A frequency regulation method and system for a hybrid wind turbine group
By constructing the state-space equations of hybrid wind farms and optimizing active power allocation, the control parameters of grid-connected wind turbines are dynamically adjusted, solving the problem of insufficient frequency regulation capability of hybrid wind farms and achieving faster response and more stable frequency support.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUNAN UNIV
- Filing Date
- 2026-02-05
- Publication Date
- 2026-05-19
AI Technical Summary
In existing technologies, the frequency regulation capability of hybrid wind farms is insufficient, especially the slow response speed of grid-connected wind turbines, which makes it difficult to effectively regulate when the grid frequency fluctuates, resulting in weak anti-interference ability and easy large-scale disconnection of wind turbines from the grid.
By establishing mathematical models of the power control loop for grid-connected and grid-connected wind turbines, a state-space equation for a hybrid wind farm is constructed and discretized into a discrete state-space equation. The active power allocation is optimized, and the control parameters of the grid-connected wind turbines are dynamically adjusted by combining parameters such as virtual inertia and damping, so as to achieve rapid and accurate tracking of the power reference value.
It significantly enhances the frequency support capability of hybrid wind farms, improves the response performance of wind turbine units, effectively suppresses parameter oscillations during regulation, and improves the frequency regulation capability of the power grid.
Smart Images
Figure CN121642988B_ABST
Abstract
Description
Technical Field
[0001] This invention mainly relates to the field of wind power technology, specifically to a frequency control method and system for hybrid wind turbine clusters. Background Technology
[0002] In the global acceleration of the transition to clean energy, wind power technology has been widely used due to its significant advantages such as being clean and renewable. However, the intermittency and volatility of wind power generation make it a primary obstacle to grid connection, resulting in difficulties in precise grid dispatch.
[0003] Wind turbines currently achieve grid connection primarily through grid-connected and grid-connected control technologies. Grid-connected wind turbines achieve grid tracking by obtaining the grid phase through phase-locked loops (PLLs), and are widely used in strong grids. However, they have poor disturbance rejection capabilities when the grid experiences disturbances and cannot provide the necessary inertia for the grid. Grid-connected wind turbines, on the other hand, achieve grid connection by simulating the characteristics of traditional synchronous generators. For example, virtual synchronous machine control technology simulates the rotor motion equations of a synchronous motor, providing inertia and damping to the grid, and exhibiting strong disturbance rejection capabilities. They are widely used in microgrids or off-grid scenarios. However, due to inertial response, grid-connected wind turbines have a slower response speed to the external grid compared to grid-connected turbines, which limits regulation capabilities and increases scheduling difficulties.
[0004] The current power grid exhibits a high proportion of both renewable energy and power electronic equipment, displaying "dual-high" characteristics. This results in weak disturbance rejection and insufficient tolerance to frequency deviations, easily triggering large-scale wind turbine disconnections. This places higher demands on the participation of wind turbines in frequency regulation. Future research should focus on improving the frequency support performance of hybrid wind farms, optimizing the slow response of their grid-connected wind turbines, and more effectively addressing the issue of frequency fluctuation disturbance rejection. Summary of the Invention
[0005] To address the technical problems existing in the prior art, the present invention provides a frequency control method and system for hybrid wind turbine clusters that significantly enhances the overall frequency support capability of hybrid wind farms.
[0006] To solve the above-mentioned technical problems, the technical solution proposed by this invention is as follows:
[0007] A frequency control method for a hybrid wind turbine group includes the following steps:
[0008] S1. Based on the power flow control loop mathematical model of grid-connected wind turbines and grid-connected wind turbines in a hybrid wind farm, as well as the power grid model, establish the state-space equation of the hybrid wind farm and discretize it into a discrete state-space equation.
[0009] S2. Based on the discrete state-space equations obtained in step S1, and combined with the power capacity constraints, construct and solve the frequency support optimization problem with minimizing grid frequency fluctuations as the objective function, thereby outputting the active power reference value of each wind turbine; the power capacity constraints include: the sum of the total active power output of all wind turbines is equal to the dispatch command value, and the power reference value of each wind turbine does not exceed the remaining available capacity.
