Self-adaptive overload protection and fault self-recovery device and method for low-voltage distribution network

Abstract

The invention discloses a self-adaptive overload protection and fault self-healing device and method for a low-voltage distribution network, and the device comprises a multi-parameter real-time monitoring module, an intelligent decision control unit, a dynamic execution module, and a fault self-healing and communication module, and all the modules achieve the data interaction through the Ethernet. The multi-parameter real-time monitoring module collects current, voltage and temperature data of a power distribution loop and transmits the data to the intelligent decision control unit. The intelligent decision control unit judges an overload or fault state based on a preset rule and a core algorithm, and generates a control instruction; the dynamic execution module receives an instruction to execute loop on-off operation to guarantee continuous power supply of a key load; and the fault self-healing and communication module realizes the functions of automatic power supply recovery of a fault loop, data uploading and alarm pushing. Overload grading protection, rapid fault positioning and automatic power supply recovery can be realized, and the problems that traditional power distribution protection is slow in response and needs manual intervention are solved.

Description

Technical Field

[0001] This application relates to the field of fault self-healing technology, and in particular to an adaptive overload protection and fault self-healing device and method for low-voltage power distribution networks. Background Technology

[0002] In current low-voltage power distribution networks, traditional protection devices (such as molded case circuit breakers and thermal relays) mainly rely on the passive protection mode of "overcurrent tripping," which has three major problems: First, rigid overload protection: regardless of the importance of the load, the entire circuit is directly cut off when an overload occurs, forcing critical equipment (such as production machine tools and servers) to shut down, affecting the continuity of production or service; Second, inefficient fault location: when a short circuit or ground fault occurs, maintenance personnel need to disconnect the power and check each circuit one by one, with an average fault location time of more than 30 minutes, extending the power outage duration; Third, lack of self-healing capability: after the fault is cleared, manual reconnection is required to restore power supply, which cannot achieve a closed loop of "fault-repair-recovery," increasing maintenance costs.

[0003] While some existing smart power distribution solutions can monitor current and voltage, they lack an integrated logic of "load classification + dynamic decision-making + automatic execution," making it difficult to meet the reliability and intelligence requirements of low-voltage power distribution networks. Summary of the Invention

[0004] This application provides an adaptive overload protection and fault self-healing device and method for low-voltage power distribution networks to solve the above-mentioned problems.

[0005] On one hand, this application provides an adaptive overload protection and fault self-healing device for low-voltage power distribution networks. The device includes: a multi-parameter real-time monitoring module, an intelligent decision control unit, a dynamic execution module, and a fault self-healing and communication module. Each module interacts with the other via Ethernet. The multi-parameter real-time monitoring module collects current, voltage, and temperature data of the power distribution circuit and transmits them to the intelligent decision control unit. The intelligent decision control unit determines the overload or fault state based on preset rules and core algorithms and generates control commands. The dynamic execution module receives the commands and executes circuit switching operations to ensure continuous power supply to critical loads. The fault self-healing and communication module realizes automatic power restoration of faulty circuits and data uploading and alarm push functions.

[0006] In one implementation of this application, the multi-parameter real-time monitoring module includes: a high-precision Hall current sensor connected in series in each power distribution circuit, a voltage sensor connected in parallel, and a temperature sensor installed at the bus. The multi-parameter real-time monitoring module transmits data to the intelligent decision control unit via RS485 wireless communication.

[0007] In one implementation of this application, the hardware core of the intelligent decision control unit is an embedded microprocessor, which integrates an analog input interface adapted to the monitoring requirements of the power distribution circuit and a digital output interface adapted to the output requirements of control commands; the core algorithms include an overload hierarchical decision algorithm and a fault location algorithm. The overload hierarchical decision algorithm implements hierarchical disconnection logic based on preset critical load thresholds and non-critical load thresholds, and the fault location algorithm implements fault location based on current surge characteristics, voltage drop characteristics and line impedance characteristics.

[0008] In one implementation of this application, the specific logic of the overload classification decision algorithm is as follows: preset critical load threshold and non-critical load threshold; when the monitored current exceeds the preset warning ratio of the threshold, an early warning is triggered; when the current exceeds the preset overload judgment ratio of the threshold, non-critical circuits are cut off first; if the current still exceeds the threshold, other non-critical circuits are cut off until the current returns to the normal range.

