A Distributed Inertia Simulation Method and System for Hybrid AC / DC Microgrids

Abstract

This invention belongs to the field of microgrid inertia simulation technology. It proposes a distributed inertia simulation method and system for hybrid AC / DC microgrids. The system is built around a closed-loop logic of "frequency information without communication transmission - adaptive high-precision sensing - nonlinear inertia accurate output - IPSO optimized multi-topology aggregation - overall system stable control". A reference value is constructed by superimposing an AC disturbance signal onto the rated voltage of the DC bus. The average value of this disturbance signal is zero, so the steady-state DC component of the DC bus voltage is not changed, keeping it stable near the rated value. The DC bus capacitor only serves as a medium for transmitting frequency information and does not participate in energy storage and release. This solves the voltage deviation problem caused by energy release and absorption in traditional capacitor inertia simulation methods, avoids the risk of overvoltage / undervoltage protection actions and system instability caused by this, and ensures the stability of system operation.

Description

Technical Field

[0001] This invention relates to the field of microgrid inertia simulation technology, and in particular to a distributed inertia simulation method and system for hybrid AC / DC microgrids. Background Technology

[0002] With the increasing penetration of renewable energy in power systems and the widespread application of power electronic converters, the inherent inertia of modern power grids continues to decrease, leading to a decline in system frequency stability. Hybrid AC / DC microgrids, as an effective topology integrating distributed generation units (DGUs) and energy storage systems, require inertia simulation to participate in frequency response under grid-connected mode to ensure stable system operation.

[0003] Existing inertia simulation methods are mainly divided into two categories: one category uses the DC bus capacitor of the grid-connected inverter (GTI) to store energy and provide inertia, but the DC bus capacitor capacity is limited and it is difficult to meet the system inertia requirements. Moreover, the energy release process will cause the DC bus voltage to deviate from the rated value, causing system instability. The other category provides inertia through DGU or energy storage system, but it requires a communication link to transmit grid frequency information, which has problems such as signal delay, noise interference and signal loss, affecting the real-time performance and accuracy of inertia simulation.

[0004] Furthermore, existing distributed inertia simulation methods are difficult to apply to DC distribution networks with multi-bus topologies. Due to the impedance differences between different buses, frequency information transmission is distorted, making accurate inertia aggregation control impossible. Therefore, there is an urgent need for a distributed inertia simulation technology that does not require communication, does not affect the stability of DC bus voltage, and is applicable to multi-bus topologies. Summary of the Invention

[0005] Therefore, one objective of this invention is to propose a distributed inertia simulation method and system for hybrid AC / DC microgrids to solve the problems mentioned in the background art and overcome the shortcomings of the prior art.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a distributed inertia simulation method for hybrid AC / DC microgrids, comprising: An AC disturbance signal is generated by a grid-connected inverter and injected into the DC bus voltage to maintain the steady-state DC component of the DC bus voltage at its rated value. In the local controller of the interface converter of the DC-side distributed generation unit, the grid frequency information carried in the DC bus voltage is extracted by a cascaded second-order generalized integrator phase-locked loop, and the frequency change rate is calculated. Based on the frequency change rate and the nonlinear virtual inertia constant, the power reference compensation amount of the DC-side distributed generation unit is determined, the output power of the DC-side distributed generation unit is adjusted, and the virtual inertia simulation of the microgrid is realized. In a multi-bus radial topology, the power reference compensation amount of each DC-side distributed generation unit is allocated by aggregation control to realize the collaborative aggregation inertia simulation under the multi-bus topology.

[0007] Preferably, the step of generating an AC disturbance signal through a grid-connected inverter and injecting the AC disturbance signal into the DC bus voltage includes: The three-phase voltage signal from the grid side is collected, and the single-phase grid voltage is extracted in the local controller of the grid-connected inverter. The amplitude of the single-phase voltage is adjusted according to the preset amplitude coefficient to generate an AC disturbance signal carrying grid frequency information. The expression for single-phase grid voltage is extracted as follows: ; in, This is the voltage of a single-phase power grid. The voltage amplitude of the power grid. The angular frequency of the power grid is t, and time is t. The AC disturbance signal is as follows: ; in, For AC disturbance signals, The preset amplitude coefficient; Construct a DC bus voltage reference value that includes AC disturbances: ; in, This is the reference value for the DC bus voltage. This is the rated voltage of the DC bus.

[0008] Preferably, the cascaded second-order generalized integrator phase-locked loop includes two stages of second-order generalized integrators and phase-locked loops. The first-stage second-order generalized integrator is used to eliminate DC offset, and the second-stage second-order generalized integrator is used to generate based on the single-phase grid voltage signal. Reference voltage in coordinate system and The phase-locked loop extracts the frequency information from the three-phase voltage after model predictive control optimization, obtains the grid frequency estimate after sliding mode filtering, and obtains the frequency change rate by differentiating the grid frequency estimate.

[0009] Preferably, the power reference compensation amount is calculated using the following expression: ; in, This is the power reference compensation amount. The nonlinear virtual inertia constant of the DC-side distributed generation unit. As the system reference power, The rated frequency of the power grid. This represents the rate of change of frequency.

[0010] Preferably, the nonlinear virtual inertia constant is as follows: ; in, As the reference inertia constant, and For the grading threshold, The inertia gain coefficient, To limit the inertia to the maximum.

[0011] Preferably, the method of allocating the power reference compensation amount of each DC-side distributed generation unit through aggregation control to achieve collaborative aggregation inertia simulation under a multi-bus topology includes: Calculate the total rated power and global rated power of the DC-side distributed generation units participating in the inertia simulation on each bus; Based on the total rated power of a single bus and the global rated power, the initial power allocation coefficient of a single DC-side distributed generation unit is calculated, and the power reference compensation amount for adjusting a single DC-side distributed generation unit is determined according to the initial power allocation coefficient; the initial power allocation coefficient is dynamically determined according to the proportion of the rated power of the unit in the corresponding total rated power. A multi-objective optimization function is constructed, which aims to maximize inertia aggregation efficiency, balance power output, and minimize line loss. An improved particle swarm optimization algorithm is used to optimize and solve the initial power allocation coefficients to obtain the optimal allocation coefficients. Adjust the power reference compensation amount of the corresponding DC-side distributed generation unit according to the optimal allocation coefficient to realize the collaborative aggregation inertia simulation of multiple buses and multiple DC-side distributed generation units.

