Inertia characteristic analysis method of fan under different controls

Abstract

The invention discloses a method for analyzing inertia characteristics of a fan under different controls, and relates to the technical field of new energy power generation, and the method is characterized in that a system frequency response (SFR) model without virtual inertia, network tracking type and network constructing type virtual inertia control is established, and stability constraint and rotor kinetic energy constraint are introduced; and screening control parameters of the equivalent inertia supporting capacity by taking the average inertia supporting power as a unified evaluation index. And in combination with multi-wind power permeability scene simulation, system frequency response characteristics are compared, and inertia support effects of various control modes are evaluated. The method is used for analyzing the inertia characteristics of the fan under different control under the fan operation parameters, a foundation is laid for evaluation of the inertia characteristics of the direct-driven wind power plant containing virtual inertia control, and guidance is provided for design of the inertia control parameters.

Description

Technical Field

[0001] This invention relates to the field of new energy power generation technology, and more specifically, to a method for analyzing the inertia characteristics of wind turbines under different control conditions. Background Technology

[0002] With the rapid development of new energy power generation technologies, the phenomenon of "wind power grid connection reducing system inertia" in my country's power system is becoming increasingly prominent. This is mainly manifested in the increasingly high wind power penetration rate in the system, and the fact that the inertia level of wind power is lower than that of traditional synchronous turbines. This results in a weaker system resistance to disturbances. The problem of system frequency drop after power disturbances in low-inertia systems will be severely aggravated, and excessively low system frequencies will cause wind turbines to disconnect from the grid, affecting wind power consumption and threatening the safe and stable operation of the power system. Specifically, wind turbines generally operate in maximum power point tracking mode, which completely decouples the turbine speed from the grid frequency. Although wind turbines themselves have considerable rotational kinetic energy, their rotor kinetic energy cannot participate in the dynamic regulation of the system through traditional electromagnetic coupling methods, making it difficult to convert the mechanical inertia of wind turbines into effective system inertia.

[0003] For virtual inertia control of direct-drive wind turbines, scholars both domestically and internationally have conducted in-depth research. Currently, inertia support control of direct-drive wind turbines can be divided into two categories: grid-following control and grid-connected control. For grid-following virtual inertia control, most studies implement the control method by adding a power controller to the turbine-side controller; while the implementation strategies for grid-connected virtual inertia control include DC capacitor inertial synchronization control, virtual synchronization control, droop control, and virtual oscillator control. However, several problems exist in existing inertia assessment research: 1) In the frequency regulation control strategy based on rotor kinetic energy and distributed energy storage wind turbine, rotor kinetic energy is considered to be the source of virtual inertia power support, but the capacitor energy of the DC link is not discussed; 2) In existing research, the four methods for equivalent inertia assessment each have their shortcomings. The parameter identification method requires modeling in conjunction with a detailed model of the wind turbine, and the selection of the model order and the reduction of the inertia order have a significant impact on the calculation accuracy, and the workload is large. The modal analysis method does not depend on the disturbance conditions, but its research object is limited to synchronous machine-dominated systems, and its application is less common in high-penetration wind power systems. Most of the research on the data association method focuses on the rotating inertia and rarely involves the study of virtual inertia. As for the direct calculation method, the calculation formula for the wind farm inertia parameters under the turbine terminal frequency fluctuation is derived from the perspective of energy change, but it requires detailed parameters and operating status of all wind turbines in the entire field, which is also a large workload.

[0004] 3) Simplified wind turbine model and wind farm model with virtual inertial control. The frequency domain and time domain analytical solutions of the inertial time constant were calculated, but the next step of inertia assessment was not carried out.

[0005] In view of this, the present invention proposes a method for analyzing the inertia characteristics of a fan under different control conditions. Summary of the Invention

[0006] This invention proposes a method for analyzing the inertia characteristics of a fan under different control conditions to solve the above problems.

