A wind turbine generator frequency modulation parameter optimization method considering twice frequency drop

Abstract

The present application relates to a kind of wind turbine frequency modulation parameter optimization method considering frequency twice drop, belong to power system frequency modulation technical field.The method is in the multi-machine power system including power generation equipment, the system overall frequency response characteristic under the analysis power disturbance ΔP L (s) is established simplified frequency response model;The system overall frequency response characteristic is expressed using frequency common mode component Δω (s);Combined with wind turbine participating in frequency modulation and exiting frequency modulation action, system frequency trajectory analytical expression considering frequency twice drop is obtained, and the analytical expression of frequency first drop and second drop minimum point is obtained based on derivation of the analytical expression;Based on the analytical expression of frequency first drop and second drop minimum point, the wind turbine frequency modulation parameter that satisfies system frequency modulation demand is optimized by optimization algorithm.The present application can comprehensively consider the frequency minimum point in the process of system frequency first drop and second drop to optimize wind power frequency modulation parameter, and it is favorable to better support system frequency.

Description

Technical Field

[0001] This invention belongs to the field of power system frequency regulation technology, and relates to a method for optimizing the frequency regulation parameters of wind turbine generators, specifically a method for optimizing the frequency regulation parameters of wind turbine generators that takes into account two frequency drops. Background Technology

[0002] In recent years, the penetration rate of new energy sources such as wind and solar power in the power system has been continuously increasing. Since new energy sources generally operate in maximum power point tracking mode and do not participate in frequency regulation, this reduces system inertia and frequency regulation capability, adversely affecting system frequency stability. To address this, scholars at home and abroad have proposed control strategies for new energy sources to actively participate in frequency regulation upon grid connection.

[0003] Wind turbines are typically connected to the grid via converters, decoupling their rotor speed from the power system frequency. To utilize the kinetic energy in the turbine rotor to support the frequency, additional frequency regulation control is required. Based on this control, the turbine releases rotor kinetic energy during frequency support, causing its speed to decrease. Once the rotor reaches its minimum speed limit, it can no longer release kinetic energy to support the system frequency; instead, it needs to absorb power from the grid to increase its speed, potentially leading to a secondary frequency drop. Currently, there is limited research on wind power frequency regulation parameter tuning that comprehensively considers the frequency characteristics during both the primary and secondary frequency drops. If the frequency regulation parameter tuning only aims to raise the minimum point of the primary frequency drop, the wind turbine will provide significant active power support to the system during the primary frequency drop. However, correspondingly, it needs to absorb more energy to recover its speed, further lowering the minimum point of the secondary frequency drop. If the frequency regulation parameter tuning only aims to avoid the secondary frequency drop, the wind turbine's active power support is limited during the primary frequency drop, preventing the secondary frequency drop, but the minimum point of the primary frequency drop is not significantly raised.

[0004] Therefore, in order to provide effective frequency support for the system and meet the actual frequency modulation requirements of the system, it is necessary to comprehensively consider the entire frequency dynamic process, including the first drop and the second drop, to raise the minimum point of the first drop as much as possible, and to ensure that the minimum point of the second drop frequency does not go lower. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies, optimize wind turbine frequency regulation parameters to provide effective frequency support for the system, and provide a method for optimizing wind turbine frequency regulation parameters that takes into account two frequency drops. This method can use a simplified frequency response model to analyze the first and second minimum points of the frequency, optimize the wind turbine frequency regulation parameters to meet the system's frequency regulation requirements, and then perform frequency regulation.

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

[0007] A method for optimizing the frequency regulation parameters of wind turbines that takes into account two frequency drops includes the following steps:

[0008] Step (1): In a multi-machine power system containing power generation equipment, a simplified frequency response model is established to analyze the power disturbance ΔP. L The overall frequency response characteristics of the system under (s); the overall frequency response characteristics of the system are represented by the frequency common-mode component Δω(s);

[0009] Step (2) combines the wind turbine's participation in and withdrawal from frequency regulation to derive the analytical expression of the system frequency trajectory considering the second frequency drop;

[0010] Step (3) derive the analytical expressions for the first and second frequency drop minimum points by differentiating the analytical expression of the system frequency trajectory;

[0011] Step (4): Based on the analytical expressions of the lowest points of the first and second frequency drops, the frequency regulation parameters of the wind turbine are optimized to meet the frequency regulation requirements of the system through an optimization algorithm.