[0012] As a preferred option, the formula for calculating the total rated power of a single busbar is: ; in, This refers to the total rated power of a single busbar. This refers to the number of DC-side distributed generation units connected to a single busbar. , where is the rated power of a single DC-side distributed generation unit on a single bus, and k is the DC-side distributed generation unit corresponding to the UPS that does not participate in the inertia simulation; The formula for calculating the global rated power is: ; in, This is the global rated power. This refers to the number of DC-side distributed generation units connected to a single busbar. This refers to the number of DC buses. The rated power of the i-th DC-side distributed generation unit on the j-th bus; The formula for calculating the initial power allocation factor is: ; in, The initial power allocation factor, This is the global rated power; The formula for calculating the power reference compensation is: ; in, This is the power reference compensation amount. This refers to the real-time power grid frequency.

[0013] Preferably, the multi-objective optimization function includes: Objective function for maximizing inertia pooling efficiency: ; DGU power output equalization objective function: ; Line loss minimization objective function: ; in, This is the power reference compensation amount. For the total compensation amount, Rated active power, Bus current, This represents the line impedance.

[0014] Preferably, the grid-connected inverter adopts a dual-loop control strategy, with its outer loop being a proportional-integral-resonant voltage controller used to track the DC bus voltage reference value containing the AC disturbance signal and suppress harmonic components; and its inner loop being a proportional-integral current controller used to adjust the grid-connected current. In the interface converter control link of the DC-side distributed generation unit, the frequency change rate signal is smoothed and the parameters of its current loop proportional-integral controller are optimized to ensure stable tracking of output power.

[0015] Secondly, the present invention provides a distributed inertia simulation system for a hybrid AC / DC microgrid, comprising: The signal injection module is used to generate an AC disturbance signal through the grid-connected inverter and inject the AC disturbance signal into the DC bus voltage so that the steady-state DC component of the DC bus voltage is maintained at the rated value. The frequency extraction module is used to extract the grid frequency information carried in the DC bus voltage in the local controller of the interface converter of the DC-side distributed generation unit through a cascaded second-order generalized integrator phase-locked loop, and to calculate the frequency change rate. The power adjustment module is used to determine the power reference compensation amount of the DC-side distributed generation unit based on the frequency change rate and the nonlinear virtual inertia constant, adjust the output power of the DC-side distributed generation unit, and realize the virtual inertia simulation of the microgrid. The aggregation control module is used to distribute the power reference compensation amount of each DC-side distributed generation unit in a multi-bus radial topology through aggregation control, thereby realizing the collaborative aggregation inertia simulation under the multi-bus topology.

[0016] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described distributed inertia simulation method for hybrid AC / DC microgrids.

[0017] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described distributed inertia simulation method for hybrid AC / DC microgrids.

[0018] Compared with the prior art, the advantages and beneficial effects of the present invention are as follows: This invention constructs a reference value by superimposing an AC disturbance signal onto the rated DC bus voltage. The average value of this disturbance signal is zero, thus not changing the steady-state DC component of the DC bus voltage, keeping it stable near the rated value. This allows the DC bus capacitor to serve only as a medium for transmitting frequency information, without participating in energy storage and release. This solves the voltage deviation problem caused by energy release and absorption in traditional capacitor inertia simulation methods, avoids the risk of overvoltage / undervoltage protection actions and system instability caused by this, and ensures the stability of system operation.

[0019] This invention eliminates the reliance on traditional communication by modulating grid frequency information into a precisely amplitude-controlled AC disturbance signal through a grid-connected inverter and injecting it into the DC bus voltage. The DC-side DGU can then deduce the frequency information by locally measuring the DC bus voltage, achieving communication-free frequency transmission from the grid connection point to the distributed generation unit. This avoids the inertial response lag caused by communication delays, as well as the impact of signal noise and interruptions on simulation accuracy. It not only improves the reliability and real-time performance of the system response but also simplifies the system architecture and reduces the purchase, installation, and maintenance costs of communication equipment.

[0020] This invention introduces an aggregation control strategy based on an improved particle swarm optimization algorithm. This algorithm takes inertia aggregation efficiency, power output balance, and line loss minimization as comprehensive objectives, dynamically calculates the optimal power allocation coefficient for each DGU, and actively offsets the uneven power allocation caused by the line impedance difference band in the multi-bus radial topology. This enables precise coordination of the inertia support behavior of all participating units, enhances the adaptability to multi-bus radial topologies, and improves system scalability by eliminating the need to reconstruct the control logic when the system is expanded to add DGUs or buses, only updating the allocation coefficients is required.

[0021] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0022] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is an overall flowchart of a distributed inertia simulation method for a hybrid AC / DC microgrid provided in an embodiment of the present invention.

[0023] Figure 2 This is a structural diagram of a distributed inertia simulation system for a hybrid AC / DC microgrid, provided as an embodiment of the present invention.

[0024] Figure 3 A schematic diagram of a grid-connected hybrid microgrid with a radial subgrid topology provided in an embodiment of the present invention.

[0025] Figure 4 The system feature value root locus diagram provided in the embodiments of the present invention.

[0026] Figure 5 Frequency response diagram of a radial topology provided in an embodiment of the present invention.

[0027] Figure 6 This is a schematic diagram of the electronic device structure provided in an embodiment of the present invention. Detailed Implementation

[0028] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0029] With the penetration rate of renewable energy (RES) in the power system exceeding 50% (global average data in 2025), the "low inertia characteristic" of hybrid AC / DC microgrids has become a core bottleneck restricting the stable operation of the system: in scenarios with a high proportion of wind power / solar power integration, the "no inertia" characteristic of power electronic converters can lead to the grid frequency dropping by more than 0.5Hz and RoCoF (rate of frequency change) exceeding 0.5Hz / s when there is a load impact or RES power fluctuation (far exceeding the limit of GB / T15945-2022 "Permissible Deviation of Frequency in Power Systems").

