Multi-machine interconnection system low-frequency power oscillation suppression method

Abstract

The invention provides a method for suppressing low-frequency power oscillation of a multi-machine interconnection system. The direct suppression of the low-frequency power oscillation of the multi-machine interconnection system is realized by detecting the interaction power parameters among the grid-forming inverters in real time and superposing the differential signals of the interaction power parameters to the power control loop through the preset feedback gain coefficient. And by dynamically adjusting the equivalent system damping coefficient, the dynamic stability of the parallel inverter system is remarkably improved. Compared with a traditional method depending on a fixed damping coefficient or indirect current control, the method does not need a communication cooperation mechanism, and can achieve the quick attenuation of the power oscillation mode only based on a local signal. Meanwhile, the introduction of a differential feedback mechanism can accurately capture the dynamic change trend of power interaction, avoids the oscillation divergence risk caused by the sudden change of line impedance or load, and improves the robustness in a weak power grid and other scenes.

Description

Technical Field

[0001] This application relates to the field of electrical control, and particularly to a method for suppressing low-frequency power oscillation in a multi-machine interconnected system. Background Art

[0002] With the continuous consumption of traditional fossil energy, the penetration rate of renewable energy in the power grid has gradually increased, resulting in a decline in the proportion of traditional synchronous generators. There is a serious lack of inertia and damping in the power grid, further exacerbating the risk of abnormal operation of the power system. However, when multiple virtual synchronous machines are connected to the large power grid, the interaction between the virtual synchronous machines will cause low-frequency power oscillation in the power system, endangering the stable operation of the system.

[0003] The oscillation suppression of traditional grid-forming inverters mainly focuses on the oscillation between a single grid-forming inverter and the large power grid, the oscillation between multiple inverters and the large power grid, and the oscillation between the grid-forming inverter and the large power grid considering line resistance, or the oscillation between the grid-forming inverter and the large power grid considering a concentrated load. However, the above operating environment is different from the actual situation. Usually, the grid-forming inverter supplies power to local loads and transmits electrical energy to the large power grid or other grid-forming inverters and loads through tie lines, resulting in limitations in the analysis of control process data. In addition, the power oscillation suppression of traditional grid-forming inverters usually adopts indirect control strategies such as current differential feedforward and passivity-based current control, and various problems can lead to insufficient control effectiveness. Therefore, a method for suppressing low-frequency power oscillation in a multi-machine interconnected system is needed to improve the effectiveness of power oscillation suppression during the operation of multiple grid-forming inverters. Summary of the Invention

[0004] The purpose of this application aims to solve at least one of the above technical defects, especially the technical defect of insufficient effectiveness in suppressing low-frequency power oscillation of existing grid-forming inverters.

[0005] In a first aspect, this application provides a method for suppressing low-frequency power oscillation in a multi-machine interconnected system, the method comprising:

[0006] Real-time detecting the interaction power parameters between grid-forming inverters;

[0007] Adding the differential signal of the interaction power parameters with a preset feedback gain coefficient to the input signal of the power control loop of the corresponding inverter in the parallel system power control model to adjust the system damping coefficient of the parallel system power control model;

[0008] Wherein, the parallel system power control model includes the power control loops of at least two grid-forming inverters, the parallel system power control model is constructed through the physical response characteristics of each grid-forming inverter, and the system damping coefficient is used to suppress the low-frequency power oscillation of the multi-machine interconnected system.

[0009] As an alternative implementation, the construction method of the parallel system power control model includes:

[0010] Establish a rotor motion equation including virtual inertia and damping coefficient for each network-forming inverter;

[0011] Based on the bandwidth difference between the voltage loop and the power loop, simplify the rotor motion model to obtain a power loop control model corresponding to each network-forming inverter;

[0012] Integrate the power loop control models of each network-forming inverter to obtain a parallel system power control model corresponding to the overall system.

[0013] As an alternative implementation, the real-time detection of the interaction power parameters between each network-forming inverter includes:

[0014] Synchronously collect the output voltage phase differences of each network-forming inverter, and calculate the interaction power parameters between each network-forming inverter according to the product of the system power transfer coefficient and the output voltage phase difference.

[0015] As an alternative implementation, the method further includes an equivalent transformation step, specifically including:

[0016] Determine the equivalent feedback gain through block diagram transformation according to the differential signal and the feedback gain coefficient;

[0017] Superimpose the feedback signal on the output angular frequency signal of the power control loop of the corresponding inverter in the parallel system power control model through the equivalent feedback gain.

[0018] As an alternative implementation, the method further includes:

[0019] Determine the current system damping response situation and dynamically adjust the feedback gain coefficient;

[0020] Wherein, if the system oscillation amplitude exceeds the first threshold, gradually increase the feedback gain coefficient according to the preset parameter adjustment method, and if the system stable time exceeds the second threshold, gradually decrease the feedback gain coefficient according to the preset parameter adjustment method.

[0021] As an alternative implementation, the method further includes:

[0022] Collect the step response waveform after the system damping coefficient is adjusted, and calculate the damping ratio improvement amplitude;

[0023] If the damping ratio improvement amplitude does not reach the preset safety margin, perform secondary optimization on the target parameters;

[0024] Among them, the target parameter is used to indicate the adjustable parameters in the physical response characteristics of each grid-forming inverter in the parallel system power control model and the feedback gain coefficient.

[0025] As an optional implementation manner, the secondary optimization includes:

[0026] Establish a multi-dimensional parameter optimization space according to the target parameter;

[0027] Taking the system step response index as the optimization goal, use a swarm optimization algorithm for global search to determine the optimal combination of the target parameter in the multi-dimensional parameter optimization space.