[0007] The above-mentioned technical objective of the present invention is achieved through the following technical solution: The first aspect of this invention provides a method for analyzing the inertia characteristics of a fan under different control conditions, comprising the following steps: Obtain system parameters and operating scenarios, including: no virtual inertia control, network-based virtual inertia control, and network-based virtual inertia control; Stability constraints and rotor kinetic energy constraints are introduced to filter the virtual inertia control parameters, and the filtered virtual inertia control parameters are obtained. Based on the selected virtual inertia control parameters, the average inertia support power diagram under different operating scenarios is calculated. The average inertia support power diagram under different operating scenarios is introduced into the rotor kinetic energy constraint. A set of control parameters with the same inertia support capability under the virtual inertia control of the grid type and the grid type is taken. At the same time, another set of control parameters is taken on the average inertia support power diagram of the virtual inertia control of the grid type. Under a given disturbance power condition, based on the system frequency response model, system frequency response models are established for wind turbine control without virtual inertia, wind turbine following grid virtual inertia control, and wind turbine following grid virtual inertia control, respectively. The dynamic change process of system frequency over time is calculated according to the model to obtain the system frequency response characteristic curve. The system frequency response results corresponding to various control methods under different wind power penetration rates are analyzed through the system frequency response characteristic curve.

[0008] A second aspect of the present invention also provides an apparatus / device / system for analyzing the inertia characteristics of a wind turbine under different controls, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0009] A third aspect of the present invention also provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0010] A fourth aspect of the present invention also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0011] In summary, the present invention has the following beneficial effects: 1) This study investigates the inertia characteristics of wind turbines under two control conditions. It analyzes the inertia support capability of the wind turbine system under different control conditions in response to power disturbances as wind power penetration changes. When a power disturbance of 0.02 pu occurs, the wind turbine system without virtual inertia control can stably deliver power, while the grid-connected and grid-connected virtual inertia control turbines can additionally increase output to enhance the system's inertia support capability. As wind power penetration increases, the system frequency deteriorates during disturbances, but the system inertia's ability to withstand system frequency deterioration further strengthens as the power supported by the wind turbine's inertia increases.

[0012] 2) Compared with the grid-following virtual inertia control method 2, when the wind turbine adopts the grid-following virtual inertia control method 1 (i.e., the higher the inertia support energy), after the disturbance occurs, the system frequency change rate decreases, the amplitude of the lowest point of the system frequency decreases, and the maximum output power used for inertia support increases. This indicates that the higher the average power of inertia support, the stronger the inertia support capability of the wind turbine. Attached Figure Description

[0013] Figure 1 This is the SFR (Synchronizer Flow) model in Embodiment 1 of the present invention; Figure 2 This is the SFR model of the virtual inertia control system for grid-connected wind turbines in Embodiment 1 of the present invention; Figure 3 This is the SFR model of the virtual inertia control system for the grid-type wind turbine in Embodiment 1 of the present invention; Figure 4 This is a diagram showing the average inertia-supported power of the grid-type direct-drive fan in Embodiment 1 of the present invention; Figure 5 This is a diagram showing the average inertia-supported power of the grid-type direct-drive fan in Embodiment 1 of the present invention; Figure 6 This is the rotor energy constraint diagram for mesh control in Embodiment 1 of the present invention; Figure 7 This is the energy constraint diagram of the grid-type control rotor in Embodiment 1 of the present invention; Figure 8 This is a parameter diagram showing the same average inertia support power in Embodiment 1 of the present invention; Figure 9 This is a frequency response characteristic diagram of the wind turbine non-virtual inertia control system in Embodiment 1 of the present invention; Figure 10 This is a frequency response characteristic diagram of the wind turbine and grid-type virtual inertia control system in Embodiment 1 of the present invention; Figure 11 This is a frequency response characteristic diagram of the wind turbine and grid-type virtual inertia control system in Embodiment 1 of the present invention; Figure 12 This is a flowchart of the method in Embodiment 1 of the present invention; Figure 13 This is the system simulation model in Embodiment 2 of the present invention; Figure 14 This describes the output of the fan under different control conditions in Embodiment 2 of the present invention; Figure 15 This describes the output of the fan under different control conditions in Embodiment 2 of the present invention; Figure 16 This describes the system frequency variation under different control conditions in Embodiment 2 of the present invention; Figure 17 This describes the output of the fan under different control conditions in Embodiment 2 of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] Example 1: Step 1: Obtain system parameters and operating scenario Operating scenarios include: no virtual inertia control, network-based virtual inertia control, and network-based virtual inertia control; System parameters include modeling parameters for the system frequency response model, state variable parameters, and virtual inertia control-related parameters: AC system frequency parameters. f System rated angular frequency, DC side voltage of converter station U dc Measured angular frequency, wind turbine speed, wind turbine grid-connected power, and wind turbine-side converter output power. P m , output power of wind turbine grid-side converter P e DC-side capacitor inertia time constant H c Virtual rotational inertia Jeq of direct-drive wind turbine, number of pole pairs np of direct-drive wind turbine, and natural inertia time constant of wind turbine. H w .

