Intelligent power distribution control method and system for power distribution cabinet

Abstract

The application discloses a kind of intelligent power distribution control method and system of switchboard, it is related to intelligent switchboard technical field.The present application includes the voltage and current signal of the grid-connected point of switchboard, extracts fundamental electrical quantity and each harmonic voltage amplitude;According to the equivalent impedance angle of grid-connected point calculated according to the fundamental electrical quantity, the voltage unbalance degree and its rate of change are calculated according to the fundamental component of three-phase voltage, according to each harmonic voltage amplitude Construction harmonic energy distribution characteristics, and according to the voltage-reactive sensitivity calculated by reactive power regulation disturbance;The present application simultaneously uses the detection means of four dimensions of impedance angle criterion, three-phase voltage unbalance degree criterion, harmonic energy distribution criterion and voltage-reactive sensitivity criterion, and determines island state by voting comprehensive decision mechanism.When three or more of the four criteria output suspected island signal, it is confirmed that island, effectively avoid the problem that single criterion is easily ineffective under certain working conditions, significantly improve the accuracy and reliability of island detection.

Description

Technical Field

[0001] This invention belongs to the field of intelligent power distribution cabinet technology, and in particular relates to an intelligent power distribution control method and system for power distribution cabinets. Background Technology

[0002] With the large-scale grid connection of renewable energy sources such as distributed photovoltaic power generation, the distribution cabinet, as a key interface device between the power grid and distributed power sources, directly affects power supply security and power quality through its intelligent power distribution control capabilities. Islanding is a core safety issue faced by distributed generation systems operating in the grid—when the grid is interrupted due to faults or maintenance, if the distributed power source continues to supply power to local loads, an island is formed that is not controlled by the grid. Islanding can lead to voltage and frequency instability, damage to electrical equipment, and even endanger the safety of maintenance personnel. Therefore, grid-connected power generation systems must possess rapid and accurate islanding detection and anti-islanding capabilities.

[0003] Currently, islanding detection methods are mainly divided into two categories: passive detection and active detection. Passive detection methods identify islanding by monitoring changes in electrical quantities such as voltage, frequency, phase, or harmonics at the point of common coupling. Their advantages include simplicity, no disturbance to the power grid, and no impact on power quality. However, passive methods have a significant detection blind spot—when the output power of distributed generation is well matched with the local load power, the changes in voltage and frequency are very small, making it difficult to effectively trigger passive criteria; furthermore, their detection threshold is difficult to set reasonably, easily leading to missed detections or false positives.

[0004] Active detection methods identify islanding by injecting disturbance signals such as frequency, phase, or reactive power into the grid and utilizing the differences in the system's response to disturbances after islanding occurs. While active methods reduce the detection blind zone to some extent, their inherent drawbacks are also prominent: on the one hand, continuously injected disturbances can degrade the grid-connected current waveform, increase harmonic distortion, and affect power quality; on the other hand, in scenarios with multiple inverters operating in parallel, the disturbance signals injected by each inverter may interfere with or even cancel each other out, leading to detection failure. Furthermore, existing methods mostly rely on single-criteria decision-making, resulting in insufficient reliability and adaptability under complex operating conditions.

[0005] Therefore, there is an urgent need for a smart power distribution control solution for power distribution cabinets that can achieve high reliability and blind-spot-free islanding detection while ensuring power quality. Summary of the Invention

[0006] The purpose of this invention is to provide a smart power distribution control method and system for power distribution cabinets that can more reliably detect islanding effects.

[0007] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution: This invention relates to an intelligent power distribution control method for a power distribution cabinet, comprising: Collect voltage and current signals at the grid connection point of the distribution cabinet, and extract the fundamental electrical quantity and the amplitude of each harmonic voltage; The equivalent impedance angle at the grid connection point is calculated based on the fundamental electrical quantities. The voltage unbalance and its rate of change are calculated based on the fundamental components of the three-phase voltage. The harmonic energy distribution characteristics are constructed based on the amplitudes of each harmonic voltage. The voltage-reactive power sensitivity is calculated based on the reactive power regulation disturbance. The detection results of impedance angle criterion, unbalance criterion, harmonic criterion and sensitivity criterion are combined to make a decision, and protection control actions are executed when the island is determined.