[0012] Furthermore, preferably, the power generation equipment includes a synchronous machine and a wind turbine.

[0013] Furthermore, preferably, the specific method of step (1) is as follows:

[0014] A multi-machine power system has a total of n frequency-modulated power generation devices; the power disturbance is ΔP. L (s), ΔP L (s)=-ΔP L / s, where s represents the Laplace operator, ΔP L Indicate the magnitude of the disturbance; analyze the system's frequency common-mode component Δω(s) and power disturbance ΔP. L The simplified frequency response model of the (s) relationship is as follows:

[0015]

[0016] In the formula, J us D us and K us J represents the system's effective inertia, effective damping coefficient, and effective static droop coefficient, respectively. us The effective inertia J of each frequency modulation power generation device ui It is formed by superposition (i.e., summation), D us The effective damping coefficient D of each frequency modulation power generation device ui K is formed by superposition. us The effective static droop coefficient K of each frequency regulation power generation device ui The system is formed by superposition, where T0 is the system droop time constant.

[0017] Power response ΔP of each frequency modulation power generation deviceei (s) and the frequency common-mode component Δω(s) satisfy:

[0018]

[0019] In the formula, J ui D ui and K ui These are respectively represented as the effective inertia, effective damping coefficient, and effective static droop coefficient of each frequency-modulated generator; the above effective coefficients are based on the actual model G of each device. i The power response ΔP derived from (s) ei (s) is the optimization objective, which is obtained by fitting using the least squares algorithm.

[0020] Furthermore, preferably, in step (2), by combining the wind turbine's participation in and withdrawal from frequency regulation, the analytical expression for the system frequency trajectory considering the second frequency drop is derived as follows:

[0021]

[0022] In the formula,

[0023]

[0024] Among them, J us1 D us1 1 / K us1 J represents the effective inertia, effective damping coefficient, and effective static droop coefficient of the system when the wind turbine participates in frequency regulation. us2 D us2 1 / K us2 This represents the coefficient after the wind turbine is removed from frequency regulation; ω d ω d1 σ and σ1 represent the damped oscillation frequencies during the first and second frequency drops of the system, respectively; σ and σ1 represent the attenuation coefficients during the first and second frequency drops of the system, respectively; t1 represents the time when the wind turbine exits frequency regulation; P1 represents the magnitude of the system input power disturbance at time t1; and P0 represents the magnitude of the system input power disturbance at time t0.

[0025] Furthermore, preferably, the specific method of step (3) is as follows:

[0026] (3.1) The lowest point of the first frequency drop Δf nadir1

[0027]

[0028] In the formula, t nadir1 This is the moment when the maximum frequency deviation occurs;

[0029] (3.2) The lowest point of the second frequency drop Δfnadir2

[0030]

[0031] In the formula, t nadir2 This refers to the moment when the second maximum frequency deviation occurs.

[0032] Furthermore, preferably, the specific method of step (4) is as follows:

[0033] The optimization problem derived from the system frequency regulation requirements is specifically described as follows:

[0034]

[0035] In the formula, J ul D ul 1 / K ul The parameters are represented as those obtained by equating the frequency-power response transfer function of a wind turbine to the simplified frequency response model; P w (t), P m (t) represent the output electromagnetic power and input mechanical power of the wind turbine, respectively; H W ω is represented as the equivalent time constant of the wind turbine; r This represents the rotor speed of the wind turbine.

[0036] By constructing the above inequality constraints and objective function into a Lagrange function that satisfies the KKT conditions, and then using the nested Lagrange multiplier method and global search algorithm, the optimal control parameter tuning result in the active frequency regulation process of wind turbine units can be obtained.

