Network-constructed wind power integration system based on source end dynamic characteristics and stability analysis method

Abstract

The application belongs to the technical field of wind power grid connection, and discloses a grid-connected wind power system based on source end dynamic characteristics, which comprises a wind turbine, a PMSG, a machine-side converter for adjusting wind power electromagnetic power based on an MPPT mode, and a grid-side converter adopting a VSG control system; the output end of the wind turbine is connected with the input end of the PMSG, the output end of the PMSG is connected with the input end of the machine-side converter, the output end of the machine-side converter is connected with the input end of the grid-side converter, and the output end of the grid-side converter is connected with the input end of the power grid; and a stability analysis method of the grid-connected wind power system based on source end dynamic characteristics is also disclosed. The application is suitable for analyzing the stability of the grid-connected wind power system based on source end dynamic characteristics, and can provide a reference for applying virtual synchronization technology to the stability control of wind turbines in actual variable operation states.

Description

Technical Field

[0001] This invention belongs to the field of wind power grid connection technology, and relates to a grid-connected wind power system, specifically a grid-connected wind power system based on source-end dynamic characteristics and a stability analysis method. Background Technology

[0002] In recent years, with the increasing prominence of energy and environmental problems caused by the large-scale combustion of fossil fuels, wind power has become an increasingly important part of the power system. Therefore, utilizing the abundant wind resources in deserts and Gobi regions, wind power generation, characterized by safety, cleanliness, and low cost, has attracted widespread attention in the energy sector as an important choice for green and ecological energy strategies. However, wind power inverters, which rely on highly electronic grid connection, lack the ability to respond to grid frequency fluctuations in rotor speed. Furthermore, with the continuous increase in wind power penetration, high-proportion renewable energy power systems will gradually evolve into systems with low inertia and weak damping characteristics. Existing wind power systems mostly operate in MPPT power control mode and employ a vector grid-connected control strategy based on phase-locked loop (PLL) synchronization, generally considered a grid-fed control structure. However, to maximize wind resource utilization, grid-fed wind turbines lack the ability to adjust the damping and inertia of the grid-connected system. Especially in scenarios with weak grid access, the coupling relationship between PLL control and turbine current control can easily lead to system instability risks.

[0003] Currently, to ensure the stability of new energy power systems, wind turbines are required to possess mechanisms similar to synchronous machines to respond to grid frequency and voltage fluctuations. Among existing control methods for improving wind turbine system stability, based on whether or not a PLL (Programmable Logic Controller) is used to achieve grid synchronization, two control strategies are categorized: PLL-based droop control and virtual inertia control. Droop control enables wind power to achieve primary frequency regulation with slight deviations, but lacks sufficient dynamic response characteristics to the grid. Virtual inertia control can reduce the control conflict with MPPT (Multi-Pulse Test-Pulse Control) by releasing the turbine rotor energy during disturbances to achieve inertial response to the system; however, its grid-synchronized phase-locked loop mechanism also carries the risk of system instability.

[0004] To address the aforementioned issues, scholars have proposed a grid-connected self-synchronizing voltage source (VSG) control strategy for wind power that does not require PLL dominance. This strategy establishes virtual rotor mechanical equations to give wind power grid-connected characteristics equivalent to synchronous machines. Compared to grid-connected wind power, grid-connected wind power VSG (Virtual Synchronizer Generator) systems offer significant advantages in improving the stability of weak grids. Existing computer science research primarily focuses on analyzing the VSG grid structure and its own inertia and damping enhancement capabilities, neglecting the impact of the actual operating state and regulation characteristics of the source-end wind turbine and the coupling relationship between the VSG and the wind power VSG system's stability. Therefore, studying the impact of the wind turbine source-end dynamic characteristics on the stability of grid-connected wind power systems is of great significance to researchers in this field. Summary of the Invention

[0005] The purpose of this invention is to provide a grid-connected wind power system based on the dynamic characteristics of the source end. By establishing a virtual synchronous PMSG grid-connected system based on the mechanical characteristics of the PMSG source end, the minimum value of the damping parameter of the virtual synchronous PMSG grid-connected system is obtained, providing an engineering reference for the tuning of control parameters of grid-connected wind turbines.

[0006] Another objective of this invention is to provide a stability analysis method for the above-mentioned grid-connected wind power system based on the dynamic characteristics of the source end.

[0007] To achieve the above objectives, the technical solution adopted by this invention is as follows:

[0008] A grid-connected wind power system based on source-end dynamic characteristics includes a wind turbine, a PMSG, a turbine-side converter that regulates the electromagnetic power of the wind power based on MPPT mode, and a grid-side converter using a VSG control system.

[0009] The output end of the wind turbine is connected to the input end of the PMSG, the output end of the PMSG is connected to the input end of the turbine-side converter, the output end of the turbine-side converter is connected to the input end of the grid-side converter, and the output end of the grid-side converter is connected to the input end of the power grid.

[0010] The machine-side converter is used to control the DC voltage stability; the grid-side converter simulates the external characteristics of the PMSG through virtual speed regulation and virtual excitation, and has active frequency and voltage support capabilities.

[0011] This invention also provides the above-mentioned stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics, comprising the following steps:

[0012] S1. Connect the wind turbine, PMSG, turbine-side converter and grid-side converter to the power grid. By adjusting the electromagnetic power of the wind turbine according to the MPPT mode of the turbine-side converter, a virtual synchronous PMSG grid-connected system based on the mechanical characteristics of the PMSG source end is established.