[0008] Furthermore, the impedance angle criterion obtains the current impedance angle by subtracting the fundamental current phase from the fundamental voltage phase. Combining the mean and standard deviation of historical impedance angles, when the current impedance angle deviates from the mean by more than 5 times the standard deviation and the deviation direction is consistent for 5 consecutive cycles and the absolute value of the deviation is greater than 12°, a suspected islanding signal is output.

[0009] Furthermore, the unbalance criterion is to extract positive and negative sequence voltage components using the symmetrical component method to calculate the voltage unbalance. When the unbalance is greater than 5% and the rate of change is greater than 2% for more than 3 consecutive cycles, a suspected islanding signal is output.

[0010] Furthermore, the harmonic criterion constructs a harmonic energy distribution vector by the ratio of each harmonic voltage amplitude to the fundamental voltage amplitude, calculates the cosine similarity between the measured fingerprint and the reference fingerprint, and outputs a suspected island signal when the similarity is lower than a set threshold or the similarity is lower than another threshold and the deviation of the odd harmonic energy ratio exceeds 30%.

[0011] Furthermore, the reference fingerprint is calculated every 15 minutes for the first 48 hours after commissioning, and the arithmetic mean is taken to obtain the initial reference fingerprint. Subsequently, it is dynamically updated according to the weighted update formula.

[0012] Furthermore, the voltage-reactive power sensitivity criterion calculates the sensitivity by measuring the reactive power and bus voltage changes before and after the reactive power regulation disturbance. When the sensitivity calculation results are both greater than 3 times the historical average, a suspected islanding signal is output.

[0013] Furthermore, the comprehensive decision-making process is as follows: the output results of the impedance angle criterion, unbalance criterion, harmonic criterion, and sensitivity criterion are voted and scored. When the total score is greater than or equal to 3, it is confirmed as an island. When the total score is equal to 2, it is re-voted after a delay. When the total score is less than or equal to 1, it is judged as normal.

[0014] Furthermore, the protection control actions include: issuing a PWM blocking command within 5ms after confirming islanding, activating the damping discharge resistor when the bus voltage exceeds the limit, issuing a tripping command after a 50ms delay, and confirming the tripping status through auxiliary contacts and electrical quantities. It also includes a synchronization reclosing step: during the circuit breaker opening period, the grid side voltage is monitored. When the grid voltage and frequency recover to the set range and remain stable for 200ms, the voltage difference, frequency difference and phase difference between the grid side and the bus side are measured. When the set conditions are met and the condition remains stable for 100ms, a closing command is issued.

[0015] Furthermore, it also includes an adaptive threshold tuning step: the first 48 hours after the power distribution cabinet is put into operation is a self-learning phase, during which the maximum or minimum values ​​of the relevant parameters of each criterion are collected, the threshold of each criterion is tuned according to the set multiple and stored in non-volatile memory for subsequent detection.

[0016] A smart power distribution control system for a power distribution cabinet is provided, which uses the aforementioned method to achieve intelligent power distribution control of the power distribution cabinet.

[0017] The present invention has the following beneficial effects: This invention employs four detection methods simultaneously: impedance angle criterion, three-phase voltage imbalance criterion, harmonic energy distribution criterion, and voltage-reactive power sensitivity criterion. A voting-based comprehensive decision-making mechanism is used to determine islanding status. Islanding is confirmed when three or more of the four criteria output suspected islanding signals. This effectively avoids the problem of single criteria failing under specific operating conditions, significantly improving the accuracy and reliability of islanding detection.