[0037] Compared with the prior art, the beneficial effects of this invention are as follows:

[0038] This invention can analyze the overall frequency characteristics of the system using a simplified frequency response model and obtain analytical expressions for the first and second frequency minimums. Taking into account both frequency drops, it establishes an optimization problem to optimize wind power frequency regulation parameters with the goal of improving the minimum, which is beneficial to better support the system frequency.

[0039] After frequency modulation using the frequency modulation parameters obtained by the method of this invention, compared with frequency modulation using existing methods, it can simultaneously improve the minimum point of the second frequency drop and the minimum point of the first frequency drop. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating the method of the present invention.

[0041] Figure 2 This is a schematic diagram of the three-machine system in the simulation verification of an embodiment of the present invention.

[0042] Figure 3This is a model diagram of the turbine governor system in the simulation verification of an embodiment of the present invention.

[0043] Figure 4 This is a power control diagram of a wind turbine generator in a simulation verification of an embodiment of the present invention.

[0044] Figure 5 This is a comparison diagram of the simulated trajectory of the wind turbine participating in frequency regulation and the approximate trajectory under the simplified frequency response model in the simulation verification of the embodiments of the present invention.

[0045] Figure 6 This is a comparison chart of frequency and rotor speed under different parameter setting methods for wind turbine units. Detailed Implementation

[0046] The present invention will now be described in further detail with reference to the embodiments.

[0047] Those skilled in the art will understand that the following embodiments are for illustrative purposes only and should not be construed as limiting the scope of the invention. Where specific techniques or conditions are not specified in the embodiments, they are performed in accordance with the techniques or conditions described in the literature in the field or according to the product instructions. Materials or equipment whose manufacturers are not specified are all conventional products that can be obtained by purchase.

[0048] 1) In multi-machine power systems containing power generation equipment (synchronous machines, wind turbines, etc.), a simplified frequency response model is proposed to analyze the power disturbance ΔP. L The overall frequency response characteristics (frequency common-mode component) of the system under (s) Δω(s);

[0049] 2) Combining the wind turbine's participation in and withdrawal from frequency regulation, the system frequency trajectory considering the second frequency drop is derived;

[0050] 3) Based on the derivative of the system frequency trajectory analytical expression, the analytical expressions for the first and second frequency drop minimum points are obtained;

[0051] 4) Based on the analytical expressions of the first and second frequency drop minimum points, the frequency regulation parameters of the wind turbine are optimized to meet the frequency regulation requirements of the system through optimization algorithms;

[0052] In step 1), the multi-machine power system has a total of n frequency regulation generating units (to consider the dynamic response of loads and other equipment, these can be treated as special generating units); the power disturbance (such as a sudden load increase) is ΔP. L (s), ΔP L (s)=-ΔP L / s, where s represents the Laplace operator, ΔP L Indicate the magnitude of the disturbance; analyze the system's frequency common-mode component Δω(s) and power disturbance ΔP. L The simplified frequency response model of the (s) relationship is as follows:

[0053]

[0054] In the formula, J us D us and K us These are respectively represented as the system's effective inertia, effective damping coefficient, and effective static droop coefficient, which are formed by superimposing the effective coefficients of each frequency-regulating generator. T0 is the system droop time constant.

[0055] Power response ΔP of each device ei (s) satisfies the following with the common-mode component Δω(s) of the system frequency:

[0056]

[0057] In the formula, J ui D ui and K ui These represent the effective inertia, effective damping coefficient, and effective static droop coefficient for each frequency-modulated generator, respectively. The above effective coefficients are based on the actual model G of each device. i The power response ΔP derived from (s) ei (s) is the optimization objective, which is obtained by fitting using the least squares algorithm.