[0016] Specifically, the system frequency parameters, power parameters, and inertia-related parameters obtained in step one are used to establish a system frequency response model (SFR model) containing a synchronous machine and a wind turbine in step two, and to derive the system transfer function; among them, the wind turbine's inherent inertia time constant, virtual rotational inertia, and DC-side capacitor inertia time constant are further used for inertia support energy, average power, and equivalent inertia characteristic analysis in subsequent steps.

[0017] Step 2: Wind Turbine Inertia Support Power Analysis Step two specifically includes stability constraints and rotor kinetic energy constraints. The transfer function of the entire system under different wind turbine control conditions is calculated, and the distribution of the eigenvalues ​​of the transfer function is used to analyze the system's stability. In this application, by analyzing the wind turbine inertia support power, stability constraints and rotor kinetic energy constraints are introduced to screen the virtual inertia control parameters to ensure that the system remains stable and physically feasible under different wind power penetration rates. Based on this, the average inertia support power during the inertia response period is calculated as a unified evaluation index to compare and analyze the system frequency response characteristics of different virtual inertia control methods under conditions of equal inertia support capacity, thereby achieving a reasonable configuration and optimization of the wind turbine inertia support capacity.

[0018] Direct-drive fans without virtual inertia control The change in active power output caused by wind power participation in frequency regulation is equivalent to a change in SFR model parameters. The SFR model for a system considering wind power participation in frequency regulation is as follows: Figure 1 As shown, when a power disturbance in the system causes a frequency shift, the frequency deviation signal is fed back to the primary frequency regulation stage, causing the synchronous machine to adjust its mechanical power through the speed governor to offset the disturbance. At the same time, the change in active power during wind power frequency regulation is equivalently mapped to the change in SFR model parameters. The synchronous machine inertia and frequency regulation capability are corrected by the penetration rate, and the effect of wind power is equivalent to the change in system inertia and damping. Thus, the system frequency response is improved in the closed loop, and wind power participation in frequency regulation is realized.

[0019] The transfer function is: ; in, H G The generator's inertia constant ，D The damping coefficient is... η For wind power penetration rate, T R This is the time constant of the speed controller.

[0020] 2) Direct-drive fan and grid-type virtual inertia control The wind turbines without virtual inertia control are replaced with those of equal capacity that are connected to the grid and have virtual inertia control. When a power disturbance in the system causes a frequency shift, the frequency deviation signal is used as input to trigger the virtual inertia control of the grid-connected direct-drive wind turbine. The wind turbine adjusts its electromagnetic power output to participate in frequency regulation according to the frequency change and its rate of change, providing active power support rapidly in the early stages of frequency change and continuously compensating during the recovery process. The active power change generated by this control is equivalently mapped to the change in SFR model parameters, and the synchronous machine inertia and frequency regulation capability are corrected in conjunction with the wind power penetration rate. Thus, together with the primary frequency regulation of the synchronous machine, a closed-loop frequency regulation is formed, enabling the wind turbine to participate in system frequency regulation without changing the basic structure of SFR.