[0018] This invention primarily employs passive detection methods such as impedance angle analysis, voltage imbalance analysis, and harmonic energy distribution analysis. It eliminates the need for continuous injection of disturbance signals into the power grid, thus avoiding the distortion of the grid-connected current waveform and increased harmonic pollution caused by active detection methods. Only a controllable, short-duration reactive power regulation disturbance is used in the voltage-reactive power sensitivity criterion; the disturbance amplitude is small, the duration is short, and its impact on power quality is negligible.

[0019] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1This is a flowchart of the method mentioned in this invention. Detailed Implementation

[0022] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0023] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0024] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0026] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0028] Please see Figure 1 As shown, the present invention is an intelligent power distribution control method for a power distribution cabinet; As an embodiment of this application, it specifically includes: Collect voltage and current signals at the grid connection point of the distribution cabinet, and extract the fundamental electrical quantity and the amplitude of each harmonic voltage; The equivalent impedance angle at the grid connection point is calculated based on the fundamental electrical quantities. The voltage unbalance and its rate of change are calculated based on the fundamental components of the three-phase voltage. The harmonic energy distribution characteristics are constructed based on the amplitudes of each harmonic voltage. The voltage-reactive power sensitivity is calculated based on the reactive power regulation disturbance. The detection results of impedance angle criterion, unbalance criterion, harmonic criterion and sensitivity criterion are combined to make a decision, and protection control actions are executed when the island is determined.

[0029] As a second embodiment of this application, this embodiment provides an intelligent power distribution control method, including the following steps: Step 1: Data Acquisition and Preprocessing; The three-phase voltage signals ua, ub, uc and the three-phase current signals ia, ib, ic of the distribution cabinet grid connection point are collected synchronously at a sampling rate of 256 sampling points per cycle; for 50Hz power frequency signals, the sampling frequency is 12800Hz. Perform a fast Fourier transform on 256 sampling points for each power frequency cycle, and extract the fundamental voltage amplitude U1 and phase φu1, the fundamental current amplitude I1 and phase φi1, and the voltage amplitudes Uk of each harmonic from the 2nd to the 50th order from the transform results, k=2, 3, ..., 50; Before processing each cyclic data, first verify whether the three-phase voltage is within 50%-120% of the rated value and whether the three-phase current exceeds 120% of the rated secondary value; If three consecutive cycles of data are invalid, the sampling system is deemed faulty, all criteria are locked, and an alarm is issued.

[0030] Step 2: Analyze the equivalent impedance angle at the grid connection point. The specific analysis method is as follows: Subtracting the fundamental current phase from the fundamental voltage phase yields the current grid connection point equivalent impedance angle φZ, where φZ = φu1 - φi1. Store the historical impedance angle data for the most recent 100 cycles in memory and calculate their arithmetic mean μφ and standard deviation σφ.

[0031] When all three of the following conditions are met: (1) The absolute value of the current impedance angle deviating from the historical average is greater than or equal to 5 standard deviations, i.e., |φZ-μφ|≥5σφ; (2) The deviation direction remains consistent for 5 consecutive cycles, that is, the difference between φZ-4, ..., φZ and μφ is always positive or negative. (3) The absolute value of the deviation is greater than 12°, that is, |φZ-μφ|>12°; The impedance angle criterion outputs D1=1, indicating a suspected island; otherwise, it outputs D1=0.

[0032] Step 3: Analyze the three-phase voltage imbalance. The specific analysis method is as follows: The voltage unbalance ε is calculated by extracting the positive and negative sequence components from the fundamental voltage phasor using the symmetrical component method. ε = (Negative sequence component amplitude / Positive sequence component amplitude) × 100% Calculate the rate of change of imbalance dε / dt = current cycle ε - previous cycle ε; When all three of the following conditions are met: (1) ε>5%; (2) dε / dt > 2% / cycle; (3) The above two conditions are met consecutively for more than 3 cycles; The imbalance criterion outputs D2=1, indicating a possible island; otherwise, it outputs D2=0.