[0058] In step 2), the approximate frequency trajectory under a step disturbance can be obtained using a simplified frequency response model:

[0059]

[0060] If the wind turbines are removed from frequency regulation after a period of time, the uniform structural parameters of the system and the system input power disturbance will change. Define J. us1 D us1 1 / K us1 J is the effective coefficient of the unified structure of the system when wind turbines participate in frequency regulation. us2 D us2 1 / K us2 ΔP is the coefficient of the wind turbine after it exits frequency regulation at time t1; L1 The system input power disturbance at time t1 is compared with the power disturbance ΔP at time t0. L This is related to the speed recovery strategy adopted by the wind turbine when it exits frequency regulation; if the wind turbine adopts a constant output electromagnetic power recovery strategy, then the change in electromagnetic power output ΔP of the wind turbine at time t1 is... w (t1)=ΔP m (t1)-ΔP d ΔP m (t1) represents the change in mechanical power input to the wind turbine at time t1, ΔP d To customize the power difference, satisfying ΔPL1 =ΔP L +ΔP d +ΔP m (t1).

[0061] An approximate frequency-time domain analytical expression considering the first and second frequency drops can be obtained using the state-space solution method:

[0062]

[0063] In the formula,

[0064]

[0065] Where, ω d ω d1 σ, σ1 represent the damped oscillation frequency and attenuation coefficient during the first and second frequency drops of the system, respectively; t1 represents the time when the wind turbine exits frequency regulation; P1 represents the magnitude of the system input power disturbance at time t1; and P0 represents the magnitude of the system input power disturbance at time t0.

[0066] The input mechanical power of the wind turbine unit meets the following requirements:

[0067]

[0068] In the formula, ρ, R, and v represent air density, rotor radius, and undisturbed wind speed, respectively; C p (λ,β) are the wind energy utilization coefficients, and we have:

[0069]

[0070] Where λ and β are the tip speed ratio and the blade pitch angle, respectively, and ω r This represents the rotor speed of the wind turbine; the coefficients c1 to c8 satisfy the following: c1 = 0.5176, c2 = 116, c3 = 0.4, c4 = 5, c5 = 21, c6 = 0.0068, c7 = 0.08, c8 = 0.035.

[0071] In step 3), by differentiating the frequency trajectory equation considering the first and second frequency drops, the analytical expressions for the lowest points of the first and second frequency drops can be obtained as follows:

[0072]

[0073] In the formula, t nadir1 For the moment when the maximum frequency deviation occurs, t nadir2 This refers to the moment when the second maximum frequency deviation occurs.

[0074] In step 4), the system frequency regulation requirement is to maximize the minimum point of the first frequency drop and ensure that the minimum point of the second frequency drop is not greater than the minimum point of the first frequency drop. Furthermore, during the period when the wind turbine is not out of frequency regulation, the wind turbine speed should be guaranteed not to reach the minimum speed limit, causing the wind turbine to stall and resulting in a more severe frequency drop.

[0075] The optimization problem derived from the system frequency regulation requirements is specifically described as follows:

[0076]

[0077] In the formula, J ul D ul 1 / K ul Represented as parameters in a unified structure equivalent to the frequency-power response transfer function of a wind turbine; P w (t), P m (t) represent the output electromagnetic power and input mechanical power of the wind turbine, respectively; H W Let ω be the equivalent time constant of the wind turbine generator; r This represents the rotor speed of the wind turbine.

[0078] The above inequality constraints and objective function are constructed into a Lagrangian function that satisfies the KKT (Karush-Kuhn-Tucker) conditions. The optimal control parameter tuning result in the active frequency regulation process of wind turbines can be obtained by nesting the Lagrange multiplier method and the global search algorithm.

[0079] Application Examples

[0080] like Figure 1 As shown, the method of the present invention is used to process power generation equipment such as synchronous machines and wind turbines in a multi-machine power system.

[0081] By combining the simplified frequency response model, the power disturbance ΔP is obtained. L The relationship between (s) and the overall system frequency response Δω(s) is then established. The least squares algorithm is then used, combined with the transfer functions G of each device. i (s) Four parameters are obtained for each power generation device: effective inertia, effective damping, effective static droop, and system droop time constant. Finally, the minimum points of the two frequency drops are obtained using the above parameters, and the frequency regulation parameters of the wind turbine are optimized.

