A dynamic angle of view wind power primary frequency control performance evaluation index design method

Abstract

The application provides a dynamic angle of view wind power primary frequency control performance evaluation index design method, and belongs to the field of power system primary frequency regulation. The method is realized based on an evaluation model under multiple frequency control modes of a wind turbine generator unit. First, a dynamic evaluation model of the wind turbine generator unit primary frequency regulation under a rotor kinetic energy control mode and a pitch angle control mode is established respectively, and the control performance evaluation index is designed based on the dynamic evaluation model. The application is aimed at the deficiency of the traditional unit primary frequency control performance evaluation method, and proposes a dynamic angle of view wind power primary frequency control performance evaluation index design method in the field of power system frequency stability analysis and control, which can effectively improve the accuracy of the unit primary frequency regulation evaluation result. The application can accurately and reliably evaluate the real primary frequency control performance of the unit by using the proposed wind turbine generator unit primary frequency regulation evaluation model and the proposed dynamic angle of view primary frequency control performance evaluation index.

Description

Technical Field

[0001] This invention belongs to the field of primary frequency regulation in power systems, and relates to a method for evaluating the primary frequency regulation control performance of wind turbine generators, particularly a method for designing evaluation indicators for primary frequency regulation control performance of wind power from a dynamic perspective. Background Technology

[0002] The evaluation of primary frequency regulation control performance of a generating unit involves assessing and analyzing its primary frequency regulation effect after a disturbance. By analyzing the primary frequency regulation response power data, relevant evaluation indicators are obtained to clarify whether its actual performance meets theoretical performance specifications. Based on the evaluation results, rewards are given for good performance and penalties for poor performance, aiming to better guide and regulate the primary frequency regulation control behavior of the unit and help supervise and ensure the rapid recovery capability of the power grid from frequency instability. The "Two Detailed Rules" clearly state that grid-connected renewable energy generating units also need to participate in the system's primary frequency regulation; however, currently, there is a lack of in-depth research on the evaluation methods for the primary frequency regulation of renewable energy generating units. Wind turbine generators, due to their objective existence of rotating mechanical components similar to traditional synchronous generators, possess enormous potential for primary frequency regulation, thus requiring more meticulous management of their primary frequency regulation control performance.

[0003] The essence of wind turbine evaluation is the comparison between its expected and actual power output. Traditional primary frequency regulation evaluation methods simplify the dynamic process of primary frequency regulation as if the theoretical power output of the turbine should increase linearly with frequency deviation according to the unit regulation power setpoint. While simple and easy to implement, this method is too coarse in determining the expected power output of the turbine and is not conducive to constraining the primary frequency regulation control performance of wind turbines. In contrast to traditional evaluation methods, the primary frequency regulation evaluation method from a dynamic perspective uses the standard transfer function of the turbine's primary frequency regulation as the evaluation criterion. Using the transfer function as the evaluation criterion takes into account the dynamic process of the turbine's response frequency difference, hence it is also called a dynamic evaluation method. This invention starts with a dynamic evaluation method and proposes corresponding dynamic perspective primary frequency regulation control performance evaluation indicators and their identification methods, which are more suitable for the primary frequency regulation evaluation problem of wind turbines under the current power system frequency stability control situation. Summary of the Invention

[0004] This invention addresses the shortcomings of traditional static evaluation methods in terms of the principle of acquiring evaluation parameters. In the field of primary frequency regulation control performance evaluation of wind turbine units, it proposes a method for acquiring control performance evaluation parameters and designing rating indicators based on the primary frequency regulation control model of wind turbine units.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for designing performance evaluation indicators for primary frequency regulation control of wind power from a dynamic perspective is proposed. Based on evaluation models under various frequency regulation control modes of wind turbines, the method first establishes dynamic evaluation models for primary frequency regulation of wind turbines under rotor kinetic energy control mode and pitch angle control mode, respectively. Then, control performance evaluation indicators are designed based on these dynamic evaluation models. The method includes the following steps:

[0007] S1: Evaluation model for primary frequency regulation of wind turbines under rotor kinetic energy control mode:

[0008] S1-1: The process of wind turbines participating in primary frequency regulation by releasing rotor kinetic energy is a dynamic power conversion process. The power increment ΔP resulting from the change in rotor speed is composed of the following two parts: one part comes from the rotor kinetic energy ΔP released by the change in rotor speed. W The other part is the difference in wind energy captured by the DFIG due to changes in rotational speed ΔP. Wem The calculation method is as follows:

[0009] ΔP=ΔP W +ΔP Wem (1)

[0010] S1-2: Using the system frequency difference as the input signal, the power control signal ΔP is obtained through droop and virtual inertial control. We_s :

[0011]

[0012] In the formula, K WD To simulate the droop coefficient, K WI T is the virtual inertia coefficient. WD is the time constant.

[0013] S1-3: Based on the speed change equation, the rotor kinetic energy change ΔP is obtained. W The relationship between the rotational speed change Δω and the rotational speed change:

[0014]

[0015] In the formula, T JW ω is the rotor's moment of inertia; ω0 is the rotor's initial speed; Δω is the change in rotor speed; and t is time.

[0016] S1-4: When the fan speed changes to perform frequency regulation, the actual rotor speed is between 0.7 pu and 1.2 pu. Under normal disturbances, the speed change Δω is less than 0.2 pu, so the higher-order terms of Δω can be ignored, and the approximate simplification is as follows:

[0017]

[0018] In the formula, k de=f'(v,ω0+ε), representing the rate of change of wind energy captured power caused by changes in rotational speed; P MPPT The active power of the wind turbine operating in maximum power point tracking mode; k opt is the control coefficient for maximum power point tracking mode; f(v,ω0+Δω) is the mechanical power captured by the wind turbine; v is the wind speed.

[0019] S1-5: Due to ΔP Wem To capture the wind power difference in the DFIG, therefore:

[0020] ΔP Wem =k de Δω (5)

[0021] S1-6: According to formulas (1) to (5), the transfer function of the primary frequency regulation evaluation model of the wind turbine under rotor kinetic energy control mode can be obtained:

[0022]

[0023] In the formula, s is a complex variable in the Laplace transform domain.

[0024] S2: Evaluation model for primary frequency regulation of wind turbines under pitch angle control mode:

[0025] S2-1: Pitch angle control is achieved by controlling the pitch angle, thereby changing the wind turbine's capture mechanical power for primary frequency regulation. The magnitude of the wind turbine's capture mechanical power P is:

[0026]

[0027] In the formula, ρ is the air density; R is the fan rotation radius; v is the ambient wind speed; C p (λ,θ) represents the wind energy utilization coefficient; λ represents the tip speed ratio; and θ represents the blade pitch angle.

[0028] S2-2: The pitch angle control mode uses the system frequency difference as the input signal, which is then proportionally amplified to obtain the pitch angle control signal P. s for:

[0029] P s =K σ Δf(s) (8)

[0030] In the formula, K σ Δf(s) represents the droop coefficient; Δf(s) represents the Laplace transform of the frequency deviation.

[0031] S2-3: The pitch angle control signal is used to adjust the pitch angle via a servo motor. If the inertial time constant of the servo motor is T, then the pitch angle change Δθ is:

[0032]

[0033] S2-4: Substituting the change in pitch angle into formula (7) for the wind turbine capture mechanical power expression, we obtain the power increment ΔP as follows:

[0034]

[0035] In the formula, θ0 is the initial pitch angle of the wind turbine.

[0036] S2-5: According to formulas (7) to (10), the transfer function of the primary frequency regulation evaluation model of the wind turbine under pitch angle control mode can be obtained:

[0037]

[0038] In the formula, k del =f'(ω0,θ) represents the rate of change of wind energy capture power caused by the change in pitch angle.

