GFL-GFM parallel system fault ride-through control method, system, device and medium

Abstract

The invention relates to the technical field of electric power systems, and discloses a GFL-GFM parallel system fault ride-through control method, system, device and medium, according to the method, under the condition that a GFL-GFM parallel system breaks down, a magnetic flux coupling current limiter is used for achieving fault ride-through, and when the fault of the GFL-GFM parallel system recovers to be normal, fault ride-through is achieved. When the power angle fluctuation of the GFL system and the power angle fluctuation of the GFM system are both larger than a preset power angle fluctuation threshold value, a phase-locked loop parameter of the GFL system and a control parameter of the GFM system are set based on a Sigmoid function until the power angle fluctuation of the GFL system and the power angle fluctuation of the GFM system are both not larger than the preset power angle fluctuation threshold value, the equivalent inertia and damping characteristics of the GFL system and the GFM system are enhanced, and the damping performance of the GFL system and the GFM system is improved. And the whole process of the GFL-GFM parallel system from a fault transient state to fault recovery is controlled, and the robustness of fault ride-through control of the GFL-GFM parallel system is improved.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a fault ride-through control method, system, device and medium for GFL-GFM parallel systems. Background Technology

[0002] Currently, research on fault ride-through control of GFL (Global Fault Limited) and GFM (Grid-Forming Module) systems operating in parallel can be divided into two categories: control loop improvement methods and deep reinforcement learning (DRL). Each approach has its advantages and disadvantages: control loop improvement methods are based on transient stability mechanisms, and their effectiveness is directly limited by the reliability and completeness of the underlying theory; in contrast, while DRL-based transient stability control methods have achieved some results, as the system scale increases, the amount of data required for DRL training increases, which can easily lead to poor robustness of fault ride-through control in GFL-GFM parallel systems, making it difficult to guarantee the system's transient stability. Summary of the Invention

[0003] In view of this, the present invention provides a fault ride-through control method, system, device and medium for GFL-GFM parallel systems, which solves the technical problem of poor robustness of fault ride-through control in GFL-GFM parallel systems and difficulty in ensuring the transient stability of the system.

[0004] The first aspect of this invention provides a fault ride-through control method for a GFL-GFM parallel system, comprising:

[0005] In the event of a fault in the GFL-GFM parallel system, the flux coupling current limiter is activated to handle the fault until the GFL-GFM parallel system returns to normal.

[0006] When the fault in the GFL-GFM parallel system is restored to normal, and when the power angle fluctuations of both the GFL system and the GFM system are greater than the predetermined power angle fluctuation threshold, the phase-locked loop parameters of the GFL system and the control parameters of the GFM system are adjusted based on the Sigmoid function until the power angle fluctuations of both the GFL system and the GFM system are no greater than the predetermined power angle fluctuation threshold, and then the adjustment ends.

[0007] Preferably, the control parameters of the GFM system include virtual inertia and virtual damping coefficient;

[0008] The process of adjusting the control parameters of the GFM system based on the Sigmoid function includes:

[0009] The virtual inertia adjustment strategy is constructed based on the Sigmoid function, and the virtual inertia of the GFM system is tuned by combining the virtual inertia adjustment strategy with the angular frequency deviation and power angle fluctuation of the GFM system.

[0010] Based on the actual change in active power, the change in reference active power, and the virtual inertia of the GFM system, the transfer function of the small-signal model of the GFM system is determined.

[0011] Based on the transfer function of the small-signal model of the GFM system, a first quantization relationship function between the virtual damping coefficient and the virtual inertia is determined, and the virtual damping coefficient of the GFM system is tuned according to the first quantization relationship function.

[0012] Preferably, the adjustment strategy for the virtual inertia is as follows:

[0013]

[0014] In the formula, For virtual inertia, This refers to the reference virtual inertia in the GFM system at steady state. , This is the dynamic adjustment coefficient for GFM inertia. The threshold for angular frequency variation. Angular frequency, For time, It is the difference in angular frequency. denoted as ω0, where ω is the power angle fluctuation value and e is a constant.

[0015] Preferably, the transfer function of the small-signal model of the GFM system is:

[0016]

[0017] In the formula, G GFM (s) is the transfer function of the small-signal model of the GFM system, ΔP GFM ΔP represents the actual change in active power of the GFM. GFM,ref The change in active power reference value of GFM is represented by E and U, respectively, where E and U are the amplitudes of the voltage at the GFM terminal and the grid voltage, respectively, and X represents the line impedance. ω N The angular frequency is the rated frequency, s is the Laplace operator, and D represents the damping coefficient;

[0018] Accordingly, determining the first quantization relationship function between the virtual damping coefficient and the virtual inertia based on the transfer function of the small-signal model of the GFM system, and tuning the virtual damping coefficient of the GFM system according to the first quantization relationship function, includes:

[0019] Based on the transfer function of the small-signal model of the GFM system, determine the first damping ratio of the GFM system;

[0020] Based on the principle of optimal damping ratio, a first quantization relationship function between the virtual damping coefficient and the virtual inertia is determined using the first damping ratio.

[0021] By combining the first quantization relationship function and the virtual inertia, the virtual damping coefficient of the GFM system is determined.