[0009] In one implementation of this application, the specific judgment conditions of the fault location algorithm are as follows: when the current sudden change meets the characteristics of a short circuit fault in a low-voltage power distribution network, it is determined to be a short circuit fault; when the voltage drop amplitude meets the characteristics of a ground fault, it is determined to be a ground fault; and the fault circuit number is located and the fault type is identified by combining the line impedance characteristics.

[0010] In one implementation of this application, the dynamic execution module includes a smart circuit breaker corresponding to each circuit. The smart circuit breaker has remote opening and closing functions, and its response time meets the real-time control requirements for circuit on / off. The smart circuit breaker is labeled as critical circuit and non-critical circuit according to the importance of the load, and is used to receive instructions from the intelligent decision control unit to perform circuit on / off operations under overload or fault conditions.

[0011] In one implementation of this application, the fault self-healing and communication module specifically performs the following process: after the fault is disconnected, it continuously monitors the current and voltage signals of the fault circuit. When it detects that the electrical parameters of the circuit have recovered to the preset normal range and have remained stable for a preset time, it automatically issues a closing command. If the abnormality is not detected to be eliminated within the preset alarm time, a secondary alarm is triggered. The communication function is implemented through an integrated wireless communication / Ethernet module, which supports data uploading to the power distribution monitoring platform and alarm push to mobile terminals.

[0012] In one implementation of this application, the data uploaded by the fault self-healing and communication module includes overload warning information, fault information and self-healing results. Maintenance personnel can remotely view the equipment operating status through the power distribution monitoring platform or mobile terminal.

[0013] On the other hand, this application also provides an adaptive overload protection and fault self-healing method for low-voltage power distribution networks. The method includes: Step S1: Real-time collection of current, voltage, and temperature data of each circuit through sensors; the intelligent decision control unit compares the collected data with preset thresholds; if no abnormality is found, all circuits are kept powered normally and the data is uploaded to the monitoring platform; Step S2: If an overload is detected, non-critical circuits are preferentially disconnected according to the load level until the current returns to normal; if a fault is detected, the faulty circuit is quickly located and the circuit breaker of that circuit is disconnected, triggering an audible and visual alarm and uploading the fault information; Step S3: After the fault is disconnected, the faulty circuit signal is continuously monitored; if the preset normal conditions are met, the circuit breaker is automatically closed to restore power supply; if the conditions are not met, a secondary alarm is triggered to remind manual intervention.

[0014] The adaptive overload protection and fault self-healing device and method for low-voltage power distribution networks provided in this application have the following beneficial effects: 1. By using multi-parameter real-time monitoring and overload classification decision-making algorithms, thresholds are preset according to the importance of the load and non-critical circuits are dynamically cut off. This avoids critical equipment from tripping and shutting down due to rigidity, ensuring production and service continuity, and solving the pain point of traditional overload protection that does not distinguish priorities and affects the operation of core business.

[0015] 2. By integrating fault location algorithms based on current surges, voltage drops, and line impedance characteristics, fault circuits and types can be quickly identified, significantly reducing fault investigation time. This eliminates the need for manual power outage testing, reduces power outage duration, and improves the efficiency of fault response and handling in low-voltage distribution networks.

[0016] 3. By continuously monitoring the electrical parameters of the fault circuit through the fault self-healing module, the power supply is automatically restored after the normal conditions are met. This realizes the "fault-repair-restoration" closed loop without manual intervention, reducing the on-site operation cost of maintenance personnel and reducing the impact of power outages caused by manual closing delays.

[0017] 4. By integrating wireless communication / Ethernet modules, overload warnings, fault information, and self-healing results are uploaded to the monitoring platform and pushed to mobile terminals, enabling maintenance personnel to remotely monitor equipment status in real time, receive alarm information promptly, and quickly intervene to handle complex faults, thereby improving the level of intelligent operation and maintenance of low-voltage power distribution networks. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This application provides a schematic diagram of an adaptive overload protection and fault self-healing device for a low-voltage power distribution network. Figure 2This is a flowchart of an adaptive overload protection and fault self-healing method for a low-voltage power distribution network provided in an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] In current low-voltage power distribution networks, traditional protection devices (such as molded case circuit breakers and thermal relays) mainly rely on the passive protection mode of "overcurrent tripping," which has three major problems: First, rigid overload protection: regardless of the importance of the load, the entire circuit is directly cut off when an overload occurs, forcing critical equipment (such as production machine tools and servers) to shut down, affecting the continuity of production or service; Second, inefficient fault location: when a short circuit or ground fault occurs, maintenance personnel need to disconnect the power and check each circuit one by one, with an average fault location time of more than 30 minutes, extending the power outage duration; Third, lack of self-healing capability: after the fault is cleared, manual reconnection is required to restore power supply, which cannot achieve a closed loop of "fault-repair-recovery," increasing maintenance costs.