[0030] Existing inertia simulation technologies have significant drawbacks in practical engineering: ① The "capacity-stability" contradiction of capacitor-based inertia schemes: When relying on DC-link capacitors for inertia, a 1000μF capacitor can only support an inertia response of approximately 0.02s, and energy exchange can cause the DC bus voltage to deviate from its rated value by ≥5%, triggering GTI overvoltage / undervoltage protection (a microgrid in an industrial park experienced three trips in 2024 due to this). ② The "reliability-cost" contradiction of communication-dependent schemes: When using fiber optic / wireless communication to transmit frequency information, communication delays (≥20ms) can lead to lag in inertia response, and the maintenance cost of communication equipment in remote areas (such as mountain photovoltaic microgrids) accounts for more than 12% of the total system investment, while there is also the risk of signal loss under extreme weather conditions. ③ Lack of multi-topology adaptability: Existing distributed schemes only support single-bus topologies, and when expanded to multi-bus radial structures, the required adaptability is limited. ① Line impedance differences can lead to frequency information transmission distortion exceeding 15%, making it impossible to achieve collaborative inertia support for DGUs; ② Obstacles to the "engineering implementation" of complex control loops: Some improvement schemes enhance performance by adding triple control loops and multi-objective optimization algorithms, but there are more than 30 control parameters, making parameter tuning extremely difficult and hard for on-site maintenance personnel to master; at the same time, complex algorithms cause a surge in controller computational load, extending response time to more than 100ms, losing the real-time advantage of inertia support; ③ Shortcomings of "complex working condition adaptation" of fixed parameter algorithms: Existing frequency extraction algorithms (such as traditional SOGI-PLL) adopt fixed parameter design. Under complex working conditions such as sudden changes in grid frequency (such as ±2Hz / s) or harmonic distortion rate exceeding 30%, the frequency estimation error will increase to more than 0.1Hz, and the RoCoF calculation deviation will exceed 0.05Hz / s, resulting in a significant decrease in the accuracy of inertia support.

[0031] To address the aforementioned practical pain points, the core objective of this invention is to provide a distributed inertia simulation method and system for hybrid AC / DC microgrids. This method is built around a closed-loop logic of "frequency information transmission without communication - adaptive high-precision sensing - precise nonlinear inertia output - IPSO optimization and multi-topology aggregation - stable control of the entire system." It integrates technologies from multiple fields, including power electronic conversion, adaptive signal processing, nonlinear control, and intelligent optimization, and achieves performance breakthroughs through algorithmic innovation and refined design.

[0032] like Figure 1 As shown, this embodiment of the invention provides a distributed inertia simulation method for a hybrid AC / DC microgrid, including: S1: An AC disturbance signal is generated by the grid-connected inverter and injected into the DC bus voltage to maintain the steady-state DC component of the DC bus voltage at its rated value.

[0033] Furthermore, the step of generating an AC disturbance signal through a grid-connected inverter and injecting the AC disturbance signal into the DC bus voltage includes: The three-phase voltage signal from the grid side is collected, and the single-phase grid voltage is extracted in the local controller of the grid-connected inverter. The amplitude of the single-phase voltage is adjusted according to the preset amplitude coefficient to generate an AC disturbance signal carrying grid frequency information.

[0034] Specifically, the generation and injection of AC disturbance signals. The GTI local controller collects the three-phase voltage of the power grid through a high-precision voltage sensor (error ≤ 0.1%), using this as a carrier of frequency information. By selecting single-phase voltage instead of three-phase voltage, excessive disturbance amplitude caused by the superposition of multi-phase signals can be avoided, reducing the pressure on GTI voltage control. Taking phase A voltage as an example, the calculation formula is: ; in, This is the voltage of a single-phase power grid. The voltage amplitude of the power grid. The angular frequency of the power grid is t, and time is t. To avoid DC bus voltage distortion, the preset amplitude coefficient is used. Adjust the amplitude of the single-phase voltage to generate an AC disturbance signal. Amplitude coefficient. The selection strictly adhered to the IEEE P2030.10 standard to ensure that the peak-to-peak low-frequency noise of the injected DC bus did not exceed 8V and did not trigger GTI's overvoltage / undervoltage protection mechanism. Combined with the tracking accuracy of GTI's PIR voltage controller (±0.5%), the amplitude coefficient of the AC disturbance signal was finally determined through Matlab / Simulink simulation iterations. This amplitude ensures effective transmission of frequency information without triggering the GTI's overvoltage / undervoltage protection (the protection threshold is typically ±10% of the rated voltage). The formula for calculating the AC disturbance signal is: ; The AC disturbance signal is superimposed on the rated DC bus voltage to construct a new DC bus voltage reference value, the calculation formula of which is: ; in, This is the rated voltage of the DC bus. Because... As a sinusoidal alternating signal with an average value of 0, the steady-state DC component of the DC bus voltage is always maintained within the rated value of 400V±0.2%, completely solving the voltage deviation problem of the traditional capacitor inertia scheme.

[0035] The DC bus capacitor serves only as a medium for transmitting frequency information and does not participate in energy storage or release. Simultaneously, a digital filtering module is added to the signal generation stage, specifically an IIR digital filtering module (4th order, 1kHz cutoff frequency) to filter out high-frequency harmonics (mainly the 3rd, 5th, and 7th harmonics) from the grid voltage. This ensures that Vinj's waveform distortion rate is ≤1%, preventing harmonic components from affecting the accuracy of subsequent frequency extraction.

[0036] S2: In the local controller of the interface converter of the DC-side distributed generation unit, the grid frequency information carried in the DC bus voltage is extracted by a cascaded second-order generalized integrator phase-locked loop, and the frequency change rate is calculated.

[0037] Furthermore, the cascaded second-order generalized integrator phase-locked loop includes two stages of second-order generalized integrators and phase-locked loops. The first-stage second-order generalized integrator is used to eliminate DC offset, and the second-stage second-order generalized integrator is used to generate based on the single-phase grid voltage signal. Reference voltage in coordinate system and The phase-locked loop extracts the frequency information from the three-phase voltage after model predictive control optimization, obtains the grid frequency estimate after sliding mode filtering, and obtains the frequency change rate by differentiating the grid frequency estimate.

[0038] Specifically, the adaptive CSOGI-PLL grid frequency and RoCoF are accurately extracted.