[0010] S3. The active power reference value output in step S2 is sent to the corresponding grid-type wind turbine. After receiving the power reference value, the grid-type wind turbine coordinates the adjustment of the grid control parameters and solves the power reference value tracking optimization problem with the objective function of minimizing the deviation between the output power and the power reference value, so as to achieve coordinated optimization of power reference value tracking and frequency support performance.
[0011] Preferably, in step S1, the specific process of establishing the state-space equations of the hybrid wind farm is as follows:
[0012] For grid-connected wind turbines, the state-space equation of the power flow control loop is established based on the second-order time-delay transfer function, and the Routh approximation method is used to reduce the second-order transfer function to a first-order time-delay transfer function.
[0013] For grid-connected wind turbines, a power flow control loop state-space equation is established based on a virtual synchronous machine model, and the Routh approximation method is used to reduce the third-order transfer function to a first-order delayed transfer function.
[0014] For the power grid, the state-space equations of the power grid model are established based on the rotor rotation equations of the synchronous generator;
[0015] Based on the state-space equations of the power flow control loop of grid-connected and grid-connected wind turbines, as well as the state-space equations of the power grid model, a state-space equation for a hybrid wind farm is constructed.
[0016] Preferably, the state-space equation for the power flow control loop of the grid-connected wind turbine is:
[0017]
[0018] in and These represent the increase in active power and the increase in the active power reference value of the grid-connected wind turbine, respectively. This represents the time constant of the power flow control loop of the grid-connected wind turbine. for The first derivative with respect to time;
[0019] The state-space equation for the power flow control loop of a grid-connected wind turbine is:
[0020]
[0021] in and These represent the increase in active power and the increase in the reference value of active power for grid-connected wind turbines, respectively. This represents the time constant of the power flow control loop in a grid-connected wind turbine generator. for The first derivative with respect to time.
[0022] Preferably, the state-space equations of the power grid model are:
[0023]
[0024] in, Indicates the speed increment of the generator set. Indicates the mechanical damping coefficient. This represents the moment of inertia of the rotor. This represents the electromagnetic torque of the generator; for The first derivative with respect to time.
[0025] Preferably, the state-space equation of the hybrid wind farm is:
[0026]
[0027] It is a state vector; for The first derivative with respect to time; The input vector; This is the output vector; , and These are the coefficients of the state-space equations.
[0028] Preferably, the objective function of the frequency support optimization problem in step S2 is... for:
[0029]
[0030] in, Indicates the first The grid angular frequency increment at each predicted time; This indicates the number of prediction steps.
[0031] Preferably, in step S3, the network control parameters include virtual inertia. Virtual damping and droop coefficient The process of collaboratively adjusting the network control parameters is described by the following state-space equations:
[0032]
[0033] in, For state variables, including virtual angular frequency increments Increment of power angle Voltage amplitude increment Virtual inertia increment Virtual damping increment , Increment of droop coefficient and the increase in grid angular frequency Control variables Including the increment of virtual inertia reference value Virtual damping reference value increment Sag coefficient reference value increment ; For output variables; , , These are the coefficients of the state-space equations; for The first derivative with respect to time.
[0034] Preferably, in step S3, the output power of the grid-connected wind turbine is calculated using a prediction formula, specifically:
[0035]
[0036] in For grid-connected wind turbines in the first The predicted total active power at each sampling time; This is the measured active power of the grid-connected wind turbine at the current moment; For the state variables of grid-connected wind turbines in the first... The increment at each sampling time; This is the weight vector.
[0037] Preferably, in step S3, the objective function of the power reference value tracking optimization problem is... for:
[0038]
[0039] in Indicates that the grid-connected wind turbine is in the first The increase in active power at each predicted time point; This indicates the reference value for the active power of a grid-connected wind turbine generator. This indicates the number of prediction steps.