[0021] While some existing intelligent power distribution solutions can monitor current and voltage, they lack an integrated logic of "load classification + dynamic decision-making + automatic execution," making it difficult to meet the reliability and intelligence requirements of low-voltage power distribution networks. This application provides an adaptive overload protection and fault self-healing device and method for low-voltage power distribution networks. The technical solution proposed in this application will be described in detail below with reference to the accompanying drawings.

[0022] Figure 1 This is a schematic diagram of an adaptive overload protection and fault self-healing device for a low-voltage power distribution network, provided as an embodiment of this application. Figure 1 As shown, this device comprises four main modules: a multi-parameter real-time monitoring module, an intelligent decision control unit, a dynamic execution module, and a fault self-healing and communication module. The specific configuration is as follows: The multi-parameter real-time monitoring module features the following hardware configuration: Each power distribution circuit is connected in series with one high-precision Hall current sensor (measurement range 0-500A, accuracy ±0.5%) and in parallel with one voltage sensor (measurement range 0-400V, accuracy ±0.2%). A temperature sensor (measurement range -20℃-120℃) is also installed at the busbar. Functionally, it collects current, voltage, and temperature data at a 50Hz sampling frequency and transmits the data to the intelligent decision control unit via RS485 wireless communication with a delay of ≤100ms. This configuration offers significant advantages in terms of accuracy, comprehensiveness, and real-time performance: the high-precision Hall current and voltage sensors are compatible with common measurement ranges in low-voltage power distribution scenarios, and their high measurement accuracy ensures reliable current and voltage data, providing precise data for overload detection and fault identification; the busbar temperature sensor covers a wide temperature range, enabling timely detection of potential overheating and filling the blind spots of single-parameter monitoring. The 50Hz sampling frequency can dynamically track parameter changes, and the RS485 wireless communication with ≤100ms low latency enables fast data transmission. This allows the intelligent decision control unit to obtain the circuit status in real time, avoiding untimely protection response due to data lag, and providing solid data support for subsequent graded protection and rapid fault location.

[0023] Intelligent Decision Control Unit, Hardware Core: Employs an STM32H743 embedded microprocessor, integrating 12 analog input interfaces and 8 digital output interfaces; Core Algorithms: - Overload Graded Decision Algorithm: Presets "critical load thresholds" (e.g., 80A current threshold for production equipment circuits) and "non-critical load thresholds" (e.g., 50A current threshold for air conditioning circuits). When the monitored current exceeds the threshold by 80%, an early warning is triggered. When it exceeds 100%, non-critical circuits are cut off first. If the current still exceeds the threshold, other non-critical circuits are cut off until the current returns to normal; Fault Location Algorithm: Based on the current mutation rate (≥1000A / ms is determined as a short circuit), voltage drop amplitude (≤30% of rated voltage is determined as a ground fault), and line impedance characteristics, the fault circuit number is located within 1 second, and fault type (short circuit / ground fault) information is generated. This setup not only adapts to the needs of low-voltage power distribution scenarios but also addresses the pain points of traditional protection systems, offering significant advantages: On the hardware side, the STM32H743 embedded microprocessor is selected due to its strong computing performance and fast response speed, enabling efficient processing of multi-loop monitoring data and complex algorithms; 12 analog input interfaces accommodate multi-parameter acquisition needs, while 8 digital output interfaces meet loop on / off control command output, ensuring precise matching between hardware and function. On the algorithm side, the overload tiered decision-making system addresses the "one-size-fits-all" problem of traditional protection by differentiating between critical and non-critical load thresholds, prioritizing power supply to core equipment; the fault location algorithm integrates multi-dimensional electrical parameter features, as single parameters are prone to misjudgment, and combining multiple features improves fault identification accuracy; and the 1-second rapid location specifically addresses the pain point of inefficient traditional troubleshooting. The overall setup achieves "precise calculation + intelligent decision-making," ensuring power supply continuity while shortening fault handling time, significantly improving the reliability and intelligence level of the power distribution network.

