Remote load removal and reset method for large-current switch built-in electric energy meter

Abstract

The invention discloses a remote load removal and reset method for a large-current switch built-in electric energy meter, and relates to the technical field of intelligent power grids, and the method comprises the steps: collecting current data and voltage data in real time through a dynamic load monitoring module, and generating an early warning signal when the current data and the voltage data exceed a load threshold value; load data are synchronized in the distributed network, and a master control node sends an instruction to control load removal of the electric energy meter; and detecting the stable state of the load, and executing remote reset after a reset condition is met. According to the method, the system response speed and the overload detection capability are improved, the potential damage risk caused by overload to equipment and the system is reduced, the high efficiency and the reliability of load management are ensured, the efficiency and the reliability of load removal are improved, the safety and the stability of power grid operation are ensured, and the economic benefit is increased. The stability and reliability of power supply recovery are improved, the fault tolerance of the system is improved through an exception handling mechanism, and the stability of reset operation is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of smart grids, and in particular to a remote load shedding and resetting method for an electric energy meter with a built-in large current switch. Background Art

[0002] With the rapid development of power systems and smart grid technologies, smart energy meters have become an important interface between power users and power companies. They can not only achieve accurate energy metering, but also undertake intelligent functions such as load management. In modern power consumption scenarios, the dynamic changes of power loads are significant, especially during peak power consumption periods, load fluctuations may cause power grid overload or even system instability. In order to address this problem, remote load management technology has received widespread attention. Its core lies in achieving optimal allocation of power resources and efficient operation of the power grid through real-time monitoring and control of load status. At present, the combination of dynamic monitoring, distributed data synchronization, and remote control technologies provides technical support for the in-depth application of smart energy meters in the field of load management. However, the existing technology still has many limitations in terms of response speed, data collaboration, and stability of load reset, and is in urgent need of further improvement and optimization.

[0003] Although the existing remote load management technology has realized the load monitoring and control functions to a certain extent, its limitations are obvious. In terms of dynamic load monitoring, traditional electric energy meters usually rely on a monitoring mode with a fixed sampling frequency, which makes it difficult to capture real-time changes in load status. This hysteresis makes the system take a long time to respond to the overload state, which may lead to untimely load shedding operations, thereby increasing the risk of equipment damage and system instability. In a distributed network environment, the synchronization efficiency of load data is low. In the prior art, the dispersion and isolation of load data limit the master control node's accurate judgment of the global load state, which in turn affects the coordination and accuracy of the load shedding instruction. In the reset operation after load shedding, the traditional method is usually based on a fixed time or a simple threshold setting, and fails to comprehensively consider the dynamic balance of the load state. This single reset strategy causes new load fluctuations due to premature reset, and delayed reset reduces the power supply recovery efficiency, affecting user experience and grid operation stability. Therefore, the prior art cannot achieve the technical effects of real-time monitoring, rapid response and remote reset proposed by the present invention, which limits the application scope and efficiency of electric energy meters in smart grids. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: the existing load management technology has monitoring lag, low efficiency of distributed data collaboration, insufficient dynamic balance of reset operation, and how to improve the accuracy and stability of load management through real-time monitoring, distributed collaboration and dynamic reset.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a remote load shedding and resetting method for a large current switch built-in electric energy meter, comprising real-time collection of current data and voltage data through a dynamic load monitoring module, and generating a warning signal when the load threshold is exceeded; synchronizing load data in a distributed network, and issuing instructions from a master control node to control load shedding of the electric energy meter; detecting the stable state of the load, and performing remote resetting after the reset conditions are met.

[0007] As a preferred solution of the remote load shedding and resetting method of the large current switch built-in electric energy meter described in the present invention, the real-time collection of current data and voltage data through the dynamic load monitoring module includes automatically detecting the fluctuation frequency of current and voltage within each second, performing weighted processing on the collected real-time data, and filtering out the impact of instantaneous fluctuations.