[0013] S2. Through the virtual synchronous PMSG grid-connected system, obtain the PMSG rotor motion equation and the active power of the virtual synchronous PMSG grid connection under MPPT mode, and establish the state space model of the virtual synchronous PMSG grid-connected system.

[0014] S3. By using the state-space model of the virtual synchronous PMSG grid-connected system, the dynamic equation of the virtual synchronous PMSG is obtained, and the inertia and damping torque coefficient based on the mechanical characteristics of the PMSG source end are obtained.

[0015] S4. Analyze the impact of PMSG parameter changes on system transient stability, establish a small-signal model of the virtual synchronous PMSG grid-connected system based on wind speed, calculate the initial speed of the wind turbine when the PMSG is running at the critical wind speed and the wind turbine participates in frequency regulation based on the system characteristic value corresponding to the initial wind speed, obtain the function of the damping torque coefficient with respect to the virtual damping coefficient, and obtain the minimum value of the damping parameter of the virtual synchronous PMSG grid-connected system.

[0016] As a limitation of step S2 in the above method, in step S2, the motion equation of the PMSG rotor in MPPT mode is obtained by formulas (12) and (13):

[0017]

[0018]

[0019] In the formula, δ is the wind power angle, ω is the wind angular velocity, and ω n ω is the rated angular velocity of the system. r H represents the rotor speed of the PMSG. p P is the PMSG inertial constant. w To allow the PMSG to absorb the mechanical energy of the fan, P e D is the electromagnetic power output of the wind turbine. p is the rotor damping constant.

[0020] As a further limitation of step S2 in the above method, in step S2, the active power of the virtual synchronous PMSG grid connection under MPPT mode is obtained by formula (15):

[0021]

[0022] In the formula, k m Here are the MPPT parameters for the fan, m is the frequency regulation parameter, and D is the frequency regulation parameter. v ω is the virtual damping coefficient. f ω is the angular frequency of the VSG voltage. g H is the rated angular velocity of the fan. v This is the virtual inertia coefficient.

[0023] As a further limitation of step S2 in the above method, the state-space model of the virtual synchronous PMSG grid-connected system in step S2 is as follows:

[0024]

[0025] In the formula, Δ represents a small perturbation, and Δδ f The virtual power angle deviation of the VSG is Δω. f The voltage angular frequency deviation of the VSG is Δω. r K represents the rotor speed deviation of the PMSG. v ω is the synchronous torque parameter of the VSG. r0 This is the initial rotational speed of the fan when it participates in frequency regulation.

[0026] As a limitation of step S3 in the above method, in step S3, the dynamic equation of the virtual synchronization PMSG is obtained by formula (19):

[0027]

[0028] In the formula, s is the Laplace operator, s = jω v , where j is the imaginary part of the complex frequency domain.

[0029] As a further limitation of step S3 in the above method, in step S3, the inertia and damping torque coefficient based on the mechanical characteristics of the PMSG source end are obtained by formula (20):

[0030]

[0031] In the formula, H' v For the inertia based on the mechanical properties of the PMSG source end, D' v This is the damping torque coefficient.

[0032] As a limitation of step S4 in the above method, the small-signal model of the wind speed-based virtual synchronous PMSG grid-connected system in step S4 is as follows:

[0033]

[0034]

[0035] In the formula, R is the radius of the wind turbine blade; k pw and k iw These are the PI control parameters for the fan, λ opt The optimal tip speed ratio for adjusting the fan angular velocity, v r0 Z is the initial wind speed corresponding to frequency modulation. ∑ V is the system impedance. fabc V is the output voltage of the wind turbine grid-side inverter. gabc For the voltage phasor of the power grid; δf Output virtual power angle for VSG.

[0036] As a limitation of step S4 in the above method, the critical wind speed in step S4 is obtained by formula (28):

[0037]

[0038] The initial speed of the fan at the moment of frequency regulation is obtained by formula (29):

[0039]

[0040] As a further limitation of step S4 in the above method, in step S4, the function of the damping torque coefficient with respect to the virtual damping coefficient is:

[0041]

[0042] In the formula, n is an intermediate variable, and m and n are obtained from formula (31):

[0043]

[0044] The minimum damping parameter of the virtual synchronous PMSG grid-connected system is obtained by formula (33):

[0045] D vmin =5H v k m (2 / 3) / H p (33)

[0046] The present invention, by adopting the above-described technical solution, achieves the following technical advancements compared to existing technologies:

[0047] (1) Based on the VSG control system, this invention establishes a virtual synchronous PMSG grid-connected system that considers the mechanical characteristics of the PMSG source end, and realizes the simulation application of VSG control strategy in the wind turbine grid-side inverter;

[0048] (2) This invention clarifies the key factors affecting the stability of the wind power VSG control system under MPPT mode by using a small-signal model of a virtual synchronous PMSG grid-connected system based on wind speed.

[0049] (3) From the perspective of grid-type wind power engineering applications, this invention analyzes the coupling relationship between the wind turbine source end operating characteristics and the VSG power control loop, and evaluates the impact of its dynamic adjustment on the inertia and damping of the VSG control system.