[0024] The dynamic execution module's hardware configuration includes one intelligent circuit breaker per circuit (with remote opening and closing function, response time ≤50ms), labeled as "critical circuits" (e.g., red) and "non-critical circuits" (e.g., blue) according to load importance. Its function is to receive instructions from the intelligent decision control unit, disconnecting the designated non-critical circuit breaker during overload and disconnecting the faulty circuit breaker during fault, without affecting the power supply to other normal circuits. This configuration is designed to accurately receive intelligent decision instructions, overcoming the pain points of slow response and crude operation in traditional execution devices. The selection of intelligent circuit breakers with remote opening and closing functions is to match the automated control requirements of the decision unit, avoiding delays caused by manual closing. The ≤50ms rapid response time can promptly prevent overload or fault escalation. Labeling circuits by load importance is to correspond with the overload hierarchical decision algorithm, ensuring that critical and non-critical circuits are not confused during execution, accurately implementing the "prioritize core circuits" logic. Its advantages are significant: remote control reduces manual intervention and improves operational efficiency; rapid response ensures timely protection and reduces the impact of faults on the power distribution network; precise disconnection of target circuits ensures continuous power supply to critical equipment during overload and avoids power outages in normal circuits during faults, greatly improving power supply continuity; clear circuit labeling also facilitates operation and maintenance, further optimizing the reliability and practicality of the power distribution network.

[0025] Fault self-healing and communication module: Self-healing logic: After the fault is disconnected, the current and voltage signals of the fault circuit are continuously monitored. When no abnormality is detected in the circuit (current ≤ 5A, voltage recovers to 380V±5%) for 3 seconds, a closing command is automatically sent to the intelligent circuit breaker of the fault circuit. If no abnormality is detected and eliminated within 10 minutes, a secondary alarm is triggered. Communication function: Integrated 4G / Ethernet module, which uploads overload warning, fault information (circuit number + fault type), and self-healing results to the power distribution monitoring platform, and supports push alarm information to mobile APP. Maintenance personnel can remotely view the status. This configuration is specifically designed to address the pain points of traditional power distribution systems, such as the need for manual reclosing after a fault and delayed maintenance information. In the self-healing logic, continuous monitoring of fault circuit parameters ensures the fault is truly eliminated; a 3-second stabilization period prevents accidental reclosing that could lead to secondary faults; and a 10-minute secondary alarm prevents repeated attempts to close the circuit before the fault is resolved, balancing automation and safety. The integrated 4G / Ethernet module adapts to different network requirements and ensures stable information transmission. App push notifications and platform uploads allow maintenance personnel to obtain critical information in real time, reducing reliance on on-site monitoring. The benefits are significant: the self-healing function achieves a closed loop of "fault-repair-recovery," restoring normal power supply without manual intervention, shortening outage time and reducing maintenance costs; the communication function synchronizes overload, fault, and self-healing information in real time, allowing maintenance personnel to remotely and accurately determine the fault location and type for rapid response; secondary alarms in the absence of self-healing prevent delayed fault handling, significantly improving the intelligent maintenance level and power supply reliability of the power distribution network.

[0026] The above describes an adaptive overload protection and fault self-healing device for low-voltage power distribution networks provided in this application. Based on the same concept, this application also provides a method for adaptive overload protection and fault self-healing in low-voltage power distribution networks. Figure 2 As shown, the process is divided into three stages: "routine monitoring - abnormal response - self-healing recovery". The specific steps are as follows: 1. During the routine monitoring phase, sensors collect real-time data on current, voltage, and temperature of each circuit. The intelligent decision control unit compares the data with preset thresholds. When no abnormalities are found, all circuits are kept powered normally, and the data is uploaded to the monitoring platform. This comprehensively captures the core parameters of current, voltage, and temperature of each circuit, accurately controls the operating status, and avoids the omission of potential hazards caused by monitoring only one parameter. When no abnormalities are found, the entire circuit is kept powered normally, ensuring the continuity of production and service. The data is uploaded to the monitoring platform in real time, which allows maintenance personnel to remotely monitor the equipment status in real time, providing accurate data support for subsequent anomaly response and improving the stability and monitorability of the power distribution network.

[0027] 2. Abnormal Response Phase: Overload Response: If the current in a certain circuit exceeds the threshold, the control unit determines the overload level and prioritizes disconnecting the circuit breakers of non-critical loads associated with that circuit (such as workshop air conditioning and lighting). The disconnection is completed within 100ms. If the current still exceeds the threshold, the next non-critical load is disconnected until the current returns to within the threshold. Fault Response: If a sudden current change and voltage drop are detected, the control unit locates the faulty circuit within 1 second, immediately disconnects the intelligent circuit breaker of that circuit, and triggers an audible and visual alarm (red light flashing on the device panel + buzzer), and uploads the fault information to the platform. This breaks away from the traditional "one-size-fits-all" overload disconnection mode, prioritizing the disconnection of non-critical loads to ensure continuous power supply to core circuits such as production equipment and avoid interruption of core business operations. The rapid response within 100ms can promptly curb the escalation of overload and prevent the fault from spreading. The logic of gradually disconnecting non-critical loads is precisely adapted to the overload level, solving the overload problem while minimizing the impact on power supply, and improving the adaptive protection capability and operational stability of the power distribution network.

