Micro-grid fault self-healing control and recovery method

Abstract

The invention provides a micro-grid fault self-healing control and recovery method, and relates to the technical field of power system distributed control, and the method comprises the steps: sampling a bus voltage waveform, calculating a real-time total harmonic distortion rate, carrying out the weight mapping of a prediction phase before a fault and a current measurement phase, and outputting a reference phase vector; calculating normalized physical conflict intensity, and generating a switching decision variable based on the deviation between the normalized physical conflict intensity and a preset threshold value; according to the jump state of the switching decision variable, characteristic current injection is triggered, a complex impedance characteristic value of a distributed unit port is identified, and a role grade index is generated; a droop control gain is configured according to the role level index, and a power adjustment vector is generated in combination with the frequency slip rate. According to the method, communication message interaction is replaced by logic evolution of physical characteristic quantity, and the method is used for self-healing control of the low-inertia micro-grid under the working condition of communication interruption.

Description

Technical Field

[0001] This invention relates to the field of distributed control technology for power systems, and particularly to a method for self-healing control and recovery of microgrid faults. Background Technology

[0002] With a high proportion of power electronic devices connected to the microgrid, the system exhibits significant characteristics of low inertia and weak damping. Existing microgrid self-healing technologies are generally built on a dual-coupling architecture of "information layer-physical layer," and heavily rely on high-speed communication networks to achieve state synchronization and control authorization among distributed units.

[0003] The core technical problem addressed in this invention is that, under conditions where extreme faults cause communication link interruptions or logic message loss due to high-intensity electromagnetic interference, the distributed units of a microgrid will lose external command support and become isolated. Due to the lack of a unified logical synchronization benchmark, each unit will experience physical uncertainties such as phase alignment deviations, master-slave control conflicts, and power flow disorder during the moment of disconnection and the subsequent self-healing process. These uncertainties can easily trigger huge transient circulating current impacts and frequency / voltage support collapse, leading to the failure of self-healing attempts and causing a chain reaction of system collapse. Summary of the Invention

[0004] This invention provides a microgrid fault self-healing control and recovery method to solve the problem that microgrid distributed units will lose external command support and become isolated when communication links are interrupted due to extreme faults or logic messages are lost due to high-intensity electromagnetic interference.

[0005] In view of the above problems, the present invention provides a microgrid fault self-healing control and recovery method, comprising the following steps: Phase feature acquisition steps: After sampling and acquiring the bus voltage waveform, calculate the real-time total harmonic distortion (THD) of the bus voltage waveform. Based on the numerical distribution of the real-time THD, perform weighted mapping between the pre-fault predicted phase vector and the current measured phase vector, and output a reference phase vector. State arbitration steps: Input the reference phase vector into the logic processing operation, calculate and obtain the normalized physical conflict strength, and generate switching decision variables based on the deviation between the normalized physical conflict strength and the preset threshold. Feature identification steps: Based on the jump state of the switching decision variable, trigger the feature current injection operation, and identify the complex impedance feature value of each distributed unit port based on the collected feature response current. Sort the magnitude values ​​of each complex impedance feature value and generate the corresponding role level index. Collaborative compensation steps: Configure the corresponding droop control gain according to the role level index, and generate a power adjustment vector by combining it with the monitored frequency slip rate; In the state arbitration step, the switching decision variable The calculation formula is: in: The normalized physical conflict intensity; The suppression coefficient is determined based on the real-time total harmonic distortion rate, and ,in The real-time total harmonic distortion rate; This is a preset safety constant; The preset action threshold, and satisfies ; This is the decision sensitivity coefficient. Sensitivity factor; The normalized physical conflict intensity The specific calculation formula is as follows: in: The angular deviation of the reference phase vector relative to the base vector. This is the reference value for the rated phase. This represents the instantaneous fluctuation amplitude vector of the bus voltage waveform. The reference value is the rated voltage. This is a preset dimensionless positive minimum constant.

[0006] Furthermore, the specific method for generating the reference phase vector in the phase feature acquisition step is as follows: Establish the correspondence between the real-time total harmonic distortion rate and the phase trust weight; when the real-time total harmonic distortion rate exceeds a preset threshold, increase the proportion of the pre-fault predicted phase vector in the weight mapping, and decrease the correction magnitude of the current measured phase vector to the reference phase vector.