[0050] (4) This invention analyzes the mechanism of the effect of operating wind speed on the inertia and damping characteristics of the VSG control system, and derives the minimum damping control value to ensure system stability in the critical wind speed range, providing engineering guidance for the tuning of control parameters of grid-type wind turbines.

[0051] (5) Based on the laboratory RTLAB mixed simulation platform, this invention establishes a virtual synchronous PMSG grid-connected system. The simulation results verify the accuracy of the model and the effectiveness of the analysis method.

[0052] This invention is applicable to the stability analysis of grid-connected wind power systems based on the dynamic characteristics of the source end, and can provide a reference for the application of virtual synchronization technology to the stable control of wind turbines in actual variable operating conditions. Attached Figure Description

[0053] Figure 1 The diagram shown is a circuit schematic of Embodiment 1 of the present invention;

[0054] Figure 2 The figure shown is a stability analysis diagram of the virtual synchronous PMSG grid-connected system under the influence of VSG virtual inertia coefficient variation in Embodiment 2 of the present invention.

[0055] Figure 3 The figure shown is a stability analysis diagram of the virtual synchronous PMSG grid-connected system under the influence of the VSG virtual damping coefficient variation in Embodiment 2 of the present invention.

[0056] Figure 4 The figure shows a small-signal model of the wind speed-based virtual synchronous PMSG grid-connected system in Embodiment 2 of the present invention;

[0057] Figure 5 The figure shown is a characteristic root locus diagram of the virtual synchronous PMSG grid-connected system under different initial wind speeds corresponding to different frequency modulations in Embodiment 2 of the present invention;

[0058] Figure 6 The figure shows the influence curves of different initial operating wind speeds on the inertia characteristics of the virtual synchronous PMSG grid-connected system in an embodiment of the present invention.

[0059] Figure 7 The image shows the simulation experimental platform of Embodiment 2 of the present invention;

[0060] Figure 8 The figure shows the reference power comparison curves of the virtual synchronous PMSG grid-connected system and the VSG grid-connected system in Embodiment 2 of the present invention;

[0061] Figure 9 The figure shows a comparison curve of the system angular frequency of the virtual synchronous PMSG grid-connected system and the VSG grid-connected system in Embodiment 2 of the present invention;

[0062] Figure 10The figure shown is a comparison of the AC-side transient frequency effects of the virtual synchronous PMSG grid-connected system and the VSG grid-connected system under the same virtual inertia coefficient in Embodiment 2 of the present invention.

[0063] Figure 11 The figure shown is a comparison of the impact of AC-side transient frequency on different virtual inertia coefficients in the virtual synchronous PMSG grid-connected system of Embodiment 2 of the present invention.

[0064] Figure 12 The figure shown is a comparison of the AC-side transient frequency effects of the virtual synchronous PMSG grid-connected system and the VSG grid-connected system under the same virtual damping coefficient in Embodiment 2 of the present invention.

[0065] Figure 13 The figure shown is a comparison of the impact of AC-side transient frequency on different virtual damping coefficients in the virtual synchronous PMSG grid-connected system of Embodiment 2 of the present invention.

[0066] Figure 14 The figure shows the frequency variation curves of the virtual synchronous PMSG grid-connected system of Embodiment 2 of the present invention under different initial wind speeds;

[0067] Figure 15 The figure shows the electromagnetic power variation curves of the virtual synchronous PMSG grid-connected system in Embodiment 2 of the present invention under different virtual damping coefficients. Detailed Implementation

[0068] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0069] Example 1: A grid-connected wind power system based on source-end dynamic characteristics

[0070] like Figure 1 As shown, this embodiment discloses a grid-connected wind power system based on source-side dynamic characteristics, including a wind turbine, a PMSG, a turbine-side converter that regulates the electromagnetic power of the wind power based on MPPT mode, and a grid-side converter using a VSG control system.

[0071] The wind turbine's output is connected to the PMSG's input, the PMSG's output is connected to the turbine-side converter's input, the turbine-side converter's output is connected to the grid-side converter's input, and the grid-side converter's output is connected to the grid's input. The turbine-side converter is used to control DC voltage stability. The grid-side converter, through virtual speed regulation and virtual excitation, simulates the PMSG's external characteristics and possesses active frequency and voltage support capabilities.

[0072] In this embodiment, the grid-side converter is controlled according to VSG, P w The mechanical power of the VSG active modulation loop is used to construct the VSG power control loop. Figure 1 In the figure, ΔU is the difference between the DC-side capacitor voltage and its reference value, and H is the voltage across the capacitor. S The filter function, after passing through PI control, yields the reference value I of the q-axis current in the inner current loop. sqref , where P w and P e These represent the mechanical energy and electromagnetic power output of the PMSG absorption fan, respectively. sd I sdref These are the d-axis current of the inner current loop and its reference value, respectively. V fabc ∠δ f V gabc ∠0 represents the voltage phasor of VSG and the power grid, respectively.