[0022] Preferably, the phase-locked loop parameters of the GFL system include equivalent inertia, PLL integral coefficient, and PLL proportional coefficient;

[0023] The process of adjusting the phase-locked loop parameters of the GFL system based on the Sigmoid function includes:

[0024] An adjustment strategy for the PLL integral coefficient is constructed based on the Sigmoid function, and the PLL integral coefficient of the GFL system is tuned by combining the adjustment strategy of the PLL integral coefficient and the power angle fluctuation of the GFL system.

[0025] The transfer function of the small-signal model of the GFL system is determined based on the voltage phase angle change at the port of the GFL system, the q-axis voltage change of the GFL system, and the PLL integral coefficient.

[0026] Based on the transfer function of the small-signal model of the GFL system, a second quantization relationship function between the PLL integral coefficient and the PLL proportional coefficient is determined, and the PLL proportional coefficient of the GFL system is tuned according to the second quantization relationship function.

[0027] The equivalent inertia is determined based on the inverse ratio of the PLL integral coefficients.

[0028] Preferably, the adjustment strategy for the PLL integral coefficient is as follows:

[0029]

[0030] In the formula, k I,PLL0 K represents the reference PLL integral coefficient in the steady-state state of the GFL system, K3 and K4 represent the dynamic adjustment coefficients of the GFL inertia, and k I,PLL This represents the PLL integral coefficient.

[0031] Preferably, the transfer function of the small-signal model of the GFL system is:

[0032]

[0033] In the formula, G(s) is the transfer function of the small-signal model of the GFL system, and Δθ GFL Let ΔU be the voltage phase angle change at the GFL port. GFL,q U represents the q-axis voltage change of the GFL system. GFL k is the voltage at the GFL port. P,PLL This is the PLL scaling factor;

[0034] Accordingly, determining the second quantization relationship function between the PLL integral coefficients and the PLL proportional coefficients based on the transfer function of the small-signal model of the GFL system, and tuning the PLL proportional coefficients of the GFL system according to the second quantization relationship function, includes:

[0035] The second damping ratio of the GFL system is determined based on the transfer function of the small-signal model of the GFL system.

[0036] Based on the principle of optimal damping ratio, a second quantization relationship function between the PLL integral coefficient and the PLL proportional coefficient is determined using the second damping ratio.

[0037] By combining the second quantization relationship function and the virtual inertia, the PLL scaling factor of the GFL system is determined.

[0038] Secondly, the present invention also provides a fault ride-through control system for a GFL-GFM parallel system, comprising:

[0039] The fault ride-through module is used to activate the flux coupling current limiter to handle the fault in the case of a fault in the GFL-GFM parallel system until the fault in the GFL-GFM parallel system returns to normal.

[0040] The parameter tuning module is used to adjust the phase-locked loop parameters of the GFL system and the control parameters of the GFM system based on the Sigmoid function when the fault of the GFL-GFM parallel system is restored to normal and the power angle fluctuation of both the GFL system and the GFM system is greater than the predetermined power angle fluctuation threshold, until the power angle fluctuation of both the GFL system and the GFM system is no greater than the predetermined power angle fluctuation threshold, and then the adjustment ends.

[0041] Thirdly, the present invention also provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, the computer program being executed by the processor causing the processor to perform the steps of the GFL-GFM parallel system fault ride-through control method as described in the first aspect.

[0042] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the steps of the GFL-GFM parallel system fault ride-through control method as described in the first aspect.

[0043] As can be seen from the above technical solutions, this invention achieves fault ride-through by activating a flux coupling current limiter when a fault occurs in the GFL-GFM parallel system. After the GFL-GFM parallel system recovers from the fault, and when the power angle fluctuations of both the GFL and GFM systems exceed a predetermined power angle fluctuation threshold, the phase-locked loop parameters of the GFL system and the control parameters of the GFM system are tuned based on the Sigmoid function until the power angle fluctuations of both systems are no greater than the predetermined power angle fluctuation threshold. This optimizes the phase-locked loop parameters of the GFL system and the control parameters of the GFM system, enhances the equivalent inertia and damping characteristics of the GFL and GFM systems, and enables full-process control of the GFL-GFM parallel system from fault transient to fault recovery. This improves the robustness of the fault ride-through control of the GFL-GFM parallel system and comprehensively enhances the transient stability of the system. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is an application environment diagram of a fault ride-through control method for a GFL-GFM parallel system provided in an embodiment of the present invention;

[0046] Figure 2 A flowchart of a fault ride-through control method for a GFL-GFM parallel system provided in an embodiment of the present invention;

[0047] Figure 3 A schematic diagram of fault ride-through control for a GFL-GFM parallel system provided in an embodiment of the present invention;

[0048] Figure 4 The control block diagram of the transfer function of the small-signal model of the PLL provided in the embodiment of the present invention;

[0049] Figure 5a This is a dynamic adjustment curve of the virtual inertia of the GFM system under severe voltage sag provided in an embodiment of the present invention.

[0050] Figure 5bThe diagram shows the dynamic adjustment curve of the damping coefficient of the GFM system under severe voltage sag provided in this embodiment of the invention.