[0033] Step 4: Calculate the harmonic energy distribution characteristics; The harmonic energy distribution vector H = [h2, h3, ..., h3] is constructed from the amplitudes of each harmonic voltage. 50 ], where h k =U k / U1×100%; Establish reference fingerprint HR: H is calculated every 15 minutes during the first 48 hours after commissioning, and the arithmetic mean of all results is taken as the initial reference fingerprint. After normal operation, the reference fingerprint Hr is updated with weighted average according to Hr_new=0.95×Hr_old+0.05×Hc; here Hr_new refers to the updated reference fingerprint value calculated according to the formula, and Hr_old refers to the reference fingerprint value before the update. Calculate the cosine similarity S between the measured fingerprint and the reference fingerprint; Calculate the energy proportion of odd harmonics and their deviation rate ΔRd from the reference fingerprint. Odd harmonics refer to the 1st, 3rd, 5th, 7th, and 9th harmonics. When any of the following conditions are met: (1) S < 0.85 and lasts for more than 5 cycles; (2) S < 0.90 and ΔRd > 30%; If the standard deviation of a certain harmonic frequency exceeds 50% of its average value within 24 hours, the frequency will be automatically blocked from the fingerprint. The harmonic criterion outputs D3=1, indicating a suspected island; otherwise, it outputs D3=0.

[0034] Step 5: Calculate voltage-reactive power sensitivity; When the reactive power compensation device performs reactive power regulation, or when there is no regulation for 5 consecutive minutes, it actively sends a disturbance accounting for 10% of the rated compensation capacity, and records the reactive power Q1, Q2 and bus voltage U1, U2 before and after the regulation. Calculate the voltage-reactive power sensitivity SV = |U2-U1| / |Q2-Q1|.

[0035] Store the most recent 50 sensitivity calculation results and calculate the historical average value in μS. When two consecutive sensitivity calculation results are both greater than 3 times the historical average value, output D4=1 directly to indicate a suspected island; otherwise, output D4=0 as the sensitivity criterion. Step Six: Make a comprehensive decision; Summarize the outputs of the four criteria and calculate the total voting score V = D1 + D2 + D3 + D4; When V≥3, it is confirmed as an isolated event, proceed to step seven; When V=2, a new vote is held after a 100ms delay. If V≥2 is still present, the island is confirmed as isolated. When V≤1, it is considered normal.

[0036] If any sensor fails, the fault criterion is removed, and the remaining criteria are subject to a consistent rule. If there are fewer than two valid criteria, detection is locked and an alarm is triggered.

[0037] Step 7: Control Execution Once the island is confirmed, a PWM lockout command is sent to all inverters via hardwired within 5ms; Detect the bus voltage Ubus. If Ubus > 1.05Un, connect the damping discharge resistor with a resistance value R = Un. 2 / Pn (Pn is 5% of the rated capacity of the distribution cabinet), disconnect after the voltage drops below 1.02Un; After a 50ms delay, a tripping command is sent to the grid-connected circuit breaker, and the tripping status is confirmed by both auxiliary contacts and electrical quantities.

[0038] Step 8: Check the synchronization reclosing; During the circuit breaker tripping period, the grid voltage is continuously monitored. When the grid voltage recovers to 85%~110% of its rated value, the frequency is within the range of 49.5Hz~50.5Hz, and this recovery lasts for 200ms, the grid is considered restored.

[0039] Measure the voltage difference ΔU, frequency difference Δf, and phase difference Δθ between the grid side and the bus side. When ΔU < 5%Un, Δf < 0.2Hz, and Δθ < 5° and remain stable for 100ms, a closing command is issued. If the conditions are not met within 60 seconds, closing is stopped and an alarm is triggered.

[0040] Example 3 The difference between this embodiment and Embodiment 2 lies in the different triggering method of step five.