[0021] Calculate the electromagnetic power increment using the following formula: ; Where τ is the converter response time constant; ω r0 Δ is the initial angular velocity of the rotor. ω r Δ represents the rotor speed increment. ω e This represents the increment of the grid angular frequency. K d For the differential control coefficients of virtual inertia control; K p This refers to the proportional control coefficient for virtual inertia control. T f This is the time constant of the low-pass filter.

[0022] The relationship between system frequency and electromagnetic power increment is given by the following formula: ; in, ω r0 The initial angular velocity of the rotor; K d For the differential control coefficients of virtual inertia control; K p This refers to the proportional control coefficient for virtual inertia control. C This is the capacitor voltage; H w This is the inherent inertial time constant of the wind turbine.

[0023] The system is penetrating with wind power. η When a variable wind turbine employs grid-based virtual inertia control, the system's frequency response model (SFR model) is as follows: Figure 2 As shown: The transfer function is: ; in, H wThe inherent inertial time constant of the wind turbine. ω r0 The initial angular velocity of the rotor, C This is the power increment coefficient. F H For the dynamic gain of the prime mover 3) Direct-drive fan mechanism grid-type virtual inertia control Replace the direct-drive wind turbines without virtual inertia control with grid-type virtual inertia control of the same capacity. When system power disturbances cause frequency deviation, the frequency deviation signal drives the synchronous machine to adjust the mechanical power through primary frequency regulation on the one hand, and is input into the virtual inertia channel of the grid-type direct-drive wind turbine on the other hand. The wind turbine adjusts the electromagnetic power output through virtual inertia and power control, and its active power increment is equivalently superimposed to the system power balance. In addition, the system inertia and frequency regulation capability are corrected in combination with the wind power penetration rate, forming a closed-loop frequency regulation together with the synchronous machine to improve the system frequency response.

[0024] The active power increment of the virtual inertia of a grid-type direct-drive wind turbine is calculated using the following formula: ; in, U dc DC voltage K c is the virtual inertia control coefficient. The active power reference value increment is based on the following formula: ; in, C This is the equivalent capacitance value of the DC-side capacitor; ω r0 The initial angular velocity of the rotor; K c is the virtual inertia control coefficient. f n is the system's rated frequency.

[0025] Calculate the electromagnetic power increment using the following formula: ; in, K ps This is the proportionality coefficient; K is Δ is the integral coefficient; P vic The virtual inertia control power increment; τ is the converter response time constant; Δ P MPPT Track power increments at the maximum power point.

[0026] After sorting, we can obtain: ; The frequency response model (SFR) of a wind turbine system with varying wind power penetration rate η, when using grid-type virtual inertia control, is as follows: Figure 3 As shown: The transfer function is: ; in, K is and K ps Virtual inertia control parameters The energy provided by the inertial support is less than or equal to the kinetic energy loss of the impeller and rotor during the inertial response.

[0027] The rotor kinetic energy E is calculated using the following formula: ; in, ω This refers to the rotor angular velocity; n This refers to the rotor speed; J This refers to the moment of inertia of the fan. N This refers to the gearbox ratio.

[0028] The energy required for inertial support can be calculated using the following formula. W : ; in, H Let be the inertia constant. S N This refers to the rated capacity of the fan. f N This is the rated capacity.

[0029] And satisfy Step 3: Estimation of the average power of inertial support Step three specifically includes: The average power of the synchronous machine is calculated using the following formula: ; The average power of a grid-type direct-drive fan is calculated using the following formula: ; in, J eq The virtual moment of inertia of the direct-drive wind turbine; n p The number of pole pairs for a direct-drive fan; H w The inherent inertial time constant of the wind turbine; ω nom This refers to the rated angular velocity of the fan. ω r0 Δ is the initial angular velocity of the rotor. ωr This represents the rotor speed increment. ω e Δ is the initial angular frequency of the power grid. ω e Increase the angular frequency of the power grid; frequency differential coefficient K d and frequency proportionality coefficient K p And will K d and K p As a variable, we can obtain: Among them, the inherent inertia of the wind turbine H w Take 4 seconds, initial angular velocity of the wind turbine rotor W r0 Take 18.9 rad / s, the initial angular velocity of the system is taken as 314 rad / s, and the rated angular velocity of the fan is... W nom Take 18.9 rad / s.

