Virtual inertia collaborative optimization method, system, device, medium and product based on commutation margin

Abstract

The present application relates to the technical field of network construction energy storage control, and discloses a virtual inertia collaborative optimization method, system, equipment, medium and product based on commutation margin. The method can simultaneously master the actual volt-second area of the commutation process and the power angle motion state of the network construction energy storage converter by acquiring the commutation voltage and real-time power angle, and determine the commutation margin, dynamic inertia and commutation failure risk on this basis. By predicting the commutation voltage phase at the next moment and forming active power feedforward compensation, the active control instruction can be corrected in advance before the power angle feedback error is fully formed. By collaborative adjustment of the dynamic inertia and reference damping coefficient through the commutation failure risk, the inertia can be reduced to speed up the power angle recovery and the damping can be increased to suppress power oscillation when the commutation risk increases, so as to reduce the commutation failure risk and improve the stability recovery after the fault.

Description

Technical Field

[0001] This invention relates to the field of grid-connected energy storage control technology, and in particular to a method, system, device, medium and product for virtual inertia collaborative optimization based on commutation margin. Background Technology

[0002] Grid-based energy storage typically uses a virtual synchronous machine to control the rotor motion characteristics of a synchronous generator, enabling the energy storage converter to autonomously establish voltage and frequency references and provide inertia and frequency support to the grid. Under grid fault or weak grid operating conditions, the power angle and commutation voltage of grid-based energy storage are prone to large fluctuations. The settings of virtual inertia and damping coefficients will directly affect the power angle recovery process and commutation safety.

[0003] Existing virtual synchronous machine control typically employs fixed inertia and fixed damping, or adjusts inertia solely based on frequency deviation and rate of change, without fully considering the coupling relationship between commutation margin, power angle dynamics, and control parameters. When the virtual inertia is too large, it can delay power angle adjustment, leading to a wider commutation voltage phase shift and insufficient actual commutation voltage-time integral area, increasing the risk of commutation failure. Conversely, when the virtual inertia is too small, it weakens frequency support capability. Furthermore, adjusting inertia alone makes it difficult to simultaneously address power oscillation suppression and rapid recovery after commutation. Moreover, when the commutation voltage phase changes abruptly, relying solely on power angle feedback control results in response lag, leading to a higher risk of commutation failure. Summary of the Invention

[0004] In view of this, in order to solve the above-mentioned technical problems, the present invention provides a method, system, device, medium and product for virtual inertia cooperative optimization based on commutation margin.

[0005] The first aspect of this invention provides a virtual inertia cooperative optimization method based on commutation margin, the method comprising:

[0006] The commutation voltage and real-time power angle of the grid-type energy storage converter are obtained. The commutation margin is determined based on the commutation voltage, and the dynamic power angle index is determined based on the real-time power angle.

[0007] Based on the state change of the commutation voltage, the phase of the commutation voltage at the next moment is predicted, and the active power feedforward compensation amount is determined according to the predicted commutation voltage phase.

[0008] The dynamic inertia and commutation failure risk are determined based on the commutation margin and the power angle dynamic index, and the dynamic inertia and the preset reference damping coefficient are coordinated and adjusted according to the commutation failure risk to obtain the target inertia and the target damping coefficient.

[0009] The active power feedforward compensation is superimposed on the current active power control command of the grid-type energy storage converter, and the power angle trajectory of the grid-type energy storage converter is adjusted based on the superimposed active power control command, the target inertia, and the target damping coefficient.

[0010] In one example, determining the commutation margin based on the commutation voltage and determining the dynamic power angle index based on the real-time power angle includes:

[0011] Determine the commutation time interval of the grid-type energy storage converter, integrate the commutation voltage within the commutation time interval, and obtain the time integral area of ​​the actual commutation voltage.

[0012] Obtain the critical commutation area required to complete the current commutation process, and determine the commutation margin based on the ratio of the time integral area of ​​the actual commutation voltage to the critical commutation area;

[0013] The real-time power angle is differentially tracked using a second-order differential tracker to obtain the power angle change rate and the power angle second derivative. Based on the power angle change rate and the power angle second derivative, the power angle dynamic index is determined.

[0014] In one example, determining the commutation time interval of the grid-type energy storage converter and integrating the commutation voltage within the commutation time interval to obtain the time integral area of ​​the actual commutation voltage includes:

[0015] The commutation start time and commutation end time are determined based on the trigger pulse window or current commutation process of the grid-type energy storage converter.

[0016] Determine the line voltage between the two phases undergoing commutation, and use the line voltage between the two phases as the commutation voltage;

[0017] The time integral area of ​​the actual commutation voltage is obtained by integrating the commutation voltage between the start of commutation and the end of commutation.

[0018] In one example, the step of predicting the commutation voltage phase at the next moment based on the state change of the commutation voltage, and determining the active power feedforward compensation amount based on the predicted commutation voltage phase, includes:

[0019] The commutation voltage state parameters are constructed based on the voltage amplitude, angular frequency, and initial phase angle of the commutation voltage.

[0020] Based on the change in commutation voltage state between adjacent sampling times, the Kalman filter estimator is used to predict the commutation voltage state at the current time, and the predicted commutation voltage state at the next time is obtained.

[0021] The commutation voltage phase at the next moment is determined based on the angular frequency and initial phase angle in the predicted commutation voltage state.

[0022] The active power feedforward compensation amount is determined based on the predicted change in the commutation voltage phase.

[0023] In one example, determining the dynamic inertia and commutation failure risk based on the commutation margin and the power angle dynamic index, and coordinating the adjustment of the dynamic inertia and the preset reference damping coefficient based on the commutation failure risk, includes:

[0024] Determine the margin difference between the commutation margin and the lower limit of the safe commutation margin;

[0025] The degree of inertia decay is determined based on the relationship between the absolute value of the second derivative of the work angle and the margin difference.

[0026] The reference inertia is attenuated according to the stated degree of inertia attenuation to obtain the dynamic inertia;

[0027] The risk component of power angle change is determined based on the ratio between the power angle change rate and the maximum permissible power angle change rate.

[0028] Based on the relationship between the commutation margin and the commutation margin reference threshold, the commutation margin insufficiency risk component is determined;

[0029] The commutation failure risk is obtained by combining the power angle change risk component and the commutation margin insufficient risk component according to the preset risk weight.

[0030] The inertia risk adjustment factor is determined based on the commutation failure risk and the preset inertia adjustment weight, and the dynamic inertia is attenuated using the inertia risk adjustment factor to obtain the target inertia.

[0031] The damping risk adjustment factor is determined based on the commutation failure risk and the preset damping adjustment weight, and the target damping coefficient is obtained by increasing the reference damping coefficient using the damping risk adjustment factor.

[0032] In one example, the step of superimposing the active power feedforward compensation amount onto the current active power control command of the grid-type energy storage converter, and adjusting the power angle trajectory of the grid-type energy storage converter based on the superimposed active power control command, the target inertia, and the target damping coefficient, includes:

[0033] Obtain the current active power control command output by the active power control loop of the grid-type energy storage converter;

[0034] The active power feedforward compensation amount is superimposed with the current active power control command to obtain the target active power control command;

[0035] The target inertia and the target damping coefficient are used to update the inertia parameters and damping parameters in the virtual synchronous machine control process, respectively.

[0036] The voltage phase reference value of the grid-type energy storage converter is determined based on the target active power control command, the updated inertia parameters and damping parameters, and the power angle trajectory of the grid-type energy storage converter is adjusted based on the voltage phase reference value.

[0037] Secondly, the present invention also provides a virtual inertia cooperative optimization system based on commutation margin, the system comprising:

[0038] The index determination module is used to obtain the commutation voltage and real-time power angle of the grid-type energy storage converter, determine the commutation margin based on the commutation voltage, and determine the dynamic index of the power angle based on the real-time power angle.

[0039] The active power feedforward compensation module is used to predict the commutation voltage phase at the next moment based on the state change of the commutation voltage, and determine the active power feedforward compensation amount according to the predicted commutation voltage phase.

[0040] The inertia adjustment module is used to determine the dynamic inertia and commutation failure risk based on the commutation margin and the power angle dynamic index, and to coordinately adjust the dynamic inertia and the preset reference damping coefficient based on the commutation failure risk to obtain the target inertia and the target damping coefficient.

[0041] The power angle adjustment module is used to superimpose the active power feedforward compensation amount onto the current active power control command of the grid-type energy storage converter, and adjust the power angle trajectory of the grid-type energy storage converter based on the superimposed active power control command, the target inertia and the target damping coefficient.

[0042] 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 virtual inertia cooperative optimization method based on commutation margin as described in the first aspect.

[0043] 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 virtual inertia cooperative optimization method based on commutation margin as described in the first aspect.

[0044] Fifthly, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein, when the program instructions are executed by a computer, the computer performs the steps of the virtual inertia cooperative optimization method based on commutation margin as described in the first aspect.