[0082] Specific embodiments of the present invention are as follows:

[0083] Establish a three-machine power system in Matlab / Simulink software, such as Figure 2As shown in the diagram, the synchronous generators G1 and G2 at nodes 1 and 2 have capacities of 200MVA and 100MVA respectively, both using steam turbines as prime movers. The doubly-fed wind turbine WTG3 at node 3 has a capacity of 30MVA. Nodes 4-6 are network nodes. Nodes 7-9 are load nodes, and the loads are constant power loads. Network nodes and load nodes are collectively referred to as constant power nodes. The line is purely inductive; when per-unit scaling is performed using the capacity of G2 as the capacity reference value, the line parameters are shown in Table 1. In steady state, the voltage at each node is converted to 1, and the phase angle difference between each line is converted to 0.

[0084] Table 1. Line reactance values ​​in simulation verification of the embodiments.

[0085] <![CDATA[X 14 ]]> 0.05 <![CDATA[X 25 ]]> 0.15 <![CDATA[X 36 ]]> 0.05 <![CDATA[X 47 ]]> 0.1 <![CDATA[X 48 ]]> 0.1 <![CDATA[X 57 ]]> 0.2 <![CDATA[X 59 ]]> 0.2 <![CDATA[X 68 ]]> 0.1 <![CDATA[X 69 ]]> 0.1

[0086] Using the capacity of G2 as the baseline capacity, then F = [F1, F2, F3] T =[2,1,1] T F i This represents the capacity ratio of each power generation device.

[0087] G1 and G2 are steam turbine units, and the frequency-active power transfer function G... i (s) is

[0088] G i (s)=F i g i (s)

[0089] g i (s)=J i s+D i +G TSi (s)

[0090]

[0091] Among them G TSi (s) is G i The transfer function of the governor-turbine system (referred to as the governor system) is shown in the model below. Figure 3 As shown. The parameters under their own rated power per unit are: moment of inertia J1=J2=8s; damping coefficient D1=D2=2; rate of descent R1=R2=0.05; governor time constant T. G1 =T G2 =0.2s; Steam inlet chamber time constant T CH1 =T CH2 =0.3s; Time constant T of the reheater RH1 =10s, T RH2 =5s; High-pressure cylinder power ratio F HP1 =F HP2 =0.3.

[0092] Wind turbines using the DFIG model, such as Figure 4 As shown in the figure, V sq ω represents the q-axis component of the stator-side voltage of the wind turbine generator; PLL is a phase-locked loop; ref The rated angular frequency of the power grid; ω g ω is the angular frequency of the power grid. r K represents the rotor speed of the wind turbine. J K is the virtual inertia coefficient. D P is the droop coefficient; T1 is the time constant of the filter stage; MPPT P is the active power reference value obtained from the MPPT curve. in With P dp These are the virtual inertia and the additional active reference value components generated by droop control, respectively; P ref Pm represents the active power reference value of the wind turbine generator; P is the wind turbine mechanical power. W Wind power generates electromagnetic power; ΔP d The difference between mechanical power and electromagnetic power at the moment of exiting frequency modulation.

[0093] Speed ​​recovery power difference ΔP d =0.03 pu, and the frequency-active power transfer function G3(s) in electromechanical scale is:

[0094] G3(s) = F3g3(s)

[0095]

[0096] The parameter values ​​are shown in Table 2.

[0097] Table 2 shows the parameter values ​​of some inverter variables in the simulation verification of the embodiment.

[0098]

[0099]

[0100] Using the method of this invention, the relationship between disturbance and frequency response is obtained:

[0101]

[0102] When a 50MW power disturbance occurs at node 8, the least squares algorithm is used to analyze the common-mode frequency component within an 8s timeframe, taking into account the transfer functions G of each device. i (s) The four parameters of effective inertia, effective damping, effective static droop, and system droop time constant of each power generation device are obtained. The calculation results are shown in Table 3.