[0041] In this embodiment, the distribution cabinet is not equipped with a static var generator, but only with a capacitor bank. Step five is performed as follows: Sensitivity calculations are triggered by a periodic switching mechanism of the capacitor bank. The capacitor bank switching operation is performed automatically every 5 minutes, switching only one set of capacitors with the smallest capacity (1 / 10 of the total reactive power compensation capacity) each time. The reactive power Q1 and Q2 and the bus voltage U1 and U2 before and after the switching are recorded, and the sensitivity is calculated using SV = |U2-U1| / |Q2-Q1|.

[0042] The remaining steps are the same as in Example 1.

[0043] Example 4 The difference between this embodiment and embodiment two lies in the implementation method of step six. This embodiment adds adaptive weight adjustment for the corresponding line; the specific method in this embodiment is as follows: When the corresponding power distribution cabinet is in an islanded state (i.e., when a fault occurs), which criterion prioritizes the output of the suspected islanding signal, i.e., the one that first obtains D... i =1, where i = 1, ..., 4; the priority number of each criterion is counted and marked as Yi, i = 1, ..., 4, where Yi corresponds one-to-one with Di, corresponding to the criterion of this type; At the same time, the error rate of each criterion output is obtained, that is, if the output D i =1, but no islanding effect occurred, indicating one error. Similarly, if the output is D i =0, but at this point the island effect occurs, which also represents one error. Divide the number of errors by the total number of errors to get the error rate, and label it as Loi, i=1, ...,4. Here Loi and D i One-to-one correspondence, corresponding to the type criterion; Perform comprehensive value calculation, the calculation method is as follows: Overall value = Yi × (1 - Loi); Then, D is ranked from largest to smallest based on its comprehensive value. i Sort according to D i The values ​​are sequentially assigned to 2, 1.5, 1, and 0.8; thus obtaining the corresponding D for each criterion. i The weights are assigned to D and labeled as Gi, i = 1, ..., 4. Here, Gi and D are related. i It is a one-to-one correspondence; V = G1×D1 + G2×D2 + G3×D3 + G4×D 4； The remaining determination methods are consistent with those in Example 1; Example 5 The difference between this embodiment and Embodiment 2 is that an adaptive threshold tuning function has been added.

[0044] The first 48 hours after the distribution cabinet is put into operation is the self-learning phase, during which steps one through five are executed in full, but steps six through eight are not executed.

[0045] After the learning process ends, the following values ​​are obtained: The standard deviation coefficient of the impedance angle is taken as twice the maximum deviation value within 48 hours, with a setting range of 3-8 times. The absolute value threshold for impedance angle deviation is set to three times the average deviation over 48 hours, with a setting range of 8°-20°. The imbalance threshold is set to twice the maximum imbalance within 48 hours, with a tuning range of 3%-8%. The harmonic similarity threshold is set to 0.9 times the minimum similarity within 48 hours, with an adjustment range of 0.75-0.95.

[0046] The adjusted threshold is stored in non-volatile memory and used to replace the default value for subsequent detection. When there are significant changes in the grid connection point topology, relearning can be triggered via background commands.

[0047] Using the method described in the above embodiments of the present invention, the islanding detection time in simulated grid outage tests ranges from 120 milliseconds to 350 milliseconds. Under all test conditions, islanding events were successfully detected regardless of changes in photovoltaic output from 0 to 100%, local load from 10% to 100%, or power factor from 0.7 to 1.0, with no detection blind spots.

[0048] Of course, based on the above embodiments, this application also provides an intelligent power distribution control system for power distribution cabinets, which uses the method provided in any of the above embodiments to perform intelligent power distribution control of the power distribution cabinets.

[0049] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," 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, 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.

[0050] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for intelligent power distribution control of a power distribution cabinet, characterized in that, include: Collect voltage and current signals at the grid connection point of the distribution cabinet, and extract the fundamental electrical quantity and the amplitude of each harmonic voltage; The equivalent impedance angle at the grid connection point is calculated based on the fundamental electrical quantities. The voltage unbalance and its rate of change are calculated based on the fundamental components of the three-phase voltage. The harmonic energy distribution characteristics are constructed based on the amplitudes of each harmonic voltage. The voltage-reactive power sensitivity is calculated based on the reactive power regulation disturbance. The detection results of impedance angle criterion, unbalance criterion, harmonic criterion and sensitivity criterion are combined to make a decision, and protection control actions are executed when the island is determined.