[0008] As a preferred solution of the remote load shedding and resetting method of the large current switch built-in electric energy meter described in the present invention, the generation of the warning signal includes automatically generating a load shedding warning signal and uploading it to the distributed network when the electric energy meter detects that the preset current threshold exceeds the normal operating upper limit by 20% or the voltage exceeds the preset limit by 15%, and performing averaging processing on the high-frequency sampling data by setting the adaptive sampling algorithm of the data processing module to suppress the interference of sudden fluctuations, and after the warning signal is generated, uploading it to the master control node in the distributed network in an encrypted form.

[0009] As a preferred solution of the remote load shedding and resetting method of the large current switch built-in electric energy meter described in the present invention, wherein: the synchronization of load data in the distributed network includes establishing a point-to-point data transmission protocol between the master node and the slave node, the load data is updated in real time during the execution of the shedding or reset instruction, and the data of each node is encrypted and verified through the distributed ledger to confirm data consistency.

[0010] When any slave node loses communication during the removal or reset process, the master node triggers data synchronization and generates an exception report, marking the abnormal node and automatically executing the backup plan.

[0011] As a preferred solution of the remote load shedding and resetting method of the large current switch built-in electric energy meter described in the present invention, wherein: the main control node issues an instruction to control the load shedding of the electric energy meter, including when the early warning signal is uploaded to the main control node, the main control node verifies the identity information and location data of the electric energy meter through the distributed ledger, and when it is confirmed that the early warning signal is valid, the main control node sends a load shedding instruction to the corresponding electric energy meter, the instruction is transmitted with a high priority transmission protocol, the shedding instruction reaches the target electric energy meter within 0.1 seconds, and after the electric energy meter receives the shedding instruction, it starts the internal circuit breaker control module and automatically cuts off the load power supply according to the shedding response time set by the system, and the distributed ledger records the data during the shedding process, including load parameters, time and operation status.

[0012] As a preferred solution of the remote load shedding and resetting method of the large current switch built-in electric energy meter described in the present invention, the detection of the load stability state includes monitoring the load state of the electric energy meter every 5 seconds after the load is sheared off, recording whether the current fluctuation is within the preset threshold of 10% and the voltage fluctuation is within the preset limit of 8% within 10 consecutive seconds, as a stability standard for judging whether the load has been restored, and detecting the external temperature and humidity conditions through the built-in environmental sensor module of the electric energy meter to ensure that the environmental conditions meet the reset requirements. When the stable state and environmental conditions are met at the same time, a reset instruction is generated and reported to the main control node.

[0013] As a preferred solution of the remote load shedding and resetting method of the large current switch built-in electric energy meter described in the present invention, wherein: the remote reset is performed after the reset condition is met, including that after receiving the reset instruction of the main control node, the electric energy meter gradually restores the load power supply within 3 seconds, and gradually increases the power supply load through the soft start module to prevent instantaneous power shock. When the power supply load is restored to 95% of the preset current, the real-time data of the temperature sensor is detected to confirm that there is no temperature overload during the power supply process. When a sudden temperature increase occurs, the reset is immediately suspended and the load detection is re-triggered. Otherwise, normal power supply is restored and operation data is recorded in the absence of abnormalities to complete the reset process.

[0014] Exception handling during the reset process includes when a slave node is disconnected or abnormal fluctuations are detected during the removal or reset process, the master control node quickly switches to the backup node through the multipath protocol, records the load data of the faulty node, and predicts the impact that the reset may have on the system based on the load history data. When the reset risk exceeds the set value, the master control node delays the reset operation or continues to maintain the removal state. When the load meets the reset conditions, the master control node regenerates the reset instruction and performs secondary verification.

[0015] Another object of the present invention is to provide a remote load shedding and resetting system for a large current switch built-in electric energy meter, which can synchronize load data in a distributed network and control the load shedding of the electric energy meter by issuing instructions from a master control node, thereby solving the problems of insufficient system real-time performance and data reliability in current load management technology.