[0045] As can be seen from the above technical solutions, this invention, by acquiring the commutation voltage and real-time power angle, can simultaneously grasp the actual volt-second area of ​​the commutation process and the power angle motion state of the grid-type energy storage converter, and thereby determine the commutation margin, dynamic inertia, and commutation failure risk. By predicting the commutation voltage phase at the next moment and forming active power feedforward compensation, the active power control command can be corrected in advance before the power angle feedback error is fully formed. By coordinating the adjustment of dynamic inertia and reference damping coefficient through commutation failure risk, the inertia can be reduced to accelerate power angle recovery when the commutation risk increases, while the damping can be increased to suppress power oscillation. Thus, by applying the active power feedforward compensation, target inertia, and target damping coefficient together to the power angle trajectory of the virtual synchronous machine, the grid-type energy storage converter is no longer constrained by the slow response of fixed inertia and the limited adjustment capability of a single parameter during a fault. While maintaining the normal operating frequency support capability, it improves the power angle's following and recovery speed to voltage phase changes, thereby reducing the commutation failure risk and improving the stability recovery after a fault. Attached Figure Description

[0046] 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.

[0047] Figure 1 An application environment diagram for a virtual inertia collaborative optimization method based on commutation margin provided in an embodiment of the present invention;

[0048] Figure 2 A flowchart illustrating a virtual inertia collaborative optimization method based on commutation margin, provided for an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of a virtual inertia collaborative optimization system based on commutation margin provided in an embodiment of the present invention;

[0050] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0051] 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.

[0052] The virtual inertia cooperative optimization method based on commutation margin provided in this application can be applied to, for example... Figure 1 The application environment shown is illustrated. 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 it can be located in the cloud or on another network server. Terminal 101 or server 102 executes a virtual inertia collaborative optimization method based on commutation margin. The method includes: acquiring the commutation voltage and real-time power angle of the grid-type energy storage converter; determining the commutation margin based on the commutation voltage; determining the power angle dynamic index based on the real-time power angle; predicting the commutation voltage phase at the next moment based on the state change of the commutation voltage; determining the active power feedforward compensation amount based on the predicted commutation voltage phase; determining the dynamic inertia and commutation failure risk based on the commutation margin and the power angle dynamic index; and coordinating the dynamic inertia and the preset reference damping coefficient based on the commutation failure risk to obtain the target inertia and the target damping coefficient; superimposing the active power feedforward compensation amount onto the current active power control command of the grid-type energy storage converter; and adjusting the power angle trajectory of the grid-type energy storage converter based on the superimposed active power control command, the target inertia, and the target damping coefficient.

[0053] Terminal 101 can be, but is not limited to, various personal computers, laptops, smartphones, and tablets.

[0054] 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.

[0055] like Figure 2 As shown, this application provides a virtual inertia cooperative optimization method based on commutation margin, which is applied to... Figure 1 Taking terminal 101 or server 102 as an example, the explanation includes the following steps S1 to S4. Wherein:

[0056] Step S1: Obtain the commutation voltage and real-time power angle of the grid-type energy storage converter, determine the commutation margin based on the commutation voltage, and determine the dynamic power angle index based on the real-time power angle.

[0057] A grid-connected energy storage converter is an energy storage converter that can autonomously generate voltage amplitude and voltage phase references within its control system and exhibit external voltage source characteristics through virtual synchronous machine control. Compared with grid-following converters that rely on grid voltage phase for tracking control, grid-connected energy storage converters can utilize virtual inertia and virtual damping to simulate the rotor motion process of a synchronous generator, providing frequency and voltage support to the grid.

[0058] In this embodiment, the commutation voltage refers to the voltage that drives the current to transfer from the current conducting phase or branch to the target conducting phase or branch during the current commutation process. For example, when the current transfers from phase a to phase b, the line voltage between phase a and phase b can be... As commutation voltage When current shifts between two other phases, the commutation voltage becomes the line voltage between the corresponding two phases.

[0059] Real-time power angle refers to the phase angle difference between the internal voltage vector of a grid-connected energy storage converter and the reference voltage vector on the grid side. This power angle reflects the dynamic relationship between the converter's output power and the grid's operating status.

[0060] Commutation margin is a core indicator for measuring whether the commutation process can be completed smoothly. It characterizes the extent to which the commutation energy provided by the commutation voltage during the commutation process is sufficient compared to the minimum energy required to complete the commutation. The lower the commutation margin, the higher the risk of commutation failure. Dynamic power angle indicators describe the dynamic trend of the current power angle and can reflect the severity of system power oscillations, such as the rate of change of power angle and the second derivative of power angle.

[0061] Step S2: Predict the commutation voltage phase at the next moment based on the state change of the commutation voltage, and determine the active power feedforward compensation amount based on the predicted commutation voltage phase.

[0062] Under grid fault conditions or weak grid operation, the voltage at the point of common coupling may experience sudden amplitude drops, frequency shifts, or phase jumps. If feedback adjustment is only performed based on the power angle deviation after the phase shift has already occurred, the feedback control process may be delayed by virtual inertia, making it impossible to correct the power angle trajectory in a timely manner. Therefore, this embodiment predicts the amplitude, angular frequency, and initial phase angle of the commutation voltage to generate active power feedforward compensation before the actual arrival of the commutation voltage phase at the next moment.

[0063] In this embodiment, the commutation voltage state does not refer to a single voltage sample value, but rather to a state quantity that can characterize the sinusoidal waveform variation of the commutation voltage. By predicting the state quantity, a relatively smooth commutation voltage phase prediction result can be obtained even in the presence of measurement noise and voltage distortion.

[0064] Step S3: Determine the dynamic inertia and commutation failure risk based on the commutation margin and dynamic power angle index, and adjust the dynamic inertia and the preset reference damping coefficient in a coordinated manner according to the commutation failure risk to obtain the target inertia and target damping coefficient.

[0065] Virtual inertia is used to simulate the inertial response of a synchronous generator rotor to power imbalance. When the virtual inertia is large, the frequency and power angle change more slowly to short-term power disturbances, which is beneficial for suppressing frequency abrupt changes, but may also prevent the power angle from falling back in time during a fault. When the virtual inertia is small, the power angle responds faster to power adjustments, but too small a virtual inertia may reduce frequency support capability.

[0066] Virtual damping is used to simulate the damping torque of a synchronous generator, and its main function is to suppress the reciprocating oscillations of the power angle and active power. If the damping coefficient is too small, the power angle may oscillate continuously after a fault; if the damping coefficient is too large, it may excessively restrict the power angle movement and prolong the recovery time. Therefore, this embodiment does not adjust the inertia or damping separately, but first obtains the dynamic inertia based on the commutation margin and the second derivative of the power angle, and then performs a second coordinated correction on the dynamic inertia and the reference damping coefficient based on the comprehensive commutation failure risk.

[0067] Step S4: Add the active power feedforward compensation to the current active power control command of the grid-type energy storage converter, and adjust the power angle trajectory of the grid-type energy storage converter based on the added active power control command, target inertia and target damping coefficient.

[0068] The current active power control command is the power reference value output by the active power control loop of the grid-type energy storage converter when no commutation voltage phase feedforward compensation is added. This active power control loop may include frequency droop control, virtual synchronous machine power-frequency control, or upper-level energy management control.

[0069] First, the current active power control command is obtained, and the active power feedforward compensation obtained in step S2 is superimposed on the current active power control command to obtain the target active power control command. The superposition method can be executed according to the predefined positive power direction. When the active power feedforward compensation is positive, it indicates that the active power reference is increased under the current power direction definition; when the active power feedforward compensation is negative, it indicates that the active power reference is decreased.

[0070] The role of active power feedforward compensation is to change the power input of the virtual synchronous machine in advance, rather than directly replacing the original active power control loop. During normal operation, the predicted commutation voltage phase change is small, the active power feedforward compensation is close to zero, and the grid-type energy storage converter mainly operates according to the original active power control command. When a phase jump or fault occurs, the active power feedforward compensation increases to quickly correct the current active power control command.

[0071] The power angle trajectory is the motion trajectory formed by the change of the phase difference between the output voltage phase of the grid-type energy storage converter and the grid voltage over time. The change of the power angle trajectory directly reflects the power balance and stability of the system. In this embodiment, by changing the voltage phase reference value, the power angle is corrected according to the preset stability target, avoiding the continuous increase of the power angle that may cause commutation failure or system instability. While suppressing power oscillation, it accelerates the speed at which the power angle recovers to the stable range.

[0072] After power angle trajectory adjustment, the commutation voltage and real-time power angle are reacquired in the next control time step, and the commutation margin is recalculated. If the time integral area of ​​the commutation voltage recovers, the commutation margin gradually increases, the risk of commutation failure decreases, the target inertia gradually recovers to the reference inertia, the target damping coefficient gradually recovers to the reference damping coefficient, and the active power feedforward compensation also decreases with the predicted phase change. Thus, a closed-loop process is formed to smoothly recover from the fault risk adjustment state to the normal frequency support state.