[0103] Table 3 Effectiveness coefficients of various power generation equipment

[0104] Simplified frequency response model effective coefficient G1 G2 WTG3 <![CDATA[T0]]> 5 5 5 <![CDATA[J ui ]]> 13.94 6.79 4.50 <![CDATA[D ui ]]> 11.46 5.73 6.64 <![CDATA[1 / K ui ]]> 23.58 16.73 -1.06

[0105] According to the method of the present invention, the frequency trajectory and the system common-mode trajectory are obtained by using a simplified frequency response model, for example... Figure 5 As shown. By Figure 5 It can be seen that at different frequency regulation exit times t1, the frequency trajectories obtained based on the simplified frequency response model are basically consistent with the system common-mode trajectory. The established simplified frequency response model can analyze the system common-mode frequency characteristics over a relatively long period of time, and the analytical expressions of the two lowest points of the system frequency drop calculated under this model can be used to optimize the wind power frequency regulation parameters.

[0106] When simulating the frequency regulation parameter tuning of wind turbines, the main focus is on the impact of the wind turbine frequency regulation control parameters on the minimum points of the primary and secondary frequency drops. In the optimization, the frequency regulation exit time t1 = 4s was given. The initial speed of the wind turbine is 1.1 / pu, and the minimum speed limit ω is taken. rmin The value is 0.7 / pu. The optimized algorithm yielded the wind turbine parameter tuning results for different capacity ratios under WTG3, as shown in Table 4.

[0107] Table 4. Results of Optimal Control Parameter Tuning for Wind Turbine Units

[0108]

[0109]

[0110] To verify the effectiveness of the proposed frequency regulation parameter tuning method, taking a wind power capacity ratio of 5% as an example, the system frequency response obtained by the following frequency regulation parameter tuning methods is compared: (1) the method proposed in this paper; (2) making full use of rotor kinetic energy and mainly using virtual inertia control; (3) making full use of rotor kinetic energy and mainly using droop control; (4) consuming the same rotor kinetic energy as the method proposed in this paper and mainly using virtual inertia control; (5) the wind turbine does not participate in frequency regulation.

[0111] Under the system and disturbances described above, considering rotor kinetic energy constraints and with droop control as the primary factor, the wind turbine parameter D... u3 The maximum value is approximately 230; when virtual inertia control is the primary method, the wind turbine parameter J... u3 The maximum value is approximately 400; the virtual inertia control parameter Ju3 is 22.9 under the same rotor kinetic energy consumption as the optimization result.

[0112] Simulations were performed by comparing the above tuning parameters to obtain the system frequency variation and wind turbine rotor speed variation, as follows: Figure 6As shown in the figure, among the aforementioned five methods for tuning the frequency control parameters of wind turbine generators, the method proposed in this paper can optimally improve the minimum points of the first and second frequency drops in the system. Therefore, by using optimization problems to tune the control parameters of wind turbine generators under different capacity ratios, effective frequency support, including the second frequency drop process, can be achieved.

[0113] The results show that by using the optimized algorithm based on the lowest frequency point obtained from the analysis, the frequency regulation parameters of the wind turbine can be reasonably adjusted to meet the frequency regulation requirement that the second frequency drop minimum point is greater than the first frequency drop minimum point while ensuring that the deviation of the first frequency drop minimum point is as small as possible.

[0114] The examples of this invention demonstrate the effectiveness of the approximate method for the overall frequency trajectory of a multi-machine power system including wind turbines and the algorithm for adjusting the frequency regulation parameters of wind turbines.