[0016] As a preferred solution of the remote load shedding and resetting system of the electric energy meter with built-in large current switch described in the present invention, it includes: a monitoring and early warning module, a synchronous control module, and a remote resetting module.

[0017] The monitoring and early warning module is used to collect current data and voltage data in real time through the dynamic load monitoring module, and generate an early warning signal when the load threshold is exceeded; the synchronization control module is used to synchronize load data in the distributed network, and the master control node issues instructions to control the load removal of the electric energy meter; the remote reset module is used to detect the stable state of the load and perform remote reset after the reset conditions are met.

[0018] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a remote load shedding and resetting method for a large current switch built-in electric energy meter.

[0019] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a remote load shedding and resetting method for a large current switch built-in electric energy meter.

[0020] Beneficial effects of the present invention: The remote load shedding and resetting method of the large current switch built-in electric energy meter provided by the present invention collects current data and voltage data in real time through the dynamic load monitoring module, and generates an early warning signal when the load threshold is exceeded. Through real-time and accurate load monitoring, the system response speed and overload detection capability are improved, the potential damage risk caused by overload to equipment and systems is reduced, and the efficiency and reliability of load management are ensured. The load data is synchronized in the distributed network, and the main control node issues instructions to control the load shedding of the electric energy meter, which ensures the security and consistency of data transmission, improves the efficiency and reliability of load shedding, and significantly reduces the impact risk of overload on the power grid and power-consuming equipment through the rapid shedding mechanism, ensures the safety and stability of the power grid operation, detects the load stable state, and performs remote reset after the reset condition is met. By dynamically evaluating the load stable state, the accuracy and safety of the reset operation are ensured. The way of gradually restoring the load reduces the possibility of the system being subjected to instantaneous impact, improves the stability and reliability of power supply recovery, and the abnormal handling mechanism improves the fault tolerance of the system and ensures the stability of the reset operation. The present invention achieves better results in terms of the accuracy of real-time load monitoring, the efficiency of distributed network control, and the safety and stability of load shedding and resetting. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0022] Figure 1 The present invention provides an overall flow chart of a remote load shedding and resetting method for a high-current switch built-in electric energy meter according to the first embodiment of the present invention.

[0023] Figure 2 The third embodiment of the present invention provides an overall flow chart of a remote load shedding and resetting system for an electric energy meter with a built-in large current switch. DETAILED DESCRIPTION

[0024] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0025] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides a remote load shedding and resetting method for a large current switch built-in electric energy meter, comprising:

[0026] S1: The dynamic load monitoring module collects current and voltage data in real time and generates a warning signal when the load threshold is exceeded.

[0027] Furthermore, the real-time collection of current data and voltage data by the dynamic load monitoring module includes automatic detection of the fluctuation frequency of current and voltage per second, weighted processing of the collected real-time data, and filtering of the impact of instantaneous fluctuations.

[0028] It should be noted that the generation of warning signals includes automatically generating a load shedding warning signal and uploading it to the distributed network when the electric energy meter detects that the preset current threshold exceeds the normal operating upper limit by 20% or the voltage exceeds the preset limit by 15%. The signal is then averaged over the high-frequency sampling data by setting the adaptive sampling algorithm of the data processing module to suppress the interference of sudden fluctuations. After the warning signal is generated, it is uploaded to the master control node in the distributed network in an encrypted form.