[0030] The average power of inertial support is calculated using the following formula: ; The virtual inertia constant of the wind turbine is calculated using the following formula: ; Performing an inverse Laplace transform on the above equation and substituting the average power of the inertia support, we obtain the following figure: Among them, the inherent inertia of the wind turbine H w Take 4 seconds, initial angular velocity of the wind turbine rotor W r0 Take 19.8 rad / s, the initial angular velocity of the system is taken as 314 rad / s, and the rated angular velocity of the fan is... W nom Take 19.8 rad / s, adjustment coefficient K c Take 0.35, the proportionality coefficient K ps and integral coefficient K is For variables.

[0031] The DC capacitor inertia time constant can be calculated using the following formula. H c : ; Step 4: Determining the values ​​of control parameters for equal inertia support capacity Step four specifically involves: Since the control structures of the mesh type and the structural mesh type differ significantly, they cannot be directly analyzed using the inertia constant. Therefore, from an energy perspective, we need to find the parameter values ​​corresponding to the inertia support energy for the two sets of structures, and then proceed with the next step of analysis.

[0032] The figure shows the power of the grid-controlled fan under rotor kinetic energy constraints. Figure 6 and Figure 7 .

[0033] The frequency dynamic characteristics of wind turbines under virtual inertia control of grid type and network type cannot be directly compared. Figure 5 and Figure 6 By combining these parameters, a set of control parameters with the same inertia support capacity can be obtained at the curve intersection. Simultaneously, another set of control parameters is taken from the power evaluation diagram of the grid-type virtual inertia control wind turbine, and compared with the first set. All parameter values ​​are within the range of system stability and rotor kinetic energy constraints. Figure 8 .

[0034] Step 5: Analyze the system frequency response characteristics under different control conditions and different wind power penetration rates. Step five specifically includes: determining the control parameters of the wind turbine and the synchronous machine. As the wind power penetration rate increases, the proportion of the synchronous machine decreases, and the missing capacity is filled by the wind turbine.

[0035] Under the premise of satisfying the aforementioned stability constraints and rotor kinetic energy constraints, and based on the principle of having the same average inertia support power, the control parameter combination of the wind turbine and synchronous generator is determined. As the wind power penetration rate increases, the proportion of the synchronous generator in the system decreases accordingly, and its inertia support capacity decreases. The missing inertia support capacity in the system is supplemented by the wind turbine through a corresponding virtual inertia control method.

[0036] Under a given disturbance power condition, based on the system frequency response model, system frequency response models are established for wind turbine control without virtual inertia, wind turbine following grid virtual inertia control, and wind turbine following grid virtual inertia control, respectively. The dynamic change process of system frequency over time is calculated according to the model, thereby obtaining the system frequency response characteristic curve.

[0037] Input the two sets of parameters obtained in step four into the system frequency response model and output the system frequency response characteristic curve.

[0038] Draw the system frequency response characteristic curve according to the following formula: Without considering virtual inertia control, the system frequency response model can be expressed as: ; Among them, H G Where is the generator inertia constant, D is the damping coefficient, η is the wind power penetration rate, and T is the generator moment of inertia constant. RThis is the time constant of the speed controller.

[0039] Under mesh-based virtual inertia control, the system frequency response model can be expressed as: Where Hw is the inherent inertial time constant of the wind turbine, ω r0 Where C is the initial angular velocity of the rotor, and F is the power increment coefficient. H This represents the dynamic gain of the prime mover.

[0040] Under network-based virtual inertia control, the system frequency response model can be expressed as: Where Kis and Kps are virtual inertia control parameters, K C f is the adjustment coefficient. n This is the system's rated frequency; the meanings of the other parameters are the same as in the aforementioned model.

[0041] Based on this, we analyze the system frequency response results of various control methods under different wind power penetration rates, compare the impact of different virtual inertia control methods on the dynamic characteristics of system frequency under the condition of equivalent inertia support capability, and thus evaluate the inertia support effect of different control methods under high wind power penetration conditions.