[0007] Furthermore, the feature identification step specifically includes: When the switching decision variable exceeds the preset threshold, the characteristic current injection operation is driven; The magnitudes of the obtained complex impedance characteristic values ​​are arranged in descending order; The node with the largest modulus value is defined as the first control role, and the remaining nodes are defined as the second control roles, thus generating the corresponding role level index.

[0008] Furthermore, the collaborative compensation step specifically includes: Establish a mapping relationship between the role level index and the droop control gain; when the absolute value of the frequency slip rate is detected to be greater than the preset frequency protection threshold, adjust the amplitude vector of the bus voltage waveform.

[0009] Furthermore, the method operates under conditions where the communication link message transmission is interrupted or the transmission delay is greater than a preset time consumption threshold.

[0010] The technical solution provided in this application has at least the following technical effects: This method utilizes objective physical indicators such as transient characteristics of the bus voltage waveform, physical field conflict intensity, and port complex impedance fingerprints to establish a set of physical action triggering sequences within a millisecond-level spatiotemporal scale. This ensures that even under extreme constraints of complete communication blindness, the microgrid can still spontaneously complete timing alignment, identity establishment, and energy balance through the synchronous sensing and logical arbitration of local physical quantities by each node. This reconstructs the physical and logical foundation for low-inertia microgrids to achieve global deterministic collaborative self-healing in a loss-of-trust environment, guaranteeing the steady-state survival and recovery quality of the system under extreme disaster conditions. Attached Figure Description

[0011] Figure 1 This is a flowchart of the microgrid fault self-healing control and recovery method in an embodiment of the present invention. Detailed Implementation

[0012] The above technical solutions will now be described in detail with reference to the accompanying drawings and specific embodiments to provide a better understanding of them. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments used only to explain the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. Furthermore, it should be noted that, for ease of description, only the parts related to the present invention are shown in the drawings, not all of them.

[0013] For examples, please refer to Figure 1 The flowchart shown illustrates a microgrid fault self-healing control and recovery method. This invention provides a microgrid fault self-healing control and recovery method. The method includes a phase feature acquisition step, a state arbitration step, a feature identification step, and a collaborative compensation step.

[0014] In the phase feature acquisition step, after sampling and acquiring the bus voltage waveform, the microgrid control unit calculates the real-time total harmonic distortion (THD) of the bus voltage waveform. Based on the numerical distribution of the real-time THD, it performs a weighted mapping between the predicted phase vector before the fault and the currently measured phase vector, and outputs a reference phase vector. In the state arbitration step, the microgrid control unit inputs the reference phase vector into logic processing operations to calculate and acquire the normalized physical conflict strength. Based on the deviation between the normalized physical conflict strength and a preset threshold, it generates a switching decision variable. In the feature identification step, the microgrid control unit triggers a feature current injection operation according to the transition state of the switching decision variable. It identifies the complex impedance characteristic values ​​of each distributed unit port based on the acquired feature response current, sorts the magnitudes of each complex impedance characteristic value, and generates a corresponding role level index. In the collaborative compensation step, the microgrid control unit configures the corresponding droop control gain according to the role level index and generates a power regulation vector by combining it with the monitored frequency slip rate.

[0015] The acquisition of the bus voltage waveform is performed by hardware sampling circuits deployed at key nodes of the microgrid. These circuits capture instantaneous voltage signals during microgrid operation at a sampling frequency of 10 kHz and convert the analog signals into discrete bus voltage waveform data streams via a 16-bit analog-to-digital converter. To extract characteristic quantities reflecting waveform quality from the bus voltage waveform data stream, the microgrid control unit performs a full-wave Fourier transform within each 20 ms power frequency sliding window. By calculating the square root of the sum of squares of the effective values ​​of the 2nd to 31st harmonics in the bus voltage waveform data stream and comparing it with the fundamental effective value, the microgrid control unit calculates the real-time total harmonic distortion (THD). The real-time THD value is stored in the microgrid control unit's register in real time, serving as an input variable to drive subsequent weight mapping logic.