[0039] Firstly, adaptive gain adjustment using cascaded SOGI is employed. A two-stage second-order generalized integrator (CSOGI) is used to construct the frequency extraction front-end, innovatively introducing an adaptive gain mechanism based on harmonic content feedback. A harmonic distortion rate (THD) evaluation metric is defined. ( The fundamental amplitude, (where the amplitude is n), calculate the THD value of the DC bus voltage in real time: when (Ideal operating conditions), SOGI error gain coefficient To balance dynamic characteristics and stability; when (Medium harmonic interference), through scaling factor Dynamic improvement Enhance harmonic response capability; when (Severe harmonic interference), activate gain saturation mechanism. To avoid excessive gain that could cause system oscillation.

[0040] In the local controller of the interface converter on the DC side DGU, a CSOGI-PLL structure is introduced for frequency information parsing. This structure consists of two levels of SOGI and PLL units: the first-level SOGI is used to eliminate the DC offset component in the DC bus voltage (suppressing DC disturbances within the ±5V range), and the second-level SOGI converts the single-phase voltage signal into... Reference voltage in coordinate system and It achieves a suppression ratio of 55dB for the 3rd harmonic and 60dB for the 5th harmonic, which is significantly better than the traditional fixed gain SOGI.

[0041] Secondly, the PLL's model predictive adaptive parameter tuning is performed. Model predictive control (MPC) is used to optimize the PLL parameters and construct a frequency estimation error prediction model. ; in, Let k be the frequency estimation error at time k. , This refers to the parameter adjustment amount. With the objective of minimizing the error over the next three sampling periods, the optimal parameters are solved through rolling optimization. When the rate of change of frequency (Stable operating conditions) , To ensure the accuracy of the estimation; when (Dynamic operating conditions), MPC dynamic improvement Increase the response speed to 200-250; when (Unexpected work situation) , To avoid the accumulation of errors.

[0042] The optimized PLL has a tracking bandwidth dynamic range of 50Hz-80Hz, a frequency estimation response time ≤3ms, an estimation error ≤0.005Hz, and a RoCoF calculation error ≤0.01Hz / s.

[0043] In addition, RoCoF's sliding mode filtering smoothing mechanism is used to replace the traditional low-pass filter. Sliding mode filtering (SMF) is used to process the frequency estimate, and a sliding surface is designed. By switching functions Suppressing high-frequency noise ( (For sliding mode gain), the high-frequency fluctuation amplitude of RoCoF is reduced to below 0.005Hz / s, and there is no phase lag, avoiding frequent fluctuations in the DGU power reference.

[0044] S3: Based on the frequency change rate and the nonlinear virtual inertia constant, determine the power reference compensation amount of the DC-side distributed generation unit, adjust the output power of the DC-side distributed generation unit, and realize the virtual inertia simulation of the microgrid.

[0045] Specifically, the dynamic adjustment of the DGU power reference is discussed. Based on the core principle of virtual inertia, the power reference compensation is derived using the convergent swing equation. The fundamental equations for virtual inertia simulation originate from a variation of the swing equation of a synchronous generator. in, Let ω be the virtual inertia constant and ω be the system angular frequency. This is a per-unit power reference.

[0046] Breaking through the limitations of traditional linear inertia models, a nonlinear virtual inertia constant is constructed based on the "RoCoF hierarchical adaptive" concept. : in As the reference inertia function, , For the grading threshold, The inertia gain coefficient, Maximum inertia limit (to avoid DGU overload).

[0047] Based on the swing equation of the synchronous generator, the formula for calculating the nonlinear power compensation is derived: ; The model provides stronger inertia support as the RoCoF increases, especially under extreme perturbations. The compensation amount is 60% higher than that of the linear model, effectively suppressing the rapid drop in frequency.

[0048] The power reference compensation is superimposed on the initial steady-state power reference value of the DGU. The updated DGU power reference is obtained. The interface converter adjusts the inductor current through a PI controller to achieve dynamic tracking of the DGU output power and complete the inertia simulation. The updated DGU power reference calculation formula is as follows: ; For different types of DGUs (energy storage type, photovoltaic type, and wind power type), a dynamically adjustable virtual inertia constant is designed: the Hb value range of energy storage type DGUs (such as lithium battery energy storage) is 4.0s-6.0s, which can provide continuous inertia support; the Hb value range of photovoltaic type DGUs is 2.0s-3.0s, which is adapted to its power fluctuation; and the Hb value range of wind power type DGUs is 3.0s-5.0s, which balances the impact of wind speed changes.

[0049] S4: In a multi-bus radial topology, the power reference compensation amount of each DC-side distributed generation unit is allocated through aggregation control to realize the collaborative aggregation inertia simulation under the multi-bus topology.

[0050] The method of allocating power reference compensation amounts to each DC-side distributed generation unit through aggregation control to achieve collaborative aggregation inertia simulation under a multi-bus topology includes: Calculate the total rated power and global rated power of the DC-side distributed generation units participating in the inertia simulation on each bus; Based on the total rated power and global rated power of a single bus, the initial power allocation coefficient of a single DC-side distributed generation unit is calculated, and the power reference compensation amount for adjusting a single DC-side distributed generation unit is determined according to the initial power allocation coefficient. The initial power allocation coefficient is dynamically determined according to the proportion of the rated power of the unit in the corresponding total rated power (the corresponding total rated power is: the total rated power of the bus where the unit is located under a single bus topology, and the global total rated power of the entire microgrid under a multi-bus topology). A multi-objective optimization function is constructed, which aims to maximize inertia aggregation efficiency, balance power output, and minimize line loss. An improved particle swarm optimization algorithm is used to optimize and solve the initial power allocation coefficients to obtain the optimal allocation coefficients. Adjust the power reference compensation amount of the corresponding DC-side distributed generation unit according to the optimal allocation coefficient to realize the collaborative aggregation inertia simulation of multiple buses and multiple DC-side distributed generation units.