[0029] It should also be noted that by setting the adaptive sampling algorithm of the data processing module, the collected high-frequency sampling data is averaged in real time. The adaptive sampling algorithm automatically adjusts the sampling frequency and weight distribution according to the characteristics of current and voltage fluctuations to adapt to the requirements of different load fluctuation scenarios, thereby suppressing the interference of sudden fluctuations. The specific steps are as follows: During the sampling process, the data processing module prioritizes marking abnormal fluctuation points, and performs multiple iterative calculations on the sampling data of continuous high-frequency fluctuations to eliminate the influence of abnormal data points on the overall data accuracy. After generating the early warning signal, the signal data is encrypted layer by layer through the encryption algorithm, including key data fields such as load parameters, electric energy meter equipment identification, sampling timestamp and fluctuation curve summary, to ensure that the uploaded data is in the distributed network. In order to ensure the integrity and security of the network transmission, the warning signal is transmitted to the master control node in the form of a high-priority data packet in the distributed network; during the transmission process, the master control node verifies the integrity of each data packet through the preset distributed ledger, and records the transmission path, time and related equipment information of the uploaded signal in real time; once the master control node completes data verification and identity authentication, it will distribute the verified warning signal to the relevant slave nodes through the intelligent routing function to ensure efficient synchronization of load data in the network; after receiving the warning signal, the master control node can trigger the dynamic resampling mechanism of the load status, and perform short-term intensive sampling of the load status of the high-priority node to further enhance the decision-making accuracy of the load shedding instruction and provide more accurate basic data support for subsequent operations.

[0030] It should also be noted that the real-time collection of current and voltage data by the dynamic load monitoring module, combined with the automatic detection of fluctuation frequency and weighted processing mechanism, effectively filters out the impact of instantaneous fluctuations on data accuracy. This processing method has higher accuracy and stability than traditional load monitoring technology, especially in complex load fluctuation environments, and can capture more realistic load states. The system uses an adaptive sampling algorithm to average high-frequency sampling data, further eliminating monitoring errors caused by short-term fluctuations, thereby ensuring the credibility of the monitoring data. When the load exceeds the set threshold (such as current exceeding the limit by 20% or voltage exceeding the limit by 15%), the system can quickly generate an early warning signal and upload it to the distributed network through encryption. After the early warning signal is uploaded, the master control node verifies its validity to ensure the authenticity and reliability of the signal. This automatic generation and upload mechanism improves the response speed of load management, while reducing the delay and error risks that may be caused by human intervention, providing timely and reliable basis for subsequent load shedding, which not only reduces the risk of equipment damage caused by overload, but also avoids the stability problems caused by overload of the power grid.

[0031] S2: Synchronize load data in the distributed network, and the master control node sends instructions to control the load shedding of the energy meter.

[0032] Furthermore, synchronizing load data in a distributed network includes establishing a point-to-point data transmission protocol between a master node and slave nodes, updating load data in real time during the execution of a shedding or reset instruction, and encrypting and verifying data for each node through a distributed ledger to confirm data consistency.

[0033] When any slave node loses communication during the removal or reset process, the master node triggers data synchronization and generates an exception report, marking the abnormal node and automatically executing the backup plan.

[0034] It should be noted that the main control node issues instructions to control the load shedding of the electricity meter, including when the early warning signal is uploaded to the main control node, the main control node verifies the identity information and location data of the electricity meter through the distributed ledger. When the early warning signal is confirmed to be valid, the main control node sends a load shedding instruction to the corresponding electricity meter. The instruction is transmitted using a high-priority transmission protocol, and the shedding instruction reaches the target electricity meter within 0.1 seconds. After the electricity meter receives the shedding instruction, it starts the internal circuit breaker control module and automatically cuts off the load power supply according to the shedding response time set by the system. The distributed ledger records the data during the shedding process, including load parameters, time and operation status.

[0035] It should also be noted that the encryption and consistency check of data through distributed ledgers ensures the security and reliability of data transmission, avoids misoperation problems caused by data transmission errors or delays, and adopts a high-priority transmission protocol during the instruction transmission process, which can deliver the removal instruction to the target power meter within 0.1 seconds to ensure the timeliness of the removal operation; in actual applications, the load removal operation ensures the accuracy and targeting of the instruction through multiple verifications of the warning signal by the main control node; after the power meter receives the removal instruction, the internal circuit breaker control module responds quickly and cuts off the load power supply according to the response time set by the system; at the same time, the system records the data during the removal process through distributed ledgers, including load parameters, time and operation status, to provide a reliable basis for subsequent analysis. The combination of distributed networks and rapid removal mechanisms not only improves the efficiency of load management, but also improves the system's ability to respond to sudden load overloads, reduces equipment damage or power grid instability caused by delayed removal, improves the stability and reliability of the load management system, and provides a guarantee for safe operation in complex power grid environments.