[0073] This application, by acquiring commutation voltage and real-time power angle, can simultaneously grasp the actual volt-second area during the commutation process and the power angle motion state of the grid-type energy storage converter, thereby determining the commutation margin, dynamic inertia, and commutation failure risk. By predicting the commutation voltage phase at the next moment and forming active power feedforward compensation, the active power control command can be corrected in advance before the power angle feedback error fully forms. By coordinating the adjustment of dynamic inertia and reference damping coefficient based on commutation failure risk, the inertia can be reduced to accelerate power angle recovery when the commutation risk increases, while the damping can be increased to suppress power oscillation. Thus, the active power feedforward compensation, target inertia, and target damping coefficient are applied together to the power angle trajectory of the virtual synchronous machine, so that the grid-type energy storage converter is no longer constrained by the slow response of fixed inertia and the limited adjustment capability of a single parameter during faults. While maintaining the normal operating frequency support capability, it improves the power angle's following and recovery speed of voltage phase changes, thereby reducing the commutation failure risk and improving the stable recovery performance after a fault.

[0074] In some embodiments, determining the commutation margin based on the commutation voltage and the dynamic index of the power angle based on the real-time power angle includes: determining the commutation time interval of the grid-type energy storage converter; integrating the commutation voltage within the commutation time interval to obtain the time integral area of ​​the actual commutation voltage; obtaining the critical commutation area required to complete the current commutation process; determining the commutation margin based on the ratio between the time integral area of ​​the actual commutation voltage and the critical commutation area; performing differential tracking processing on the real-time power angle using a second-order differential tracker to obtain the power angle change rate and the second derivative of the power angle; and determining the dynamic index of the power angle based on the power angle change rate and the second derivative of the power angle.

[0075] The commutation time interval refers to the time range from the start to the end of commutation. The start time of commutation can be determined based on the moment when the converter sends a trigger pulse to the target switching device, or based on the moment when the target phase current begins to rise and the original conducting phase current begins to fall. The end time of commutation can be determined based on the moment when the original conducting phase current drops to a preset threshold, the moment when the target phase current reaches a preset steady-state value, or the moment when the commutation overlap process ends.

[0076] In some embodiments, determining the commutation time interval of the grid-type energy storage converter and integrating the commutation voltage within the commutation time interval to obtain the time integration area of ​​the actual commutation voltage includes: determining the commutation start time and commutation end time based on the trigger pulse window or current commutation process of the grid-type energy storage converter; determining the line voltage between the two phases undergoing commutation and using the line voltage between the two phases as the commutation voltage; and integrating the commutation voltage from the commutation start time to the commutation end time to obtain the time integration area of ​​the actual commutation voltage.

[0077] In one implementation, the commutation start time is set to... The commutation overlap angle is The angular frequency during the commutation process is Then the commutation end time can be expressed as:

[0078]

[0079] Within the commutation time interval, the commutation voltage is integrated over time to obtain the time integral area of ​​the actual commutation voltage. :

[0080]

[0081] in, The time integral area of ​​the actual commutation voltage can be expressed in volt-seconds (V·s). This represents the instantaneous commutation voltage within the commutation time interval; Indicates the moment when commutation begins; Indicates the commutation overlap angle; This represents the angular frequency corresponding to the commutation process.

[0082] The time integral area of ​​the actual commutation voltage is used to characterize the volt-second area that can actually be provided during the current commutation process. The higher the commutation voltage amplitude or the longer the effective commutation duration, the larger the time integral area of ​​the actual commutation voltage. When the power grid experiences voltage dips, phase jumps, or voltage waveform distortions, the effective amplitude or effective duration of the commutation voltage may decrease, thus leading to a decrease in the time integral area of ​​the actual commutation voltage.

[0083] To reduce the impact of voltage harmonics, measurement noise, and instantaneous spikes on the integration results, the acquired commutation voltage can be first processed by low-pass filtering, band-pass filtering, or moving average, and then the filtered commutation voltage can be integrated. Filtering is mainly used to retain the fundamental or target frequency components that drive the commutation process without changing the main phase change trend of the commutation voltage.

[0084] For example, during the current transfer from phase a to phase b, the controller records the current time as after detecting the phase b trigger pulse. And continuously collect line voltage When the phase a current is detected to drop to the commutation end threshold, this moment is recorded as... Then calculate to The integral value of the line voltage during the period is used to obtain the actual commutation voltage time integral area of ​​the current commutation process.

[0085] Critical commutation area The critical commutation area refers to the minimum voltage-time integral area required to complete the commutation process under current operating conditions. The critical commutation area can be pre-calculated based on parameters such as DC current command, commutation circuit inductance, or commutator transformer leakage reactance, or can be set through offline simulation. Generally, the larger the DC current or the larger the equivalent inductance of the commutation circuit, the larger the volt-second area required to complete the current transfer, and the larger the corresponding critical commutation area.

[0086] In one implementation, a critical commutation area lookup table can be established for different DC currents and commutation circuit equivalent reactances. Each entry in the lookup table corresponds to a set of DC current intervals, commutation circuit equivalent reactance intervals, and critical commutation areas. During real-time operation, adjacent entries are looked up based on the current DC current command and the current commutation circuit equivalent reactance, and the critical commutation area corresponding to the current operating condition is obtained through interpolation.

[0087] Commutation margin Determined according to the following formula:

[0088]

[0089] in, Indicates commutation margin; This represents the time integral area of ​​the commutation voltage actually obtained during the current commutation process; This represents the critical commutation area required to complete the commutation.

[0090] When the commutation margin is greater than 1, it indicates that the actual commutation area is higher than the critical area required to complete commutation, and the commutation process has a certain margin of safety. When the commutation margin is close to 1, it indicates that the current commutation process is approaching the commutation safety boundary. When the commutation margin is less than or equal to 1, it indicates that the actual commutation area may be insufficient, and there is a risk of commutation failure. In engineering applications, to avoid the controller only taking adjustment measures when the commutation margin is close to 1, the lower limit of the safe commutation margin can be set to a value greater than 1, such as 1.2 to 1.5. Therefore, the inertia can be reduced or the damping increased before the actual commutation area decreases to the critical area.

[0091] The phase-locked loop or virtual synchronous machine phase generation unit outputs the real-time power angle. Then, the second-order differential tracker continuously tracks the real-time power angle and outputs the first and second derivatives of the power angle:

[0092]

[0093]

[0094] in, This represents the rate of change of the work angle, used to characterize the speed at which the work angle changes relative to time. It represents the second derivative of the work angle, used to characterize the rate of change of the work angle, that is, the degree of acceleration of the work angle.

[0095] The power angle change rate can also be based on the real-time angular frequency of the grid-type energy storage converter. With the rated angular frequency Determine the difference between them:

[0096]

[0097] in, It can be obtained from the internal frequency state variables of a frequency-locked loop, a phase-locked loop, or a virtual synchronous machine; This is the rated angular frequency. When the rated frequency of the power grid is 50Hz, the rated angular frequency can be taken as... .

[0098] The second-order differential tracker does not simply perform two differences between adjacent sampled values. Instead, it smooths the input power angle by tracking the state, reducing the amplification of measurement noise through differential operations. The rate of change of power angle is mainly used to determine whether the power angle is rapidly approaching the commutation limit, while the second derivative of the power angle is mainly used to determine whether the power angle is in the acceleration opening phase. Both constitute the dynamic power angle index, but their uses in subsequent control differ: the second derivative of the power angle and the commutation margin are used together to calculate dynamic inertia, while the rate of change of power angle and the commutation margin are used together to calculate the risk of commutation failure.

[0099] For example, when the rate of change of the power angle is positive and the second derivative of the power angle is positive, it indicates that the power angle is not only increasing, but the rate of increase is also accelerating, and the power angle may be rapidly approaching the commutation safety boundary. When the rate of change of the power angle is positive and the second derivative of the power angle is negative, it indicates that the power angle is still increasing, but the rate of increase has slowed down, and the system may be entering the recovery phase. By simultaneously utilizing first-order and second-order dynamic information, the acceleration and recovery phases of the power angle can be distinguished more accurately than using only the frequency deviation.

[0100] Through the above process, the physical safety quantity and power angle motion state quantity of the commutation process can be obtained simultaneously, providing a unified input for subsequent dynamic inertia calculation and commutation failure risk assessment, avoiding the problem of not being able to directly perceive the commutation safety state by adjusting the inertia only based on the frequency deviation.

[0101] In some embodiments, predicting the commutation voltage phase at the next moment based on the state change of the commutation voltage, and determining the active power feedforward compensation amount based on the predicted commutation voltage phase, includes: constructing a commutation voltage state quantity based on the voltage amplitude, angular frequency, and initial phase angle of the commutation voltage; using a Kalman filter estimator to infer the commutation voltage state quantity at the current moment based on the commutation voltage state change between adjacent sampling moments to obtain the predicted commutation voltage state at the next moment; determining the commutation voltage phase at the next moment based on the angular frequency and initial phase angle in the predicted commutation voltage state; and determining the active power feedforward compensation amount based on the change in the predicted commutation voltage phase.

[0102] The commutation voltage is approximated as a sinusoidal signal with slowly varying amplitude, frequency, and phase, and the following commutation voltage state vector is constructed:

[0103]

[0104] in, Indicates the first Commutation voltage state quantity at each sampling time; Indicates the commutation voltage amplitude; Indicates the commutation voltage angular frequency; It represents the initial phase angle of the commutation voltage; the superscript T indicates vector transpose.

