefficient being zero. When the current wind speed is less than or equal to the critical wind speed, the maximum power reduction capability is taken as the output power corresponding to the maximum power point tracking condition at the current wind speed; when the current wind speed is greater than the critical wind speed, the maximum power reduction capability is calculated based on the unit's equivalent moment of inertia, rated mechanical angular velocity, speed constraint, and maximum fault duration.

3. The low voltage ride-through control method for grid-type direct-drive wind turbines according to claim 1, characterized in that: The process of constructing the DC voltage risk factor includes: The DC bus voltage change rate is subjected to first-order filtering, and the DC bus voltage at the next moment is predicted in one step based on the filtered voltage change rate. Based on the relative deviation between the predicted voltage and the DC bus reference voltage and the upper limit of the voltage allowable, the DC voltage risk coefficient, normalized by a saturation function, is constructed.

4. The low voltage ride-through control method for grid-type direct-drive wind turbines according to claim 1, characterized in that: The process of obtaining the effective energy absorption coefficient includes: A fault severity coefficient normalized by a saturation function is constructed based on the degree of voltage drop at the grid connection point. Based on the squared difference relationship between the maximum permissible speed, the current speed and the initial speed of the fault, a rotor energy margin normalized by a saturation function is constructed. The effective energy absorption coefficient is obtained by multiplying the fault severity coefficient by the rotor energy margin.

5. The low voltage ride-through control method for grid-type direct-drive wind turbines according to claim 1, characterized in that: The fuzzy controller adopts a zero-order Sugeno-type fuzzy inference system; The DC voltage risk coefficient and the effective energy absorption coefficient are both divided into three fuzzy sets: small, medium, and large. A piecewise linear normalized membership function is used. The output variables are divided into multiple correction levels, corresponding to different single-point output values; The power correction coefficient is obtained by reasoning based on the preset IF-THEN fuzzy rule and using the weighted average method to defuzzify the fuzzy rules.

6. The low voltage ride-through control method for grid-type direct-drive wind turbines according to claim 1, characterized in that: After obtaining the corrected active power reference value, the process also includes safety limiting and dynamic constraint processing: An event-triggered update mechanism is set up so that when the changes in the DC voltage risk coefficient and the effective energy absorption coefficient at adjacent sampling times are both less than the corresponding set thresholds, the power correction coefficient at the previous time is maintained. A bidirectional power change rate constraint is applied to the corrected machine-side active power reference value to limit the power decrease rate and the power increase rate, respectively.

7. The low voltage ride-through control method for grid-type direct-drive wind turbines according to claim 1, characterized in that: During a low-voltage fault, control actions are executed according to a multi-level priority system: The first priority is for grid-side converters to meet the low-voltage ride-through dynamic reactive power support requirements. The second priority is for the machine-side converter to reduce the active power input based on the aforementioned safety lower boundary; The third priority is to start the DC unloading circuit to consume the remaining surplus power when the generator-side power has dropped to the minimum allowable output power of the generator side, or when the predicted DC bus voltage reaches the unloading start threshold; the remaining surplus power is the difference between the corrected generator-side active power reference value and the grid-side maximum active power output capacity. The fourth priority is to enter the power limiting protection or shutdown protection logic when the DC bus voltage rises to the protection threshold.

8. The low voltage ride-through control method for grid-type direct-drive wind turbines according to claim 7, characterized in that: The DC unloading circuit adopts a joint triggering method, and the unloading power command adopts a composite control structure of feedforward and feedback: The DC unloading circuit is activated when one of the following conditions is met: the DC bus voltage reaches the unloading start threshold, the predicted DC bus voltage reaches the unloading start threshold, or the corrected generator-side active power reference value is equal to the generator-side minimum allowable output power and the remaining surplus power meets the triggering condition. The unloading power command is composed of the superposition of the remaining surplus power feedforward component, the DC voltage deviation feedback component, and the voltage change rate feedback component, and is subject to output upper limit saturation constraint.

9. The low voltage ride-through control method for grid-type direct-drive wind turbines according to claim 1, characterized in that: The process after fault clearing also includes an adaptive smooth recovery step: Using the active power command on the machine side at the moment of fault clearance as the initial value, exponential trajectory control is adopted to smoothly restore the machine side power to the maximum power point tracking operation state; The recovery time constant is adaptively adjusted based on the positive deviation of rotor speed and the positive deviation of DC bus voltage. The larger the positive deviation of rotor speed or the positive deviation of DC bus voltage, the larger the recovery time constant.

10. A grid-type direct-drive wind turbine low-voltage ride-through control system, used to implement the method as described in claim 1, characterized in that, It includes a rotor boundary calculation module, a basic instruction generation module, a state feature evaluation module, a fuzzy adaptive correction module, and an output control module; The rotor boundary calculation module is used to determine the minimum allowable output power on the machine side under rotor energy storage constraints based on the maximum power reduction capability of the unit rotor overspeed control, as the safe lower boundary of power regulation. The basic instruction generation module is used to determine the target power for power balance based on the DC-side power balance requirements during low-voltage faults, and to generate the basic active power reference value for the generator side by taking the maximum value of the target power for power balance and the minimum allowable output power on the generator side. The state characteristic assessment module is used to collect DC bus voltage, rotor speed and grid connection point voltage in real time, perform short-time voltage prediction based on DC bus voltage change rate, and construct a normalized DC voltage risk coefficient; at the same time, it determines the fault severity coefficient according to the degree of grid connection point voltage drop, constructs a normalized rotor energy margin using the square of speed, and multiplies the fault severity coefficient with the normalized rotor energy margin to obtain the effective energy absorption coefficient. The fuzzy adaptive correction module is used to obtain a power correction coefficient through fuzzy inference by taking the DC voltage risk coefficient and the effective energy absorption coefficient as inputs, and then taking the difference between the machine-side basic active power reference value and the machine-side minimum allowable output power as the adjustable power range. Based on the power correction coefficient, an additional power reduction amount is determined within the adjustable power range. After subtracting the additional power reduction amount from the machine-side basic active power reference value, the maximum value is taken from the minimum allowable output power of the machine side to obtain the corrected machine-side active power reference value. The output control module is used to output the corrected active power reference value to the machine-side converter and adjust the active power output to achieve fault ride-through.

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