[0036] S3: Detect the load stable state and perform remote reset after the reset conditions are met.

[0037] Furthermore, the detection of load stability includes monitoring the load status of the electric energy meter every 5 seconds after the load is removed, recording whether the current fluctuation is within the preset threshold of 10% and the voltage fluctuation is within the preset limit of 8% within 10 consecutive seconds, as a stability standard for judging whether the load has been restored, and detecting the external temperature and humidity conditions through the built-in environmental sensor module of the electric energy meter to ensure that the environmental conditions meet the reset requirements. When the stable state and environmental conditions are met at the same time, a reset command is generated and reported to the main control node.

[0038] It should be noted that performing remote reset after the reset conditions are met includes that after receiving the reset command from the main control node, the electric energy meter gradually restores the load power supply within 3 seconds, and gradually increases the power supply load through the soft start module to prevent instantaneous power shock. When the power supply load recovers to 95% of the preset current, the real-time data of the temperature sensor is detected to confirm that there is no temperature overload during the power supply process. When a sudden temperature increase occurs, the reset is immediately suspended and the load detection is re-triggered. Otherwise, normal power supply is restored and operation data is recorded in the absence of abnormalities to complete the reset process.

[0039] Exception handling during the reset process includes when a slave node is disconnected or abnormal fluctuations are detected during the removal or reset process, the master control node quickly switches to the backup node through the multipath protocol, records the load data of the faulty node, and predicts the impact that the reset may have on the system based on the load history data. When the reset risk exceeds the set value, the master control node delays the reset operation or continues to maintain the removal state. When the load meets the reset conditions, the master control node regenerates the reset instruction and performs secondary verification.

[0040] It should also be noted that after the load is removed, the system chooses to monitor once every 5 seconds and records the fluctuation status of current and voltage for 10 seconds continuously. The design is based on the balance between the regularity of dynamic fluctuations and monitoring efficiency during the load recovery process. Monitoring is performed every 5 seconds to ensure that the latest load data is obtained in a sufficiently short time, so as to avoid the failure to timely discover abnormal load fluctuations due to long monitoring intervals, and at the same time avoid the burden of system resources being increased by too high a sampling frequency. On this basis, a continuous recording time of 10 seconds can provide sufficient data volume. Based on the stability assessment model, the load state can be ensured to truly meet the stability requirements through statistical analysis of the fluctuation range and trend. The specific operations are as follows: The monitoring module uses a preset sampling algorithm to perform high-precision measurements of current and voltage every 5 seconds, records the collected data as a time series, and transmits it to the distributed ledger in real time for synchronization. After the recording is completed, the system calculates whether the current fluctuation is less than 10% and the voltage fluctuation is less than 8% within 10 consecutive seconds through the built-in statistical analysis module, and compares the results with the stability judgment threshold. When all conditions are met, a stability confirmation signal is generated and reported to the main control node, ensuring a reasonable match between the monitoring frequency and the amount of evaluation data, avoiding monitoring blind spots, and providing sufficient basic data for accurate judgment of the load state, which not only improves the accuracy and reliability of the reset condition judgment, but also reduces the risk of system instability caused by misjudgment.