[0051] Figure 5c A dynamic adjustment curve of the PLL proportional coefficient of a GFL system under severe voltage sag provided in an embodiment of the present invention;

[0052] Figure 5d The dynamic adjustment curve of the PLL integral coefficient of the GFL system under severe voltage sag provided in the embodiment of the present invention;

[0053] Figure 6 A schematic diagram of the structure of a fault ride-through control system for a GFL-GFM parallel system provided in an embodiment of the present invention;

[0054] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0055] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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.

[0056] The fault ride-through control method for GFL-GFM parallel systems provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be integrated onto server 102 or placed in the cloud or on another network server. In the event of a fault in the GFL-GFM parallel system, terminal 101 or server 102 engages a flux coupling current limiter to handle the fault until the GFL-GFM parallel system returns to normal. Once the GFL-GFM parallel system has returned to normal, and when the power angle fluctuations of both the GFL and GFM systems exceed a predetermined power angle fluctuation threshold, the phase-locked loop parameters of the GFL system and the control parameters of the GFM system are adjusted based on the Sigmoid function until the power angle fluctuations of both systems are no longer greater than the predetermined power angle fluctuation threshold, at which point the adjustment ends.

[0057] Terminal 101 can be, but is not limited to, various personal computers, laptops, smartphones, and tablets.

[0058] Server 102 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides cloud computing services.

[0059] like Figure 2 As shown, this application provides a fault ride-through control method for a GFL-GFM parallel system, which is applied to... Figure 1 Taking terminal 101 or server 102 as an example, the explanation includes the following steps S1 to S2. Wherein:

[0060] Step S1: In the event of a fault in the GFL-GFM parallel system, activate the flux coupling current limiter to handle the fault until the GFL-GFM parallel system returns to normal.

[0061] like Figure 3 As shown, by real-time monitoring of the voltage and current over-limit signals of the GFL-GFM parallel system, when the voltage over-limit signal exceeds a certain threshold (e.g., 0.8 pu) or the current over-limit signal exceeds a certain threshold (e.g., 2 pu), it is determined that a fault has occurred in the GFL-GFM parallel system. By activating the flux-coupling fault current limiters (FC-FCLs), the fault current is quickly suppressed to ensure the safe operation of the power supply, complete the short-circuit fault clearance, and control the flux-coupling current limiters to disconnect, thus completing the fault clearance and restoring the GFL-GFM parallel system to normal operation.

[0062] Step S2: After the fault in the GFL-GFM parallel system is restored to normal, and when the power angle fluctuations of both the GFL system and the GFM system are greater than the predetermined power angle fluctuation threshold, adjust the phase-locked loop parameters of the GFL system and the control parameters of the GFM system based on the Sigmoid function until the power angle fluctuations of both the GFL system and the GFM system are no greater than the predetermined power angle fluctuation threshold, and then end the adjustment.

[0063] like Figure 3 As shown, during the fault recovery phase, stability is assessed based on the angular frequency change rate of the GFL and GFM. When the power angle fluctuation of the GFL and GFM systems is detected to be greater than the set angular frequency change threshold (|dω / dt| > α), the stability assessment is determined. th ), where |dω / dt| is the power angle fluctuation, α th If the angular frequency change threshold is set, the phase-locked loop parameters of the GFL system and the control parameters of the GFM system need to be dynamically adjusted. By suppressing the power angle oscillation, the transient stability of the system is improved. Finally, when the power angle fluctuation of the GFL and GFM systems is detected to be no greater than the angular frequency change threshold, the control is exited and the system returns to steady-state operation.

[0064] By optimizing the GFL phase-locked loop parameters and GFM control parameters, the equivalent inertia and damping characteristics of the GFL and GFM can be enhanced respectively, thereby improving their transient stability. Simultaneously, due to the power angle interaction of the GFL-GFM parallel system, the transient stability of the SG will improve synchronously with the improvement of the GFL / GFM transient stability.

[0065] It should be noted that, in the case of a fault in the GFL-GFM parallel system, a flux coupling current limiter is activated to achieve fault ride-through. After the fault in the GFL-GFM parallel system returns to normal, and when the power angle fluctuations of both the GFL and GFM systems are greater than a predetermined power angle fluctuation threshold, the phase-locked loop parameters of the GFL system and the control parameters of the GFM system are tuned based on the Sigmoid function until the power angle fluctuations of both the GFL and GFM systems are no greater than the predetermined power angle fluctuation threshold. This optimizes the phase-locked loop parameters of the GFL system and the control parameters of the GFM system, enhances the equivalent inertia and damping characteristics of the GFL and GFM systems, and enables full-process control of the GFL-GFM parallel system from fault transient to fault recovery. This improves the robustness of the fault ride-through control of the GFL-GFM parallel system and comprehensively enhances the transient stability of the system.

[0066] In some embodiments, the control parameters of the GFM system include virtual inertia and virtual damping coefficient. Virtual inertia is used to simulate the inertial response characteristics of a traditional synchronous generator to introduce dynamic power support into the system and enhance its frequency stability. Virtual damping coefficient is used to increase system damping, reduce power oscillations, and improve the system's dynamic response speed and stability. By precisely adjusting the virtual inertia and virtual damping coefficient, the control performance of the GFM can be further optimized, ensuring stable operation under various conditions. In this case, the process of adjusting the control parameters of the GFM system based on the Sigmoid function includes:

[0067] Step S201: Construct a virtual inertia adjustment strategy based on the Sigmoid function, and combine the virtual inertia adjustment strategy with the angular frequency deviation and power angle fluctuation of the GFM system to tune the virtual inertia of the GFM system.