[0105] The commutation voltage amplitude can be estimated from the commutation voltage collected by the voltage transformer, or it can be provided by the voltage amplitude status quantity of the converter voltage control loop. The angular frequency can be provided by the frequency status quantity of the frequency-locked loop, phase-locked loop, or virtual synchronous machine. The initial phase angle can be estimated from the current sampled value, amplitude, and angular frequency of the commutation voltage, or it can be provided by the phase output of the phase-locked loop.

[0106] Under normal operating conditions, the commutation voltage amplitude, angular frequency, and initial phase angle typically change continuously between adjacent sampling times; however, these state variables may change rapidly during a fault. Incorporating these three state components into the state vector helps to distinguish the different effects of voltage amplitude decrease, frequency shift, and phase jump on the commutation voltage waveform.

[0107] This embodiment uses a constant-rate prediction model to describe the commutation voltage state change between adjacent sampling times, and its state transition equation can be expressed as:

[0108]

[0109] in, This represents the commutation voltage state quantity at the previous sampling time. This represents the commutation voltage state quantity at the current sampling moment; Represents the state transition matrix; This represents model noise.

[0110] The state transition matrix can be represented as:

[0111]

[0112] in, This represents the sampling period. The state transition matrix indicates that within a short sampling period, the commutation voltage amplitude and angular frequency remain approximately constant, while the initial phase angle continues to accumulate according to the current angular frequency. Model noise is used to characterize the random deviations in amplitude, angular frequency, and phase relative to the constant-velocity model during actual operation.

[0113] Model noise can be represented as a random quantity that follows a zero-mean Gaussian distribution:

[0114]

[0115] in, This represents the model noise covariance matrix. The model noise covariance matrix can be set as a diagonal matrix, with each diagonal element representing the degree of random variation in the commutation voltage amplitude, angular frequency, and initial phase angle, respectively. When the power grid is operating relatively stably, the model noise covariance can be appropriately reduced to make the prediction results smoother; during power grid faults, the model noise of relevant state components can be appropriately increased to improve the speed at which state estimation tracks abrupt changes.

[0116] In the Before obtaining the actual commutation voltage measurement value at the sampling time, the first sampling time is used... The optimal state estimate at each sampling time is used for one-step prediction:

[0117]

[0118] in, Indicates according to the first The measured values ​​at each sampling time complete the optimal state of the corrected commutation voltage; Indicates obtaining the first The prior state of the commutation voltage obtained before the actual measurement value at each sampling time.

[0119] The prior state of commutation voltage includes the following three components:

[0120]

[0121] in, This indicates the predicted commutation voltage amplitude; Indicates the predicted angular frequency; This indicates the predicted initial phase angle.

[0122] The commutation voltage observation model can be expressed as:

[0123]

[0124] in, Indicates the first The commutation voltage measurement value at each sampling time; This represents a nonlinear observation function that maps commutation voltage state variables to instantaneous voltage values. This indicates measurement noise.

[0125] Measurement noise can be expressed as:

[0126]

[0127] in, The variance of measurement noise can be determined based on the measurement accuracy of the voltage transformer, the quantization error of the sampling device, and the level of electromagnetic interference at the site.

[0128] Calculate the predicted observation value at the current sampling time based on the prior state of the commutation voltage:

[0129]

[0130] Specifically:

[0131]

[0132] in, Indicates the first Each sampling time; This represents the predicted commutation voltage value at the current moment, obtained based on the state prediction model.

[0133] The commutation voltage measured at the current moment Compared with observed and predicted values By comparison, the measurement residuals are obtained:

[0134]

[0135] The measurement residual reflects the difference between the state prediction model and the actual commutation voltage. When the power grid is operating smoothly, the measurement residual is usually small; when the commutation voltage experiences a phase jump, a sudden drop in amplitude, or other changes that are not fully described by the constant-rate model, the measurement residual increases accordingly.

[0136] Kalman gain The model noise covariance is determined in real time based on the prediction error covariance, model noise covariance, and measurement noise covariance, and is used to balance the model prediction results with the actual measurement results. When the measurement noise is low, it can enhance the role of the measurement residual in state correction; when the measurement noise is high, it can enhance the role of the state prediction model in the estimation process.

[0137] The predicted commutation voltage can be corrected using the following formula:

[0138]

[0139] in, This represents the predicted commutation voltage at a future time. This represents the model prediction component extrapolated from the current commutation voltage state to future times; Indicates Kalman gain; This represents the measurement residual.

[0140] In practical Kalman filtering, the commutated voltage state vector can be corrected first using the measurement residual and Kalman gain, and then extrapolated to the next sampling time using the corrected amplitude, angular frequency, and initial phase angle. The above formula can be understood as the equivalent expression of this state update and future extrapolation process at the voltage output level.

[0141] By measuring residual correction, the prediction process can remain smooth during normal operation and quickly track the actual state when there are sudden changes in voltage phase or amplitude, avoiding the amplification of high-frequency interference by directly differentiating the noisy instantaneous voltage or phase-locked loop phase.

[0142] The predicted commutation voltage state includes the predicted angular frequency and predicted initial phase angle for the next moment. Therefore, the predicted phase corresponding to the commutation voltage at the next moment can be determined based on these two values. The predicted phase is denoted as... The predicted phase is represented as:

[0143]

[0144] in, This represents the phase angle extracted from the predicted commutated voltage phasor. In practice, the predicted phase can be directly determined from the predicted angular frequency and the predicted initial phase angle output by the Kalman filter, or the corresponding complex voltage phasor can be constructed first, and then the phase angle can be extracted.

[0145] The predicted phase reflects the position where the commutation voltage phase may reach at the next control moment. When a phase jump occurs in the grid-side voltage, the predicted phase will reflect the change before the traditional power angle feedback loop, thus providing an advance for active power feedforward compensation.

[0146] The active power feedforward compensation is calculated according to the following formula:

[0147]

[0148] in, Indicates the amount of active power feedforward compensation; This represents the active power compensation coefficient; Indicates the predicted commutation voltage phase; This represents the rate of change of the predicted phase relative to time; This indicates the DC bus voltage of a grid-type energy storage converter.

[0149] Active power compensation coefficient The small-signal stability analysis can be performed based on the inner current loop bandwidth, DC bus voltage dynamic characteristics, and outer loop dynamic characteristics of the virtual synchronous machine of the grid-type energy storage converter. Specifically, a closed-loop small-signal model including the active power feedforward channel can be established, and an active power compensation coefficient that keeps the damping ratio of the closed-loop system within the range of 0.6 to 0.8 can be selected to improve the feedforward response speed while avoiding the induction of new power oscillations.

[0150] The active power feedforward compensation is directly superimposed on the original active power control command of the virtual synchronous machine. When the predicted phase indicates that the commutation voltage is about to shift rapidly in a direction unfavorable to commutation, the active power feedforward channel changes the active power output trend of the converter in advance, allowing the virtual synchronous machine's power angle to begin adjusting before the feedback error has fully formed. This process can reduce the feedback response lag caused by the large virtual inertia.

[0151] In some embodiments, dynamic inertia and commutation failure risk are determined based on commutation margin and dynamic power angle index, and the dynamic inertia and a preset reference damping coefficient are coordinated and adjusted according to the commutation failure risk, including: determining the margin difference between the commutation margin and the lower limit of the safe commutation margin; determining the degree of inertia attenuation based on the relationship between the absolute value of the second derivative of the power angle and the margin difference; attenuating the reference inertia according to the degree of inertia attenuation to obtain the dynamic inertia; determining the power angle change risk component based on the ratio between the power angle change rate and the maximum allowable power angle change rate; and adjusting the dynamic inertia and a preset reference damping coefficient according to the commutation margin. The relationship between the degree and the commutation margin reference threshold is used to determine the commutation margin insufficient risk component; the power angle change risk component and the commutation margin insufficient risk component are combined according to preset risk weights to obtain the commutation failure risk; the inertia risk adjustment factor is determined based on the commutation failure risk and the preset inertia adjustment weight, and the dynamic inertia is attenuated using the inertia risk adjustment factor to obtain the target inertia; the damping risk adjustment factor is determined based on the commutation failure risk and the preset damping adjustment weight, and the benchmark damping coefficient is increased using the damping risk adjustment factor to obtain the target damping coefficient.

[0152] Safety commutation margin lower limit The safety boundary used to represent the start-up inertia decay is determined based on the commutation characteristics, protection requirements, and operating experience of the grid-type energy storage converter; for example, it can be taken as 1.2 to 1.5. The margin difference between the commutation margin and the lower limit of the safe commutation margin can be expressed as:

[0153]

[0154] When the margin difference is large, it indicates that the current commutation state is far from the lower limit of the safe commutation margin, which can keep the dynamic inertia close to the reference inertia; when the margin difference gradually decreases, it indicates that the current commutation safety margin is reduced, and the degree of inertia decay needs to be increased.

[0155] Dynamic inertia can be calculated using the following formula:

[0156]

[0157] in, Represents dynamic inertia; Indicates the reference inertia; This represents the inertia adjustment gain, and ; This represents the second derivative of the work angle; Indicates commutation margin; This indicates the lower limit of the safety commutation margin.