[0073] Based on the rotor motion equation of the synchronous machine, the virtual power angle δ of the VSG output can be obtained from formula (1). f VSG voltage angular frequency ω f Relationship with power:

[0074]

[0075] In the formula, δ f To output a virtual power angle for the VSG, ω f ω is the angular frequency of the VSG voltage. g P is the rated angular velocity of the fan. m Input virtual mechanical power to VSG, P g H represents the electromagnetic power output by the VSG. v D is the virtual inertia coefficient. v As a virtual damping coefficient, ignoring the influence of losses, the active power of the wind turbine, i.e., the electromagnetic power output by the VSG, is obtained by formula (2):

[0076]

[0077] In the formula, X Σ V is the impedance between the VSG and the power grid. fabc V is the output voltage of the wind turbine grid-side inverter. gabc For the voltage phasor of the power grid; σ f For the VSG rotor value, after PMSG virtual synchronization control, the voltage reference value and command value are V respectively. ref V g0 The following is obtained through the virtual excitation control loop:

[0078] V ref =V fabc0 (3);

[0079] In the formula, V fabc0 This is the initial value of the output voltage of the grid-side inverter for the wind turbine;

[0080] Simplify the small-signal model of the system, neglect the voltage regulation process, V fabc0 Treat it as a constant value, i.e., V fabc0 =V fabc By linearizing equations (1) and (2) near the equilibrium point, the small-signal model of the PMSG grid-connected system is derived as follows:

[0081]

[0082] In the formula, Δ represents a small perturbation, and σ f(0) For the initial value of the VSG rotor, Δσ f The deviation of the VSG rotor value, Δω f The virtual angular frequency deviation of the VSG, ΔP m Input the virtual mechanical power deviation ΔP into the VSG. g This refers to the deviation of the electromagnetic power output of the VSG. If we disregard the dynamic power regulation of the wind turbine-side converter, i.e., the DC side of the VSG is a traditional ideal voltage source, then P... m =0, the system dynamic equations are derived from formulas (5) and (6) as follows:

[0083]

[0084]

[0085] In the formula, Δδ f δ is the virtual power angle deviation of VSG. f(0) K is the initial value of the VSG virtual power angle. v U is the synchronous torque parameter of the VSG. gabc Given the grid voltage; combining equations (4) and (5), the dynamic equation of the VSG system is expressed by equation (7):

[0086]

[0087] Furthermore, the dominant oscillation frequency f of the VSG system is obtained from formulas (8) and (9). v And the damping ratio ξ, it is observed that H v The larger the value of ξ, the slower the system's response to disturbances, and the weaker the system's damping characteristics. Simultaneously, the damping ratio ξ is related to D. v Proportional, D v It plays a crucial role in ξ;

[0088]

[0089]

[0090] The above analysis assumes the VSG DC power supply is operating under ideal conditions. However, after the PMSG is controlled by the VSG, both virtual speed regulation and virtual excitation control will cause P mTherefore, it is necessary to fully consider the impact of the dynamics at the wind turbine source end on the control performance of the VSG control system.

[0091] Example 2: A stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics

[0092] In practical applications, power-speed (P) w / ω r The characteristic curve is coupled with the virtual synchronous control: disturbances such as voltage and frequency in the power grid are transmitted to the DC side through power, causing fluctuations in DC voltage, which in turn cause changes in the PMSG speed. Ultimately, the speed change is transmitted back to the P w / ω r The curve causes disturbances to the grid-side converter power. Therefore, this embodiment provides a stability analysis method for a grid-connected wind power system based on source-end dynamic characteristics, including the following steps:

[0093] S1. Connect the wind turbine, PMSG, turbine-side converter and grid-side converter to the power grid. By adjusting the electromagnetic power of the wind turbine according to the MPPT mode of the turbine-side converter, a virtual synchronous PMSG grid-connected system based on the mechanical characteristics of the PMSG source end is established.

[0094] In this step, when the fan is operating in MPPT mode, the wind speed V r The corresponding maximum output power of the fan is the mechanical energy P of the PMSG absorption fan. w We can obtain the following from formulas (10) and (11):

[0095]

[0096]

[0097] In the formula, ω r C is the rotor speed of the PMSG. max ρ is the maximum wind energy utilization coefficient, R is the air density, R is the wind turbine blade radius, and λ is the tip speed ratio.

[0098] S2. Through the virtual synchronous PMSG grid-connected system, obtain the PMSG rotor motion equation and the active power of the virtual synchronous PMSG grid connection under MPPT mode, and establish the state space model of the virtual synchronous PMSG grid-connected system.

[0099] In this step, the turbine-side converter adjusts the wind power electromagnetic power according to the MPPT mode. The PMSG rotor motion equations in the MPPT mode are obtained from formulas (12) and (13):

[0100]

[0101]

[0102]

[0103]

[0104] In the formula, k m Here are the MPPT parameters for the fan, m is the frequency regulation parameter, and D is the frequency regulation parameter. v ω is the virtual damping coefficient. f ω is the angular frequency of the VSG voltage. g H is the rated angular velocity of the fan. v This is the virtual inertia coefficient;

[0105] Considering equation (5) and linearizing equations (13) and (15), we derive:

[0106]

[0107]

[0108] In the formula, ω r0 This is the initial rotational speed of the fan when it participates in frequency regulation.

[0109] Combining equations (16), (17), and (4), the state-space model of the virtual synchronous PMSG grid-connected system is:

[0110]

[0111] In the formula, Δ represents a small perturbation, and Δδ f The virtual power angle deviation of the VSG is Δω. f The voltage angular frequency deviation of the VSG is Δω. r K represents the rotor speed deviation of the PMSG. v ω is the synchronous torque parameter of the VSG. r0 This is the initial rotational speed of the fan when it participates in frequency regulation.