[0068] Specifically, for different oscillation stages of the GFM, appropriately increasing / decreasing the virtual inertia can effectively suppress oscillations and improve the transient stability of the GFM. Meanwhile, to avoid GFM power overshoot caused by excessive changes in virtual inertia, a Sigmoid function is introduced to achieve smooth adjustment of the GFM inertia. When the GFM is in steady state or oscillation stages I and II, the GFM virtual inertia remains constant; when the GFM is in oscillation stages III and IV, the GFM will dynamically adjust the virtual inertia, as shown in Table 1.

[0069] Table 1. Virtual inertia tuning principles for different oscillation stages

[0070]

[0071] The adjustment strategy for virtual inertia is as follows:

[0072]

[0073] In the formula, For virtual inertia, This refers to the reference virtual inertia in the GFM system at steady state. , This is the dynamic adjustment coefficient for GFM inertia. The threshold for angular frequency variation. Angular frequency, For time, It is the difference in angular frequency. Here, α represents the power angle fluctuation value, and e is a constant. In this application, K1 = 0.4, K2 = 0.1; α th Set to π / 100.

[0074] Based on the virtual inertia adjustment strategy, the strategy is further optimized by considering the changing trend of power angle volatility. Specifically, when an increasing trend in power angle volatility is detected, the adjustment range of virtual inertia is appropriately reduced to avoid overshoot due to excessive virtual inertia; conversely, when a decreasing trend in power angle volatility is detected, the adjustment range of virtual inertia is appropriately increased to accelerate the system's stable recovery. By introducing the changing trend of power angle volatility as an adjustment basis, the transient stability of the GFM system can be further improved, and the robustness of the GFL-GFM parallel system during fault ride-through can be ensured.

[0075] Step S202: Determine the transfer function of the small-signal model of the GFM system based on the actual change in active power, the change in active power reference value, and the virtual inertia of the GFM system.

[0076] To ensure that the GFM dynamic model is in the "optimal damping ratio" state, the virtual damping coefficients of the GFM need to be coordinated and tuned.

[0077] The active power output of the GFM, obtained from the small-signal analysis circuit of the GFM, is as follows:

[0078]

[0079] In the formula, P GFM Let E be the rated active power of the GFM system, and U be the voltage amplitude at the GFM terminal and the voltage amplitude at the grid, respectively. GFM For the output inductive reactance of GFM, θGFM This is the voltage phase angle at the GFM port.

[0080] Therefore, by combining the expression for the active power output of the GFM system with the dynamic equations of the GFM system, the transfer function of the small-signal model of the GFM system is obtained as follows:

[0081]

[0082] In the formula, G GFM (s) is the transfer function of the small-signal model of the GFM system, ΔP GFM Δ represents the actual change in active power of the GFM. PGFM,ref The change in active power reference value of GFM is represented by E and U, respectively, where E and U are the amplitudes of the voltage at the GFM terminal and the grid voltage, respectively, and X represents the line impedance. ω N ω is the rated angular frequency, s is the Laplace operator, and D represents the damping coefficient.

[0083] The transfer function of the small-signal model of the GFM system describes the relationship between the actual change in active power and the change in the reference active power. In the derivation, the influence of factors such as the terminal voltage amplitude, grid voltage amplitude, output inductive reactance, and voltage phase angle at the ports on the active power output of the GFM system is considered.

[0084] Step S203: Based on the transfer function of the small-signal model of the GFM system, determine the first quantization relationship function between the virtual damping coefficient and the virtual inertia, and tune the virtual damping coefficient of the GFM system according to the first quantization relationship function.

[0085] Specifically, step S203 includes:

[0086] Step S2031: Determine the first damping ratio of the GFM system based on the transfer function of the small-signal model of the GFM system.

[0087] The transfer function of the small-signal model of the GFM system conforms to a classical second-order oscillatory element, thus allowing the derivation of the first damping ratio ζ. This damping ratio reflects the dynamic response characteristics of the GFM system under active power fluctuations. When the first damping ratio ζ is within the optimal damping ratio range, the GFM system exhibits good stability and dynamic performance.

[0088] First damping ratio ζ and natural angular frequency ω n As shown in the following formula:

[0089]

[0090] Step S2032: Based on the principle of optimal damping ratio, determine the first quantitative relationship function between virtual damping coefficient and virtual inertia through the first damping ratio.

[0091] The optimal damping ratio principle refers to selecting a suitable damping ratio value in system design so that the system can quickly recover stability after being disturbed, while avoiding excessive overshoot and oscillations. According to classical control theory, for a second-order system, when the first damping ratio ζ equals 0.707, the system has the best overall performance, namely, a faster response speed and a smaller overshoot. Therefore, when tuning the virtual damping coefficient of the GFM system, setting the first damping ratio ζ to 0.707 yields the first quantization relation function as follows:

[0092]

[0093] Step S2033: Combine the first quantization relationship function and the virtual inertia to determine the virtual damping coefficient of the GFM system.