2. The intelligent power distribution control method for a power distribution cabinet according to claim 1, characterized in that, The impedance angle criterion is obtained by subtracting the fundamental current phase from the fundamental voltage phase to obtain the current impedance angle. Combined with the mean and standard deviation of historical impedance angles, when the current impedance angle deviates from the mean by more than 5 times the standard deviation and the deviation direction is consistent for 5 consecutive cycles and the absolute value of the deviation is greater than 12°, a suspected islanding signal is output.

3. The intelligent power distribution control method for a power distribution cabinet according to claim 1, characterized in that, The unbalance criterion is calculated by extracting positive and negative sequence voltage components using the symmetrical component method. When the unbalance is greater than 5% and the rate of change is greater than 2% for more than 3 consecutive cycles, a suspected islanding signal is output.

4. The intelligent power distribution control method for a power distribution cabinet according to claim 1, characterized in that, The harmonic criterion constructs a harmonic energy distribution vector by the ratio of each harmonic voltage amplitude to the fundamental voltage amplitude, calculates the cosine similarity between the measured fingerprint and the reference fingerprint, and outputs a suspected island signal when the similarity is lower than a set threshold or the similarity is lower than another threshold and the deviation of the odd harmonic energy ratio exceeds 30%.

5. The intelligent power distribution control method for a power distribution cabinet according to claim 4, characterized in that, The reference fingerprint is calculated every 15 minutes for the first 48 hours after commissioning, and the arithmetic mean is taken to obtain the initial reference fingerprint. Subsequently, it is dynamically updated according to the weighted update formula.

6. The intelligent power distribution control method for a power distribution cabinet according to claim 1, characterized in that, The voltage-reactive power sensitivity criterion calculates the sensitivity by measuring the changes in reactive power and bus voltage before and after the reactive power regulation disturbance. When the sensitivity calculation results are both greater than 3 times the historical average, a suspected islanding signal is output.

7. The intelligent power distribution control method for a power distribution cabinet according to claim 1, characterized in that, The comprehensive decision-making process is as follows: the output results of the impedance angle criterion, unbalance criterion, harmonic criterion, and sensitivity criterion are voted and scored. When the total score is greater than or equal to 3, it is confirmed as an island. When the total score is equal to 2, it is re-voted after a delay. When the total score is less than or equal to 1, it is judged as normal.

8. The intelligent power distribution control method for a power distribution cabinet according to claim 1, characterized in that, The protection and control actions include: issuing a PWM blocking command within 5ms after confirming islanding, activating the damping discharge resistor when the bus voltage exceeds the limit, issuing a tripping command after a 50ms delay, and confirming the tripping status through auxiliary contacts and electrical quantities. It also includes a synchronization reclosing step: during the circuit breaker opening period, the grid side voltage is monitored. When the grid voltage and frequency recover to the set range and remain stable for 200ms, the voltage difference, frequency difference and phase difference between the grid side and the bus side are measured. When the set conditions are met and the condition remains stable for 100ms, a closing command is issued.

9. The intelligent power distribution control method for a power distribution cabinet according to claim 1, characterized in that, It also includes an adaptive threshold tuning step: the first 48 hours after the power distribution cabinet is put into operation is a self-learning phase, during which the maximum or minimum values ​​of the relevant parameters of each criterion are collected, the threshold of each criterion is tuned according to the set multiple and stored in non-volatile memory for subsequent detection.

10. An intelligent power distribution control system for a power distribution cabinet, characterized in that, The system employs the method described in any one of claims 1-9 to achieve intelligent power distribution control of the distribution cabinet.

Images