[0115] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing the frequency regulation parameters of a wind turbine generator considering two frequency drops, characterized in that, Includes the following steps: Step (1): In a multi-machine power system containing power generation equipment, establish a simplified frequency response model to analyze power disturbances. The overall system frequency response characteristics are described below; the overall system frequency response characteristics are expressed using the common-mode component. express; Step (2): Combining the wind turbine's participation in and withdrawal from frequency regulation, the analytical expression of the system frequency trajectory considering the second frequency drop is derived. Step (3): Based on the analytical expression of the system frequency trajectory, the analytical expressions for the first and second frequency drop minimum points are obtained by taking the derivative. Step (4): Based on the analytical expressions of the lowest points of the first and second frequency drops, the frequency regulation parameters of the wind turbine are optimized to meet the frequency regulation requirements of the system through an optimization algorithm.

2. The method for optimizing wind turbine frequency regulation parameters considering two frequency drops according to claim 1, characterized in that, Power generation equipment includes synchronous generators and wind turbines.

3. The method for optimizing wind turbine frequency regulation parameters considering two frequency drops according to claim 1, characterized in that, The specific method for step (1) is as follows: The multi-machine power system has a total of n Taiwan can participate in frequency regulation power generation equipment; power disturbance is , , s Represents the Laplace operator. Indicates the magnitude of the disturbance; Analyze the common-mode components of the system frequency With power disturbance The simplified frequency response model of the relationship is as follows: In the formula, J us , D us and K us These are respectively represented as the system's effective inertia, effective damping coefficient, and effective static droop coefficient. J us The effective inertia of each frequency modulation power generation device J ui It is formed by stacking. D us The effective damping coefficient of each frequency modulation power generation device D ui It is formed by stacking. K us Effective static droop coefficient of each frequency regulation power generation device K ui It is formed by stacking. T 0 represents the system droop time constant; Power response of various frequency modulation power generation devices Common-mode components with frequency satisfy: In the formula, J ui , D ui and K ui These are respectively represented as the effective inertia, effective damping coefficient, and effective static droop coefficient of each frequency-modulated generator.

4. The method for optimizing wind turbine frequency regulation parameters considering two frequency drops according to claim 3, characterized in that, In step (2), combining the wind turbine's participation in and withdrawal from frequency regulation, the analytical expression for the system frequency trajectory considering the second frequency drop is derived as follows: In the formula, in, J us1 , D us1 1 / K us1 These represent the system's effective inertia, effective damping coefficient, and effective static droop coefficient when the wind turbine participates in frequency regulation. J us2 , D us2 1 / K us2 This represents the coefficient after the wind turbine is removed from frequency regulation. , These represent the damped oscillation frequencies during the first and second frequency drops of the system, respectively. , These represent the attenuation coefficients during the first and second frequency drops of the system, respectively. t 1 indicates the time when the wind turbine unit exits frequency regulation; P 1 represents t The magnitude of the system input power disturbance at time 1; P0 express t The magnitude of the system input power disturbance at time 0.

5. The method for optimizing wind turbine frequency regulation parameters considering two frequency drops according to claim 4, characterized in that, The specific method for step (3) is as follows: (3.1) The lowest point of the first frequency drop Δ f nadir1 In the formula, t nadir1 This is the moment when the maximum frequency deviation occurs; (3.2) The lowest point of the second frequency drop Δ f nadir2 In the formula, t nadir2 This refers to the moment when the second maximum frequency deviation occurs.

6. The method for optimizing wind turbine frequency regulation parameters considering two frequency drops according to claim 5, characterized in that, The specific method for step (4) is as follows: The optimization problem derived from the system frequency regulation requirements is specifically described as follows: In the formula, J ul , D ul 1 / K ul These are expressed as parameters derived from the wind turbine frequency-power response transfer function and converted to a simplified frequency response model. P w ( t ), P m ( t These represent the output electromagnetic power and input mechanical power of the wind turbine, respectively. H W This is expressed as the equivalent time constant of the wind turbine. This represents the rotor speed of the wind turbine. ω rmin This is the minimum speed limit for wind turbine generators; By constructing the above inequality constraints and objective function into a Lagrange function that satisfies the KKT conditions, and then using the nested Lagrange multiplier method and global search algorithm, the optimal control parameter tuning result in the active frequency regulation process of wind turbine units can be obtained.

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