[0042] The frequency response characteristics of the wind turbine's non-virtual inertia control system, the wind turbine's grid-type virtual inertia control system, and the wind turbine's grid-type virtual inertia control system are respectively... Figure 9 , 10 And Figure 11.

[0043] Example 2: Establish as Figure 13 The simulation model shown uses the CIGRE standard example model for the fan and AC-side synchronous machine. The rated capacity of the synchronous machine is set to 50 MVA, the rated capacity of the fan is 2 MVA, and the load is P. L1 =200 MW, Q L1 =0 MVar, P L2 =10MW, Q L2 =0 MVar. The inertia characteristics of the fan under different control conditions are compared and analyzed through simulation experiments.

[0044] The system parameters are as follows: the rated voltage of the permanent magnet direct drive fan is V. n =690V, rated power P m =2MW, stator resistance R s =0.0017pu, stator inductance L s =0.0364pu, rotor resistance R r =0.055pu, rotor inductance Lr =0.62pu, magnetizing inductance L m =1pu, inherent inertia time constant H w =4s, rated angular velocity ωn=157.08rad / s, rated wind speed Vwind=10m / s, initial blade pitch angle β0=0°, synchronous generator inertial time constant H J =6s, X d =1.014 pu, =0.314 pu, X q =0.77pu, =0.428, =0.375, T d0 =6.55s, =0.039s, T q0 =0.95s, =0.51s, R s =0.002pu, H J =6s. The transformer has a non-standard turns ratio of 1.0, R t +jX t =0+j0.15pu; Transmission line R L =0.0001 pu / km, X L =0.001 pu / km, B C =0.00175 pu / km.

[0045] 1) Simulation results when wind power penetration rate is 25% Four simulation models were set up: wind turbine control without virtual inertia, wind turbine and grid virtual inertia control mode 1, wind turbine and grid virtual inertia control mode 2, and wind turbine and grid virtual inertia control. The wind power penetration rate was set to 25%, and the load PL2 was connected to the system at 20s.

[0046] like Figure 14 and Figure 15 When there is no virtual inertia control for the wind turbines, the system inertia response is entirely dominated by the synchronous machine. Due to the addition of wind power, the system inertia support capacity decreases, and the system frequency drops significantly when disturbances occur. At the same time, the wind turbines maintain a stable output of 2MW per unit without any additional power output. When the wind turbines adopt grid-following and grid-connected virtual inertia control, the deterioration of the system frequency is slowed down, the wind turbines increase additional output, and the system frequency change rate and the amplitude of the lowest frequency point are reduced.

[0047] 2) Simulation results when wind power penetration rate is 50% Similarly, four simulation models were set up: wind turbine without virtual inertia control, wind turbine and grid virtual inertia control mode 1, wind turbine and grid virtual inertia control mode 2, and wind turbine and grid virtual inertia control. The wind power penetration rate was set to 50%, and the load PL2 was connected to the system at 20s.

[0048] like Figure 16 and Figure 17 Without inertia control, as wind power penetration increases from 25% to 50%, the system frequency deteriorates further after power disturbances. However, wind turbines using virtual inertia control can still provide some inertia support. Compared to grid-connected virtual inertia control method two, when wind turbines use grid-connected virtual inertia control method one, the system frequency change rate decreases after a disturbance, the amplitude of the lowest system frequency point decreases by approximately 0.02Hz, and the maximum output power additionally used for inertia support increases by approximately 0.4MW. It can be observed that the higher the average power of inertia support during the inertia response period, i.e., the higher the inertia support energy, the stronger the inertia support capability of the wind turbine. In high wind power penetration scenarios, grid-connected virtual inertia control releases power faster and has better inertia support performance. Simultaneously, under both virtual inertia control methods, the system frequency drop does not exceed ±0.2Hz, meeting the system frequency safety requirements.

[0049] Example 3: The present invention also provides an apparatus / device / system for analyzing the inertia characteristics of a wind turbine under different control conditions, comprising a memory, a processor, and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the steps of the above method.