[0158] This formula maps the acceleration of the power angle and the commutation safety margin to the dynamic inertia through an exponential decay relationship. When the absolute value of the second derivative of the power angle is small and the commutation margin is sufficient, the exponential term is close to zero, and the dynamic inertia is close to the reference inertia, thus maintaining the normal frequency support capability of the grid-type energy storage converter. When the absolute value of the second derivative of the power angle increases or the commutation margin approaches the lower limit of the safe commutation margin, the absolute value of the exponential term increases, and the dynamic inertia decreases rapidly, enabling the power angle to respond more quickly to active power adjustments and return to the commutation safety region.

[0159] Reference inertia The default virtual inertia of the grid-type energy storage converter can be used, or it can be calculated based on the rated capacity of the energy storage system and the inertial constant of a typical synchronous generator:

[0160]

[0161] in, Indicates the preset inertia constant; Indicates the system's reference power; This represents the synchronization angular frequency. This conversion method matches the virtual inertia with the energy storage system capacity and the target inertial response level.

[0162] Inertia Adjustment Gain Tuning can be performed through step disturbance simulation or fault ride-through simulation. Specifically, it can be gradually adjusted under preset short-circuit, voltage sag, or phase jump conditions. This ensures that the peak value of the first swing angle does not exceed the preset commutation limit angle, and a certain safety margin is retained based on this setting value.

[0163] For example, when the commutation margin is sufficient and the power angular acceleration is small, the dynamic inertia remains close to The grid-type energy storage converter maintains a strong frequency support capability. When a short-circuit fault causes the power angle to open rapidly, and the commutation margin decreases to near the lower limit of the safe commutation margin, the dynamic inertia decreases rapidly, enabling the power angle to respond more quickly to the active feedforward compensation and power difference, and avoiding further delay in power angle recovery due to excessive inertia.

[0164] Maximum permissible rate of change of work angle This parameter is used to characterize the maximum allowable rate of change of the power angle while meeting commutation safety requirements. It can be predetermined based on the rated DC current, minimum allowable commutation voltage, commutation limit angle, and transient simulation results of the converter.

[0165] The risk component of power angle variation can be represented by the ratio between the absolute value of the power angle variation rate and the maximum permissible power angle variation rate:

[0166]

[0167] When the ratio is small, it indicates that the power angle change rate is far from the maximum allowable value; when the ratio is close to or exceeds 1, it indicates that the power angle is rapidly approaching or has exceeded the preset change rate boundary, and the possibility of the power angle crossing the commutation safety zone increases.

[0168] Using the absolute value of the rate of change of the power angle, the risks posed by rapid changes in the power angle along both positive and negative directions can be evaluated simultaneously. In practical implementation, the current direction of the power angle can also be considered to determine whether to increase the risk weight only for the direction of change that moves the power angle away from the safe zone.

[0169] Commutation margin reference threshold This reference point is used to determine when the risk of insufficient commutation margin begins to increase significantly. Its value can be greater than the commutation critical value of 1, for example, it can be 1.3. Setting the commutation margin reference threshold to be greater than 1 can identify the risk in advance before the actual commutation area has decreased to the critical commutation area.

[0170] The risk component of insufficient commutation margin can be expressed as:

[0171]

[0172] When the commutation margin is close to the commutation margin reference threshold, the risk component is small; as the commutation margin decreases, the risk component gradually increases, indicating that the current actual commutation area is less than the reference safe area.

[0173] The commutation margin deficiency risk component originates directly from the volt-second integral of the commutation voltage, thus reflecting the combined impact of voltage dips, phase jumps, and shortened commutation time on commutation safety. Compared to using only voltage amplitude as a risk indicator, this risk component considers both the commutation voltage amplitude and the effective duration.

[0174] The risk of commutation failure can be calculated using the following formula:

[0175]

[0176] in, This indicates the risk of commutation failure; Indicates the rate of change of the work angle; Indicates the maximum permissible rate of change of the work angle; Indicates commutation margin; This indicates the commutation margin reference threshold; and This represents the risk weighting factor.

[0177] In one implementation, it can be taken , This makes the risk of commutation failure more sensitive to the degree of insufficient commutation margin. The reason is that the rate of change of the power angle reflects the trend of the power angle approaching the commutation boundary, while the commutation margin directly reflects whether the actual usable commutation area is sufficient. Therefore, it can be improved by having a larger [percentage missing]. The impact of increasing commutation margin in risk assessment.

[0178] Commutation failure risk can be understood as a combined result of the risks of rapid changes in power angle and insufficient commutation area. The risk of commutation failure increases significantly only when the power angle changes rapidly and the commutation margin decreases; when the power angle changes slowly or the commutation margin is sufficient, the risk of commutation failure remains at a low level. Therefore, it is possible to avoid frequent triggering of strong inertia and damping adjustments due to short-term fluctuations in a single voltage sample value.

[0179] For example, in the early stages of a fault, the commutation margin may not have decreased significantly, but the rate of change of the power angle has already increased rapidly, at which point the risk of commutation failure begins to rise. As the fault continues, the time integral area of ​​the commutation voltage decreases, further reducing the commutation margin and accelerating the increase in the risk of commutation failure. Based on this, the controller gradually increases the inertia decay and damping gain, without having to wait for an actual commutation failure to occur before taking remedial measures.

[0180] The dynamic inertia is further modified based on the commutation failure risk to obtain the target inertia:

[0181]

[0182] in, Indicates the target inertia; This represents the dynamic inertia obtained from the commutation margin and the second derivative of the power angle. Indicates the inertia adjustment weight; This indicates the risk of commutation failure.

[0183] The target damping coefficient is determined according to the following formula:

[0184]

[0185] in, Indicates the target damping coefficient; Indicates the reference damping coefficient; This indicates the damping adjustment weight.

[0186] The first decay of dynamic inertia is mainly determined by the power angle acceleration and commutation margin, used to improve the power angle response speed when the power angle accelerates and the commutation safety margin decreases. The second correction of the target inertia is determined by the overall commutation failure risk, used to further consider the rate of change of power angle and the degree of insufficient commutation margin. Therefore, the target inertia is the result of the combined effect of commutation margin, the second derivative of power angle, and the rate of change of power angle.

[0187] When the risk of commutation failure increases, the target inertia decreases, enabling the power angle to respond more quickly to the target active power control command; the target damping coefficient increases, suppressing power oscillations during faults and the fault recovery phase. By simultaneously reducing inertia and increasing damping, it is possible to avoid significant oscillations caused by an excessively fast system response after only reducing inertia, and it is also possible to avoid the power angle recovery speed still being limited by a large inertia after only increasing damping.

[0188] Inertia Adjustment Weight and damping adjustment weight It can be tuned through offline simulation. Specifically, various voltage drop depths, fault durations, phase transition amplitudes, and grid short-circuit ratios can be set. Weighting parameters can be selected under the conditions that the target inertia is not lower than the minimum allowable inertia, the target damping does not exceed the maximum allowable damping, and the power angle does not exceed the commutation limit.

[0189] Reference damping coefficient The virtual damping coefficient used during normal operation of the grid-type energy storage converter can be taken. During normal operation, the risk of commutation failure is low, and the target damping coefficient is close to the reference damping coefficient; during a fault, the risk of commutation failure increases, and the target damping coefficient increases accordingly.

[0190] In one control mode implementation, the system can switch between normal operation mode and fault ride-through mode based on the commutation failure risk. When the commutation failure risk is below a preset risk threshold, the normal operation mode is maintained, with inertia and damping close to their respective reference values. When the commutation failure risk reaches or exceeds the preset risk threshold, the system enters fault ride-through mode, reducing the target inertia and increasing the target damping coefficient according to the risk value. During mode switching, the target inertia and target damping coefficient can be smoothly changed using a ramp function or a low-pass filter, reducing secondary transient shocks caused by sudden changes in control parameters.

[0191] In some embodiments, the active power feedforward compensation is superimposed on the current active power control command of the grid-type energy storage converter, and the power angle trajectory of the grid-type energy storage converter is adjusted based on the superimposed active power control command, the target inertia, and the target damping coefficient. This includes: acquiring the current active power control command output by the active power control loop of the grid-type energy storage converter; superimposing the active power feedforward compensation with the current active power control command to obtain the target active power control command; updating the inertia parameters and damping parameters in the virtual synchronous machine control process with the target inertia and the target damping coefficient, respectively; determining the voltage phase reference value of the grid-type energy storage converter according to the target active power control command, the updated inertia parameters, and the damping parameters, and adjusting the power angle trajectory of the grid-type energy storage converter according to the voltage phase reference value.

[0192] Specifically, first, the current active power control command is acquired, and then the active power feedforward compensation is superimposed on the current active power control command to obtain the target active power control command. The superposition method can be executed according to a pre-defined positive power direction. When the active power feedforward compensation is positive, it indicates that the active power reference is increased under the current power direction definition; when the active power feedforward compensation is negative, it indicates that the active power reference is decreased.