[0040] The present invention also discloses a frequency control system for a hybrid wind turbine group, including a memory and a processor connected to each other. The memory stores a computer program, which, when run by the processor, executes the steps of the method described above.
[0041] Compared with the prior art, the advantages of the present invention are as follows:
[0042] This invention constructs and discretizes the state-space equations of a hybrid wind turbine cluster by establishing power control loop models for grid-connected and grid-connected wind turbines, as well as a power grid model. Based on this, it solves the overall power optimization allocation problem with the goal of minimizing frequency fluctuations, and distributes the obtained power reference values to each wind turbine. Addressing the slow response of grid-connected wind turbines, a collaborative optimization problem for control parameters is further established in their local controllers. By dynamically adjusting parameters such as virtual inertia and damping, it ensures rapid and accurate tracking of the power reference values, thereby improving the response performance of individual turbines while effectively suppressing parameter oscillations during the adjustment process, ultimately significantly enhancing the overall frequency support capability of the hybrid wind farm. Attached Figure Description
[0043] Figure 1 A flowchart illustrating the frequency control method for a hybrid wind turbine group provided in an embodiment of the present invention.
[0044] Figure 2 This is a block diagram of the small-signal model of the virtual synchronizer in an embodiment of the present invention.
[0045] Figure 3 The diagram shows the output power and power reference values of the hybrid wind farm, grid-connected wind turbine, and grid-connected wind turbine in this invention; (a) is the response of the hybrid wind farm; (b) is the response of the grid-connected wind turbine; and (c) is the response of the grid-connected wind turbine.
[0046] Figure 4 This is a schematic diagram of the coordinated adjustment of control parameters for the grid-type wind turbine of the present invention; (a) virtual inertia; (b) virtual damping; (c) droop coefficient. Detailed Implementation
[0047] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.
[0048] like Figure 1 As shown, the frequency control method for hybrid wind turbine groups provided in this embodiment of the invention includes the following steps:
[0049] S1. Considering the frequency regulation function of the hybrid wind farm, it is necessary to model the hybrid wind farm and the power grid. Specifically, based on the state space equation of the wind turbine power flow control loop, the number of various types of units in the hybrid wind farm, and the power grid model, the state space equation of the hybrid wind farm and the corresponding discretized equation are established.
[0050] Since the capacity of the power grid is much larger than that of a hybrid wind farm, it is generally replaced by an ideal voltage source. However, in actual operation, the power grid is a system with a large inertia. After a frequency drop, there will be a long frequency support process, which is difficult to reflect by modeling with a general ideal voltage source. Therefore, this invention uses a large-capacity synchronous generator set as an equivalent power grid and derives the rotor rotation equation based on Newton's second law:
[0051]
[0052] in, This represents the moment of inertia of the generator rotor. Indicates the generator's rotational speed. Represents mechanical torque. Indicates electromagnetic torque. Indicates the mechanical damping coefficient. Indicates the rated speed.
[0053] The mechanical torque of the generator unit can be considered constant over a short period of time; therefore, the state-space equation of the power grid is as follows:
[0054]
[0055] This indicates the generator's speed increment;
[0056] For a power grid model equivalent to a large-capacity synchronous generator, the electromagnetic torque is equivalent to the torque generated by the load power within the power grid, i.e.:
[0057]
[0058] in, Indicates the load torque. Indicates the load power within the power grid. The generator's rotational speed can be considered as the grid system frequency; to simplify calculations, it is assumed that the generator speed fluctuates within a small range of its rated speed.
[0059]
[0060] Assuming that the frequency fluctuations in the power grid system are entirely supported by the hybrid wind farm, the load torque within the power grid can be expressed as:
[0061]
[0062] in, This represents the equivalent load torque supplied to the grid by the hybrid wind farm. The equivalent load torque can be expressed as:
[0063]
[0064] in, This represents the total power of the hybrid wind farm. ; This indicates the number of grid-connected wind turbine units. This indicates the number of grid-connected wind turbine units.