[0039] S3: Design of performance evaluation indicators for primary frequency regulation control of wind turbine units from a dynamic perspective:

[0040] It includes two parts: a power perspective and an energy perspective.

[0041] The power perspective primarily evaluates the magnitude of the unit's primary frequency regulation active power adjustment. It assumes that the unit increases or decreases its active power output according to the frequency difference using a droop coefficient, and the magnitude of the unit's primary frequency regulation power at any given time mainly depends on the set value of the droop coefficient parameter; specifically:

[0042] S3-1: From a power perspective, the least squares parameter identification method is used to reasonably calculate the actual power performance. Taking the pitch angle control mode as an example, the droop coefficient is set as the parameter β to be identified. Actu :

[0043]

[0044] S3-2: Convert the frequency domain expression of the identification process into a time domain expression:

[0045]

[0046] In the formula, This is the second derivative of the actual frequency response power of the unit; P is the derivative of the actual frequency response power of the unit; theo (t) represents the actual frequency response power of the unit; Δf cal (t) represents the system frequency deviation.

[0047] S3-3: Define the error function ε:

[0048]

[0049] S3-4: Minimize the error function, that is, let Solving for:

[0050]

[0051] S3-5: Based on the above calculations, the actual value β of the unit droop coefficient parameter can be achieved. Actu The calculation is as follows: The dynamic adjustment amplitude index K%, is defined to reflect the degree of compliance of the dynamic adjustment amplitude parameter with the standard value during the primary frequency regulation response process. β Actu The actual value obtained from equation (15); β Theo This is the theoretical value of the dynamic adjustment amplitude parameter, which is the reciprocal of the unit's droop coefficient. Therefore, the formula for calculating K% is:

[0052] K% = β Actu / β Theo (16)

[0053] The energy perspective primarily evaluates the integral active power contribution of the unit during primary frequency regulation, focusing more on the unit's contribution to the energy deficit during primary frequency regulation. The magnitude of the unit's total contribution during the entire primary frequency regulation process depends on the unit's primary frequency regulation control mode and response characteristics. Specifically: S3-6: From an energy perspective, convolution operation technology is used to reasonably calculate the theoretical performance benchmark of the integral energy. Taking the rotor kinetic energy control mode as an example, its active power adjustment value P Theo Represented as:

[0054] P Theo =Δf Cal (s)×G(s) (17)

[0055] S3-7: To solve for the integral power of primary frequency regulation of wind turbine generators, the frequency domain characteristics are transformed into time domain convolution operations based on the convolution theorem:

[0056]

[0057] In the formula, "*" represents the convolution operator.

[0058] S3-8: Since the system frequency difference and power time series are sampled at equal intervals, the product of the sampled value and the sampling period at each sampling point can be used to approximate the integral value:

[0059]

[0060] In the formula, k is the sampling point number in the time series; [t z / T] is not greater than t z The largest integer of / T; g(t) is the inverse Laplace transform expression of G(s).

[0061] S3-9: For P theo Integrating the sampled time, the theoretical value of the unit's primary frequency regulation integral power during the sampling time is calculated:

[0062]

[0063] In the formula, k end This represents the end sampling position in the time series.

[0064] S3-10: Based on the above calculations, the theoretical value of the unit's primary frequency regulation integral power W can be achieved. Theo The calculation of the dynamic cumulative effect index W% is defined to reflect the degree of compliance of the dynamic cumulative effect parameter of the primary frequency modulation response process with the standard value. Theo The theoretical value obtained from equation (19); W Actu The actual value of the integral power during primary frequency regulation can be directly calculated by integrating the primary frequency regulation response power data. Therefore, the formula for calculating W% is:

[0065] W% = W Actu / W Theo (twenty one)

[0066] The beneficial effects of this invention are:

[0067] This invention addresses the shortcomings of traditional methods for evaluating the primary frequency regulation control performance of wind turbine units. In the field of power system frequency stability analysis and control, it proposes a design method for wind power primary frequency regulation control performance evaluation indicators from a dynamic perspective. Specifically, it presents a primary frequency regulation evaluation model under wind turbine rotor kinetic energy control and pitch angle control modes, and further provides a method for designing dynamic perspective evaluation indicators based on the evaluation model and obtaining evaluation parameters, which can effectively improve the accuracy of the unit's primary frequency regulation evaluation results. This invention utilizes the proposed wind turbine primary frequency regulation evaluation model and, based on the proposed dynamic perspective primary frequency regulation control performance evaluation indicators, can accurately and reliably assess the actual primary frequency regulation control performance of the unit. Attached Figure Description

[0068] Figure 1 An open-loop evaluation model for primary frequency regulation of wind turbine generators under rotor kinetic energy control mode;

[0069] Figure 2 An open-loop evaluation model for primary frequency regulation of wind turbines under pitch angle control mode;

[0070] Figure 3 To evaluate the effectiveness of parameter acquisition under rotor kinetic energy control mode; Figure 3 (a) shows the actual performance from a power perspective; Figure 3 (b) Theoretical performance benchmarks from an energy perspective;

[0071] Figure 4 To evaluate the effectiveness of parameter acquisition in pitch angle control mode; Figure 4 (a) shows the actual performance from a power perspective; Figure 4 (b) Theoretical performance benchmark from an energy perspective. Detailed Implementation

[0072] To make the technical solution and advantages of the present invention clearer, a primary frequency regulation simulation model of a wind turbine is introduced below, using a step signal of 5% pu to simulate a high power loss fault. In conjunction with specific embodiments and accompanying drawings, the technical solution of the present invention will be clearly and completely described.

[0073] This invention addresses the shortcomings of traditional static evaluation methods in terms of parameter acquisition principles. In the field of wind turbine primary frequency regulation control performance evaluation, it proposes a method for acquiring control performance evaluation parameters and designing rating indicators based on a wind turbine primary frequency regulation control model. This embodiment, based on evaluation models under various frequency regulation control modes of wind turbines, firstly establishes dynamic evaluation models for wind turbine primary frequency regulation in rotor kinetic energy control mode and pitch angle control mode, respectively. Then, it designs control performance evaluation indicators based on these dynamic evaluation models. The method includes the following steps:

[0074] S1: Evaluation model for primary frequency regulation of wind turbines under rotor kinetic energy control mode:

[0075] S1-1: The process of wind turbines participating in primary frequency regulation by releasing rotor kinetic energy is a dynamic power conversion process. The power increment ΔP resulting from the change in rotor speed is composed of the following two parts: one part comes from the rotor kinetic energy ΔP released by the change in rotor speed. W The other part is the difference in wind energy captured by the DFIG due to changes in rotational speed ΔP. Wem The calculation method is as follows:

[0076] ΔP=ΔP W +ΔP Wem (twenty two)

[0077] S1-2: Using the system frequency difference as the input signal, the power control signal ΔP is obtained through droop and virtual inertial control. We_s :

[0078]

[0079] In the formula, K WD To simulate the droop coefficient, K WI T is the virtual inertia coefficient. WD is the time constant.

[0080] S1-3: Based on the speed change equation, the rotor kinetic energy change ΔP is obtained. WThe relationship between the rotational speed change Δω and the rotational speed change:

[0081]

[0082] In the formula, T JW ω is the rotor's moment of inertia; ω0 is the rotor's initial speed; Δω is the change in rotor speed; and t is time.