[0028] In a second aspect, the present application provides a device for suppressing low-frequency power oscillation in a multi-machine interconnected system. The device includes:

[0029] A detection module for real-time detecting the interaction power parameters between each grid-forming inverter;

[0030] A processing module for adding the differential signal of the interaction power parameter to the input signal of the power control loop of the corresponding inverter in the parallel system power control model through a preset feedback gain coefficient, and adjusting the system damping coefficient of the parallel system power control model;

[0031] Among them, the parallel system power control model includes the power control loops of at least two grid-forming inverters. The parallel system power control model is constructed through the physical response characteristics of each grid-forming inverter. The system damping coefficient is used to suppress the low-frequency power oscillation of the multi-machine interconnected system.

[0032] In a third aspect, the present application provides a computer device, including one or more processors and a memory. Computer-readable instructions are stored in the memory. When the computer-readable instructions are executed by the one or more processors, the steps of the method described in the first aspect are executed.

[0033] In a fourth aspect, the present application provides a storage medium. Computer-readable instructions are stored in the storage medium. When the computer-readable instructions are executed by one or more processors, one or more processors are caused to execute the steps of the method described in the first aspect.

[0034] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0035] Based on any of the above embodiments, the method provided by this application realizes precise damping control of complex high-order systems by constructing a simplified model of the power time scale and an interactive power differential feedback mechanism. First, an equivalent rotor model including inertia and damping is established based on the virtual synchronous machine principle, and the model order is reduced through the bandwidth separation assumption, making it possible to analyze the dynamic characteristics. Secondly, through the differential feedback of the tie-line interactive power, an adjustable damping term is directly introduced into the power loop, breaking through the non-linear limitation of the traditional indirect current loop control. In addition, a parameter optimization mechanism is provided in some embodiments to ensure the robustness and universality of the suppression effect in the multi-machine parallel scenario. Compared with the prior art, this solution significantly reduces the low-frequency oscillation amplitude while maintaining the system inertia support ability, and does not rely on a communication network, providing core technical support for the stable operation of a high-proportion new energy power grid. Through local signal processing and parameter closed-loop regulation, problems such as PLL instability and multi-machine impedance coupling oscillation under weak grids are effectively solved, and it has wide engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of this application, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0037] Figure 1 Schematic flow chart of the method for suppressing low-frequency power oscillation in a multi-machine interconnected system provided by an embodiment of this application;

[0038] Figure 2 Parallel system of two virtual synchronous machines and its control block diagram provided by an embodiment of this application;

[0039] Figure 3 Simplified model of the parallel system of two virtual synchronous machines provided by an embodiment of this application;

[0040] Figure 4 Control block diagram of the simplified model of the parallel system of two virtual synchronous machines provided by an embodiment of this application;

[0041] Figure 5 Power loop control block diagram of two virtual synchronous machines provided by an embodiment of this application;

[0042] Figure 6 Power control loop at each bandwidth frequency provided by an embodiment of this application (a) Bode plot; (b) System zero-pole diagram;

[0043] Figure 7System response variation with the increase of the tie-line inductance Lg for two virtual synchronous machines provided in an embodiment of this application (a) System zero-pole diagram; (b) System step response diagram

[0044] Figure 8 Step response diagram (a) and zero-pole diagram (b) of the virtual synchronous machine parallel system provided in an embodiment of this application

[0045] Figure 9 System control block diagram of the low-frequency power oscillation suppression method for a multi-machine interconnected system provided in an embodiment of this application

[0046] Figure 10 Alternative implementation system control block diagram of the low-frequency power oscillation suppression method for a multi-machine interconnected system provided in an embodiment of this application

[0047] Figure 11 Step response diagram (a) and zero-pole diagram (b) of the system after applying the interactive power differential feedback method provided in an embodiment of this application

[0048] Figure 12 Virtual synchronous machine parallel system with interactive power feedback provided in an embodiment of this application (a) System step response; (b) System closed-loop poles

[0049] Figure 13 Internal structure diagram of the computer device provided in an embodiment of this application Detailed implementation manners

[0050] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0051] With the continuous consumption of traditional fossil energy, the penetration rate of renewable energy in the power grid has gradually increased, resulting in a decrease in the proportion of traditional synchronous generators and a serious lack of inertia and damping in the power grid, further exacerbating the risk of abnormal operation of the power system. However, when multiple virtual synchronous generators (VSGs) are connected to the large power grid, the interaction between the virtual synchronous machines will cause the power system to generate low-frequency power oscillations, endangering the stable operation of the system.

[0052] Currently, a relatively simple and effective method for suppressing low-frequency oscillations is to adjust the damping coefficient of the swing equation to suppress oscillations. However, in actual situations, changes in the damping coefficient will affect the steady-state power output of the virtual synchronous generator, and its value depends on the rated power of the virtual synchronous generator and the maximum frequency deviation of the power grid. In addition, reasonably applying power angle droop control or power differential droop control can also effectively mitigate low-frequency oscillations. Moreover, using a phase-locked loop to obtain the frequency of the power grid and then superimposing the frequency difference between the power grid and the virtual synchronous generator onto the active power command through a negative feedback link can also effectively suppress power oscillations. However, this method has a measurement state where the phase-locked loop becomes unstable under a weak power grid.