[0065] For grid-connected wind turbines, a mathematical model of the power flow control loop is established based on the power flow control loop transfer function and filter model. Considering the inclusion of a filter to reduce the impact of power harmonics, a first-order filter is added to the power control loop. The mathematical model of the power flow control loop is described by a second-order delay transfer function.
[0066]
[0067] in and These represent the increase in active power and the increase in the active power reference value of the grid-connected wind turbine, respectively. , and These represent the reference value and the real-time measured value of the active power of the grid-connected wind turbine, respectively. This represents the time constant of the power flow control loop of the grid-connected wind turbine. s It is a complex variable. This represents the filter time constant.
[0068] The power flow control loop of a grid-connected wind turbine is a second-order transfer function, while the state-space equations of the subsequent hybrid wind farm only contain first-order quantities. However, the power flow control loop of a grid-connected wind turbine contains second-order quantities. Using the Routh approximation, the second-order transfer function is reduced to a first-order delayed transfer function:
[0069]
[0070] Based on the transfer function of the power flow control loop, the state-space equation of the power flow control loop of the grid-connected wind turbine is derived:
[0071]
[0072] in, The equivalent time constant of the power flow control loop for grid-connected wind turbine units. .
[0073] For grid-connected wind turbines, a virtual synchronous machine control is adopted. The mathematical model of the virtual synchronous machine is as follows:
[0074]
[0075]
[0076]
[0077] in J Represents virtual inertia. D Indicates virtual damping. This represents the droop coefficient (or reactive power regulation coefficient). This represents the phase angle of the virtual synchronizer. and This represents the angular frequency of the virtual synchronous machine and the angular frequency of the power grid. E This indicates the voltage amplitude of the virtual synchronizer. , , and This indicates the active power, active power reference value, reactive power, and reactive power reference value of a grid-connected wind turbine. The reference value for voltage.
[0078] Active power and reactive power for:
[0079]
[0080]
[0081] in This indicates the power angle between the grid-connected wind turbine and the power grid. and This represents the resistance and reactance between the grid-connected wind turbine and the power grid. This indicates the grid voltage.
[0082] Active power and reactive power It can be converted into an incremental form, active power increment. and reactive power increment for:
[0083]
[0084]
[0085] in and This represents the active power increment coefficient of grid-connected wind turbines. and This represents the terminal voltage increment and power angle increment of a grid-connected wind turbine. and This represents the reactive power increment coefficient of a grid-type wind turbine.
[0086] Under steady-state operating conditions The work angle value is relatively small, which is equivalent to , Active power Simplified to:
[0087]
[0088] In actual operation, filters are added to reduce the impact of power harmonics. A first-order filter is added to the power control loop, based on the mathematical model of the virtual synchronous machine and active power. Establish a small-signal model of a virtual synchronizer, such as Figure 2 As shown, the transfer function of the power flow control loop is obtained:
[0089]
[0090] in and These represent the increments of the active power and the active power reference value of the virtual synchronous machine, respectively. This represents the time constant of the filter.
[0091] The power flow control loop of a grid-connected wind turbine is a third-order transfer function, while the state-space equations of the subsequent hybrid wind farm only contain first-order quantities. However, since the power flow control loop of a grid-connected wind turbine contains third-order quantities, the Routh approximation is used to reduce the third-order transfer function to a first-order delayed transfer function.
[0092]
[0093] This model considers the filtering requirements in practical engineering and, unlike the third-order model, replaces the third-order model with a first-order model. The parameters of the first-order model also include the key performance parameters of the original third-order model. The corresponding state-space equation is:
[0094]
[0095] in This represents the equivalent time constant of the power flow control loop of a grid-connected wind turbine. .
[0096] Specifically, based on the state-space equations of the power flow control loops of grid-connected and grid-connected wind turbines and the grid model, the state-space equations of the hybrid wind farm are as follows:
[0097]
[0098] It is a state vector; The input vector; This is the output vector;
[0099] , This indicates the number of grid-connected wind turbine units. Indicates the number of grid-connected wind turbine units;
[0100] ;
[0101] in, , and These are the coefficients of the state-space equations;
[0102] The corresponding discretized equations obtained from the state-space equations of the hybrid wind farm are as follows:
[0103]
[0104] in , , , This indicates the sampling period of the digital signal processor. Indicates the hybrid wind farm in the 1st The state at any given moment, It indicates the state at the next moment.