[0083] S1-4: When the fan speed changes to perform frequency regulation, the actual rotor speed is between 0.7 pu and 1.2 pu. Under normal disturbances, the speed change Δω is less than 0.2 pu, so the higher-order terms of Δω can be ignored, and the approximate simplification is as follows:

[0084]

[0085] In the formula, k de =f'(v,ω0+ε), representing the rate of change of wind energy captured power caused by changes in rotational speed; P MPPT The active power of the wind turbine operating in maximum power point tracking mode; k opt is the control coefficient for maximum power point tracking mode; f(v,ω0+Δω) is the mechanical power captured by the wind turbine; v is the wind speed.

[0086] S1-5: Due to ΔP Wem To capture the wind power difference in the DFIG, therefore:

[0087] ΔP Wem =k de Δω (26)

[0088] S1-6: According to formulas (1) to (5), the transfer function of the primary frequency regulation evaluation model of the wind turbine under rotor kinetic energy control mode can be obtained:

[0089]

[0090] In the formula, s is a complex variable in the Laplace transform domain. In the simulation model, K is taken as... WD =20; K WI =5;T WD =2.6; T JW =18.72; v=8.

[0091] S2: Evaluation model for primary frequency regulation of wind turbines under pitch angle control mode:

[0092] S2-1: Pitch angle control is achieved by controlling the pitch angle, thereby changing the wind turbine's capture mechanical power for primary frequency regulation. The magnitude of the wind turbine's capture mechanical power P is:

[0093]

[0094] In the formula, ρ is the air density; R is the fan rotation radius; v is the ambient wind speed; C p (λ,θ) represents the wind energy utilization coefficient; λ represents the tip speed ratio; and θ represents the blade pitch angle.

[0095] S2-2: The pitch angle control mode uses the system frequency difference as the input signal, which is then proportionally amplified to obtain the pitch angle control signal P. s for:

[0096] P s =K σ Δf(s) (29)

[0097] In the formula, K σ Δf(s) represents the droop coefficient; Δf(s) represents the Laplace transform of the frequency deviation.

[0098] S2-3: The pitch angle control signal is used to adjust the pitch angle via a servo motor. If the inertial time constant of the servo motor is T, then the pitch angle change Δθ is:

[0099]

[0100] S2-4: Substituting the change in pitch angle into formula (7) for the wind turbine capture mechanical power expression, we obtain the power increment ΔP as follows:

[0101]

[0102] In the formula, θ0 is the initial pitch angle of the wind turbine.

[0103] S2-5: According to formulas (7) to (10), the transfer function of the primary frequency regulation evaluation model of the wind turbine under pitch angle control mode can be obtained:

[0104]

[0105] In the formula, k del =f'(ω0,θ) represents the rate of change of wind energy captured power caused by the change in pitch angle. In the simulation model, T = 1; K σ =20; v=12.

[0106] S3: Design of performance evaluation indicators for primary frequency regulation control of wind turbine units from a dynamic perspective:

[0107] It includes two parts: a power perspective and an energy perspective.

[0108] The power perspective primarily evaluates the magnitude of the unit's primary frequency regulation active power adjustment. It assumes that the unit increases or decreases its active power output according to the frequency difference using a droop coefficient, and the magnitude of the unit's primary frequency regulation power at any given time mainly depends on the set value of the droop coefficient parameter; specifically:

[0109] S3-1: From a power perspective, taking pitch angle control mode as an example, the droop coefficient is set as the parameter β to be identified. Actu A 5% PU step signal was used to simulate a high-power loss fault, and the frequency deviation after the disturbance was obtained. Based on the transfer function of the unit's primary frequency regulation evaluation model, the least squares parameter identification method was used to reasonably calculate the actual power performance. The specific steps are as follows:

[0110]

[0111] S3-2: Convert the frequency domain expression of the identification process into a time domain expression:

[0112]

[0113] In the formula, This is the second derivative of the actual frequency response power of the unit; P is the derivative of the actual frequency response power of the unit; theo (t) represents the actual frequency response power of the unit; Δf cal (t) represents the system frequency deviation.