[0112] S3. By using the state-space model of the virtual synchronous PMSG grid-connected system, the dynamic equation of the virtual synchronous PMSG is obtained, and the inertia and damping torque coefficient based on the mechanical characteristics of the PMSG source end are obtained.

[0113] Converting equation (18) to Laplace form, the dynamic equations of the virtual synchronization PMSG are obtained from equation (19):

[0114]

[0115] In the formula, s is the Laplace operator, s = jω v , where j is the imaginary part of the complex frequency domain;

[0116] The inertia and damping torque coefficients based on the mechanical characteristics of the PMSG source end are obtained from formula (20):

[0117]

[0118] In the formula, H' v For the inertia based on the mechanical properties of the PMSG source end, D' v This is the damping torque coefficient.

[0119] By comparing equation (5), we can see that H v ′<H v D v ′<D v The dynamic characteristics of active power regulation of wind power and D v and H v The interrelationship indicates that, considering the mechanical characteristics of the PMSG source end, the virtual synchronous PMSG grid-connected system weakens its damping support capacity and reduces its inertial response performance during disturbances. This determines D. v One type of key parameter is related to VSG control characteristics, including the virtual inertia coefficient H. v Virtual damping coefficient D v The frequency modulation parameter m, etc., and another type are related to the characteristics of the PMSG itself, including the PMSG inertial constant H. p Rotor damping constant D p Furthermore, it can be seen that the MPPT parameter k of the wind turbine... m Frequency regulation parameter m and the initial speed ω of the fan when participating in frequency regulation r0 The initial wind speed v corresponding to frequency modulation r0 At the same time, for D v ′、H v These factors play a strong correlation role. Therefore, it is necessary to analyze the degree of influence of the above factors on system stability from the perspective of engineering practice in applying VSG to wind power to support system stability capabilities.

[0120] S4. Analyze the impact of PMSG parameter changes on system transient stability, establish a small-signal model of virtual synchronous PMSG grid-connected system based on wind speed, calculate the initial speed of the wind turbine when the PMSG is running at the critical wind speed based on the system characteristic value corresponding to the initial wind speed, obtain the function of damping torque coefficient with respect to virtual damping coefficient, and obtain the minimum value of damping parameter of virtual synchronous PMSG grid-connected system.

[0121] The specific procedures in this step include:

[0122] S41. Analyze the virtual inertia coefficient H of the PMSG under different VSG parameters and control conditions. v Virtual damping coefficient D v Frequency modulation coefficient m and system impedance Z ΣThe impact of parameter changes on the transient stability of the system;

[0123] The parameters of the virtual synchronous PMSG grid-connected system are shown in Tables 1 and 2. Figure 2 and Figure 3 As shown, the virtual inertia coefficient H v Virtual damping coefficient D v The stability analysis of the system is illustrated by the arrows, which represent the changes in the closed-loop poles as the parameters increase. The graph shows that poles S1, S2, and S3 change at H... v An increase in D indicates a shift towards the origin, suggesting a decrease in system response speed after disturbances and a weakening of the wind turbine's grid-connected stability. v As the number of poles increases, poles S2 and S3 gradually move closer to the real axis, while moving towards the imaginary axis from a position far away from it. This indicates that the transient frequency fluctuations of the system can be smoothed out, but the transient recovery speed of the system will be affected.

[0124] Table 1 PMSG parameters

[0125] parameter numerical values unit Rated frequency 50 HZ Rated active power 1.5 MW Stator rated voltage 690 V Magnetizing Reactor 3.265 pu Stator resistance 0.0110 pu Stator leakage reactance 0.097 pu Rotor resistance 0.01 pu Rotor leakage reactance 0.101 pu Fan inertia constant 1.5 s Wind turbine damping constant 0.85 s DC voltage reference value 1.1 kV DC capacitor 10 mF reactive power setpoint 0 MVA Switching frequency 2 kHZ

[0126] Table 2 VSG Controller Parameters

[0127] parameter numerical values unit Inertial gain 1.0 pu proportionality coefficient 0.1 pu Integral coefficient 1 pu High-pass filter time constant 0.05 s Power loop damping coefficient 1 pu Voltage loop damping coefficient 3.5 pu

[0128] S42. The small-signal model of the wind speed-based virtual synchronous PMSG grid-connected system is as follows:

[0129]

[0130]

[0131] In the formula, R is the radius of the wind turbine blade; k pw and k iw These are the PI control parameters for the fan, λ opt The optimal tip speed ratio for adjusting the fan angular velocity, v r0 Z is the initial wind speed corresponding to frequency modulation. ∑ V is the system impedance. fabc V is the output voltage of the wind turbine grid-side inverter. gabc For the voltage phasor of the power grid; σ f For VSG rotor values;

[0132] From equations (10) and (11), it can be seen that when the fan angular velocity is adjusted to the optimal tip speed ratio λ... opt At that time, the initial rotational speed ω of the wind turbine when it participates in frequency regulation. r0 We can obtain the following from formula (21):

[0133]

[0134] Linearization of equations (2) and (13)

[0135]

[0136] 2H p ω r0 sΔω r =Δp w -Δp e -D p Δω r (twenty three);

[0137] From equations (21) and (23), we get:

[0138]

[0139] Assuming the wind speed remains constant during system disturbances, the PMSG wind power offset ΔP w0 =0, neglecting grid connection system losses, the deviation of the wind turbine output electromagnetic power ΔP e =ΔP g In equation (14), the frequency modulation coefficient m is obtained by PI control, which leads to equation (25):

[0140]

[0141] This allows us to obtain a small-signal model for a wind-speed-based virtual synchronous PMSG grid-connected system, such as... Figure 4 As shown.