[0041] It should also be noted that when judging whether the external temperature and humidity conditions meet the reset requirements, the system conducts a comprehensive assessment based on the preset environmental safety thresholds. The specific steps are as follows: When the external temperature needs to be maintained within the normal operating temperature range of the equipment (such as -10°C to 40°C), it is monitored in real time through environmental sensors to ensure that the temperature fluctuation range remains within 5°C during continuous detection; the humidity conditions must meet the equipment protection level requirements (such as the relative humidity range of 30% to 70%), and the potential condensation risk in the environment is calculated in combination with the dew point data of the sensor to ensure that the humidity does not cause safety hazards to the electrical equipment during the reset process. Hidden dangers; the system uses the built-in environmental monitoring module to continuously sample at intervals of every 3 seconds, record the data as a time series, and transmit it to the judgment module; the judgment module calculates the stability of environmental parameters through a sliding window algorithm based on the temperature and humidity standards. If the external temperature and humidity meet the preset requirements for 10 consecutive seconds and there is no dew point risk, an environmental compliance signal is generated and uploaded to the main control node. Under certain abnormal conditions (such as temperature exceeding the limit but the trend is falling), the system will trigger a delayed reset strategy and extend the monitoring time to further confirm the stability of the environment, thereby avoiding misjudgment due to a single short-term abnormal data. Through this precise judgment mechanism, the safety and controllability of external environmental conditions in the reset operation are guaranteed.

[0042] It should also be noted that through the comprehensive judgment of load status and environmental conditions, precise control of remote reset is achieved to ensure the reliability and safety of the reset operation. After the load is removed, the current and voltage fluctuations are monitored every 5 seconds, and the current fluctuation is required to be no more than 10% and the voltage fluctuation is no more than 8% within 10 consecutive seconds. This is used as the standard for judging load stability. At the same time, the built-in environmental sensor module detects external temperature and humidity conditions to further ensure the environmental safety of the reset operation. When the load stability and environmental conditions meet the requirements, the system generates a reset command and uploads it to the main control node for confirmation. The reset operation gradually restores the load power supply through the slow start module. , to avoid the impact of instantaneous power shocks on the power grid and user-end equipment. When the power supply load recovers to 95% of the preset current, the system detects the real-time temperature data to ensure that there is no temperature overload before completing the reset operation. This not only improves the safety of the reset process, but also reduces the power supply fluctuation problem caused by improper operation. When abnormal fluctuations or node failures occur during the reset process, the master control node can quickly switch to the backup node through the multi-path protocol, and predict the impact risk that may be caused by the reset based on the load historical data. If the risk exceeds the set threshold, the master control node can delay the reset operation or continue to maintain the load shedding state to further ensure the safety and stability of the system.

[0043] Embodiment 2 is an embodiment of the present invention, which provides a remote load shedding and resetting method for a large current switch built-in electric energy meter. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0044] First of all, the experimental system consists of a dynamic load monitoring module, a master control node, 5 slave nodes, a distributed network, an environmental monitoring module and a soft start module. The operating environment simulates the real power grid load fluctuation scenario. The test process is divided into three stages: load monitoring, load shedding and reset. Multiple key parameters are set and recorded in each stage. In the dynamic load monitoring stage, all nodes are equipped with dynamic load monitoring modules to collect current and voltage data 1,000 times per second. In order to filter out the interference of instantaneous fluctuations, the system enables an adaptive sampling algorithm to dynamically adjust the sampling parameters according to the load fluctuation frequency. When the current exceeds the preset threshold by 20% or the voltage exceeds the normal range by 15%, the node automatically generates a warning signal. After the signal is generated, the monitoring module averages the raw data to suppress the impact of sudden fluctuations on the signal. The warning signal is encrypted multiple times through an encryption algorithm, including node identification, load parameters, sampling Timestamp and other key information are uploaded to the distributed network master node; in the load shedding stage, after the master node receives the early warning signal, it first verifies the validity of the signal, including the verification of the node identity and location data. After confirmation, the master node issues a load shedding instruction to the target node through a high-priority transmission protocol. The shedding instruction must reach the target node within 100 milliseconds. The target node starts the internal circuit breaker control module to perform the shedding operation and records the operation data (including shedding time, current and voltage fluctuation parameters) through the distributed ledger; during the shedding process, if the communication of the slave node is interrupted or abnormal fluctuations occur, the master node triggers the backup plan, completes the instruction transmission through other paths and generates an abnormal report. After the load is removed, each node continues to collect load data to monitor the removal effect; the reset stage mainly focuses on the recovery conditions and process of the load. Every 5 seconds, the node monitors the load status and continuously records the current and voltage fluctuation data within 10 seconds to determine whether they are within the preset range (current fluctuation does not exceed 10%, voltage fluctuation does not exceed 8%). At the same time, the environmental monitoring module collects temperature and humidity data in real time to evaluate whether the reset conditions meet the equipment operation standards. When the reset conditions are met, the main control node generates a reset instruction and gradually restores power supply through the slow start module to prevent instantaneous power shocks from threatening the stability of the power grid. The slow start module gradually increases the power supply according to the load classification strategy, and performs temperature verification when the power supply is restored to 95% of the set value. After confirming that there is no temperature overload, the reset is completed. If an abnormal fluctuation is detected during the reset process, the system automatically suspends operation and re-evaluates the load and environmental conditions to avoid fault propagation; It can be seen from the experimental results that the present invention is efficient and innovative in load management, and provides a new technical direction for the development of smart electric energy meter technology.