[0193] The role of active power feedforward compensation is to change the power input of the virtual synchronous machine in advance, rather than directly replacing the original active power control loop. During normal operation, the predicted commutation voltage phase change is small, the active power feedforward compensation is close to zero, and the grid-type energy storage converter mainly operates according to the original active power control command. When a phase jump or fault occurs, the active power feedforward compensation increases to quickly correct the current active power control command.

[0194] Subsequently, the target inertia and target damping coefficient are updated to the inertia and damping parameters used in the virtual synchronous machine control process, respectively. The updated inertia parameters determine the speed of power angle and frequency response power imbalance, while the updated damping parameters determine the degree of suppression of frequency deviation, power angle oscillation, or power oscillation.

[0195] The virtual synchronous machine controller calculates the virtual angular frequency and voltage phase reference values ​​based on the target active power control command, the actual output active power of the converter, the updated inertia parameters, and the updated damping parameters. Since the relevant virtual synchronous machine motion equations belong to the existing virtual synchronous machine control process, this embodiment does not change its basic power balance relationship. Instead, it replaces the fixed inertia and fixed damping with the target inertia and target damping coefficient, and replaces the target active power control command with an active power control command superimposed with feedforward compensation.

[0196] The voltage phase reference value is used to generate the modulation voltage or switching control signal for the grid-connected energy storage converter, thereby adjusting the AC terminal voltage phase of the converter. After the AC terminal voltage phase of the converter changes, its power angle relative to the grid voltage changes, further altering the active power output of the converter and the commutation voltage state in the next control time step. This adjusts the power angle trajectory of the grid-connected energy storage converter, further enhancing the safety of the commutation process and preventing commutation failure. The entire adjustment process adjusts the control parameters in real time based on the commutation margin and power angle change characteristics, enabling early response in the early stages of a fault. This preserves the frequency support capability of the grid-connected energy storage converter during normal operation while rapidly changing the response characteristics during a fault, preventing the power angle from continuously widening due to excessive inertia and insufficient damping. Ultimately, this achieves commutation failure prevention and improves the fault ride-through capability of the grid-connected energy storage converter after grid connection.

[0197] For example, during severe voltage dips, active power feedforward compensation is generated based on the predicted phase. A lower target inertia and a higher target damping coefficient are obtained based on a lower commutation margin, a larger power angle change rate, and the second derivative of the power angle. The target active power control command causes the converter to adjust its active power output in advance. The lower target inertia increases the power angle return speed, and the higher target damping coefficient suppresses power fluctuations during the return process. These three factors work together to shift the relationship between the power angle and the commutation voltage phase in a direction favorable to commutation.

[0198] Based on the same inventive concept, this application also provides a virtual inertia cooperative optimization system based on commutation margin for implementing the virtual inertia cooperative optimization method based on commutation margin mentioned above.

[0199] The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the virtual inertia cooperative optimization system based on commutation margin provided below can be found in the limitations of the virtual inertia cooperative optimization method based on commutation margin above, and will not be repeated here.

[0200] like Figure 3 As shown, this application provides a virtual inertia cooperative optimization system based on commutation margin, the system comprising:

[0201] The index determination module 100 is used to obtain the commutation voltage and real-time power angle of the grid-type energy storage converter, determine the commutation margin based on the commutation voltage, and determine the dynamic index of the power angle based on the real-time power angle.

[0202] The active power feedforward compensation module 200 is used to predict the commutation voltage phase at the next moment based on the state change of the commutation voltage, and to determine the active power feedforward compensation amount based on the predicted commutation voltage phase.

[0203] The inertia adjustment module 300 is used to determine the dynamic inertia and commutation failure risk based on the commutation margin and power angle dynamic index, and to coordinately adjust the dynamic inertia and the preset reference damping coefficient according to the commutation failure risk to obtain the target inertia and target damping coefficient.

[0204] The power angle adjustment module 400 is used to superimpose the active power feedforward compensation amount onto the current active power control command of the grid-type energy storage converter, and adjust the power angle trajectory of the grid-type energy storage converter based on the superimposed active power control command, target inertia and target damping coefficient.

[0205] In some embodiments, the indicator determination module 100 is configured to:

[0206] Determine the commutation time interval of the grid-type energy storage converter, integrate the commutation voltage within the commutation time interval, and obtain the time integral area of ​​the actual commutation voltage.

[0207] Obtain the critical commutation area required to complete the current commutation process, and determine the commutation margin based on the ratio of the time integral area of ​​the actual commutation voltage to the critical commutation area.

[0208] A second-order differential tracker is used to perform differential tracking processing on the real-time power angle to obtain the power angle change rate and the power angle second derivative. Based on the power angle change rate and the power angle second derivative, the power angle dynamic index is determined.

[0209] In some embodiments, the indicator determination module 100 is configured to:

[0210] The start and end times of commutation are determined based on the trigger pulse window or current commutation process of the grid-type energy storage converter.

[0211] Determine the line voltage between the two phases undergoing commutation, and use the line voltage between the two phases as the commutation voltage;

[0212] The time integral area of ​​the actual commutation voltage is obtained by integrating the commutation voltage from the start of commutation to the end of commutation.

[0213] In some embodiments, the active power feedforward compensation module 200 is used for:

[0214] The commutation voltage state variables are constructed based on the voltage amplitude, angular frequency, and initial phase angle of the commutation voltage.

[0215] Based on the change in commutation voltage state between adjacent sampling times, the Kalman filter estimator is used to predict the commutation voltage state at the current time, and the predicted commutation voltage state at the next time is obtained.

[0216] The commutation voltage phase at the next moment is determined based on the angular frequency and initial phase angle in the predicted commutation voltage state.

[0217] The active power feedforward compensation amount is determined based on the predicted changes in the commutation voltage phase.

[0218] In some embodiments, the inertia adjustment module 300 is used for:

[0219] Determine the margin difference between the commutation margin and the lower limit of the safe commutation margin;

[0220] The degree of inertia decay is determined based on the relationship between the absolute value of the second derivative of the work angle and the margin difference.

[0221] The reference inertia is attenuated according to the degree of inertia decay to obtain the dynamic inertia.

[0222] The risk component of power angle change is determined based on the ratio between the rate of change of power angle and the maximum permissible rate of change of power angle.

[0223] Based on the relationship between commutation margin and commutation margin reference threshold, determine the commutation margin insufficiency risk component;

[0224] The risk components of power angle change and insufficient commutation margin are combined according to the preset risk weights to obtain the commutation failure risk.

[0225] The inertia risk adjustment factor is determined based on the commutation failure risk and the preset inertia adjustment weight, and the dynamic inertia is attenuated using the inertia risk adjustment factor to obtain the target inertia.

[0226] The damping risk adjustment factor is determined based on the commutation failure risk and the preset damping adjustment weight, and the target damping coefficient is obtained by increasing the benchmark damping coefficient using the damping risk adjustment factor.

[0227] In some embodiments, the power angle adjustment module 400 is used for:

[0228] Obtain the current active power control command output by the active power control loop of the grid-type energy storage converter;

[0229] The active power feedforward compensation is superimposed with the current active power control command to obtain the target active power control command;

[0230] Update the inertia parameters and damping parameters in the virtual synchronous machine control process with the target inertia and target damping coefficient, respectively.

[0231] The voltage phase reference value of the grid-type energy storage converter is determined based on the target active power control command, the updated inertia parameters, and the damping parameters, and the power angle trajectory of the grid-type energy storage converter is adjusted according to the voltage phase reference value.

[0232] like Figure 4 As shown, this application provides an electronic device 10, which includes a memory 20 and a processor 30. The memory 20 stores a computer program, and when the computer program is executed by the processor 30, the processor 30 performs the following:

[0233] Obtain the commutation voltage and real-time power angle of the grid-type energy storage converter, determine the commutation margin based on the commutation voltage, and determine the dynamic power angle index based on the real-time power angle.

[0234] The commutation voltage phase at the next moment is predicted based on the state change of the commutation voltage, and the active power feedforward compensation amount is determined based on the predicted commutation voltage phase.

[0235] The dynamic inertia and commutation failure risk are determined based on the commutation margin and power angle dynamic index. The dynamic inertia and the preset reference damping coefficient are then coordinated and adjusted according to the commutation failure risk to obtain the target inertia and target damping coefficient.

[0236] The active power feedforward compensation is superimposed on the current active power control command of the grid-type energy storage converter, and the power angle trajectory of the grid-type energy storage converter is adjusted based on the superimposed active power control command, target inertia and target damping coefficient.

[0237] In some embodiments, when the computer program is executed by the processor 30, the processor 30 also performs:

[0238] Determine the commutation time interval of the grid-type energy storage converter, integrate the commutation voltage within the commutation time interval, and obtain the time integral area of ​​the actual commutation voltage.

[0239] Obtain the critical commutation area required to complete the current commutation process, and determine the commutation margin based on the ratio of the time integral area of ​​the actual commutation voltage to the critical commutation area.

[0240] A second-order differential tracker is used to perform differential tracking processing on the real-time power angle to obtain the power angle change rate and the power angle second derivative. Based on the power angle change rate and the power angle second derivative, the power angle dynamic index is determined.