[0142] S43. Based on the small-signal model of the virtual synchronous PMSG grid-connected system based on wind speed, obtain the system characteristic values ​​corresponding to the initial wind speed for different frequency modulations, and analyze the influence of the characteristic values ​​on the control stability of the virtual synchronous PMSG grid-connected system.

[0143] In this step, the system characteristic values ​​corresponding to wind speeds of 6-14 m / s were obtained, such as... Figure 5 The figure shows the characteristic root locus of a virtual synchronous PMSG grid-connected system under different initial wind speeds corresponding to different frequency modulations; Figure 5 Analysis shows that the stability of the virtual synchronous PMSG grid-connected system is affected by the actual operating wind speed of the wind turbine. As the wind speed increases, S1 and S2 continue to move to the left from their initial positions on the negative real axis, exhibiting a stable damped oscillation mode. S3 and S4, on the other hand, continuously move to the left from their initial positions on the positive real axis, gradually transitioning to a damped oscillation mode. Changes in wind speed significantly impact the system's operational stability.

[0144] S44. Calculate the initial speed of the wind turbine when the PMSG is operating at the critical wind speed based on the system characteristic value corresponding to the wind speed, obtain the function of the damping torque coefficient with respect to the virtual damping coefficient, and obtain the minimum value of the damping parameter of the virtual synchronous PMSG grid-connected system.

[0145] From equation (9), it can be seen that a damping ratio of zero indicates a critical steady state of the system. At this time, the critical wind speed can be obtained from equation (28):

[0146]

[0147] When the actual operating wind speed v r0 >v r At 0°, the virtual synchronous PMSG grid-connected system follows an oscillation decay model, and the system is...

[0148] ′

[0149] Analysis shows that the stable operating state affects v ro The main factors are related to PMSG body parameters and PMSG inertial constant H. p Rotor damping constant D p Related to this is another type of virtual inertia coefficient H, a VSG control parameter. v Virtual damping coefficient D v and system impedance Z Σ Relatedly, in addition, the PI control parameter k in the primary frequency modulation stage of the VSG... pw and k iw It has a strong correlation with the critical wind speed.

[0150] When the PMSG operates at the critical wind speed, the initial speed of the fan at the moment of frequency regulation is obtained by formula (29):

[0151]

[0152] Substituting equation (29) into equation (20), we can eliminate K. v And the frequency modulation coefficient, the function of the damping torque coefficient with respect to the virtual damping coefficient is obtained as follows:

[0153]

[0154] In the formula, n is an intermediate variable; m and n are obtained from formula (31):

[0155]

[0156] The minimum damping parameter of the virtual synchronous PMSG grid-connected system is obtained by formula (33):

[0157] D vmin =5H v k m (2 / 3) / H p (33)

[0158] When the actual operating wind speed v r0 >v rAt time 0, the virtual synchronous PMSG grid-connected system is in an oscillation-damped model and the system is in a stable operating state. At this time, the minimum damping parameter of the VSG system needs to satisfy D. v >D vmin This ensures stable system operation.

[0159] This embodiment obtains the following based on equation (20): Figure 6 The curves showing the influence of initial operating wind speed changes on the inertia characteristics of the virtual synchronous PMSG grid-connected system are presented. The influence of initial operating wind speed on the system's inertia characteristics is analyzed, where k... pw =5, k iw =0.7, H v =2.5.

[0160] Depend on Figure 6 It can be seen that in the low-frequency and mid-frequency bands, the initial operating wind speed has a significant impact on the inertia characteristics of the virtual synchronous PMSG grid-connected system. As the wind speed increases, the amplitude characteristic curve in the low-frequency band shifts upward, and the phase angle of the phase frequency characteristic curve in the mid-frequency band gradually decreases. This indicates that in MPPT control mode, the initial wind speed will affect the inertial response performance of the system, and the system inertia will gradually increase. However, the wind speed has a smaller impact on the inertia in the high-frequency band.

[0161] The following is a calculation example analysis of this embodiment:

[0162] This embodiment utilizes the OPRT5600 series RT-ALB to construct a hardware-in-the-loop experimental platform for a virtual synchronous PMSG grid-connected system in the laboratory, illustrating the impact of source-side mechanical characteristics on the dynamic performance of a PMSG system based on virtual synchronous control. The digital simulation model represents the main circuit of the virtual synchronous PMSG grid-connected system, built using Simulink, and includes models of the wind turbine, PMSG, turbine-side converter, and grid-side converter. The VSG control algorithm is implemented using the TMS320F28335 DSP28335 chip. The DSP controls the grid-side converter via fiber optic connection to the main circuit. The physical hardware component is a controller used in actual engineering projects, and the two parts interact via an AC / DC interface. The experimental platform is as follows: Figure 7 As shown, the system parameters are shown in Table 1 and Table 2.