[0094] In this process, after obtaining the first quantization relation function, the known virtual inertia is substituted into the first quantization relation function to obtain the virtual damping coefficient D of the GFM system.

[0095] In some embodiments, the phase-locked loop (PLL) parameters of the GFL system include equivalent inertia, PLL integral coefficient, and PLL proportional coefficient. The equivalent inertia is used to simulate the inertial response characteristics of a traditional synchronous generator to improve the frequency stability of the GFL system. The PLL integral coefficient is used to eliminate the steady-state error of the GFL system's PLL and improve phase-locking accuracy. The PLL proportional coefficient is used to adjust the dynamic response speed of the GFL system's PLL, while the PLL integral and proportional coefficients are used to adjust the PLL's response speed and accuracy to ensure that the GFL system can accurately track the phase and frequency of the grid voltage. In this case, the process of adjusting the GFL system's PLL parameters based on the Sigmoid function includes:

[0096] Step S211: Construct an adjustment strategy for the PLL integral coefficients based on the Sigmoid function, and combine the adjustment strategy for the PLL integral coefficients with the power angle fluctuation of the GFL system to tune the PLL integral coefficients of the GFL system.

[0097] The adjustment strategy for the PLL integral coefficient is as follows:

[0098]

[0099] In the formula, k I,PLL0 K represents the reference PLL integral coefficient in the steady-state state of the GFL system, K3 and K4 represent the dynamic adjustment coefficients of the GFL inertia, and k I,PLL This represents the PLL integration coefficient. In this application, K3 can be set to 0.2 and K4 to 0.05.

[0100] Understandably, the adjustment strategy for the PLL integral coefficients takes into account the dynamic performance and stability requirements of the GFL system's phase-locked loop, achieving smooth adjustment of the PLL integral coefficients through the Sigmoid function. When the GFL system is in steady state, the PLL integral coefficients remain at the reference value k. I,PLL0 This is to ensure the steady-state accuracy of the phase-locked loop (PLL). When the GFL system detects an increase in power angle fluctuation, the PLL integral coefficient k will be appropriately increased. I,PLL This accelerates the PLL's tracking speed of grid voltage phase and frequency changes, thereby enhancing the transient response capability of the GFL system. Conversely, when the power angle fluctuation decreases, the PLL integral coefficient k should be appropriately reduced. I,PLL To avoid overly rapid response leading to system overshoot or oscillation, and to ensure the stable operation of the GFL system, the performance of the GFL system's phase-locked loop can be further optimized by dynamically adjusting the PLL integral coefficient, thereby improving its robustness and stability during fault ride-through.

[0101] Step S212: Determine the transfer function of the small-signal model of the GFL system based on the voltage phase angle change at the port of the GFL system, the q-axis voltage change of the GFL system, and the PLL integral coefficients.

[0102] To ensure the dynamic characteristics of the PLL, the PLL scaling factor k needs to be adjusted. P,PLL Perform coordinated tuning. First, establish the small-signal model of the PLL, such as... Figure 4 As shown, the voltage q-axis change (ΔU) at the GFL port is calculated by comparing the voltage phase angle change at the GFL port with the voltage at the GFL port. GFL,q Then, through function transformation, the change in PLL angular frequency (Δω) is obtained. GFL Finally, the voltage phase angle change (Δθ) at the GFL port is obtained. GFL ):

[0103]

[0104] In the formula, Δω PLL ΔU represents the change in the angular frequency of the phase-locked loop (PLL). GFL,q Δθ represents the change in q-axis voltage of the GFL. GFL This represents the change in voltage phase angle at the GFL port.

[0105] Through derivation, the transfer function of the small-signal model of the GFL system is obtained as follows:

[0106]

[0107] In the formula, G(s) is the transfer function of the small-signal model of the GFL system, and Δθ GFLLet ΔU be the voltage phase angle change at the GFL port. GFL,q U represents the q-axis voltage change of the GFL system. GFL k is the voltage at the GFL port. P,PLL This is the PLL scaling factor.

[0108] Step S213: Based on the transfer function of the small-signal model of the GFL system, determine the second quantization relationship function between the PLL integral coefficient and the PLL proportional coefficient, and tune the PLL proportional coefficient of the GFL system according to the second quantization relationship function.

[0109] Specifically, step S213 includes:

[0110] Step S2131: Determine the second damping ratio of the GFL system based on the transfer function of the small-signal model of the GFL system;

[0111] The transfer function of the small-signal model of the GFL system conforms to a classical second-order oscillatory circuit, thus allowing the derivation of the second damping ratio. This damping ratio reflects the dynamic response characteristics of the GFL system's phase-locked loop under active power fluctuations. When the second damping ratio is within the optimal range, the GFL system's phase-locked loop exhibits good stability and dynamic performance. The second damping ratio and the natural angular frequency can be calculated using the following formulas:

[0112]

[0113] Step S2132: Based on the principle of optimal damping ratio, determine the second quantization relationship function between the PLL integral coefficient and the PLL proportional coefficient through the second damping ratio.

[0114] Similar to the GFM system, based on the principle of optimal damping ratio, the second damping ratio is set to 0.707, resulting in the second quantization relationship function between the PLL integral coefficient and the PLL proportional coefficient:

[0115]

[0116] Step S2133: Combine the second quantization relation function and the virtual inertia to determine the PLL proportional coefficient of the GFL system.