[0053] The above methods mainly focus on how to suppress the low-frequency power oscillations of the system, and conduct research on the controller design, modeling, and parameter adaptive optimization of the virtual synchronous machine single-machine system, but ignore the applicability of these methods in high-order systems. For the research on the multi-machine parallel system, usually only the case where the parameters of the virtual synchronous machines are the same is considered, ignoring the interaction between the parallel virtual synchronous machines under different parameter conditions, and lacking the analysis and suppression of the influence of local loads and tie-line impedances on the system power oscillations.

[0054] There may be the following problems in the power oscillation suppression process of the current grid-forming inverter control method: The oscillation suppression of the traditional grid-forming inverter mainly targets the oscillation between a single grid-forming inverter and the large power grid, the oscillation between multiple inverters and the large power grid, and the oscillation between the grid-forming inverter and the large power grid considering line resistance, or the oscillation between the grid-forming inverter and the large power grid considering a concentrated load. However, the above operating environments deviate from the actual situation. Usually, the grid-forming inverter supplies power to local loads and transmits electrical energy to the large power grid or other grid-forming inverters and loads through tie-lines. In this case, there are oscillations in the interactive power on the local load and the tie-line, affecting the system stability. This situation is not seen or analyzed in the traditional operating conditions. The traditional power oscillation suppression of the grid-forming inverter usually adopts indirect control strategies such as current differential feedforward and passivity-based current control, which have a non-linear mapping relationship between current and power and cannot directly suppress and analyze power oscillations starting from the transfer function of power oscillations.

[0055] The present invention aims at the actual operating scenario, that is, based on the scenario where the grid-forming inverter supplies power to local loads and transmits electrical energy to the large power grid or other grid-forming inverters and loads through tie-lines, establishes a power dynamic model of the multi-grid-forming inverter system, proposes a tie-line interactive power oscillation mechanism, and proposes a power oscillation suppression strategy for the multi-grid-forming inverter system based on tie-line interactive power differential feedback.

[0056] Based on specific embodiments, the technical concept of this application lies in achieving precise damping control of complex high-order systems by constructing a simplified model of the power-time scale and an interactive power differential feedback mechanism. First, an equivalent rotor model including inertia and damping is established based on the virtual synchronous machine principle, and the model order is reduced through the bandwidth separation assumption, making it possible to analyze the dynamic characteristics; secondly, through the differential feedback of the tie-line interactive power, an adjustable damping term is directly introduced into the power loop, breaking through the non-linear limitation of the traditional indirect control of the current loop; in addition, a parameter optimization mechanism is provided in some embodiments to ensure the robustness and universality of the suppression effect in the multi-machine parallel scenario. Compared with the prior art, this solution significantly reduces the low-frequency oscillation amplitude while maintaining the system inertia support ability, and does not rely on a communication network, providing core technical support for the stable operation of a high-proportion new energy power grid. Through local signal processing and parameter closed-loop regulation, problems such as PLL instability and multi-machine impedance coupling oscillation in a weak power grid are effectively solved, and it has wide engineering application value.

[0057] The method provided by this application will be described in detail below according to the corresponding embodiments in some actual application scenarios.

[0058] Please refer to Figure 1 , Figure 1 which is a schematic flow chart of a method for suppressing low-frequency power oscillation in a multi-machine interconnected system provided by an embodiment of this application. As Figure 1 shown, the method includes:

[0059] S101. Real-time detect the interactive power parameters between each network-forming inverter;

[0060] S102. Superimpose the differential signal of the interactive power parameter onto the input signal of the power control loop of the corresponding inverter in the power control model of the parallel system through a preset feedback gain coefficient, and adjust the system damping coefficient of the power control model of the parallel system;

[0061] Wherein, the power control model of the parallel system includes the power control loops of at least two network-forming inverters, the power control model of the parallel system is constructed through the physical response characteristics of each network-forming inverter, and the system damping coefficient is used to suppress the low-frequency power oscillation of the multi-machine interconnected system.

[0062] In this embodiment, by detecting the interactive power parameters between grid-forming inverters in real time and superimposing the differential signal of the interactive power parameters on the power control loop through a preset feedback gain coefficient, the direct suppression of low-frequency power oscillation in a multi-machine interconnected system is achieved. By dynamically adjusting the equivalent system damping coefficient, the dynamic stability of the parallel inverter system is significantly improved. Compared with traditional methods that rely on fixed damping coefficients or indirect current control, this solution does not require a communication coordination mechanism and can achieve the rapid attenuation of power oscillation modes based only on local signals. At the same time, the introduction of the differential feedback mechanism can accurately capture the dynamic change trend of power interaction, avoid the risk of oscillation divergence caused by line impedance or load mutation, and improve the robustness in scenarios such as weak power grids.

[0063] As an alternative embodiment, the method for constructing the power control model of the parallel system includes:

[0064] Establish a rotor motion equation including virtual inertia and damping coefficient for each grid-forming inverter;

[0065] Based on the bandwidth difference between the voltage loop and the power loop, simplify the rotor motion model to obtain a power loop control model corresponding to each grid-forming inverter;

[0066] Integrate the power loop control models of each grid-forming inverter to obtain a parallel system power control model corresponding to the overall system.

[0067] As an alternative embodiment, the real-time detection of the interactive power parameters between grid-forming inverters includes:

[0068] Synchronously collect the output voltage phase differences of each grid-forming inverter, and calculate the interactive power parameters between each grid-forming inverter according to the product of the system power transfer coefficient and the output voltage phase difference.