[0163] I. Impact of PMSG Source-End Characteristics on the Dynamic Performance of Virtual Synchronous PMSG Grid-Connected Systems

[0164] Traditional VSGs are static ideal DC voltage source controls. When the DC side is a direct-drive wind turbine, the PMSG operating in MPPT mode couples with the VSG power circuit through the dynamic mechanical characteristics of the rotor, affecting the stable operation of the virtual synchronous PMSG grid-connected system. This section verifies and compares the dynamic response of the VSG in the virtual synchronous PMSG grid-connected system (denoted as the PMSG grid-connected system) of this embodiment with the dynamic response of the VSG when the source end is an energy storage system (denoted as the VSG grid-connected system). By setting the system short-circuit ratio to decrease from 4 to 2.5 1 second after the start of the simulation, the parameters of the two systems remain consistent, and the virtual inertia coefficient H... v =0.6, virtual damping coefficient D v =2.5, input virtual mechanical power P m =0.7pu.

[0165] like Figure 8 The diagram shows the difference in reference power in the VSG power loop between the PMSG grid-connected system and the VSG grid-connected system. Because the PMSG speed is adjusted within the MPPT range under disturbance, according to equation (15), the PMSG mechanical dynamics are transmitted to the VSG power control loop, so P m It is no longer a constant value, but since the source end of the VSG grid-connected system has no mechanical characteristics that affect it, the power reference value remains constant.

[0166] like Figure 9 The figure shows the VSG voltage angular frequency ω in the VSG power loop of the PMSG grid-connected system and the VSG grid-connected system. f Comparing the curves, it can be seen that during the first swing after the disturbance, compared to the VSG grid-connected system, the frequency change rate dω of the PMSG grid-connected system is higher. f The / dt is more intense, and the PMSG oscillation amplitude and oscillation time are longer. Therefore, the VSG of the source is a direct-drive wind turbine, which weakens the damping capability of the grid-connected system and reduces the system stability.

[0167] II. Analysis of Factors Affecting the Stability of Virtual Synchronous PMSG Grid-Connected System

[0168] This section verifies the difference in stable operation capabilities between the PMSG grid-connected system and the VSG grid-connected system under the same control parameters, and the impact of control parameter changes on the stable operation of the virtual synchronous PMSG grid-connected system in this embodiment. It also analyzes the virtual inertia coefficient H, a key VSG control parameter that plays a crucial role in system stability. v Virtual damping coefficient D v The simulation was set to reduce the load suddenly at 1 second and increase the load suddenly at 6 seconds, with the system carrying a total load of 45kW at this time.

[0169] like Figure 10 , Figure 12The figure shows the results when the same virtual inertia coefficient H is used. v The same virtual damping coefficient D v A comparison of the transient frequency impact on the AC side of the PMSG grid-connected system and the VSG grid-connected system is shown. It can be seen that both systems possess a certain degree of disturbance immunity under the same disturbance conditions. However, compared to the VSG grid-connected system, due to the mechanical characteristics of the source end of the PMSG grid-connected system, the damping characteristics of the wind power VSG system change, its dynamic response capability decreases, and the speed of recovery to stable operation slows down. This verifies the correctness of the stability analysis of the wind power VSG system.

[0170] like Figure 11 , Figure 13 The figure shows different virtual inertia coefficients H for the virtual synchronous PMSG grid-connected system. v Virtual damping coefficient D v A comparison chart of system stability shows that as the VSG control parameters increase, the system's convergence speed improves, and the frequency overshoot after disturbance is reduced to a certain extent. Therefore, the VSG control parameters, such as the system's virtual inertia coefficient and virtual damping coefficient, can improve the stable operation capability and anti-interference strength of the virtual synchronous PMSG grid-connected system.

[0171] III. Stability Analysis of Virtual Synchronous PMSG Grid-connected System

[0172] The operating wind speed of the PMSG affects the stability characteristics of the virtual synchronous PMSG grid-connected system. When the system control parameters are set as shown in Tables 1 and 2, the critical wind speed is v. r Given an initial wind speed of 8 m / s, 10 m / s, and 11 m / s, the system's inertial response to wind speed is verified. The minimum damping parameter D corresponding to this critical wind speed is determined. vmin =2.5, under the same disturbance conditions, verify the virtual damping coefficient D. v The effect of changes on the damping characteristics of the virtual synchronous PMSG grid-connected system in this embodiment is shown with the initial wind speed set at 10 m / s.

[0173] like Figure 14 The figure shows the frequency changes of the virtual synchronous PMSG grid-connected system under different initial wind speeds. When the system load suddenly increases, compared with the wind speed of 8 m / s, when the wind speed increases to 11 m / s, the lowest system frequency decreases from 49.653 Hz to 49.879 Hz, and the frequency drop amplitude decreases by 66%. The increase in frequency drop time slows down the frequency change rate. When the system load suddenly decreases, the frequency rise time increases by 2.15 s. Therefore, increasing the initial operating wind speed will slow down the system frequency change rate and drop amplitude, and enhance the system's inertial response capability.

[0174] like Figure 15The figure shows the virtual damping coefficient D. v The electromagnetic power variation curve of the system under different values ​​of D v Increase, the system from D v <D vmin Unstable D v >D vmin The small disturbance stabilizes the transition. Furthermore, once the system reaches a stable operating state, as D... v The increase in power angle, angular frequency, and first swing amplitude of the wind turbine output power variation curves of the VSG system significantly reduced the overall swing amplitude. Simultaneously, the system's recovery time to stable operation was shortened, indicating that the system exhibits significant D-value within the minimum damping coefficient operating range. v The virtual synchronous PMSG grid-connected system has better damping characteristics and dynamic stability.