[0051] Specifically, the aggregated inertia simulation under a multi-bus topology optimized by IPSO is performed. For a multi-bus radial topology (containing N DC buses, each bus connecting M DGUs), the total rated power of the DGUs participating in the inertia simulation is first calculated: the total rated power of a single bus is calculated as follows: ; in, This refers to the total rated power of a single busbar. This refers to the number of DC-side distributed generation units connected to a single busbar. , where is the rated power of a single DC-side distributed generation unit on a single bus, and k is the DC-side distributed generation unit corresponding to the UPS that does not participate in the inertia simulation; The formula for calculating the global rated power is: ; in, This is the global rated power. This refers to the number of DC-side distributed generation units connected to a single busbar. This refers to the number of DC buses. The rated power of the i-th DC-side distributed generation unit on the j-th bus; Next, the power allocation factor for a single DGU is calculated. This factor dynamically allocates the inertia support task based on the rated power ratio of the DGU, thus offsetting the uneven power distribution caused by differences in the impedance of different bus lines. The calculation formula is as follows: ; in, The initial power allocation factor, This is the global rated power; Adjust the power reference compensation for a single DGU: ; This is the power reference compensation amount. To achieve real-time power grid frequency, collaborative aggregation inertia simulation of multiple buses and multiple DGUs is implemented.

[0052] Breaking away from the traditional allocation logic "based solely on rated power," a multi-objective optimization function is constructed, comprehensively considering three core indicators: Maximizing inertia aggregation efficiency: ( (Total compensation amount) DGU power output balance: ; Minimize line loss: ; ( Bus current, (This refers to the line impedance).

[0053] Transform it into a single objective function using the weighted summation method: ,in , , These are the weighting coefficients (optimized through simulation).

[0054] Simultaneously, the design of the Particle Swarm Optimization (IPSO) algorithm is improved: to address the tendency of traditional PSO to get trapped in local optima, three improvement mechanisms are introduced: Inertia weight adaptive ( , k is the number of iterations. ); Particle mutation mechanism: Every 10 iterations, the 5% of particles with the worst fitness are randomly mutated, varying the particle length. ; Boundary constraint handling: using a nonlinear shrinkage factor To avoid the allocation coefficient being too small or too large.

[0055] The specific process involves the DGU of each busbar calculating the total rated power of a single busbar by encoding the amplitude of the disturbance signal. The system transmits real-time SOC (State of Charge) and power margin information of the DGUs through phase difference encoding of voltage perturbations. It selects any DGU as a "temporary aggregation node," runs the IPSO algorithm to solve for the optimal allocation coefficient, and then transmits the optimal value to all DGUs by switching the amplitude level of the DC-link voltage. Finally, the DGUs adjust their power compensation to achieve globally optimal aggregation. Even in scenarios with dynamic changes in line impedance (±20%) and insufficient power margin for some DGUs, this strategy maintains an inertia aggregation efficiency of ≥92% and improves power output balance to over 85%.

[0056] Further progress includes step S5: system stability control strategy. GTI employs a dual-loop control strategy: the outer loop is a proportional-integral-resonant (PIR) voltage controller. Compared to traditional PI controllers, its resonant stage can accurately track the DC bus voltage reference value containing AC disturbances and suppress harmonic components introduced by the disturbances; the inner loop is a PI current controller, used to quickly adjust the grid-connected current and improve the system's dynamic response speed. In the control link of the DGU interface converter, the RoCoF signal is smoothed through a sliding mode filter to avoid power reference fluctuations caused by high-frequency noise, while simultaneously optimizing the PI controller parameters (proportional gain). =2.5, Integral Gain =0.7), to ensure stable tracking of the inductor current.

[0057] The stability of the system was verified using eigenvalue analysis. When the SOGI error gain coefficient... When the system varies within the range of 0.15-1.0, all its eigenvalues ​​are located in the left half of the complex plane. Two key eigenvalues ​​eventually stabilize at around -2, ensuring that the system is free from oscillation and instability risk under complex operating conditions such as load disturbances and RES power fluctuations.

[0058] In one embodiment, distributed inertia simulation is performed under a single-bus topology, such as... Figure 3 , Figure 4 and Figure 5 As shown. The system parameter settings for this embodiment are as follows: grid rated voltage Rated frequency DC bus voltage AC disturbance signal amplitude coefficient CSOGI-PLL parameters: SOGI error gain coefficient PLL regulator gain PLL frequency DGU virtual inertia constant System reference power Initial power reference .

[0059] The specific implementation steps are as follows: First, a signal is injected, and the GTI local controller extracts the voltage of phase A of the power grid. Generate AC disturbance signal Construct a DC bus voltage reference After frequency extraction, the CSOGI-PLL of the DGU interface converter... The process involves two stages: a first-stage SOGI to eliminate DC offset, and a second-stage SOGI to generate... , Frequency estimates were extracted using inverse Clark transform and PLL. Differentiation yields The second step is power adjustment, which involves calculating the power reference compensation amount. Update the DGU power reference; finally, stabilize the control. GTI uses a PIR voltage controller (voltage proportional gain controller). Integral gain Resonant gain Tracking Vdc), sliding mode filter ( , Eliminate harmonics.

[0060] The simulation results are as follows: When a load disturbance of 0.06 pu is introduced, the lowest point of the power grid frequency in the simulation without inertia is 49.676 Hz, and the maximum RoCoF is 0.3 Hz / s; after adopting this method, the lowest point of frequency is increased to 49.732 Hz, the maximum RoCoF is reduced to 0.156 Hz / s, the steady-state value of DC bus voltage is maintained at 400V, and the fluctuation amplitude meets the IEEE P2030.10 standard.

[0061] Secondly, such as Figure 2 As shown, this invention provides a distributed inertia simulation system for hybrid AC / DC microgrids, applicable to the aforementioned distributed inertia simulation method for hybrid AC / DC microgrids, comprising: The signal injection module is used to generate an AC disturbance signal through the grid-connected inverter and inject the AC disturbance signal into the DC bus voltage, so that the steady-state DC component of the DC bus voltage is maintained at the rated value.

[0062] Furthermore, the signal injection module is deployed on the GTI's local controller and consists of a voltage extraction unit, an amplitude adjustment unit, and a reference voltage construction unit. The voltage extraction unit is responsible for separating single-phase voltage signals from the three-phase voltage of the power grid; the amplitude adjustment unit dynamically adjusts the amplitude coefficient according to system parameters and IEEE standards. The system generates an AC disturbance signal that meets the requirements; the reference voltage construction unit superimposes the AC disturbance signal with the rated DC bus voltage and outputs the final DC bus voltage reference value.

[0063] The frequency extraction module is used to extract the grid frequency information carried in the DC bus voltage in the local controller of the interface converter of the DC-side distributed generation unit through a cascaded second-order generalized integrator phase-locked loop, and to calculate the frequency change rate.