[0241] In some embodiments, when the computer program is executed by the processor 30, the processor 30 also performs:

[0242] The start and end times of commutation are determined based on the trigger pulse window or current commutation process of the grid-type energy storage converter.

[0243] Determine the line voltage between the two phases undergoing commutation, and use the line voltage between the two phases as the commutation voltage;

[0244] The time integral area of ​​the actual commutation voltage is obtained by integrating the commutation voltage from the start of commutation to the end of commutation.

[0245] In some embodiments, when the computer program is executed by the processor 30, the processor 30 also performs:

[0246] The commutation voltage state variables are constructed based on the voltage amplitude, angular frequency, and initial phase angle of the commutation voltage.

[0247] Based on the change in commutation voltage state between adjacent sampling times, the Kalman filter estimator is used to predict the commutation voltage state at the current time, and the predicted commutation voltage state at the next time is obtained.

[0248] The commutation voltage phase at the next moment is determined based on the angular frequency and initial phase angle in the predicted commutation voltage state.

[0249] The active power feedforward compensation amount is determined based on the predicted changes in the commutation voltage phase.

[0250] In some embodiments, when the computer program is executed by the processor 30, the processor 30 also performs:

[0251] Determine the margin difference between the commutation margin and the lower limit of the safe commutation margin;

[0252] The degree of inertia decay is determined based on the relationship between the absolute value of the second derivative of the work angle and the margin difference.

[0253] The reference inertia is attenuated according to the degree of inertia decay to obtain the dynamic inertia.

[0254] The risk component of power angle change is determined based on the ratio between the rate of change of power angle and the maximum permissible rate of change of power angle.

[0255] Based on the relationship between commutation margin and commutation margin reference threshold, determine the commutation margin insufficiency risk component;

[0256] The risk components of power angle change and insufficient commutation margin are combined according to the preset risk weights to obtain the commutation failure risk.

[0257] The inertia risk adjustment factor is determined based on the commutation failure risk and the preset inertia adjustment weight, and the dynamic inertia is attenuated using the inertia risk adjustment factor to obtain the target inertia.

[0258] The damping risk adjustment factor is determined based on the commutation failure risk and the preset damping adjustment weight, and the target damping coefficient is obtained by increasing the benchmark damping coefficient using the damping risk adjustment factor.

[0259] In some embodiments, when the computer program is executed by the processor 30, the processor 30 also performs:

[0260] Obtain the current active power control command output by the active power control loop of the grid-type energy storage converter;

[0261] The active power feedforward compensation is superimposed with the current active power control command to obtain the target active power control command;

[0262] Update the inertia parameters and damping parameters in the virtual synchronous machine control process with the target inertia and target damping coefficient, respectively.

[0263] The voltage phase reference value of the grid-type energy storage converter is determined based on the target active power control command, the updated inertia parameters, and the damping parameters, and the power angle trajectory of the grid-type energy storage converter is adjusted according to the voltage phase reference value.

[0264] This application provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements:

[0265] Obtain the commutation voltage and real-time power angle of the grid-type energy storage converter, determine the commutation margin based on the commutation voltage, and determine the dynamic power angle index based on the real-time power angle.

[0266] The commutation voltage phase at the next moment is predicted based on the state change of the commutation voltage, and the active power feedforward compensation amount is determined based on the predicted commutation voltage phase.

[0267] The dynamic inertia and commutation failure risk are determined based on the commutation margin and power angle dynamic index. The dynamic inertia and the preset reference damping coefficient are then coordinated and adjusted according to the commutation failure risk to obtain the target inertia and target damping coefficient.

[0268] The active power feedforward compensation is superimposed on the current active power control command of the grid-type energy storage converter, and the power angle trajectory of the grid-type energy storage converter is adjusted based on the superimposed active power control command, target inertia and target damping coefficient.

[0269] In some embodiments, the computer program, when executed, also implements:

[0270] Determine the commutation time interval of the grid-type energy storage converter, integrate the commutation voltage within the commutation time interval, and obtain the time integral area of ​​the actual commutation voltage.

[0271] Obtain the critical commutation area required to complete the current commutation process, and determine the commutation margin based on the ratio of the time integral area of ​​the actual commutation voltage to the critical commutation area.

[0272] A second-order differential tracker is used to perform differential tracking processing on the real-time power angle to obtain the power angle change rate and the power angle second derivative. Based on the power angle change rate and the power angle second derivative, the power angle dynamic index is determined.

[0273] In some embodiments, the computer program, when executed, also implements:

[0274] The start and end times of commutation are determined based on the trigger pulse window or current commutation process of the grid-type energy storage converter.

[0275] Determine the line voltage between the two phases undergoing commutation, and use the line voltage between the two phases as the commutation voltage;

[0276] The time integral area of ​​the actual commutation voltage is obtained by integrating the commutation voltage from the start of commutation to the end of commutation.

[0277] In some embodiments, the computer program, when executed, also implements:

[0278] The commutation voltage state variables are constructed based on the voltage amplitude, angular frequency, and initial phase angle of the commutation voltage.

[0279] Based on the change in commutation voltage state between adjacent sampling times, the Kalman filter estimator is used to predict the commutation voltage state at the current time, and the predicted commutation voltage state at the next time is obtained.

[0280] The commutation voltage phase at the next moment is determined based on the angular frequency and initial phase angle in the predicted commutation voltage state.

[0281] The active power feedforward compensation amount is determined based on the predicted changes in the commutation voltage phase.

[0282] In some embodiments, the computer program, when executed, also implements:

[0283] Determine the margin difference between the commutation margin and the lower limit of the safe commutation margin;

[0284] The degree of inertia decay is determined based on the relationship between the absolute value of the second derivative of the work angle and the margin difference.

[0285] The reference inertia is attenuated according to the degree of inertia decay to obtain the dynamic inertia.

[0286] The risk component of power angle change is determined based on the ratio between the rate of change of power angle and the maximum permissible rate of change of power angle.

[0287] Based on the relationship between commutation margin and commutation margin reference threshold, determine the commutation margin insufficiency risk component;

[0288] The risk components of power angle change and insufficient commutation margin are combined according to the preset risk weights to obtain the commutation failure risk.

[0289] The inertia risk adjustment factor is determined based on the commutation failure risk and the preset inertia adjustment weight, and the dynamic inertia is attenuated using the inertia risk adjustment factor to obtain the target inertia.

[0290] The damping risk adjustment factor is determined based on the commutation failure risk and the preset damping adjustment weight, and the target damping coefficient is obtained by increasing the benchmark damping coefficient using the damping risk adjustment factor.

[0291] In some embodiments, the computer program, when executed, also implements:

[0292] Obtain the current active power control command output by the active power control loop of the grid-type energy storage converter;

[0293] The active power feedforward compensation is superimposed with the current active power control command to obtain the target active power control command;

[0294] Update the inertia parameters and damping parameters in the virtual synchronous machine control process with the target inertia and target damping coefficient, respectively.

[0295] The voltage phase reference value of the grid-type energy storage converter is determined based on the target active power control command, the updated inertia parameters, and the damping parameters, and the power angle trajectory of the grid-type energy storage converter is adjusted according to the voltage phase reference value.

[0296] This application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer performs the following:

[0297] Obtain the commutation voltage and real-time power angle of the grid-type energy storage converter, determine the commutation margin based on the commutation voltage, and determine the dynamic power angle index based on the real-time power angle.

[0298] The commutation voltage phase at the next moment is predicted based on the state change of the commutation voltage, and the active power feedforward compensation amount is determined based on the predicted commutation voltage phase.

[0299] The dynamic inertia and commutation failure risk are determined based on the commutation margin and power angle dynamic index. The dynamic inertia and the preset reference damping coefficient are then coordinated and adjusted according to the commutation failure risk to obtain the target inertia and target damping coefficient.

[0300] The active power feedforward compensation is superimposed on the current active power control command of the grid-type energy storage converter, and the power angle trajectory of the grid-type energy storage converter is adjusted based on the superimposed active power control command, target inertia and target damping coefficient.

[0301] In some embodiments, when program instructions are executed by the computer, the computer also performs:

[0302] Determine the commutation time interval of the grid-type energy storage converter, integrate the commutation voltage within the commutation time interval, and obtain the time integral area of ​​the actual commutation voltage.

[0303] Obtain the critical commutation area required to complete the current commutation process, and determine the commutation margin based on the ratio of the time integral area of ​​the actual commutation voltage to the critical commutation area.

[0304] A second-order differential tracker is used to perform differential tracking processing on the real-time power angle to obtain the power angle change rate and the power angle second derivative. Based on the power angle change rate and the power angle second derivative, the power angle dynamic index is determined.

[0305] In some embodiments, when program instructions are executed by the computer, the computer also performs:

[0306] The start and end times of commutation are determined based on the trigger pulse window or current commutation process of the grid-type energy storage converter.

[0307] Determine the line voltage between the two phases undergoing commutation, and use the line voltage between the two phases as the commutation voltage;

[0308] The time integral area of ​​the actual commutation voltage is obtained by integrating the commutation voltage from the start of commutation to the end of commutation.