[0117] In this process, after obtaining the second quantization relation function, the known PLL integral coefficients are substituted into the second quantization relation function, and the virtual inertia of the GFM system is considered together to obtain the PLL proportional coefficient k of the GFL system. P,PLL In this way, the phase-locked loop of the GFL system can be ensured to have good dynamic response characteristics and stability during fault ride-through.

[0118] Step S214: Determine the equivalent inertia based on the inverse ratio of the PLL integral coefficients.

[0119] Among them, based on the assumption that the GFL system only outputs q-axis current during the transient process, the equivalent inertia J of the GFL system is... GFL,eq It is inversely proportional to the PLL integral coefficient, i.e., the equivalent inertia J GFL,eq For: G FL,eq = 1 / k I,PLL .

[0120] To verify the ability of the proposed fault ride-through control method for GFL-GFM parallel systems to improve the transient stability of GFL-GFM parallel systems, time-domain simulations were conducted using MATLAB R2022a software, with the operating condition set as fault ride-through control. To further verify the applicability of the proposed fault ride-through control in different transient scenarios, a voltage sag fault with a severe disturbance of 0.7 pu was set.

[0121] like Figures 5a-5d As shown, the dynamic adjustment curves of GFL / GFM inertia and damping under severe voltage sag are illustrated. These curves indicate that during the fault recovery phase, GFM and GFL undergo four dynamic adjustments of control parameters and two adjustments of PLL parameters, respectively. Quantitative data from Tables 2 and 3 show that the maximum adjustment range of GFL / GFM parameters is controlled within 2 pu, verifying the smooth parameter adjustment capability of the proposed GFL-GFM parallel system fault ride-through control method and contributing to ensuring asymptotic stability during the system fault recovery process.

[0122] Table 2. GFM dynamic inertia damping adjustment data under severe voltage sag

[0123]

[0124] Table 3. PLL dynamic parameter adjustment data under severe voltage sag

[0125]

[0126] This invention achieves smooth adjustment of equivalent inertia and damping by adaptively adjusting the integral coefficients of the phase-locked loop (PLL) of the GFL system and the virtual inertia of the GFM system. This method effectively suppresses system power angle oscillations and avoids system instability caused by parameter mutations in traditional control strategies. By engaging a fault current limiter to restrict fault current during the fault phase and dynamically adjusting the GFL and GFM parameters during the fault recovery phase, the transient stability and fault recovery capability of the system are significantly improved.

[0127] Based on the same inventive concept, this application also provides a GFL-GFM parallel system fault ride-through control system for implementing the above-mentioned GFL-GFM parallel system fault ride-through control method.

[0128] The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more GFL-GFM parallel system fault ride-through control system embodiments provided below can be found in the limitations of the GFL-GFM parallel system fault ride-through control method above, and will not be repeated here.

[0129] like Figure 6 As shown, this application provides a fault ride-through control system for a GFL-GFM parallel system, comprising:

[0130] The fault ride-through module 100 is used to activate the flux coupling current limiter to handle the fault in the case of a fault in the GFL-GFM parallel system until the fault in the GFL-GFM parallel system returns to normal.

[0131] The parameter tuning module 200 is used to adjust the phase-locked loop parameters of the GFL system and the control parameters of the GFM system based on the Sigmoid function when the fault of the GFL-GFM parallel system is restored to normal and the power angle fluctuation of both the GFL system and the GFM system is greater than the predetermined power angle fluctuation threshold. The adjustment ends when the power angle fluctuation of both the GFL system and the GFM system is no greater than the predetermined power angle fluctuation threshold.

[0132] In some embodiments, the control parameters of the GFM system include virtual inertia and virtual damping coefficient;

[0133] The process of adjusting the control parameters of a GFM system based on the Sigmoid function includes:

[0134] A virtual inertia adjustment strategy is constructed based on the Sigmoid function, and the virtual inertia of the GFM system is tuned by combining the virtual inertia adjustment strategy with the angular frequency deviation and power angle fluctuation of the GFM system.

[0135] Based on the actual change in active power, the change in active power reference value, and the virtual inertia of the GFM system, determine the transfer function of the small-signal model of the GFM system.

[0136] Based on the transfer function of the small-signal model of the GFM system, the first quantization relationship function between the virtual damping coefficient and the virtual inertia is determined, and the virtual damping coefficient of the GFM system is tuned according to the first quantization relationship function.

[0137] In some embodiments, the virtual inertia adjustment strategy is as follows:

[0138]

[0139] In the formula, For virtual inertia, This refers to the reference virtual inertia in the GFM system at steady state. , This is the dynamic adjustment coefficient for GFM inertia. The threshold for angular frequency variation. Angular frequency, For time, It is the difference in angular frequency. denoted as ω0, where ω is the power angle fluctuation value and e is a constant.