[0114] S3-3: Define the error function ε:

[0115]

[0116] S3-4: Minimize the error function, that is, let Solving for:

[0117]

[0118] S3-5: Based on the above calculations, substituting the frequency deviation and transfer function, we can obtain β. Actu =20.20. If the result obtained using the traditional static method is β... Actu =12.48. Define the dynamic adjustment amplitude index K%, which reflects the degree of compliance of the dynamic adjustment amplitude parameter with the standard value during the primary frequency regulation response process. β Actu The actual value obtained from equation (36); β Theo This is the theoretical value of the dynamic adjustment amplitude parameter, which is the reciprocal of the unit's droop coefficient. Therefore, the formula for calculating K% is:

[0119] K% = β Actu / β Theo (37)

[0120] The energy perspective primarily evaluates the integral energy contribution of the unit's active power during primary frequency regulation, focusing more on the unit's contribution to the energy deficit during primary frequency regulation. The magnitude of the unit's energy contribution throughout the primary frequency regulation process depends on the unit's primary frequency regulation control mode and response characteristics. Specifically:

[0121] S3-6: From an energy perspective, convolution operation techniques are used to reasonably calculate the theoretical performance benchmark of integrated electric charge. Taking the rotor kinetic energy control mode as an example, its active power adjustment value P... Theo Represented as:

[0122] P Theo =Δf Cal (s)×G(s) (38)

[0123] S3-7: To solve for the integral power of primary frequency regulation of wind turbine generators, the frequency domain characteristics are transformed into time domain convolution operations based on the convolution theorem:

[0124]

[0125] In the formula, "*" represents the convolution operator.

[0126] S3-8: Since the system frequency difference and power time series are sampled at equal intervals, the product of the sampled value and the sampling period at each sampling point can be used to approximate the integral value:

[0127]

[0128] In the formula, k is the sampling point number in the time series; [t z / T] is not greater than t z The largest integer of / T; g(t) is the inverse Laplace transform expression of G(s).

[0129] S3-9: For P theo Integrating the sampled time, the theoretical value of the unit's primary frequency regulation integral power during the sampling time is calculated:

[0130]

[0131] In the formula, k end This represents the end sampling position in the time series.

[0132] S3-10: According to the above method, substituting the frequency deviation and transfer function, we can obtain W. Theo =1.35. If the result obtained using the traditional static method is W... Theo =2.86. The dynamic cumulative effect index W% is defined to reflect the degree of compliance of the dynamic cumulative effect parameter of a primary frequency modulation response process with the standard value. Theo The theoretical value obtained from equation (41); WActu The actual value of the integral power during primary frequency regulation can be directly calculated by integrating the primary frequency regulation response power data. Therefore, the formula for calculating W% is:

[0133] W% = W Actu / W Theo (42)

[0134] Based on the above calculations, the parameter acquisition results shown in Table 1 can be obtained.

[0135] Table 1 Comparison of parameter acquisition results between static and dynamic methods

[0136]

[0137] This invention discloses a design method for evaluating the performance of wind power primary frequency regulation control from a dynamic perspective. Two detailed rules explicitly state that grid-connected renewable energy units are also required to have primary frequency regulation capability, with wind turbines possessing significant potential for primary frequency regulation, necessitating meticulous management and assessment of their primary frequency regulation control performance. Traditional primary frequency regulation control performance evaluation methods rely on the unit's static power-frequency curve to examine the primary frequency regulation control process, which is overly simplistic and fails to accurately and reliably constrain the primary frequency regulation process of wind turbines with more complex control modes and response characteristics. This invention, from a dynamic perspective, uses the primary frequency regulation transfer function of wind turbines under various control modes as a basis, proposing two evaluation indicators: a power-perspective primary frequency regulation capability index and an energy-perspective primary frequency regulation integral power index. It also provides a method for identifying the actual and theoretical values ​​of the evaluation parameters included in these indicators. This method effectively improves the degree to which evaluation parameters reflect the true primary frequency regulation control performance of the unit, and the evaluation indicators can more rigorously and accurately constrain the unit's primary frequency regulation control behavior. The specific work mainly consists of two steps:

[0138] The first step is to analyze the primary frequency regulation response characteristics of wind turbines under different control modes and propose a dynamic perspective evaluation model for primary frequency regulation of wind turbines.