[0309] In some embodiments, when program instructions are executed by the computer, the computer also performs:

[0310] The commutation voltage state variables are constructed based on the voltage amplitude, angular frequency, and initial phase angle of the commutation voltage.

[0311] Based on the change in commutation voltage state between adjacent sampling times, the Kalman filter estimator is used to predict the commutation voltage state at the current time, and the predicted commutation voltage state at the next time is obtained.

[0312] The commutation voltage phase at the next moment is determined based on the angular frequency and initial phase angle in the predicted commutation voltage state.

[0313] The active power feedforward compensation amount is determined based on the predicted changes in the commutation voltage phase.

[0314] In some embodiments, when program instructions are executed by the computer, the computer also performs:

[0315] Determine the margin difference between the commutation margin and the lower limit of the safe commutation margin;

[0316] The degree of inertia decay is determined based on the relationship between the absolute value of the second derivative of the work angle and the margin difference.

[0317] The reference inertia is attenuated according to the degree of inertia decay to obtain the dynamic inertia.

[0318] The risk component of power angle change is determined based on the ratio between the rate of change of power angle and the maximum permissible rate of change of power angle.

[0319] Based on the relationship between commutation margin and commutation margin reference threshold, determine the commutation margin insufficiency risk component;

[0320] The risk components of power angle change and insufficient commutation margin are combined according to the preset risk weights to obtain the commutation failure risk.

[0321] The inertia risk adjustment factor is determined based on the commutation failure risk and the preset inertia adjustment weight, and the dynamic inertia is attenuated using the inertia risk adjustment factor to obtain the target inertia.

[0322] The damping risk adjustment factor is determined based on the commutation failure risk and the preset damping adjustment weight, and the target damping coefficient is obtained by increasing the benchmark damping coefficient using the damping risk adjustment factor.

[0323] In some embodiments, when program instructions are executed by the computer, the computer also performs:

[0324] Obtain the current active power control command output by the active power control loop of the grid-type energy storage converter;

[0325] The active power feedforward compensation is superimposed with the current active power control command to obtain the target active power control command;

[0326] Update the inertia parameters and damping parameters in the virtual synchronous machine control process with the target inertia and target damping coefficient, respectively.

[0327] The voltage phase reference value of the grid-type energy storage converter is determined based on the target active power control command, the updated inertia parameters, and the damping parameters, and the power angle trajectory of the grid-type energy storage converter is adjusted according to the voltage phase reference value.

[0328] 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, computer storage media, and computer program products described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0329] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0330] 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.

[0331] It should be understood that although the steps in the flowcharts of the embodiments described above 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 embodiments described above 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.

[0332] In the several embodiments provided by this invention, it should be understood that the disclosed systems, electronic devices, computer storage media, computer program products, 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 through some interfaces, indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0333] 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.

[0334] 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.

[0335] 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.

[0336] 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 virtual inertia co-optimization method based on commutation margin, characterized in that, The method includes: The commutation voltage and real-time power angle of the grid-type energy storage converter are obtained. The commutation margin is determined based on the commutation voltage, and the dynamic power angle index is determined based on the real-time power angle. Based on the state change of the commutation voltage, the phase of the commutation voltage at the next moment is predicted, and the active power feedforward compensation amount is determined according to the predicted commutation voltage phase. The dynamic inertia and commutation failure risk are determined based on the commutation margin and the power angle dynamic index, and the dynamic inertia and the preset reference damping coefficient are coordinated and adjusted according to the commutation failure risk to obtain the target inertia and the target damping coefficient. The active power feedforward compensation is superimposed on the current active power control command of the grid-type energy storage converter, and the power angle trajectory of the grid-type energy storage converter is adjusted based on the superimposed active power control command, the target inertia, and the target damping coefficient.

2. The virtual inertia cooperative optimization method based on commutation margin according to claim 1, characterized in that, The step of determining the commutation margin based on the commutation voltage and determining the dynamic power angle index based on the real-time power angle includes: Determine the commutation time interval of the grid-type energy storage converter, integrate the commutation voltage within the commutation time interval, and obtain the time integral area of ​​the actual commutation voltage. Obtain the critical commutation area required to complete the current commutation process, and determine the commutation margin based on the ratio of the time integral area of ​​the actual commutation voltage to the critical commutation area; The real-time power angle is differentially tracked using a second-order differential tracker to obtain the power angle change rate and the power angle second derivative. Based on the power angle change rate and the power angle second derivative, the power angle dynamic index is determined.

3. The virtual inertia cooperative optimization method based on commutation margin according to claim 2, characterized in that, The step of determining the commutation time interval of the grid-type energy storage converter and integrating the commutation voltage within the commutation time interval to obtain the time integral area of ​​the actual commutation voltage includes: The commutation start time and commutation end time are determined based on the trigger pulse window or current commutation process of the grid-type energy storage converter. Determine the line voltage between the two phases undergoing commutation, and use the line voltage between the two phases as the commutation voltage; The time integral area of ​​the actual commutation voltage is obtained by integrating the commutation voltage between the start of commutation and the end of commutation.

4. The virtual inertia cooperative optimization method based on commutation margin according to claim 1, characterized in that, The step of predicting the commutation voltage phase at the next moment based on the state change of the commutation voltage, and determining the active power feedforward compensation amount based on the predicted commutation voltage phase, includes: The commutation voltage state parameters are constructed based on the voltage amplitude, angular frequency, and initial phase angle of the commutation voltage. Based on the change in commutation voltage state between adjacent sampling times, the Kalman filter estimator is used to predict the commutation voltage state at the current time, and the predicted commutation voltage state at the next time is obtained. The commutation voltage phase at the next moment is determined based on the angular frequency and initial phase angle in the predicted commutation voltage state. The active power feedforward compensation amount is determined based on the predicted change in the commutation voltage phase.

5. The virtual inertia cooperative optimization method based on commutation margin according to claim 2, characterized in that, The step of determining the dynamic inertia and commutation failure risk based on the commutation margin and the power angle dynamic index, and coordinating the adjustment of the dynamic inertia and the preset reference damping coefficient based on the commutation failure risk, includes: Determine the margin difference between the commutation margin and the lower limit of the safe commutation margin; The degree of inertia decay is determined based on the relationship between the absolute value of the second derivative of the work angle and the margin difference. The reference inertia is attenuated according to the stated degree of inertia attenuation to obtain the dynamic inertia; The risk component of power angle change is determined based on the ratio between the power angle change rate and the maximum permissible power angle change rate. Based on the relationship between the commutation margin and the commutation margin reference threshold, the commutation margin insufficiency risk component is determined; The commutation failure risk is obtained by combining the power angle change risk component and the commutation margin insufficient risk component according to the preset risk weight. The inertia risk adjustment factor is determined based on the commutation failure risk and the preset inertia adjustment weight, and the dynamic inertia is attenuated using the inertia risk adjustment factor to obtain the target inertia. The damping risk adjustment factor is determined based on the commutation failure risk and the preset damping adjustment weight, and the target damping coefficient is obtained by increasing the reference damping coefficient using the damping risk adjustment factor.

6. The virtual inertia cooperative optimization method based on commutation margin according to claim 1, characterized in that, The step of superimposing the active power feedforward compensation amount onto the current active power control command of the grid-type energy storage converter, and adjusting the power angle trajectory of the grid-type energy storage converter based on the superimposed active power control command, the target inertia, and the target damping coefficient, includes: Obtain the current active power control command output by the active power control loop of the grid-type energy storage converter; The active power feedforward compensation amount is superimposed with the current active power control command to obtain the target active power control command; The target inertia and the target damping coefficient are used to update the inertia parameters and damping parameters in the virtual synchronous machine control process, respectively. The voltage phase reference value of the grid-type energy storage converter is determined based on the target active power control command, the updated inertia parameters and damping parameters, and the power angle trajectory of the grid-type energy storage converter is adjusted based on the voltage phase reference value.

7. A virtual inertia cooperative optimization system based on commutation margin, characterized in that, The system includes: The index determination module is used to obtain the commutation voltage and real-time power angle of the grid-type energy storage converter, determine the commutation margin based on the commutation voltage, and determine the dynamic index of the power angle based on the real-time power angle. The active power feedforward compensation module is used to predict the commutation voltage phase at the next moment based on the state change of the commutation voltage, and determine the active power feedforward compensation amount according to the predicted commutation voltage phase. The inertia adjustment module is used to determine the dynamic inertia and commutation failure risk based on the commutation margin and the power angle dynamic index, and to coordinately adjust the dynamic inertia and the preset reference damping coefficient based on the commutation failure risk to obtain the target inertia and the target damping coefficient. The power angle adjustment module is used to superimpose the active power feedforward compensation amount onto the current active power control command of the grid-type energy storage converter, and adjust the power angle trajectory of the grid-type energy storage converter based on the superimposed active power control command, the target inertia and the target damping coefficient.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the virtual inertia co-optimization method based on commutation margin as described in any one of claims 1-6.

9. 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 virtual inertia cooperative optimization method based on commutation margin as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, wherein when the program instructions are executed by a computer, the computer performs the steps of the virtual inertia cooperative optimization method based on commutation margin as described in any one of claims 1-6.

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