[0028] 3. During the self-healing recovery phase, after the fault is cleared (e.g., maintenance personnel repair the short circuit), the sensor detects a normal signal in the faulty circuit, and the control unit automatically issues a closing command, restoring power within 3 seconds. If power is not restored within 10 minutes, the device sends an alarm again, prompting manual intervention. Automatic closing after fault clearance allows for rapid power restoration without manual intervention, significantly reducing outage time and maintenance costs. Closing within 3 seconds ensures power continuity and minimizes business interruptions. A second alarm is triggered if power is not restored within 10 minutes, preventing delays in handling faults and balancing automation efficiency with safety safeguards, thus improving the self-healing capability and operational reliability of the power distribution network.

[0029] An example of a specific application scenario for this application is as follows: In the scenario of a low-voltage power distribution network in a mineral processing plant workshop, this device specifically performs the following process: 1. Equipment Deployment: The workshop power distribution network has a total of 11 circuits, of which 3 are critical loads (low-pressure equipment related to crushing, grinding, and flotation) and 8 are non-critical loads (air conditioning, lighting, fans, vibrating screens, shaking tables, filters, compressors, and belt conveyors). Each circuit is equipped with monitoring sensors and intelligent circuit breakers. The intelligent decision control unit is installed in the control cabinet of the power distribution room and connected to the workshop monitoring platform. 2. Threshold setting: Preset critical circuit current threshold of 300A, non-critical circuit current threshold of 100A; 3. Overload scenario: When critical equipment is operating at low voltage (current 290A) and all air conditioners are turned on at the same time (total current 110A), the total current reaches 400A, exceeding the threshold. The control unit will first cut off all air conditioner circuit breakers (current drops to 400-30=370A). If it still exceeds the threshold, it will continue to cut off lighting and fans until the total current supplied to critical equipment drops to below 300A, ensuring that critical equipment always operates normally. 4. Fault Scenario: If a short circuit occurs in the lighting circuit, the control unit will locate the "lighting circuit" within 1 second, cut off the circuit breaker of that circuit, and ensure that other circuits are powered normally. Maintenance personnel can go directly to the lighting circuit to troubleshoot according to the platform prompts. After repair within 5 minutes, the device will automatically close the circuit to restore lighting.

[0030] This application provides an adaptive overload protection and fault self-healing device and method for low-voltage power distribution networks. Through real-time multi-parameter monitoring and an overload hierarchical decision-making algorithm, it presets thresholds based on load importance and dynamically disconnects non-critical circuits. This avoids rigid tripping of critical equipment, ensuring production and service continuity and addressing the pain point of traditional overload protection that lacks priority and impacts core business operations. By integrating fault location algorithms based on current surges, voltage drops, and line impedance characteristics, it quickly identifies faulty circuits and their types, significantly reducing fault investigation time. It eliminates the need for manual circuit-by-circuit power disconnection and detection, reducing power outage duration and improving the efficiency of fault response and handling in low-voltage power distribution networks. The fault self-healing module continuously monitors the electrical parameters of the faulty circuit and automatically restores power supply when normal conditions are met. This achieves a closed-loop "fault-repair-recovery" process without manual intervention, reducing on-site operation costs for maintenance personnel and minimizing power outages caused by manual reclosing delays. By integrating wireless communication / Ethernet modules, overload warnings, fault information, and self-healing results are uploaded to the monitoring platform and pushed to mobile terminals, enabling maintenance personnel to remotely monitor equipment status in real time, receive alarm information promptly, and quickly intervene to handle complex faults, thereby improving the level of intelligent operation and maintenance of low-voltage power distribution networks.

[0031] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0032] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0033] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A low-voltage power distribution network adaptive overload protection and fault self-healing device, characterized in that, The device includes a multi-parameter real-time monitoring module, an intelligent decision control unit, a dynamic execution module, and a fault self-healing and communication module. Each module interacts with the others via Ethernet. The multi-parameter real-time monitoring module collects current, voltage, and temperature data from the power distribution circuit and transmits it to the intelligent decision control unit. The intelligent decision control unit determines overload or fault conditions based on preset rules and core algorithms and generates control commands. The dynamic execution module receives commands and executes circuit switching operations to ensure continuous power supply to critical loads. The fault self-healing and communication module enables automatic power restoration of faulty circuits, data uploading, and alarm push notification functions.