[0139] The second step is to provide a parameter identification method for the actual and theoretical values ​​of the evaluation parameters from a dynamic perspective. Based on the evaluation parameters and power grid control requirements, a performance evaluation index for primary frequency regulation control from a dynamic perspective is designed, and a specific evaluation process is given.

[0140] The results of the verification after substituting specific wind power primary frequency regulation data show that the evaluation parameter results obtained by the static method differ significantly from the actual benchmark; the evaluation parameter results obtained by the dynamic method proposed in this application are basically consistent with the actual benchmark. Therefore, the dynamic perspective evaluation method proposed in this application can more accurately reflect the actual primary frequency regulation control performance of the unit, and the evaluation index calculation results can more accurately reflect the qualification level of the unit's primary frequency regulation control performance.

[0141] The above-described embodiments are merely illustrative of the implementation methods of the present invention, but should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the protection scope of the present invention.

Claims

1. A method for designing a dynamic angle of view wind power primary frequency regulation control performance evaluation index, characterized in that, Includes the following steps: S1: Establish a primary frequency regulation evaluation model for wind turbines under rotor kinetic energy control mode; S1-1: The wind turbine participates in primary frequency modulation by releasing rotor kinetic energy, which is a dynamic conversion process of power. The primary frequency modulation power increment ΔP1-1 is brought by the rotor speed change P It is composed of two parts: one part is the rotor kinetic energy ΔK released by the rotor speed change P W , and the other part is the power difference ΔP2-1 captured by the DFIG due to the rotor speed change P Wem , which is calculated as follows: (1) S1-2: Using the system frequency difference as the input signal, the power control signal Δ is obtained through droop and virtual inertial control. P We_s : (2) In the formula, K WD To simulate the droop coefficient, K WI For virtual inertia coefficients, T WD It is a time constant; S1-3: Based on the speed change equation, the rotor kinetic energy change Δ is obtained. P W and speed change Δ ω Relationship: (3) In the formula, T JW The moment of inertia of the rotor; ω 0 represents the initial rotor speed; Δ ω This represents the change in rotor speed. t For time; S1-4: Ignore Δ ω The higher-order terms can be approximated as: (4) In the formula, , representing the rate of change in wind energy captured due to changes in rotational speed; P MPPT This refers to the active power of the wind turbine operating in maximum power point tracking mode. k opt These are the control coefficients for maximum power point tracking (MPPT) mode. Capture mechanical power for the wind turbine; v Wind speed; S1-5: Due to Δ P Wem To capture the wind power difference in the DFIG, therefore: (5) S1-6: Based on formulas (1) to (5), the transfer function of the primary frequency regulation evaluation model of the wind turbine under rotor kinetic energy control mode is obtained: (6) In the formula, Let be a complex variable in the Laplace transform domain; S2: Establish a primary frequency regulation evaluation model for wind turbines under pitch angle control mode; S2-1: Magnitude of mechanical power captured by the fan P for: (7) In the formula, ρ air density; R The radius of rotation of the fan; v For ambient wind speed; C p ( λ,θ () represents the wind energy utilization coefficient; λ The tip speed ratio; θ The pitch angle; S2-2: Pitch angle control mode uses the system frequency difference as the input signal, which is then proportionally amplified to obtain the pitch angle control signal. P s for: (8) In the formula, K σ This is the droop coefficient; The Laplace transform expression representing the frequency deviation; S2-3: The pitch angle control signal is used to adjust the pitch angle via a servo motor. If the inertia time constant of the servo motor is... T The change in pitch angle Δ θ for: (9) S2-4: Substitute the change in pitch angle into formula (7) for the mechanical power expression of the wind turbine capture, and obtain the power increment Δ. P for: (10) In the formula, θ 0 represents the initial pitch angle of the wind turbine; S2-5: Based on formulas (7) to (10), the transfer function of the primary frequency regulation evaluation model of the wind turbine under the pitch angle control mode is obtained: (11) In the formula, This represents the rate of change in wind energy captured due to changes in the pitch angle; S3: Based on the model established in steps S1 and S2, design the performance evaluation index for the primary frequency regulation control of the wind turbine from a dynamic perspective.