[0016] The generation of the pre-fault predicted phase vector is synchronously completed by the microgrid control unit based on historical operating data. The microgrid control unit continuously tracks the bus voltage frequency for the last five consecutive power frequency cycles before the fault triggers and determines the system's average reference angular frequency using a mean filtering algorithm. When a sudden change in the bus voltage waveform is detected and the real-time total harmonic distortion (THD) exceeds a preset interference threshold, the microgrid control unit locks the average reference angular frequency before the fault occurrence and uses the fault occurrence as the integration starting point. By performing time accumulation calculations on the average reference angular frequency, the pre-fault predicted phase vector is extrapolated. The pre-fault predicted phase vector represents the ideal phase evolution trajectory of the microgrid under conditions without physical disturbances and is unaffected by waveform distortion interference caused by fault transients.

[0017] The output of the reference phase vector relies on the dynamic adjustment logic of the real-time total harmonic distortion (THD) on the predicted phase vector before the fault and the currently measured phase vector. The microgrid control unit constructs a trust assessment mapping function to convert the real-time THD into a trust weight coefficient between 0 and 1. When the real-time THD is within a preset safe range, the trust weight coefficient is set to a high-order value, and the weight mapping logic primarily allocates the generation weight of the reference phase vector to the currently measured phase vector. If a fault causes the real-time THD to surge and exceed the preset safe range, the trust weight coefficient decreases with the trust assessment mapping function. The weight mapping logic then automatically increases the proportion of the predicted phase vector before the fault in the synthesis of the reference phase vector and simultaneously reduces the correction feedback gain of the currently measured phase vector on the reference phase vector. Through this dynamic weighting method based on the trust assessment mapping function, the microgrid control unit ensures that the reference phase vector maintains physical continuity in angle change even when the bus voltage waveform is severely distorted, providing a stable spatiotemporal reference for subsequent execution steps.

[0018] In a preferred embodiment, the trust evaluation mapping function is implemented by constructing a mapping model using an inverse hyperbolic tangent curve, specifically expressed as follows: ,in For trust weighting coefficient, This represents the real-time total harmonic distortion (THD). This is the preset distortion evaluation threshold. This is the preset curve steepness factor. When the real-time total harmonic distortion rate... Exceeding the distortion evaluation threshold At that time, the trust weight coefficient It rapidly approaches 0. The microgrid control unit follows the formula... Synthesize the reference phase vector. In the formula for synthesizing the reference phase vector: The reference phase vector; This is the trust weighting coefficient; The current measured phase vector; This refers to the predicted phase vector before the fault. The microgrid control unit achieves dynamic fitting of the physical field characteristics through the trust evaluation mapping function and the reference phase vector synthesis formula. When the bus voltage waveform undergoes severe distortion due to a short-circuit fault, causing the real-time total harmonic distortion rate to exceed the distortion evaluation threshold, the trust weight coefficient rapidly drops to 0 under the modulation of inverse hyperbolic tangent logic. In this state, the reference phase vector synthesis formula automatically increases the weight ratio of the predicted phase vector before the fault and simultaneously suppresses the correction feedback strength of the current measured phase vector on the reference phase vector.

[0019] The calculation of normalized physical conflict intensity is accomplished by the microgrid control unit by integrating the reference phase vector output from the phase feature capture step and the real-time acquired bus voltage amplitude vector. The microgrid control unit obtains the angular deviation by comparing the angular deviation between the reference phase vector and the grid reference phase vector, and simultaneously extracts the instantaneous fluctuation amplitude vector of the bus voltage amplitude vector relative to the rated voltage reference. To eliminate the impact of the dimensionless relationship between the angular deviation and the instantaneous fluctuation amplitude vector on decision accuracy, the microgrid control unit divides the angular deviation by the rated phase reference value and the instantaneous fluctuation amplitude vector by the rated voltage reference value, achieving dimensionless data processing.

[0020] The dimensionless squared term of the angular deviation and the squared term of the instantaneous fluctuation amplitude vector are fed into a summation operator for accumulation. During this process, the microgrid control unit introduces a preset dimensionless positive minimum constant into the accumulation result. This ensures that subsequent square root operations have real solutions under any numerical conditions and prevents the values ​​within the square root from diverging. The specific normalization physical conflict strength... The calculation process strictly follows the following formula: in, For angular deviation, The rated phase reference value, This is the vector of instantaneous fluctuation amplitude. This is the reference value for rated voltage. The physical conflict strength is normalized. The normalized physical conflict intensity calculated by the formula directly quantifies the intensity of electromagnetic oscillations in the physical field of the microgrid.