2. The adaptive overload protection and fault self-healing device for low-voltage power distribution networks according to claim 1, characterized in that, The multi-parameter real-time monitoring module includes: a high-precision Hall current sensor connected in series in each power distribution circuit, a voltage sensor connected in parallel, and a temperature sensor installed at the bus. The multi-parameter real-time monitoring module transmits data to the intelligent decision control unit via RS485 wireless communication.

3. The adaptive overload protection and fault self-healing device for low-voltage power distribution networks according to claim 1, characterized in that, The hardware core of the intelligent decision control unit is an embedded microprocessor, which integrates an analog input interface adapted to the monitoring needs of the power distribution circuit and a digital output interface adapted to the output needs of control commands. The core algorithms include an overload hierarchical decision algorithm and a fault location algorithm. The overload hierarchical decision algorithm implements hierarchical disconnection logic based on preset critical load thresholds and non-critical load thresholds. The fault location algorithm realizes fault location based on current change characteristics, voltage drop characteristics and line impedance characteristics.

4. The adaptive overload protection and fault self-healing device for low-voltage power distribution networks according to claim 3, characterized in that, The specific logic of the overload classification decision algorithm is as follows: preset critical load threshold and non-critical load threshold; when the monitored current exceeds the preset warning ratio of the threshold, an early warning is triggered; when the current exceeds the preset overload judgment ratio of the threshold, non-critical circuits are cut off first; if the current still exceeds the threshold, other non-critical circuits are cut off until the current returns to the normal range.

5. The adaptive overload protection and fault self-healing device for low-voltage power distribution networks according to claim 3, characterized in that, The specific judgment conditions of the fault location algorithm are as follows: when the current change meets the characteristics of a short circuit fault in a low-voltage distribution network, it is judged as a short circuit fault; when the voltage drop amplitude meets the characteristics of a ground fault, it is judged as a ground fault; and the fault circuit number is located and the fault type is identified by combining the line impedance characteristics.

6. The adaptive overload protection and fault self-healing device for low-voltage power distribution networks according to claim 1, characterized in that, The dynamic execution module includes a smart circuit breaker for each circuit. The smart circuit breaker has remote opening and closing functions, and its response time meets the real-time control requirements for circuit on / off. The smart circuit breaker is labeled as critical circuit and non-critical circuit according to the importance of the load. It is used to receive instructions from the intelligent decision control unit and perform circuit on / off operations under overload or fault conditions.

7. The adaptive overload protection and fault self-healing device for low-voltage power distribution networks according to claim 1, characterized in that, The fault self-healing and communication module specifically performs the following process: After the fault is disconnected, it continuously monitors the current and voltage signals of the fault circuit. When it detects that the circuit electrical parameters have returned to the preset normal range and have remained stable for a preset time, it automatically issues a closing command. If the abnormality is not detected to be eliminated within the preset alarm time, a secondary alarm is triggered. The communication function is implemented through an integrated wireless communication / Ethernet module, which supports data uploading to the power distribution monitoring platform and alarm push to mobile terminals.

8. The adaptive overload protection and fault self-healing device for low-voltage power distribution networks according to claim 1, characterized in that, The data uploaded by the fault self-healing and communication module includes overload warning information, fault information and self-healing results. Maintenance personnel can remotely view the equipment operating status through the power distribution monitoring platform or mobile terminal.

9. A method for adaptive overload protection and fault self-healing in low-voltage power distribution networks, characterized in that, The method includes: Step S1: Real-time data collection of current, voltage, and temperature of each circuit is performed by sensors. The intelligent decision control unit compares the collected data with preset thresholds. If no abnormalities are found, all circuits are kept powered normally and the data is uploaded to the monitoring platform. Step S2: If it is determined to be an overload, prioritize cutting off non-critical circuits according to the load level until the current returns to normal; if it is determined to be a fault, quickly locate the faulty circuit and cut off the circuit breaker of that circuit, trigger an audible and visual alarm and upload the fault information. Step S3: After the fault is disconnected, the fault circuit signal is continuously monitored. If the preset normal conditions are met, the circuit is automatically closed to restore power supply. If the conditions are not met, a secondary alarm is triggered to remind manual intervention.

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