[0105] S2. Based on the discretized state-space equation of the hybrid wind farm obtained in step S1, and combined with the power capacity constraint, construct and solve the frequency support optimization problem of the hybrid wind farm.
[0106] For hybrid wind farms, the sum of the active power outputs of grid-connected and grid-connected wind turbines should satisfy the active power dispatch command, and the dispatchable power of each wind turbine should be less than the remaining capacity.
[0107]
[0108]
[0109]
[0110] This represents the active power of the i-th grid-connected wind turbine unit; Represents the active power of the i-th grid-connected wind turbine; where This indicates the total power command for the hybrid wind farm; This represents the reference value of the active power of the i-th grid-connected wind turbine unit; This represents the reference value of the active power of the i-th grid-connected wind turbine unit; This represents the remaining available capacity of the i-th grid-connected wind turbine. This represents the remaining available capacity of the i-th grid-connected wind turbine.
[0111] Specifically, the objective function of the frequency support optimization problem for hybrid wind farms is... for:
[0112]
[0113] in, represents the overall optimization objective of the hybrid wind farm, and represents minimizing frequency fluctuations; Indicates the number of prediction steps; Indicates the first The increase in the grid angular frequency at each predicted time.
[0114] By solving the power-frequency support optimization problem of a hybrid wind farm, the frequency support performance of multiple grid-connected and grid-connected wind turbines can be optimized simultaneously.
[0115] After completing one calculation of the optimization problem, the calculated power reference value is sent to each wind turbine in the wind farm.
[0116] S3. Based on the power reference value obtained in step S2, since the grid-connected wind turbine responds better to the power command than the grid-connected wind turbine, it can quickly track the power reference value. Therefore, the grid-connected wind turbine does not need to add any additional control methods after receiving the power reference value. However, the grid-connected wind turbine has a slow response speed and needs to adjust the grid control parameters in coordination after receiving the power reference value to solve the power reference value tracking optimization problem.
[0117] Because grid-connected wind turbines have a relatively slow inertial response, fixed-parameter control cannot quickly and accurately track the power reference value. Therefore, after receiving the power reference value, grid-connected wind turbines coordinately adjust the grid control parameters to ensure tracking of the power reference value. Specifically, this includes:
[0118] S301. Establish the state-space equations of the small-signal model for the coordinated regulation of grid-connected wind turbine control parameters:
[0119]
[0120] in, For state variables, including virtual angular frequency increments Increment of power angle Voltage amplitude increment Virtual inertia increment Virtual damping increment , Increment of droop coefficient and the increase in grid angular frequency Control variables Including the increment of virtual inertia reference value Virtual damping reference value increment Sag coefficient reference value increment ; For output variables; that is , ; , , These are the coefficients of the state-space equations.
[0121] The corresponding discretized state-space equation is:
[0122]
[0123] in , , .
[0124] S302, Constructing a power tracking optimization problem
[0125] When the grid-connected wind turbine responds to the power reference value, its output power is:
[0126]
[0127] in For grid-connected wind turbines in the first The predicted total active power at each sampling time; This is the measured active power of the grid-connected wind turbine at the current moment; For grid-connected wind turbines in the first The active power increment at each sampling time;
[0128] The power increment of grid-type wind turbines and and Therefore, the output power is:
[0129]
[0130] and , … , Prediction can be made by discretizing the state-space equations:
[0131]
[0132] in, and This represents the angle of attack and terminal voltage of a grid-connected wind turbine at time k. and This represents the state matrix and input matrix corresponding to the discretized state-space equations. This represents the predicted value of the state variable at time k+1. This represents the input variable at time k; This represents the increment coefficient of active power versus power angle for grid-type wind turbines.