[0069] This embodiment proposes a calculation method for interactive power parameters based on the output voltage phase difference and the power transfer coefficient. By synchronously collecting the phase difference and dynamically calculating the interactive power in combination with the power transfer coefficient, the real-time and accuracy of parameter measurement are ensured. This method realizes the dynamic adaption to the change of line impedance through the introduction of the power transfer coefficient (related to line impedance and rated voltage), and enhances the parameter robustness in scenarios with different grid strengths. Compared with some other feasible embodiments, this solution has no instability risk under weak power grids and provides a high-precision input reference for differential feedback control.

[0070] As an alternative embodiment, the method further includes an equivalent transformation step, specifically including:

[0071] Determine the equivalent feedback gain through block diagram transformation according to the differential signal and the feedback gain coefficient;

[0072] Through the equivalent feedback gain, the feedback signal is superimposed on the output angular frequency signal of the power control loop of the corresponding inverter in the parallel system power control model.

[0073] In this embodiment, by converting the differential signal and the feedback gain coefficient into an equivalent feedback gain, the structural design of the control loop is optimized. This transformation method simplifies the pole configuration process of the closed-loop transfer function through block diagram reconstruction and signal superposition, making it possible to independently adjust the damping ratio and the natural frequency. Compared with direct differential control, this method avoids the problem of high-frequency noise amplification and ensures the stability of the feedback mechanism within the frequency domain range, providing an achievable engineering path for optimizing the dynamic response of the multi-machine system.

[0074] As an alternative embodiment, the method further includes:

[0075] Determine the current system damping response and dynamically adjust the feedback gain coefficient;

[0076] Wherein, if the system oscillation amplitude exceeds a first threshold, the feedback gain coefficient is gradually increased according to a preset parameter adjustment method, and if the system stabilization time exceeds a second threshold, the feedback gain coefficient is gradually decreased according to a preset parameter adjustment method.

[0077] The dynamic feedback gain adjustment mechanism proposed in this embodiment can adaptively adjust the gain coefficient according to the actual oscillation amplitude and stabilization time of the system. When the oscillation is detected to exceed the limit, the gain is automatically increased to enhance the damping, and when the system tends to be stable, the gain is decreased to avoid response lag caused by over-suppression. This closed-loop adjustment strategy breaks through the limitations of traditional fixed-parameter design, significantly improves the adaptability of the system under different operating conditions (such as load mutation, impedance fluctuation), and reduces the complexity of parameter adjustment.

[0078] As an alternative embodiment, the method further includes:

[0079] Collect the step response waveform after the system damping coefficient is adjusted and calculate the damping ratio improvement amplitude;

[0080] If the damping ratio improvement amplitude does not reach the preset safety margin, perform secondary optimization on the target parameters;

[0081] Wherein, the target parameters are used to indicate the adjustable parameters in the physical response characteristics of each grid-forming inverter in the parallel system power control model and the feedback gain coefficient.

[0082] In this embodiment, an evaluation mechanism for system performance is constructed by collecting step response waveforms and calculating the improvement amplitude of the damping ratio. When it is detected that the damping ratio does not reach the safety margin, secondary optimization is performed on key parameters such as virtual inertia, damping coefficient, and feedback gain. This mechanism can correct model simplification errors and the influence of external disturbances in real time, ensure that the suppression effect is always in the optimal range, and solve the defect that traditional single-parameter tuning is difficult to cope with long-term operation deviations.

[0083] As an alternative embodiment, the secondary optimization includes:

[0084] Establish a multi-dimensional parameter optimization space according to the target parameters;

[0085] Taking the system step response index as the optimization goal, use a swarm optimization algorithm to perform a global search to determine the optimal combination of the target parameters in the multi-dimensional parameter optimization space.

[0086] This embodiment uses a swarm optimization algorithm to perform a global search in the multi-dimensional parameter space, with the step response index as the optimization goal, and realizes the optimal matching of multiple parameters in a coordinated manner. Thus, it can avoid falling into local optimal solutions and obtain a parameter combination with the best system performance, which can significantly improve the global convergence of the parameter combination. By defining a multi-dimensional space including physical characteristic parameters and feedback gain, the optimization result is ensured to meet both dynamic performance and engineering feasibility at the same time.

[0087] Hereinafter, based on actual application scenarios, each embodiment of the present application, its possible extended embodiments, and specific implementation solutions will be explained and illustrated, so as to demonstrate the feasibility and actual effect of the solution of the present application in suppressing power oscillations by introducing a differential link to adjust the system transfer function. In the actual application scenario, the present application is divided into three parts for demonstration: basic modeling, model optimization and oscillation analysis, and the implementation method of the present application in the actual application scenario (including main technical features such as differential link, equivalent transformation, and gain adjustment).

[0088] The first part, basic modeling. Before the actual application of the present application, a simplified model of the power time scale of the grid-forming inverter according to the working principle of the AC-DC power supply device is first established.

[0089] The present application is described based on a simplified system of two grid-forming inverters. For systems with more grid-forming inverters, the amount of data involved in the analysis and calculation process may be more complex. To more clearly illustrate the corresponding principle of the present application, it is only described based on a two-machine system, and those skilled in the art can generalize this. Figure 2Schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of the present application, which is used to exemplify the parallel system structure of the grid-forming inverters of two AC-DC power supply devices applied in the present application and its voltage-power control block diagram, and generates a PWM control signal through the corresponding control strategy to realize the control of the virtual synchronous machine.