[0064] Furthermore, the frequency extraction module is deployed in the local controller of the DGU interface converter. Its core is a CSOGI-PLL structure, comprising an SOGI filtering unit, a coordinate transformation unit, a phase-locked loop unit, and a differential calculation unit. The SOGI filtering unit eliminates DC offset and harmonic interference through a two-stage generalized integrator; the coordinate transformation unit completes... The system performs mutual conversion between the coordinate system and the abc coordinate system; the phase-locked loop unit tracks the voltage phase and extracts the estimated grid frequency; the differential calculation unit differentiates the frequency estimate and outputs the RoCoF signal.

[0065] The power adjustment module is used to determine the power reference compensation amount of the DC-side distributed generation unit based on the frequency change rate and the nonlinear virtual inertia constant, adjust the output power of the DC-side distributed generation unit, and realize the virtual inertia simulation of the microgrid.

[0066] Furthermore, the power adjustment module consists of a parameter storage unit, a compensation calculation unit, and a current reference generation unit. The parameter storage unit pre-stores key parameters such as the system reference power, the DGU virtual inertia constant, and the grid rated frequency; the compensation calculation unit calculates the power reference compensation amount according to a preset formula based on the RoCoF signal and the stored parameters; the current reference generation unit converts the power reference compensation amount into an inductor current reference value and outputs it to the PI controller of the DGU interface converter.

[0067] The aggregation control module is used to distribute the power reference compensation amount of each DC-side distributed generation unit in a multi-bus radial topology through aggregation control, thereby realizing the collaborative aggregation inertia simulation under the multi-bus topology.

[0068] Furthermore, the aggregation control module is suitable for multi-bus topology scenarios and includes a power statistics unit and a distribution coefficient calculation unit. The power statistics unit calculates the total rated power of each bus and the DGUs participating in the global inertia simulation in real time; the distribution coefficient calculation unit generates the power distribution coefficient of each DGU according to the rated power ratio and transmits it to the power adjustment module to achieve global coordination of inertia support.

[0069] Furthermore, it also includes a stability control module, which is used to employ a dual-loop control strategy through the grid-connected inverter. Its outer loop is a proportional-integral-resonant voltage controller, which is used to track the DC bus voltage reference value containing the AC disturbance signal and suppress harmonic components; its inner loop is a proportional-integral current controller, which is used to adjust the grid-connected current. In the interface converter control link of the DC-side distributed generation unit, the frequency change rate signal is smoothed and the parameters of its current loop proportional-integral controller are optimized to ensure stable tracking of output power.

[0070] Furthermore, the stability control module integrates a sliding mode filter unit and a GTI dual-loop control unit. The sliding mode filter unit smooths RoCoF and frequency signals and suppresses high-frequency noise; the PIR voltage controller in the GTI dual-loop control unit tracks the DC bus voltage with disturbances, and the PI current controller regulates the grid-connected current. At the same time, by analyzing and optimizing control parameters, the system's stability is ensured under scenarios such as load disturbances and renewable energy fluctuations.

[0071] Furthermore, the step of generating an AC disturbance signal through a grid-connected inverter and injecting the AC disturbance signal into the DC bus voltage includes: The three-phase voltage signal from the grid side is collected, and the single-phase grid voltage is extracted in the local controller of the grid-connected inverter. The amplitude of the single-phase voltage is adjusted according to the preset amplitude coefficient to generate an AC disturbance signal carrying grid frequency information. The expression for single-phase grid voltage is extracted as follows: ; in, This is the voltage of a single-phase power grid. The voltage amplitude of the power grid. The angular frequency of the power grid is t, and time is t. The AC disturbance signal is as follows: ; in, For AC disturbance signals, The preset amplitude coefficient; Construct a DC bus voltage reference value that includes AC disturbances: ; in, This is the reference value for the DC bus voltage. This is the rated voltage of the DC bus.

[0072] Furthermore, the cascaded second-order generalized integrator phase-locked loop includes two stages of second-order generalized integrators and phase-locked loops. The first-stage second-order generalized integrator is used to eliminate DC offset, and the second-stage second-order generalized integrator is used to generate based on the single-phase grid voltage signal. Reference voltage in coordinate system and The phase-locked loop extracts the frequency information from the three-phase voltage after model predictive control optimization, obtains the grid frequency estimate after sliding mode filtering, and obtains the frequency change rate by differentiating the grid frequency estimate.

[0073] Furthermore, the calculation expression for the power reference compensation amount is as follows: ; in, This is the power reference compensation amount. The nonlinear virtual inertia constant of the DC-side distributed generation unit. As the system reference power, The rated frequency of the power grid. This represents the rate of change of frequency.

[0074] Furthermore, the nonlinear virtual inertia constant is as follows: ; in, As the reference inertia constant, and For the grading threshold, The inertia gain coefficient, To limit the inertia to the maximum.

[0075] Furthermore, the method of simulating the collaborative aggregation inertia in a multi-bus topology by allocating the power reference compensation amount of each DC-side distributed generation unit through aggregation control includes: Calculate the total rated power and global rated power of the DC-side distributed generation units participating in the inertia simulation on each bus; Based on the total rated power and global rated power of a single bus, the initial power allocation coefficient of a single DC-side distributed generation unit is calculated, and the power reference compensation amount for adjusting a single DC-side distributed generation unit is determined according to the initial power allocation coefficient. The initial power allocation coefficient is dynamically determined according to the proportion of the rated power of the unit in the corresponding total rated power (the corresponding total rated power is: the total rated power of the bus where the unit is located under a single bus topology, and the global total rated power of the entire microgrid under a multi-bus topology). A multi-objective optimization function is constructed, which aims to maximize inertia aggregation efficiency, balance power output, and minimize line loss. An improved particle swarm optimization algorithm is used to optimize and solve the initial power allocation coefficients to obtain the optimal allocation coefficients. Adjust the power reference compensation amount of the corresponding DC-side distributed generation unit according to the optimal allocation coefficient to realize the collaborative aggregation inertia simulation of multiple buses and multiple DC-side distributed generation units.