[0133] The power prediction expression for grid-connected wind turbines is:
[0134]
[0135]
[0136]
[0137] Considering the slow response speed of grid-connected wind turbines, an objective function is set to account for the deviation in power reference value tracking and the fluctuation of grid control parameters during the response process:
[0138]
[0139] in This represents the optimization target for grid-connected wind turbines, and the deviation between the power output of the grid-connected wind turbine and the reference power. Furthermore, considering the stable operation of grid-connected wind turbines, once the output power reaches the reference value, the control parameters deviate from their original stable operating values, which may lead to instability in subsequent operation. Adjusting these three parameters back to their original values ensures that the turbine's disturbance rejection capability will not decrease due to parameter changes.
[0140] S303, Solving and Parameter Update
[0141] By solving the power reference value tracking performance optimization problem of grid-type wind turbines, virtual inertia can be optimized simultaneously. Virtual damping and droop coefficient This reduces the error between the wind turbine's output power and the power reference value, thereby providing better frequency support.
[0142] This invention establishes power control loop models for grid-connected and grid-connected wind turbines, constructs and discretizes the state-space equations of a hybrid wind turbine cluster, and then solves the overall power optimization allocation problem with the goal of minimizing frequency fluctuations. The obtained power reference values are then distributed to each wind turbine. Addressing the slow response of grid-connected wind turbines, a collaborative optimization problem for control parameters is further established in their local controllers. By dynamically adjusting parameters such as virtual inertia and damping, rapid and accurate tracking of the power reference values is ensured. This improves the response performance of individual turbines while effectively suppressing parameter oscillations during the adjustment process, ultimately significantly enhancing the overall frequency support capability of the hybrid wind farm.
[0143] To verify the effectiveness of this invention, a hybrid wind farm cluster was connected to the power grid, including grid-connected wind turbines and grid-connected wind turbines. The operating responses of the hybrid wind farm cluster, grid-connected wind turbines, and grid-connected wind turbines at reduced frequency were selected, such as... Figure 3 As shown in (a), (b), and (c) of this paper, both wind turbines exhibit faster response speed and power point tracking performance after the total power command is given at the initial moment, and when the frequency decreases at 9s.
[0144] like Figure 4 As shown in (a), (b), and (c), virtual inertia is used to optimize the control parameters of grid-connected wind turbines under specific operating conditions. Virtual damping and droop coefficient All were coordinated and controlled, and returned to their original values after the grid-type wind turbines completed their response to ensure stable operation thereafter.
[0145] The present invention also discloses a computer program product, comprising a computer program that, when executed by a processor, performs the steps of the method described above.
[0146] The present invention further discloses a computer-readable storage medium having a computer program stored thereon, the computer program executing the steps of the method described above when run by a processor.
[0147] The present invention also discloses a frequency control system for a hybrid wind turbine group, including a memory and a processor connected to each other. The memory stores a computer program, which, when run by the processor, executes the steps of the method described above.
[0148] The products, media, and systems of the present invention, corresponding to the methods described above, also possess the advantages described above.
[0149] The present invention can implement all or part of the processes in the methods of the above embodiments, or it can be implemented by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium includes: any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. The memory is used to store computer programs and / or modules. The processor implements various functions by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may include high-speed random access memory, as well as non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital (SD) cards, flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.
[0150] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.