[0090] In Figure 2 , the power control loop adopts the virtual synchronous machine control strategy. In the present application, is the virtual inertia, which can enable the inverter to simulate the electromechanical transient characteristics of the synchronous generator. , for example, taking the first machine in the figure as an example, the corresponding is the virtual inertia; is the damping coefficient, which simulates the frequency regulation in the traditional power system. Correspondingly, in the figure is the damping coefficient. It should be noted that Figure 2 the 1 in the control block diagram part in should not be misinterpreted as I or the letter l. These two parts of data play important roles in the modeling process and parameter optimization process. For details, please refer to the relevant implementation methods; is the actual active power of the th grid-forming inverter of the AC-DC power supply device, which is obtained by calculating the voltage phasor and current on the power grid. is the reference active power of the th grid-forming inverter of the AC-DC power supply device. The subscript is the per-unit value. For the figure, is the actual active power of the first machine after per-unit conversion, and is the reference active power of the first machine after per-unit conversion. Details will not be elaborated later. For the input and control quantities related to voltage in the figure, it can be understood that is the input quantity,

[0091] is the control quantity. The subscript d or q or abc is used to indicate the components after dq / abc transformation. Since the voltage control can be essentially ignored in the present application, for details, please refer to the relevant implementation methods, so the principle of voltage control will not be elaborated here.

[0092]

[0093] In the formula, and are respectively the filter inductance and filter capacitance of the th grid-forming inverter of the AC-DC power supply device, ; and are respectively the The grid voltage and current of the grid-forming inverter of the AC-DC power supply device is the voltage on the inverter side is the current on the filter inductor

[0094] Equation (1) is used to describe the dynamic characteristics of the inverter filter inductor and capacitor: the first equation indicates that the change in inductor current is driven by the difference between the voltage on the inverter side and the grid voltage; the second equation indicates that the change in capacitor voltage is determined by the difference between the inductor current and the output current. Thus, it provides an electrical dynamic basis for modeling the subsequent power control loop and clarifies the influence of filter parameters on system stability

[0095] Based on the closed-loop control principle of the grid-forming inverter, the dynamic equation of the active power control loop of the grid-forming inverter of the AC-DC power supply device can be obtained as follows:

[0096]

[0097] wherein is the output angular frequency of the th grid-forming inverter ; is the rated angular frequency is the th active power output by the grid-forming inverter, which can be calculated from the output voltage and current and The per-unit values of are obtained by normalization calculation is the phase of the th grid-forming inverter, which is used for Park transformation and phase angle frequency control

[0098] It can be found therefrom that the present application mainly adjusts the power deviation through virtual inertia and damping coefficient, and the phase angle is generated by integrating the angular frequency and is used for synchronization control. In a specific implementation manner, the phase angle is an index that can be locally measured, avoiding problems brought by multi-machine communication. Equation (2) simulates the electromechanical transient characteristics of a synchronous generator, constructs a dynamic response model of the power loop, and provides a core equation for the analysis of a multi-machine parallel system

[0099] Furthermore, based on the above analysis, it can be found that when the bandwidth of the voltage control loop is much larger than the bandwidth of the power control loop, the response of the voltage loop is very fast. That is, when the bandwidth frequency of the voltage loop is extremely large, the amplitude of the closed voltage control loop is 0 dB. Therefore, the dynamic influence of the voltage control loop can be ignored in the power control loop Figure 3 is a schematic diagram of the principle of the method for suppressing low-frequency power oscillation in a multi-machine interconnected system provided by an embodiment of the present application, as shown in Figure 3 shown. At this time, a simplified model of the power time scale of the grid-forming inverter parallel system of the AC-DC power supply device can be established, and Figure 4Schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of the present application. It can be based on Figure 3 Construct the system control block diagram of the simplified model of the parallel system of two grid-forming inverters powered by AC-DC power supplies. In the specific analysis of the present application, only the power loop is required.

[0100] According to Figure 3 and Figure 4 , combined with the physical mechanism for modeling, the rotor motion equation of the power loop can be obtained:

[0101]

[0102] In the formula represents the transmission power between the two grid-forming inverters powered by AC-DC power supplies; is the local load power of the first inverter; is the local load power of the second inverter; is the system power transfer coefficient, represents the rated voltage of the corresponding grid-forming inverter, represents the reactance of the tie line, represents the rated power capacity of the system.

[0103] Based on Figure 4 , the power loops of the two grid-forming inverters can be split, Figure 5 Schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of the present application, Figure 5 that is, the corresponding split control block diagram.

[0104] According to Figure 5 obtain the open-loop transfer function of the power loop of the th grid-forming inverter as:

[0105]

[0106] Furthermore, according to Equation (4), the closed-loop transfer function of the power loop of the th grid-forming inverter powered by AC-DC power supply is:

[0107]

[0108] Figure 6 Schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of the present application, showing the performance of the system at each bandwidth frequency. According to Equation (5), when the bandwidth frequency of the voltage loop changes, the power control loop characteristics of the parallel system of grid-forming inverters powered by AC-DC power supplies are as Figure 6As shown. When the bandwidth frequency of the voltage control loop increases, the poles of the power control loop move to the left on the complex plane. The response speed of the simplified model of the system power time scale is the fastest, and the parallel system of the grid-forming inverter of the AC-DC power supply device can operate stably and reliably.

[0109] Thus, the basic modeling is completed. Further, the established model can be integrated and optimized, and the low-frequency power oscillation analysis can be carried out for the parallel system of the grid-forming inverter of the AC-DC power supply device to determine the main influencing parameters and the optimization method.