Claims

1. A stability analysis method for a grid-connected wind power system based on source-end dynamic characteristics, characterized in that, The grid-connected wind power system based on source-end dynamic characteristics includes a wind turbine, a PMSG, a turbine-side converter that regulates the electromagnetic power of the wind power based on MPPT mode, and a grid-side converter using a VSG control system. The output end of the wind turbine is connected to the input end of the PMSG, the output end of the PMSG is connected to the input end of the turbine-side converter, the output end of the turbine-side converter is connected to the input end of the grid-side converter, and the output end of the grid-side converter is connected to the input end of the power grid. The machine-side converter is used to control DC voltage stability; the grid-side converter simulates the external characteristics of the PMSG through virtual speed regulation and virtual excitation, and has active frequency and voltage support capabilities. The method includes the following steps: S1. Connect the wind turbine, PMSG, turbine-side converter and grid-side converter to the power grid. By adjusting the electromagnetic power of the wind turbine according to the MPPT mode of the turbine-side converter, a virtual synchronous PMSG grid-connected system based on the mechanical characteristics of the PMSG source end is established. S2. Through the virtual synchronous PMSG grid-connected system, obtain the PMSG rotor motion equation and the active power of the virtual synchronous PMSG grid-connected system under MPPT mode, and establish the state space model of the virtual synchronous PMSG grid-connected system. S3. By using the state-space model of the virtual synchronous PMSG grid-connected system, the dynamic equation of the virtual synchronous PMSG is obtained, and the inertia and damping torque coefficient based on the mechanical characteristics of the PMSG source end are obtained. S4. Analyze the impact of PMSG parameter changes on system transient stability, establish a small-signal model of virtual synchronous PMSG grid-connected system based on wind speed, calculate the initial speed of the wind turbine when the PMSG is running at the critical wind speed based on the system characteristic value corresponding to the initial wind speed, obtain the function of damping torque coefficient with respect to virtual damping coefficient, and obtain the minimum value of damping parameter of virtual synchronous PMSG grid-connected system. In step S4, the function of the damping torque coefficient with respect to the virtual damping coefficient is: （30）； In the formula, D v Here, n is the virtual damping coefficient, m is the intermediate variable, and m is the frequency modulation parameter. m and n are obtained from formula (31): （31）； In the formula, k m For the MPPT parameters of the wind turbine, K v H is the synchronous torque parameter of the VSG. v H is the virtual inertia coefficient. p D is the PMSG inertial constant. p The rotor damping constant is denoted by . The minimum damping parameter of the virtual synchronous PMSG grid-connected system is obtained by formula (33): （33）。 2. The stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics according to claim 1, characterized in that, In step S2, the motion equations of the PMSG rotor in MPPT mode are obtained from formulas (12) and (13): （12）； （13）； In the formula, δ is the wind power angle, ω is the wind angular velocity, and ω n ω is the rated angular velocity of the system. r P is the rotor speed of the PMSG. w To allow the PMSG to absorb the mechanical energy of the fan, P e It outputs electromagnetic power to the fan.

3. The stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics according to claim 2, characterized in that, In step S2, the active power of the virtual synchronous PMSG in MPPT mode is obtained by formula (15): （15）； In the formula, ω f ω is the angular frequency of the VSG voltage. g This is the rated angular velocity of the fan.

4. The stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics according to claim 3, characterized in that, In step S2, the state-space model of the virtual synchronous PMSG grid-connected system is as follows: （18）； In the formula, Δ represents a small perturbation, and Δδ f The virtual power angle deviation of VSG, Δω f The voltage angular frequency deviation of the VSG is Δω. r ω represents the rotor speed deviation of the PMSG. r0 This is the initial rotational speed of the fan when it participates in frequency regulation.

5. The stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics according to claim 4, characterized in that, In step S3, the dynamic equation of the virtual synchronization PMSG is obtained from formula (19): （19）； In the formula, s is the Laplace operator, s = jω v , where j is the imaginary part of the complex frequency domain.

6. The stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics according to claim 5, characterized in that, In step S3, the inertia and damping torque coefficient based on the mechanical characteristics of the PMSG source end are obtained by formula (20): （20）； In the formula, Inertia based on the mechanical properties of the PMSG source end, This is the damping torque coefficient.

7. The stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics according to claim 6, characterized in that, In step S4, the small-signal model of the wind-speed-based virtual synchronous PMSG grid-connected system is as follows: （26）； （27）； In the formula, R is the radius of the wind turbine blade; k pw and k iw These are the PI control parameters for the fan, λ opt The optimal tip speed ratio for adjusting the fan angular velocity, v r0 Z is the initial wind speed corresponding to frequency modulation. ∑ V is the system impedance. fabc V is the output voltage of the wind turbine grid-side inverter. gabc For the voltage phasor of the power grid; δ f Output virtual power angle for VSG.

8. The stability analysis method for grid-connected wind power systems based on source-end dynamic characteristics according to claim 7, characterized in that, In step S4, the critical wind speed is obtained by formula (28): （28）； The initial rotational speed of the fan at the moment of frequency regulation is obtained by formula (29): （29）。

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