[0076] Furthermore, the formula for calculating the total rated power of a single busbar is: ; in, This refers to the total rated power of a single busbar. This refers to the number of DC-side distributed generation units connected to a single busbar. This refers to the rated power of a single DC-side distributed generation unit on a single busbar. ; The formula for calculating the global rated power is: ; in, This is the global rated power. This refers to the number of DC-side distributed generation units connected to a single busbar. This refers to the number of DC buses. The rated power of the i-th DC-side distributed generation unit on the j-th bus; The formula for calculating the initial power allocation factor is: ; in, The initial power allocation factor, This is the global rated power; The formula for calculating the power reference compensation is: ; in, This is the power reference compensation amount. This refers to the real-time power grid frequency.

[0077] Furthermore, the multi-objective optimization function includes: Objective function for maximizing inertia pooling efficiency: ; DGU power output equalization objective function: ; Line loss minimization objective function: ; in, This is the power reference compensation amount. For the total compensation amount, Rated active power, Bus current, This represents the line impedance.

[0078] It should be understood that, since the above-described modules are merely for illustrating the functional units of the system disclosed herein, the physical devices corresponding to these modules may be the processor itself, or a part of the processor's software, hardware, or a combination of both. Therefore, the number of modules shown in the figures is merely illustrative.

[0079] To address the aforementioned technical problems, in a third aspect, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described distributed inertia simulation method for hybrid AC / DC microgrids.

[0080] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0081] like Figure 6 As shown, the computer / electronic device includes memory, processor, and network interface interconnected via a system bus. It should be noted that the figure only shows a computer device with components such as memory, processor, network interface, and operating system; however, it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer / electronic device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0082] Computers / electronic devices can be desktop computers, laptops, PDAs, and cloud servers, among other computing devices. They can interact with users through keyboards, mice, remote controls, touchpads, or voice-activated devices.

[0083] There may be one or more memories, and at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory may be an internal storage unit of a computer device, such as the hard disk or RAM of the computer device. In other embodiments, the memory may also be an external storage device of the computer device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on the computer device. Of course, the memory may include both internal storage units and external storage devices of the computer device. In this embodiment, the memory is typically used to store the operating system and various application software installed on the computer device, such as program code for a distributed inertia simulation method for a hybrid AC / DC microgrid. In addition, the memory may also be used to temporarily store various types of data that have been output or will be output.

[0084] In some embodiments, the processor may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor is typically used to control the overall operation of a computer device. In this embodiment, the processor is used to run program code stored in memory or process data, such as running program code for a distributed inertia simulation method for a hybrid AC / DC microgrid.

[0085] Network interfaces may include wireless network interfaces and / or wired network interfaces, which are typically used to establish communication connections between computer devices and other electronic devices.

[0086] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described distributed inertia simulation method for hybrid AC / DC microgrids.

[0087] The beneficial effects of this invention are as follows: Addressing the shortcomings of existing technologies, this invention proposes a distributed inertia simulation method, system, equipment, and storage medium for hybrid AC / DC microgrids. It solves the problems of insufficient DC bus capacitor inertia, voltage deviation, and the dependence of DGU inertia simulation on communication. Compared to other methods, it has the following advantages: No communication dependency, improved response reliability: By modulating the grid frequency information into the DC bus voltage using AC disturbance signals, frequency information transmission from the GTI to the DGU can be achieved without deploying communication equipment (such as optical fibers or wireless communication modules), completely avoiding communication delays, noise interference, and signal loss problems, and simplifying the system architecture. Simultaneously, it reduces the purchase, installation, and maintenance costs of communication equipment; the DC bus voltage is stable, mitigating system risks: the DC bus capacitor only serves as a transmission medium for frequency information and does not participate in the energy exchange for inertia support. The superposition of AC disturbance signals does not change the steady-state DC component of the DC bus voltage, ensuring that it is always maintained near the rated value. This effectively solves the equipment failure and system instability problems caused by voltage deviation in traditional capacitor inertia simulation methods, meeting the stringent requirements of the IEEE P2030.10 standard for DC bus voltage fluctuations; sufficient inertia support, adaptable to high-proportion RES scenarios: relying on the large-capacity energy storage characteristics of the DGU (compared to the DC bus... Line capacitors (DGUs can integrate energy storage from multiple RES, increasing capacity by more than an order of magnitude) provide ample inertia support, significantly reducing grid frequency and maximum RoCoF, effectively suppressing frequency fluctuations, and improving the system's tolerance to renewable energy power fluctuations; multi-topology adaptation enhances system scalability: through dynamic calculation of power allocation coefficients, the impact of line impedance differences in multi-bus radial topologies is offset, achieving collaborative inertia simulation of DGUs on different buses. When adding DGUs or expanding DC buses, there is no need to reconstruct the control logic or communication network; only the power allocation coefficients need to be updated, resulting in extremely strong system scalability; the control logic is simple, reducing... Engineering Implementation Difficulty: The CSOGI-PLL simplifies the frequency extraction process and avoids complex signal demodulation algorithms; the GTI PIR controller and DGU PI controller have clear structures and convenient parameters, eliminating the need for complex control loop designs, thus lowering the engineering implementation threshold and stability analysis difficulty; Strong Anti-interference Capability and Adaptability to Complex Operating Environments: The two-stage filtering structure of the CSOGI-PLL effectively suppresses DC offset and harmonic interference, and the sliding mode filter further smooths the RoCoF signal, ensuring that the calculation of frequency and power references is unaffected by complex operating conditions such as grid voltage distortion and load impact, thus ensuring the accuracy and stability of inertia simulation.

[0088] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0089] It will be readily understood by those skilled in the art that this invention includes any combination of the inventive description and specific embodiments outlined in the foregoing specification, as well as the various parts shown in the accompanying drawings. Due to space limitations and for the sake of brevity, not all of these combinations have been described in detail. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

[0090] Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A distributed inertia simulation method for hybrid AC / DC microgrids, characterized in that, include: An AC disturbance signal is generated by a grid-connected inverter and injected into the DC bus voltage to maintain the steady-state DC component of the DC bus voltage at its rated value. In the local controller of the interface converter of the DC-side distributed generation unit, the grid frequency information carried in the DC bus voltage is extracted by a cascaded second-order generalized integrator phase-locked loop, and the frequency change rate is calculated. Based on the frequency change rate and the nonlinear virtual inertia constant, the power reference compensation amount of the DC-side distributed generation unit is determined, the output power of the DC-side distributed generation unit is adjusted, and the virtual inertia simulation of the microgrid is realized. In a multi-bus radial topology, the power reference compensation amount of each DC-side distributed generation unit is allocated by aggregation control to realize the collaborative aggregation inertia simulation under the multi-bus topology.