[0110] According to the transfer function derived from the small-signal model of the grid-forming inverter in the first part , further, based on the simulation analysis Figure 7 is the schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of this application. The zero-pole diagrams of the grid-forming inverter under different grid equivalent inductances can be referred to Figure 7 (a), and the step response can be referred to Figure 7 (b). As increases, the imaginary part of the dominant pole gradually decreases, the system damping ratio gradually increases, the corresponding rise time of the active power step response increases, the peak time increases, the settling time remains basically unchanged, and the overshoot decreases. The results show that the increase of the grid impedance will slow down the system response speed and increase the system response time, but it can also reduce the power fluctuation, which has a significant impact on the power dynamic performance of the system. Therefore, this application can analyze and optimize the overall damping of the system to achieve the corresponding suppression effect.

[0111] Further, based on the simplified model of the power time scale of the single grid-forming inverter constructed, a simplified model of the power time scale of the parallel system of two grid-forming inverters is established, and its motion equation is as shown in (6).

[0112]

[0113] In the formula , are the inertia constants of the two grid-forming inverters respectively; , are the damping coefficients of the two grid-forming inverters of the AC-DC power supply device respectively; , are the output angular frequencies of the two grid-forming inverters respectively; , are the load powers of the local loads of the two grid-forming inverters; is the interaction power between the transmission lines of the two grid-forming inverters.

[0114] Equation (6) is used to describe the power balance dynamics of two inverters: the left side is the inertial response caused by virtual inertia; the right side includes interactive power, local load power, and damping terms. This can reveal the physical source of low-frequency oscillations in a multi-machine system and provide a mathematical model basis for the differential feedback suppression strategy.

[0115] Considering the inductive line impedance, the active power output from the th network-forming inverter to the th network-forming inverter is defined as .

[0116]

[0117] represents the rated voltage of the inverter under symmetrical parameters. The subscripts ij both represent the th network-forming inverter to the th network-forming inverter. For example, represents the proportionality coefficient of the power output obtained by linear calculation through the phase difference between two network-forming inverters. Other parameters can refer to the relevant description of Equation (3). Equation (7) shows that the interactive power is linearly related to the phase difference, and the proportionality coefficient is determined by the line impedance and rated parameters. This can simplify the non-linear power calculation, facilitate the closed-loop control design, and directly relate to the differential feedback signal of the phase difference.

[0118] Equation (7) also shows that to obtain the active power output from the th network-forming inverter to the th network-forming inverter, it can be achieved by locally measuring the output phase of each network-forming inverter.

[0119] Substituting Equation (7) into Equation (6) gives:

[0120]

[0121] Select , , as state variables to establish the state-space equation of the parallel system of network-forming inverters in the AC-DC power supply device:

[0122]

[0123] Then the transfer function from the system inputs and to the system output is:

[0124]

[0125]

[0126] Figure 8 Schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of the present application. According to Equation (10), the characteristic diagram of the parallel system of the AC-DC power supply device grid-forming inverters is obtained, as shown in Figure 8 as follows:

[0127] When no method is used to suppress the low-frequency power oscillation of the parallel system of the AC-DC power supply device grid-forming inverters, there are obvious oscillations in the system step response, and the damping ratio of the system is small. That is, the damping coefficients and of the two AC-DC power supply device grid-forming inverters are not sufficient to suppress the power oscillation generated by the parallel system.

[0128] When no method is used to suppress the low-frequency power oscillation of the parallel system of the AC-DC power supply device grid-forming inverters, there are obvious oscillations in the system step response, and the damping ratio of the system is small. That is, the damping coefficients D1 and D2 of the two AC-DC power supply device grid-forming inverters are not sufficient to suppress the power oscillation generated by the parallel system.

[0129] Furthermore, the present application proposes a low-frequency power oscillation suppression method based on the interactive power differential feedback method. Among them, the interactive power differential feedback method only needs to be based on the detection of local signals and does not depend on the communication between the AC-DC power supply device grid-forming inverters, and is applicable to the multi-machine parallel system of AC-DC power supply device grid-forming inverters with local loads. Figure 9 Schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of the present application. The system control block diagram after applying the interactive power differential feedback method is as shown in Figure 9 as follows. A differential link is introduced into the system, but the differential link oscillates severely and is difficult to implement physically. Therefore, an equivalent transformation needs to be performed on it. Figure 10 Schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of the present application. The present application adopts the method of block diagram transformation to realize the differential feedback of the interactive power while avoiding the problem of high-frequency noise amplification caused by the derivative implementation. The specific operation is as shown in Figure 10 as follows.

[0130] The derivative of the interactive power is fed back through the feedback gain to realize the feedback control link of the system. Considering the worst case of , according to Figure 10 , the transfer function from the system input to the system output is:

[0131]

[0132] According to Equation (12), the feedback gain adds the term " " in the denominator, providing a controllable amount of damping effect, which can suppress the low-frequency power oscillation of the system to a certain extent. Select the state variable ; the output variable ; the input variable , and establish the system state-space equation after applying the interactive power differential feedback.

[0133]

[0134]

[0135] According to Equations (13) and (14), the transfer function from the system input and to the system output is:

[0136]

[0137]

[0138] Figure 11 is the schematic diagram of the principle of the low-frequency power oscillation suppression method for the multi-machine interconnected system provided by an embodiment of this application. According to Equation (16), the characteristic diagram of the AC-DC power supply device grid-forming inverter parallel system after applying the interactive power differential feedback method is obtained, as shown in Figure 11 .