[0140] In some embodiments, the transfer function of the small-signal model of the GFM system is:

[0141]

[0142] In the formula, G GFM (s) is the transfer function of the small-signal model of the GFM system, ΔP GFM ΔP represents the actual change in active power of the GFM. GFM,ref The change in active power reference value of GFM is represented by E and U, respectively, where E and U are the amplitudes of the voltage at the GFM terminal and the grid voltage, respectively, and X represents the line impedance. ω N The angular frequency is the rated frequency, s is the Laplace operator, and D represents the damping coefficient;

[0143] Accordingly, based on the transfer function of the small-signal model of the GFM system, the first quantization relationship function between the virtual damping coefficient and the virtual inertia is determined, and the virtual damping coefficient of the GFM system is tuned according to the first quantization relationship function, including:

[0144] Determine the first damping ratio of the GFM system based on the transfer function of the small-signal model of the GFM system;

[0145] Based on the principle of optimal damping ratio, the first quantitative relationship function between virtual damping coefficient and virtual inertia is determined by the first damping ratio.

[0146] The virtual damping coefficient of the GFM system is determined by combining the first quantization relation function and the virtual inertia.

[0147] In some embodiments, the phase-locked loop parameters of the GFL system include equivalent inertia, PLL integral coefficient, and PLL proportional coefficient.

[0148] The process of adjusting the phase-locked loop parameters of a GFL system based on the Sigmoid function includes:

[0149] An adjustment strategy for the PLL integral coefficients is constructed based on the Sigmoid function, and the PLL integral coefficients of the GFL system are tuned by combining the adjustment strategy of the PLL integral coefficients with the power angle fluctuation of the GFL system.

[0150] The transfer function of the small-signal model of the GFL system is determined based on the voltage phase angle change at the port of the GFL system, the q-axis voltage change of the GFL system, and the PLL integral coefficients.

[0151] Based on the transfer function of the small-signal model of the GFL system, the second quantization relationship function between the PLL integral coefficient and the PLL proportional coefficient is determined, and the PLL proportional coefficient of the GFL system is tuned according to the second quantization relationship function.

[0152] The equivalent inertia is determined based on the inverse ratio of the PLL integral coefficients.

[0153] In some embodiments, the adjustment strategy for the PLL integral coefficient is as follows:

[0154]

[0155] In the formula, k I,PLL0 K represents the reference PLL integral coefficient in the steady-state state of the GFL system, K3 and K4 represent the dynamic adjustment coefficients of the GFL inertia, and k I,PLL This represents the PLL integral coefficient.

[0156] In some embodiments, the transfer function of the small-signal model of the GFL system is:

[0157]

[0158] In the formula, G(s) is the transfer function of the small-signal model of the GFL system, and Δθ GFL Let ΔU be the voltage phase angle change at the GFL port. GFL,q U represents the q-axis voltage change of the GFL system. GFL k is the voltage at the GFL port. P,PLL This is the PLL scaling factor;

[0159] Accordingly, based on the transfer function of the small-signal model of the GFL system, a second quantization relationship function between the PLL integral coefficients and the PLL proportional coefficients is determined, and the PLL proportional coefficients of the GFL system are tuned according to the second quantization relationship function, including:

[0160] Determine the second damping ratio of the GFL system based on the transfer function of the small-signal model of the GFL system;

[0161] Based on the principle of optimal damping ratio, the second quantization relationship function between the integral coefficient and the proportional coefficient of PLL is determined by the second damping ratio.

[0162] By combining the second quantization relation function and the virtual inertia, the PLL proportional coefficient of the GFL system is determined.

[0163] like Figure 7 As shown, this application provides an electronic device. The electronic device 10 includes a memory 20 and a processor 30. The memory 20 stores a computer program. When the computer program is executed by the processor 30, the processor 30 performs the steps of the GFL-GFM parallel system fault ride-through control method as described in the above embodiment.

[0164] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed, implements the steps of the GFL-GFM parallel system fault ride-through control method as described in the above embodiments.

[0165] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, electronic devices, and computer storage media described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0166] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0167] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0168] In the embodiments provided by this invention, it should be understood that the disclosed systems, electronic devices, computer storage media, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0169] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0170] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0171] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods described in the various embodiments of the present invention through a computer device (which may be a personal computer, a server, or a network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0172] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fault ride-through control method for a GFL-GFM parallel system, characterized in that, include: In the event of a fault in the GFL-GFM parallel system, the flux coupling current limiter is activated to handle the fault until the GFL-GFM parallel system returns to normal. When the fault in the GFL-GFM parallel system is restored to normal, and when the power angle fluctuations of both the GFL system and the GFM system are greater than the predetermined power angle fluctuation threshold, the phase-locked loop parameters of the GFL system and the control parameters of the GFM system are adjusted based on the Sigmoid function until the power angle fluctuations of both the GFL system and the GFM system are no greater than the predetermined power angle fluctuation threshold, and then the adjustment ends.

2. The fault ride-through control method for a GFL-GFM parallel system according to claim 1, characterized in that, The control parameters of the GFM system include virtual inertia and virtual damping coefficient; The process of adjusting the control parameters of the GFM system based on the Sigmoid function includes: The virtual inertia adjustment strategy is constructed based on the Sigmoid function, and the virtual inertia of the GFM system is tuned by combining the virtual inertia adjustment strategy with the angular frequency deviation and power angle fluctuation of the GFM system. Based on the actual change in active power, the change in reference active power, and the virtual inertia of the GFM system, the transfer function of the small-signal model of the GFM system is determined. Based on the transfer function of the small-signal model of the GFM system, a first quantization relationship function between the virtual damping coefficient and the virtual inertia is determined, and the virtual damping coefficient of the GFM system is tuned according to the first quantization relationship function.