[0050] The present invention also provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0051] The present invention also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0052] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing the inertia characteristics of a fan under different control conditions, characterized by: Includes the following steps: Obtain system parameters and operating scenarios, including: no virtual inertia control, network-based virtual inertia control, and network-based virtual inertia control; Stability constraints and rotor kinetic energy constraints are introduced to filter the virtual inertia control parameters, and the filtered virtual inertia control parameters are obtained. Based on the selected virtual inertia control parameters, the average inertia support power diagram under different operating scenarios is calculated. The average inertia support power diagram under different operating scenarios is introduced into the rotor kinetic energy constraint. A set of control parameters with the same inertia support capability under the virtual inertia control of the grid type and the grid type is taken. At the same time, another set of control parameters is taken on the average inertia support power diagram of the virtual inertia control of the grid type. Under a given disturbance power condition, based on the system frequency response model, system frequency response models are established for wind turbine control without virtual inertia, wind turbine following grid virtual inertia control, and wind turbine following grid virtual inertia control, respectively. The dynamic change process of system frequency over time is calculated according to the model to obtain the system frequency response characteristic curve. The system frequency response results corresponding to various control methods under different wind power penetration rates are analyzed through the system frequency response characteristic curve.

2. The inertia characteristic analysis method according to claim 1, characterized in that: The system parameters include AC system frequency parameters, system rated angular frequency, DC side voltage of converter station, measured angular frequency, wind turbine speed, grid-connected power of wind turbine, output power of wind turbine-side converter, output power of wind turbine grid-side converter, DC side capacitor inertia time constant, virtual rotational inertia of direct-drive wind turbine, number of pole pairs of direct-drive wind turbine, and inherent inertia time constant of wind turbine.

3. The inertia characteristic analysis method according to claim 1, characterized in that: The stability constraint is to calculate the transfer function under different operating scenarios and use the distribution of the eigenvalues ​​of the transfer function to analyze whether the system is stable.

4. The inertia characteristic analysis method according to claim 3, characterized in that: The transfer function for the virtual inertia-free control is: ； in, H G Let be the generator's inertia constant. D The damping coefficient is... η For wind power penetration rate, T R The time constant of the speed controller; The transfer function of the mesh-type virtual inertia control is: ； in, H w The inherent inertial time constant of the wind turbine. ω r0 The initial angular velocity of the rotor, C This is the power increment coefficient. F H The dynamic gain of the prime mover; The transfer function of the network-based virtual inertia control is: ； in, K is and K ps These are virtual inertia control parameters.

5. The inertia characteristic analysis method according to claim 1, characterized in that: The rotor kinetic energy constraint is the energy required to calculate the rotor kinetic energy and the inertia support, and the energy required for the inertia support is less than or equal to the rotor kinetic energy.

6. The inertia characteristic analysis method according to claim 1, characterized in that: The calculation of the average inertia support power diagram under different operating scenarios includes: average power of grid-connected direct-drive wind turbines: ； ； Average power of grid-type direct-drive fans: ； ； Where H is the inertia constant, S N f is the rated capacity of the fan. N For rated capacity, J eq The virtual moment of inertia of the direct-drive wind turbine; n p The number of pole pairs for a direct-drive fan; H w The inherent inertial time constant of the wind turbine; ω nom This refers to the rated angular velocity of the fan. ω r0 Δ is the initial angular velocity of the rotor. ω r This represents the rotor speed increment. ω e Δ is the initial angular frequency of the power grid. ω e Increase the angular frequency of the power grid; frequency differential coefficient K d and frequency proportionality coefficient K p .

7. The method for analyzing the inertia characteristics of a fan under different control conditions according to claim 1, characterized in that: The formula for calculating the system frequency response characteristic curve is: ； in, The system frequency response characteristic curve; This refers to the imbalance of active power.

8. A device / equipment / system for analyzing the inertia characteristics of a wind turbine under different control conditions, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method described in any one of claims 1-7.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method described in any one of claims 1-7.

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