[0139] After applying the interactive power differential feedback method, the damping ratio of the AC-DC power supply device grid-forming inverter parallel system increases. The system step response tends to be stable, and the poles move to the left in the complex plane, improving the robustness and anti-interference ability of the system, making the system more stable and reliable, proving that the interactive power differential feedback method can effectively suppress the low-frequency power oscillation of the two AC-DC power supply device grid-forming inverter parallel systems.

[0140] According to Equation (16), the system characteristic equation is obtained:

[0141]

[0142] Set in Equation (17) to zero, and the poles of the AC-DC power supply device grid-forming inverter parallel system are determined by the system equipment parameters , , , , and the interactive power feedback parameters , .

[0143] In general, the grid-forming inverters of parallel AC-DC power supply devices have the same rated power, and their inertia constants and damping coefficients are the same as each other. Considering the response speed, stability of the system and simulation analysis, the parameters of the system equipment are set 、 , can be calculated according to Equation (17).

[0144] Therefore, the transfer function of Equation (16) can be simplified to a second-order transfer function.

[0145]

[0146] In Equation (18), the numerator term directly reflects the power transfer intensity; the newly added term in the denominator directly enhances the system damping. Thus, the improvement effect of the differential feedback gain on the damping ratio is quantitatively demonstrated to guide parameter tuning.

[0147] Specifically, Equation (18) describes the dynamic response characteristics of the multi-machine parallel closed-loop system:

[0148] The numerator part is the power transfer coefficient, reflecting the coupling strength of the interactive power;

[0149] The squared term in the denominator part is dominated by the virtual inertia, determining the natural oscillation frequency of the system. The first-order term is the equivalent damping term, which combines the differential feedback gain and the inherent damping to suppress power oscillation. The constant term is the steady-state power balance term.

[0150] Thus, further frequency-domain stability analysis can be realized. By pole placement, the damping ratio ζ and the natural frequency ωn are optimized to provide a mathematical model for parameter tuning.

[0151] Equation (18) is a typical second-order system. When arranged in the standard form, it can be obtained:

[0152]

[0153] Equation (19) maps the system parameters to the dynamic characteristic indexes of the standard second-order system:

[0154] Natural frequency: determined by the virtual inertia and the power transfer coefficient, reflecting the response speed of the system;

[0155] Damping ratio: combining the feedback gain and the damping coefficient, determining the oscillation decay rate of the system.

[0156] Thus, the influence law of the parameters on the dynamic performance is quantitatively revealed to guide the design of the feedback gain under the critical damping condition.

[0157] The value of the interactive power differential feedback parameter when the system reaches the critical damping ratio is obtained from Equation (19):

[0158]

[0159] Equation (20) provides a way to calculate the required differential feedback gain under critical damping conditions. As the core formula for achieving a fast response without overshoot, it optimizes the system damping characteristics by dynamically adjusting the differential feedback parameters, avoiding the limitations of traditional fixed-parameter designs.

[0160] Figure 12 This is a schematic diagram of the principle of the method for suppressing low-frequency power oscillations in a multi-machine interconnected system provided by an embodiment of this application. According to Equation (14), the interactive power differential feedback parameters are calculated to obtain the system characteristic diagrams for different feedback parameter values. When the interactive power differential feedback parameter of the two grid-forming inverters of the AC-DC power supply device is 0, feedback control is performed on the system, and the damping ratio of the parallel system is extremely small. At this time, the step response of the system oscillates highly. When the feedback parameters of both grid-forming inverters of the two AC-DC power supply devices increase to When, the damping ratio of the parallel system increases, and the oscillation of the system step response is suppressed to a certain extent. When the interactive power differential feedback parameter of one of the grid-forming inverters of the AC-DC power supply device is set to For feedback, the damping ratio of the system reaches the critical value. At this time, the system has no overshoot and reaches steady-state operation within 1 s. Figure 12 In, the system poles move to the left in the complex plane as the interactive power differential feedback parameter increases, achieving a faster dynamic response.

[0161] This application also provides a device for suppressing low-frequency power oscillations in a multi-machine interconnected system. The device includes:

[0162] A detection module for real-time detecting the interactive power parameters between grid-forming inverters;

[0163] A processing module for superimposing the differential signal of the interactive power parameter onto the input signal of the power control loop of the corresponding inverter in the parallel system power control model through a preset feedback gain coefficient, and adjusting the system damping coefficient of the parallel system power control model;

[0164] Among them, the parallel system power control model includes the power control loops of at least two grid-forming inverters. The parallel system power control model is constructed through the physical response characteristics of each grid-forming inverter, and the system damping coefficient is used to suppress the low-frequency power oscillations of the multi-machine interconnected system.

[0165] In this embodiment, by detecting the interactive power parameters between the grid-forming inverters in real time and superimposing the differential signal of the interactive power parameters onto the power control loop through a preset feedback gain coefficient, the direct suppression of the low-frequency power oscillation of the multi-machine interconnected system is realized. By dynamically adjusting the equivalent system damping coefficient, the dynamic stability of the parallel inverter system is significantly improved. Compared with the traditional methods relying on fixed damping coefficients or indirect current control, this solution does not require a communication coordination mechanism and can achieve the rapid decay of the power oscillation mode only based on local signals. At the same time, the introduction of the differential feedback mechanism can accurately capture the dynamic change trend of power interaction, avoiding the risk of oscillation divergence caused by line impedance or load mutation, and improving the robustness in scenarios such as weak power grids.