2. The method for designing performance evaluation indicators for wind power primary frequency regulation control from a dynamic perspective, as described in claim 1, is characterized in that... The specific steps are as follows: S1: Establish a primary frequency regulation evaluation model for wind turbines under rotor kinetic energy control mode; S2: Establish a primary frequency regulation evaluation model for wind turbines under pitch angle control mode; S3: The dynamic perspective wind turbine primary frequency regulation control performance evaluation index design includes two parts: power perspective and energy perspective. The power perspective mainly evaluates the magnitude of the active power adjustment value of the primary frequency regulation of the unit, while the energy perspective mainly evaluates the integral energy contribution of the active power of the primary frequency regulation of the unit. The power perspective primarily evaluates the magnitude of the active power adjustment value for primary frequency regulation of the unit. Specifically: S3-1: From a power perspective, the least squares parameter identification method is used to reasonably calculate the actual power performance; in the pitch angle control mode, the droop coefficient is set as the parameter to be identified. : (12) S3-2: Convert the frequency domain expression of the identification process into a time domain expression: (13) In the formula, This is the second derivative of the actual frequency response power of the unit; This is the derivative of the unit's actual frequency response power; This represents the actual frequency response power of the generator unit. This refers to the system frequency deviation. S3-3: Define the error function ε: (14) S3-4: Minimize the error function, that is, let Solving for: (15) S3-5: Based on the above calculations, achieve the actual value of the unit droop coefficient parameter. Calculation; Definition of dynamic adjustment range index This reflects the degree of compliance of the dynamic adjustment amplitude parameter with the standard value during the primary frequency modulation response process; The actual value obtained from equation (15); The theoretical value of the dynamic adjustment amplitude parameter is the reciprocal of the unit's droop coefficient; therefore The calculation formula is: (16) The energy perspective primarily evaluates the integral energy contribution of the unit's primary frequency regulation active power. Specifically: S3-6: From an energy perspective, convolution operation techniques are used to reasonably calculate the theoretical performance benchmark of integral energy; taking the active power adjustment value in rotor kinetic energy control mode as an example. Represented as: (17) S3-7: To solve for the integral power of primary frequency regulation of wind turbine generators, the frequency domain characteristics are transformed into time domain convolution operations based on the convolution theorem: (18) In the formula, " " is the convolution operator; S3-8: Since the system frequency difference and power time series are sampled at equal intervals, the product of the sampled value and the sampling period at each sampling point can be used to approximate the integral value: (19) In the formula, k The sampling point number in the time series; Not greater than The largest integer; g(t) is the inverse Laplace transform expression of G(s); S3-9: Yes Integrating the sampled time, the theoretical value of the unit's primary frequency regulation integral power during the sampling time is calculated: (20) In the formula, k end This refers to the end sampling position in the time series; S3-10: Based on the above calculations, the theoretical value of the unit's primary frequency regulation integral power can be achieved. Calculation; Definition of the dynamic cumulative effect index This reflects the degree of compliance of the dynamic cumulative effect parameter of the primary frequency modulation response process with the standard value; The theoretical value obtained from equation (19); The actual value of the integrated power during primary frequency regulation is obtained by integrating the power data of the primary frequency regulation response; therefore The calculation formula is: (21)。

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