[0021] After obtaining the normalized physical conflict intensity, the microgrid control unit further introduces a suppression coefficient generated based on the real-time total harmonic distortion rate (THD). The microgrid control unit inputs the suppression coefficient and the normalized physical conflict intensity into the logic processing operation, and uses a pre-set exponential logic function within the logic processing operation to generate switching decision variables.

[0022] To prevent numerical collapse due to extremely low normalization physical conflict intensity leading to a zero denominator in the calculation process, the microgrid control unit adds a preset safety constant to the denominator term of the division operation. Specific switching decision variables The generation logic is implemented through the following formula: In this calculation process, increasing the normalized physical conflict intensity will increase the ratio value, while decreasing the suppression coefficient (representing a decrease in sampling confidence) will also increase the ratio value, thus achieving a positive correlation between fault severity and trigger probability. The suppression coefficient is, and ,in This represents the real-time total harmonic distortion (THD). Sensitivity factor This is the decision sensitivity coefficient. The preset action threshold, and satisfies , The selection range is typically set between 0.7 and 0.9, and is increased synchronously as the inertia level of the microgrid system decreases to ensure robustness of decision-making under extremely low inertia conditions. This is due to the suppression coefficient... This reflects the confidence level of the waveform, while the normalized physical conflict strength... This reflects the intensity of the energy field disturbance; the ratio of the two is determined by the decision sensitivity coefficient. After modulation, the switching decision variables generated through logical processing can exhibit clear transition characteristics in the range of 0 to 1.

[0023] The numerical state of the switching decision variable directly defines the criterion for the transformation of the microgrid's physical field from a transient unstable state to a logically controllable state. The microgrid control unit compares the magnitude of the switching decision variable with the preset action threshold in real time. When the value of the switching decision variable is lower than the preset action threshold, the microgrid control unit determines that the physical field is still in a transient disorder stage, maintains the current phase inertia operation mode, and blocks any hardware trigger pulses. Once the value of the switching decision variable calculated by the formula rises and exceeds the preset action threshold, the microgrid control unit determines that the physical field has achieved energy convergence, and the logic gate immediately switches from the closed state to the enabled state. The enabled state of the logic gate directly triggers the hardware drive pulse generation circuit in the subsequent feature identification step, thereby realizing closed-loop control at the physical level where the stable state of the physical field drives the self-healing logic evolution.

[0024] The feature identification step is directly driven by the switching decision variables. The microgrid control unit performs a feature signal injection operation by modulating the pulse width modulation signal of the inverter interface inside the distributed unit. The specific physical path of the feature signal injection operation is as follows: the microgrid control unit controls the power switching devices of the inverter arm of the distributed unit to generate a high-frequency carrier offset, thereby superimposing a characteristic frequency current of 175Hz at the microgrid port. Since the feature signal injection operation is implemented directly using the existing converter power topology, no additional hardware bypass circuit is required. During the execution of the feature signal injection operation, the microgrid control unit obtains the characteristic response current waveform through the current transformer and extracts the magnitude of the complex impedance eigenvalue using an orthogonal vector decomposition algorithm.

[0025] Following the characteristic current injection operation, the microgrid control unit acquires the characteristic response current waveforms generated at each distributed unit port in real time via current transformers. The microgrid control unit uses an orthogonal vector decomposition algorithm to decompose the characteristic response current waveforms into an active component in phase with the port voltage and a reactive component out of phase by 90 electrical degrees. By calculating the ratio of the port voltage vector to the active component of the characteristic response current waveform, the microgrid control unit determines the resistance component in the complex impedance characteristic value; by calculating the ratio of the port voltage vector to the reactive component of the characteristic response current waveform, the microgrid control unit determines the reactance component in the complex impedance characteristic value. Subsequently, the microgrid control unit performs a summation and square root operation on the squares of the resistance and reactance components to finally synthesize the magnitude of the complex impedance characteristic value.