[0166] It should be noted that it should be understood that the division of each module of the above device is only a logical function division. In actual implementation, it can be fully or partially integrated into a physical entity, or physically separated. And these modules can all be implemented in the form of software called by a processing element; they can also all be implemented in the form of hardware; they can also be partially implemented in the form of software called by a processing element and partially implemented in the form of hardware. For example, the processing module can be a separately established processing element, or can be integrated in a certain chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a certain processing element of the above device to perform the functions of the above determined modules. The implementation of other modules is similar. In addition, all or part of these modules can be integrated together or independently implemented. Here, the processing element can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed by the integrated logic circuit in the processor element or the instruction in the form of software.

[0167] Schematically, as Figure 13 shown, Figure 13 is a schematic internal structure diagram of a computer device provided by an embodiment of the present application. The computer device 300 can be provided as a server. Referring to Figure 13 , the computer device 300 includes a processing component 302, which further includes one or more processors, and memory resources represented by the memory 301 for storing instructions executable by the processing component 302, such as application programs. The application programs stored in the memory 301 can include one or more modules each corresponding to a set of instructions. In addition, the processing component 302 is configured to execute instructions to perform the method of any of the above embodiments.

[0168] The computer device 300 may further include a power supply component 303 configured to perform power management of the computer device 300, a wired or wireless network interface 304 configured to connect the computer device 300 to a network, and an input / output (I / O) interface 305. The computer device 300 may operate based on an operating system stored in the memory 301, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSD TM or the like.

[0169] Those skilled in the art can understand that Figure 13 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component arrangement.

[0170] The embodiment of this application provides a storage medium, in which computer-readable instructions are stored. When the computer-readable instructions are executed by one or more processors, the one or more processors are caused to execute the method provided in any of the embodiments.

[0171] Finally, it should also be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device including a series of elements includes not only those elements, but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0172] Each embodiment in this specification is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. The embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0173] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for suppressing low-frequency power oscillation in a multi-machine interconnected system, characterized in that The method includes: Real-time detecting the interaction power parameters between grid-forming inverters; Superposing the differential signal of the interaction power parameters to the input signal of the power control loop of the corresponding inverter in the parallel system power control model through a preset feedback gain coefficient, and adjusting the system damping coefficient of the parallel system power control model; Wherein, the parallel system power control model includes the power control loops of at least two grid-forming inverters, the parallel system power control model is constructed through the physical response characteristics of each grid-forming inverter, and the system damping coefficient is used to suppress the low-frequency power oscillation of the multi-machine interconnected system.

2. The method according to claim 1, wherein The construction method of the parallel system power control model includes: Establishing a rotor motion equation including virtual inertia and damping coefficient for each grid-forming inverter; Simplifying the rotor motion model based on the bandwidth difference between the voltage loop and the power loop to obtain a power loop control model corresponding to each grid-forming inverter; Integrating the power loop control models of each grid-forming inverter to obtain a parallel system power control model corresponding to the overall system.

3. The method according to claim 1, wherein The real-time detecting the interaction power parameters between grid-forming inverters includes: Synchronously collecting the output voltage phase differences of each grid-forming inverter, and calculating the interaction power parameters between each grid-forming inverter according to the product of the system power transfer coefficient and the output voltage phase difference.

4. The method according to claim 1, characterized in that The method further includes an equivalent transformation step, specifically including: Determining an equivalent feedback gain through a block diagram transformation method according to the differential signal and the feedback gain coefficient; Superposing the feedback signal to the output angular frequency signal of the power control loop of the corresponding inverter in the parallel system power control model through the equivalent feedback gain.

5. The method according to claim 1, wherein The method further includes: Determining the current system damping response situation and dynamically adjusting the feedback gain coefficient; Wherein, if the system oscillation amplitude exceeds a first threshold, the feedback gain coefficient is gradually increased according to a preset parameter adjustment method, and if the system stable time exceeds a second threshold, the feedback gain coefficient is gradually decreased according to a preset parameter adjustment method.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: Collecting the step response waveform after the system damping coefficient is adjusted and calculating the damping ratio improvement amplitude; If the damping ratio improvement amplitude does not reach a preset safety margin, secondary optimization is performed on the target parameters; Wherein, the target parameters are used to indicate the adjustable parameters in the physical response characteristics of each grid-forming inverter in the parallel system power control model and the feedback gain coefficient.

7. The method according to claim 6, characterized in that, The secondary optimization includes: Establishing a multi-dimensional parameter optimization space according to the target parameters; Taking the system step response index as the optimization target and using a swarm optimization algorithm for global search to determine the optimal combination of the target parameters in the multi-dimensional parameter optimization space.

8. A device for suppressing low-frequency power oscillation in a multi-machine interconnected system, characterized in that, The device includes: A detection module for real-time detecting the interaction power parameters between grid-forming inverters; A processing module, configured to superimpose the differential signal of the interaction power parameter onto the input signal of the power control loop of the corresponding inverter in the parallel system power control model through a preset feedback gain coefficient, and adjust the system damping coefficient of the parallel system power control model; Wherein, the parallel system power control model includes the power control loops of at least two network-forming inverters, the parallel system power control model is constructed through the physical response characteristics of each network-forming inverter, and the system damping coefficient is used to suppress the low-frequency power oscillation of the multi-machine interconnected system.

9. A computer device, characterized in that, Comprising one or more processors, and a memory, wherein computer-readable instructions are stored in the memory, and when the computer-readable instructions are executed by the one or more processors, the steps of the method according to any one of claims 1-7 are executed.

10. A storage medium, characterized in that, Computer-readable instructions are stored in the storage medium, and when the computer-readable instructions are executed by one or more processors, one or more processors are caused to execute the steps of the method according to any one of claims 1-7.

Images