3. The fault ride-through control method for a GFL-GFM parallel system according to claim 2, characterized in that, The adjustment strategy for the virtual inertia is as follows: In the formula, For virtual inertia, This refers to the reference virtual inertia in the GFM system at steady state. , This is the dynamic adjustment coefficient for GFM inertia. The threshold for angular frequency variation. Angular frequency, For time, It is the difference in angular frequency. denoted as ω0, where ω is the power angle fluctuation value and e is a constant.

4. The fault ride-through control method for a GFL-GFM parallel system according to claim 2 or 3, characterized in that, The transfer function of the small-signal model of the GFM system is: In the formula, G GFM (s) is the transfer function of the small-signal model of the GFM system, ΔP GFM ΔP represents the actual change in active power of the GFM. GFM,ref The change in active power reference value of GFM is represented by E and U, respectively, where E and U are the amplitudes of the voltage at the GFM terminal and the grid voltage, respectively, and X represents the line impedance. ω N The angular frequency is the rated frequency, s is the Laplace operator, and D represents the damping coefficient; Accordingly, determining the first quantization relationship function between the virtual damping coefficient and the virtual inertia based on the transfer function of the small-signal model of the GFM system, and tuning the virtual damping coefficient of the GFM system according to the first quantization relationship function, includes: Based on the transfer function of the small-signal model of the GFM system, determine the first damping ratio of the GFM system; Based on the principle of optimal damping ratio, a first quantization relationship function between the virtual damping coefficient and the virtual inertia is determined using the first damping ratio. By combining the first quantization relationship function and the virtual inertia, the virtual damping coefficient of the GFM system is determined.

5. The fault ride-through control method for a GFL-GFM parallel system according to claim 1, characterized in that, The phase-locked loop parameters of the GFL system include equivalent inertia, PLL integral coefficient, and PLL proportional coefficient. The process of adjusting the phase-locked loop parameters of the GFL system based on the Sigmoid function includes: An adjustment strategy for the PLL integral coefficient is constructed based on the Sigmoid function, and the PLL integral coefficient of the GFL system is tuned by combining the adjustment strategy of the PLL integral coefficient and the power angle fluctuation of the GFL system. The transfer function of the small-signal model of the GFL system is determined based on the voltage phase angle change at the port of the GFL system, the q-axis voltage change of the GFL system, and the PLL integral coefficient. Based on the transfer function of the small-signal model of the GFL system, a second quantization relationship function between the PLL integral coefficient and the PLL proportional coefficient is determined, and the PLL proportional coefficient of the GFL system is tuned according to the second quantization relationship function. The equivalent inertia is determined based on the inverse ratio of the PLL integral coefficients.

6. The fault ride-through control method for a GFL-GFM parallel system according to claim 1, characterized in that, The adjustment strategy for the PLL integral coefficient is as follows: In the formula, k I,PLL0 K represents the reference PLL integral coefficient in the steady-state state of the GFL system, K3 and K4 represent the dynamic adjustment coefficients of the GFL inertia, and k I,PLL This represents the PLL integral coefficient.

7. The fault ride-through control method for a GFL-GFM parallel system according to claim 6, characterized in that, The transfer function of the small-signal model of the GFL system is: In the formula, G(s) is the transfer function of the small-signal model of the GFL system, and Δθ GFL Let ΔU be the voltage phase angle change at the GFL port. GFL,q U represents the q-axis voltage change of the GFL system. GFL k is the voltage at the GFL port. P,PLL This is the PLL scaling factor; Accordingly, determining the second quantization relationship function between the PLL integral coefficients and the PLL proportional coefficients based on the transfer function of the small-signal model of the GFL system, and tuning the PLL proportional coefficients of the GFL system according to the second quantization relationship function, includes: The second damping ratio of the GFL system is determined based on the transfer function of the small-signal model of the GFL system. Based on the principle of optimal damping ratio, a second quantization relationship function between the PLL integral coefficient and the PLL proportional coefficient is determined using the second damping ratio. By combining the second quantization relationship function and the virtual inertia, the PLL scaling factor of the GFL system is determined.

8. A fault ride-through control system for a GFL-GFM parallel system, characterized in that, include: The fault ride-through module is used to activate the flux coupling current limiter to handle the fault in the case of a fault in the GFL-GFM parallel system until the fault in the GFL-GFM parallel system returns to normal. The parameter tuning module is used to adjust the phase-locked loop parameters of the GFL system and the control parameters of the GFM system based on the Sigmoid function when the fault of the GFL-GFM parallel system is restored to normal and the power angle fluctuation of both the GFL system and the GFM system is greater than the predetermined power angle fluctuation threshold, until the power angle fluctuation of both the GFL system and the GFM system is no greater than the predetermined power angle fluctuation threshold, and then the adjustment ends.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of the GFL-GFM parallel system fault ride-through control method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the steps of the fault ride-through control method for GFL-GFM parallel systems as described in any one of claims 1-7.

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