[0026] The generation of the role-level index is based on an objective sorting logic of the magnitudes of the complex impedance characteristic values ​​calculated for each distributed unit. The microgrid control unit compares the magnitude of the complex impedance characteristic value obtained by its node with the impedance benchmark of adjacent nodes preset in its local register, or performs a descending sorting operation under the condition of local sharing. In the sorting logic, the distributed unit with the largest magnitude of the complex impedance characteristic value is automatically defined as the first control role by the microgrid control unit, and the remaining distributed units with smaller magnitudes of the complex impedance characteristic value are defined as the second control role. The allocation result of the role-level index is written to the status register of the microgrid control unit in real time, serving as the sole basis for configuring control gains in subsequent collaborative compensation steps. Since the magnitude of the complex impedance characteristic value directly reflects the electrical distance and support capability of the distributed unit in the physical topology, this sorting mechanism based on physical attributes ensures that the unique division of master-slave control authority can still be achieved within the microgrid even under conditions without external communication negotiation.

[0027] The execution of the collaborative compensation step begins with the microgrid control unit automatically mapping and configuring internal control gains based on role-level indices. The microgrid control unit reads the role-level index from the status register and extracts the corresponding droop control gain from a preset parameter mapping table based on the index value. For distributed units assigned to the first control role, the microgrid control unit switches its control architecture to voltage-frequency support mode or adjusts the droop control gain to a high slope coefficient state, thus giving the first control role the ability to establish a voltage reference and dominate the frequency during the initial stage of islanded operation. For the remaining distributed units assigned to the second control role, the microgrid control unit maintains its original power-following mode or configures the droop control gain to a low slope coefficient state. Through this differentiated parameter configuration based on role-level indices, the microgrid control unit establishes the priority of each node in energy regulation at the physical level, eliminating logical conflicts caused by multiple master stations operating in parallel.

[0028] Real-time monitoring of the frequency slip ratio provides a dynamic trigger boundary for the activation of the power regulation vector. The microgrid control unit continuously calculates the frequency slip ratio by performing a first-order derivative operation on the sampled voltage and frequency. To determine whether there is an energy imbalance caused by sudden load changes, the microgrid control unit extracts the absolute value of the frequency slip ratio and compares it with a preset action threshold. When the microgrid is operating stably and the absolute value of the frequency slip ratio is within the preset action threshold range, the microgrid control unit blocks the output of the power regulation vector. Once the absolute value of the frequency slip ratio is detected to exceed the preset action threshold, the microgrid control unit determines that the microgrid has entered an energy imbalance state and immediately releases the blocking command for the power regulation vector. This dynamic monitoring mechanism based on the absolute value of the frequency slip ratio ensures that the power backflow compensation action is triggered only when the physical evolution trend reaches a critical point.

[0029] The physical balance of cross-regional energy gradients is achieved through the generation and issuance of the final power command vector. The microgrid control unit generates a power regulation vector based on the local frequency deviation vector and the action polarity determined by the frequency slip ratio, through proportional-integral operations or logical mapping. This power regulation vector includes active and reactive power compensation components and acts as a specific electrical command on the converter's pulse-width modulation module. Because the first control role has a higher droop control gain, it prioritizes adjusting the voltage vector amplitude and output frequency according to the power regulation vector, guiding the second control role to participate in energy distribution. Through this collaborative response method based on physical gradient evolution, the microgrid achieves steady-state recovery of voltage and frequency in an environment without communication message support.

[0030] The self-healing effect under extreme conditions was verified on a simulated microgrid test platform equipped with a high proportion of power electronic converters. The simulation of communication link interruption was achieved by artificially disconnecting the fiber optic transceiver or injecting message delay interference into the communication gateway. The microgrid control unit monitors the status feedback of the communication port in real time. When the message transmission delay exceeds a preset time consumption threshold or the physical link feedback signal is lost, the microgrid control unit automatically cuts off its dependence on remote dispatch commands and instantaneously triggers a phase characteristic acquisition step. Through this switching mechanism, the microgrid control unit transfers system control from remote dispatch mode to an autonomous mode based on local physical quantity characteristic mapping.