Claims
1. A frequency control method for a hybrid wind turbine group, characterized in that, Includes the following steps: S1. Based on the power flow control loop mathematical model of grid-connected wind turbines and grid-connected wind turbines in a hybrid wind farm, as well as the power grid model, establish the state-space equation of the hybrid wind farm and discretize it into a discrete state-space equation. S2. Based on the discrete state-space equations obtained in step S1, and combined with the power capacity constraints, construct and solve the frequency support optimization problem with minimizing grid frequency fluctuations as the objective function, and output the active power reference values of each wind turbine. The power capacity constraints include: the sum of the total active power output of all wind turbines is equal to the dispatch command value, and the power reference value of each wind turbine does not exceed the remaining available capacity. S3. The active power reference value output in step S2 is sent down to the corresponding grid-type wind turbine. After receiving the power reference value, the grid-type wind turbine coordinates the adjustment of the grid control parameters and solves the power reference value tracking optimization problem with the objective function of minimizing the deviation between the output power and the power reference value, so as to achieve the coordinated optimization of power reference value tracking and frequency support performance. In step S1, the specific process of establishing the state-space equations of the hybrid wind farm is as follows: For grid-connected wind turbines, the state-space equation of the power flow control loop is established based on the second-order time-delay transfer function, and the Routh approximation method is used to reduce the second-order transfer function to a first-order time-delay transfer function. For grid-connected wind turbines, a power flow control loop state-space equation is established based on a virtual synchronous machine model, and the Routh approximation method is used to reduce the third-order transfer function to a first-order delayed transfer function. For the power grid, the state-space equations of the power grid model are established based on the rotor rotation equations of the synchronous generator; Based on the state-space equations of the power flow control loop of grid-connected and grid-connected wind turbines, as well as the state-space equations of the power grid model, a state-space equation for a hybrid wind farm is constructed. The state-space equation for the power flow control loop of a grid-connected wind turbine is: in and These represent the increase in active power and the increase in the active power reference value of the grid-connected wind turbine, respectively. This represents the time constant of the power flow control loop of the grid-connected wind turbine. for The first derivative with respect to time; The state-space equation for the power flow control loop of a grid-connected wind turbine is: in and These represent the increase in active power and the increase in the reference value of active power for grid-connected wind turbines, respectively. This represents the time constant of the power flow control loop in a grid-connected wind turbine generator. for The first derivative with respect to time; The objective function of the frequency support optimization problem in step S2 for: in, Indicates the first The grid angular frequency increment at each predicted time; This indicates the number of prediction steps.
2. The frequency control method for a hybrid wind turbine group according to claim 1, characterized in that, The state-space equations of the power grid model are: in, Indicates the speed increment of the generator set. Indicates the mechanical damping coefficient. This represents the moment of inertia of the rotor. This represents the electromagnetic torque of the generator; for The first derivative with respect to time.
3. The frequency control method for a hybrid wind turbine group according to claim 2, characterized in that, The state-space equation for a hybrid wind farm is: It is a state vector; for The first derivative with respect to time; The input vector; This is the output vector; , and These are the coefficients of the state-space equations.
4. The frequency control method for a hybrid wind turbine group according to any one of claims 1-3, characterized in that, In step S3, the network control parameters include virtual inertia. Virtual damping and droop coefficient The process of collaboratively adjusting the network control parameters is described by the following state-space equations: in, For state variables, including virtual angular frequency increments Increment of power angle Voltage amplitude increment Virtual inertia increment Virtual damping increment , Increment of droop coefficient and the increase in grid angular frequency Control variables Including the increment of virtual inertia reference value Virtual damping reference value increment Sag coefficient reference value increment ; For output variables; , , These are the coefficients of the state-space equations; for The first derivative with respect to time.
5. The frequency control method for a hybrid wind turbine group according to claim 4, characterized in that, In step S3, the output power of the grid-connected wind turbine is calculated using a prediction formula, specifically: in For grid-connected wind turbines in the first The predicted total active power at each sampling time; This is the measured active power of the grid-connected wind turbine at the current moment; For the state variables of grid-connected wind turbines in the first... The increment at each sampling time; This is the weight vector.
6. The frequency control method for a hybrid wind turbine group according to claim 5, characterized in that, In step S3, the objective function of the power reference value tracking optimization problem is... for: in Indicates that the grid-connected wind turbine is in the first The increase in active power at each predicted time point; This indicates the reference value for the active power of a grid-connected wind turbine generator. This indicates the number of prediction steps.
7. A frequency control system for a hybrid wind turbine cluster, comprising an interconnected memory and a processor, wherein the memory stores a computer program, characterized in that, The computer program, when run by a processor, performs the steps of the method as described in any one of claims 1-6.