2. The distributed inertia simulation method for hybrid AC / DC microgrids as described in claim 1, characterized in that, The step of generating an AC disturbance signal through a grid-connected inverter and injecting the AC disturbance signal into the DC bus voltage includes: The three-phase voltage signal from the grid side is collected, and the single-phase grid voltage is extracted in the local controller of the grid-connected inverter. The amplitude of the single-phase voltage is adjusted according to the preset amplitude coefficient to generate an AC disturbance signal carrying grid frequency information. The expression for single-phase grid voltage is extracted as follows: ； in, This is the voltage of a single-phase power grid. The voltage amplitude of the power grid. The angular frequency of the power grid is t, and time is t. The AC disturbance signal is as follows: ； in, For AC disturbance signals, The preset amplitude coefficient; Construct a DC bus voltage reference value that includes AC disturbances: ； in, This is the reference value for the DC bus voltage. This is the rated voltage of the DC bus.

3. The distributed inertia simulation method for hybrid AC / DC microgrids as described in claim 1, characterized in that, The cascaded second-order generalized integrator phase-locked loop includes two stages of second-order generalized integrators and phase-locked loops. The first-stage second-order generalized integrator is used to eliminate DC offset, and the second-stage second-order generalized integrator is used to generate based on the single-phase grid voltage signal. Reference voltage in coordinate system and The phase-locked loop extracts the frequency information from the three-phase voltage after model predictive control optimization, obtains the grid frequency estimate after sliding mode filtering, and obtains the frequency change rate by differentiating the grid frequency estimate.

4. The distributed inertia simulation method for hybrid AC / DC microgrids as described in claim 1, characterized in that, The power reference compensation amount is calculated using the following expression: ； in, This is the power reference compensation amount. The nonlinear virtual inertia constant of the DC-side distributed generation unit. As the system reference power, The rated frequency of the power grid. This represents the rate of change of frequency.

5. The distributed inertia simulation method for hybrid AC / DC microgrids as described in claim 1, characterized in that, The nonlinear virtual inertia constant is as follows: ； in, As the reference inertia constant, and For the grading threshold, The inertia gain coefficient, To limit the inertia to the maximum.

6. The distributed inertia simulation method for hybrid AC / DC microgrids as described in claim 1, characterized in that, The method of allocating power reference compensation amounts to each DC-side distributed generation unit through aggregation control to achieve collaborative aggregation inertia simulation under a multi-bus topology includes: Calculate the total rated power and global rated power of the DC-side distributed generation units participating in the inertia simulation on each bus; Based on the total rated power of a single bus and the global rated power, the initial power allocation coefficient of a single DC-side distributed generation unit is calculated, and the power reference compensation amount for adjusting a single DC-side distributed generation unit is determined according to the initial power allocation coefficient; the initial power allocation coefficient is dynamically determined according to the proportion of the rated power of the unit in the corresponding total rated power. A multi-objective optimization function is constructed, which aims to maximize inertia aggregation efficiency, balance power output, and minimize line loss. An improved particle swarm optimization algorithm is used to optimize and solve the initial power allocation coefficients to obtain the optimal allocation coefficients. Adjust the power reference compensation amount of the corresponding DC-side distributed generation unit according to the optimal allocation coefficient to realize the collaborative aggregation inertia simulation of multiple buses and multiple DC-side distributed generation units.

7. The distributed inertia simulation method for hybrid AC / DC microgrids as described in claim 6, characterized in that, The formula for calculating the total rated power of a single busbar is: ； in, The total rated power of a single busbar. This refers to the number of DC-side distributed generation units connected to a single busbar. , where is the rated power of a single DC-side distributed generation unit on a single bus, and k is the DC-side distributed generation unit corresponding to the UPS that does not participate in the inertia simulation; The formula for calculating the global rated power is: ； in, This is the global rated power. This refers to the number of DC-side distributed generation units connected to a single busbar. This refers to the number of DC buses. The rated power of the i-th DC-side distributed generation unit on the j-th bus; The formula for calculating the initial power allocation factor is: ； in, The initial power allocation factor, This is the global rated power; The formula for calculating the power reference compensation is: ； in, This is the power reference compensation amount. This refers to the real-time power grid frequency.

8. The distributed inertia simulation method for hybrid AC / DC microgrids as described in claim 6, characterized in that, The multi-objective optimization function includes: Objective function for maximizing inertia pooling efficiency: ; DGU power output equalization objective function: ; Line loss minimization objective function: ; in, This is the power reference compensation amount. For the total compensation amount, Rated active power, Bus current, This represents the line impedance.

9. The distributed inertia simulation method for hybrid AC / DC microgrids as described in claim 1, characterized in that, The grid-connected inverter adopts a dual-loop control strategy, with its outer loop being a proportional-integral-resonant voltage controller used to track the DC bus voltage reference value containing the AC disturbance signal and suppress harmonic components. Its inner loop is a proportional-integral current controller, used to regulate the grid-connected current; In the interface converter control link of the DC-side distributed generation unit, the frequency change rate signal is smoothed and the parameters of its current loop proportional-integral controller are optimized to ensure stable tracking of output power.

10. A distributed inertia simulation system for a hybrid AC / DC microgrid, characterized in that, include: The signal injection module is used to generate an AC disturbance signal through the grid-connected inverter and inject the AC disturbance signal into the DC bus voltage so that the steady-state DC component of the DC bus voltage is maintained at the rated value. The frequency extraction module is used to extract the grid frequency information carried in the DC bus voltage in the local controller of the interface converter of the DC-side distributed generation unit through a cascaded second-order generalized integrator phase-locked loop, and to calculate the frequency change rate. The power adjustment module is used to determine the power reference compensation amount of the DC-side distributed generation unit based on the frequency change rate and the nonlinear virtual inertia constant, adjust the output power of the DC-side distributed generation unit, and realize the virtual inertia simulation of the microgrid. The aggregation control module is used to distribute the power reference compensation amount of each DC-side distributed generation unit in a multi-bus radial topology through aggregation control, thereby realizing the collaborative aggregation inertia simulation under the multi-bus topology.

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