[0031] In a low-inertia system environment, a comparison of impact suppression indices under different fault conditions demonstrates the physical performance of the microgrid fault self-healing control and recovery method. Under a single-phase-to-ground short-circuit fault of the same intensity, the traditional communication-dependent self-healing method results in a deviation between the control reference phase of the distributed unit and the actual transient phase of the power grid due to communication message delays. This leads to an inrush current amplitude exceeding three times the rated current, and continuous oscillations in the bus voltage frequency. In contrast, the microgrid fault self-healing control and recovery method allows the microgrid control unit to reconstruct the reference phase vector within the first power frequency cycle after disconnection via phase feature acquisition and state arbitration steps. Experimental current waveform curves show that the peak inrush current is suppressed to within 1.2 times the rated current.

[0032] Meanwhile, because the collaborative compensation step allocates energy based on the role level index, the transient fluctuation range of the bus voltage frequency is limited to within ±0.2Hz and recovers to the steady-state operating range within 0.1 seconds. Through quantitative comparison of impact suppression indices, it is demonstrated that the microgrid fault self-healing control and recovery method still possesses physical determinism in maintaining microgrid operational stability even under conditions of communication message transmission interruption.

[0033] 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; and these 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 method for self-healing control and recovery of microgrid faults, characterized in that, Includes the following steps: Phase feature acquisition steps: After sampling and acquiring the bus voltage waveform, calculate the real-time total harmonic distortion (THD) of the bus voltage waveform. Based on the numerical distribution of the real-time THD, perform weighted mapping between the pre-fault predicted phase vector and the current measured phase vector, and output a reference phase vector. State arbitration steps: Input the reference phase vector into the logic processing operation, calculate and obtain the normalized physical conflict strength, and generate switching decision variables based on the deviation between the normalized physical conflict strength and the preset threshold. Feature identification steps: Based on the jump state of the switching decision variable, trigger the feature current injection operation, and identify the complex impedance feature value of each distributed unit port based on the collected feature response current. Sort the magnitude values ​​of each complex impedance feature value and generate the corresponding role level index. Collaborative compensation steps: Configure the corresponding droop control gain according to the role level index, and generate a power adjustment vector by combining it with the monitored frequency slip rate.

2. The microgrid fault self-healing control and recovery method according to claim 1, characterized in that, In the state arbitration step, the switching decision variable The calculation formula is: in: The normalized physical conflict intensity; The suppression coefficient is determined based on the real-time total harmonic distortion rate, and ,in The real-time total harmonic distortion rate; This is a preset safety constant; The preset action threshold, and satisfies ; This is the decision sensitivity coefficient. Sensitivity factor; The normalized physical conflict intensity The specific calculation formula is as follows: in: The angular deviation of the reference phase vector relative to the base vector. This is the reference value for the rated phase. This represents the instantaneous fluctuation amplitude vector of the bus voltage waveform. The reference value is the rated voltage. This is a preset dimensionless positive minimum constant.

3. The microgrid fault self-healing control and recovery method according to claim 1, characterized in that, The specific method for generating the reference phase vector in the phase feature capture step is as follows: Establish the correspondence between the real-time total harmonic distortion rate and the phase trust weight; when the real-time total harmonic distortion rate exceeds a preset threshold, increase the proportion of the pre-fault predicted phase vector in the weight mapping, and decrease the correction magnitude of the current measured phase vector to the reference phase vector.

4. The microgrid fault self-healing control and recovery method according to claim 1, characterized in that, The feature identification step is specifically as follows: When the switching decision variable exceeds the preset threshold, the characteristic current injection operation is driven; The magnitudes of the obtained complex impedance characteristic values ​​are arranged in descending order; The node with the largest modulus value is defined as the first control role, and the remaining nodes are defined as the second control roles, thus generating the corresponding role level index.

5. The microgrid fault self-healing control and recovery method according to claim 1, characterized in that, The specific steps of the collaborative compensation are as follows: Establish a mapping relationship between the role level index and the droop control gain; when the absolute value of the frequency slip rate is detected to be greater than the preset frequency protection threshold, adjust the amplitude vector of the bus voltage waveform.

6. The microgrid fault self-healing control and recovery method according to any one of claims 1 to 5, characterized in that, The method operates under conditions where the communication link message transmission is interrupted or the transmission delay is greater than a preset time consumption threshold.

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