[0045] Example 3, reference Figure 2 , which is an embodiment of the present invention, provides a remote load shedding and resetting system for a large current switch built-in electric energy meter, including a monitoring and early warning module, a synchronous control module, and a remote resetting module.

[0046] The monitoring and early warning module is used to collect current data and voltage data in real time through the dynamic load monitoring module, and generate an early warning signal when the load threshold is exceeded; the synchronization control module is used to synchronize load data in the distributed network, and the master control node issues instructions to control the load removal of the electric energy meter; the remote reset module is used to detect the stable state of the load and perform remote reset after the reset conditions are met.

[0047] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0048] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0049] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0050] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0051] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A remote load shedding and resetting method for a large current switch built-in electric energy meter, characterized in that: include: The dynamic load monitoring module collects current and voltage data in real time and generates an early warning signal when the load threshold is exceeded; Synchronize load data in the distributed network, and the master control node issues instructions to control the load shedding of the energy meter; Detect the load stable state and perform remote reset after the reset conditions are met.

2. The remote load shedding and resetting method of the electric energy meter with built-in large current switch according to claim 1, characterized in that: The real-time collection of current data and voltage data by the dynamic load monitoring module includes automatically detecting the fluctuation frequency of current and voltage within one second, performing weighted processing on the collected real-time data, and filtering the impact of instantaneous fluctuations.

3. The remote load shedding and resetting method of the electric energy meter with built-in large current switch according to claim 2, characterized in that: The generation of the warning signal includes automatically generating a load shedding warning signal and uploading it to the distributed network when the electric energy meter detects that the preset current threshold exceeds the normal operating upper limit by 20% or the voltage exceeds the preset limit by 15%. The high-frequency sampling data is averaged by setting the adaptive sampling algorithm of the data processing module to suppress the interference of sudden fluctuations. After the warning signal is generated, it is uploaded to the main control node in the distributed network in an encrypted form.

4. The remote load shedding and resetting method of the electric energy meter with built-in large current switch as claimed in claim 3, characterized in that: Synchronizing load data in the distributed network includes establishing a point-to-point data transmission protocol between the master node and the slave node, updating the load data in real time during the execution of the removal or reset instruction, and encrypting and verifying the data of each node through the distributed ledger to confirm the data consistency; When any slave node loses communication during the removal or reset process, the master node triggers data synchronization and generates an exception report, marking the abnormal node and automatically executing the backup plan.

5. The remote load shedding and resetting method of the electric energy meter with built-in large current switch according to claim 4, characterized in that: The main control node issues an instruction to control the load shedding of the electric energy meter, including that after the early warning signal is uploaded to the main control node, the main control node verifies the identity information and location data of the electric energy meter through the distributed ledger. When it is confirmed that the early warning signal is valid, the main control node sends a load shedding instruction to the corresponding electric energy meter. The instruction is transmitted using a high-priority transmission protocol. The shedding instruction reaches the target electric energy meter within 0.1 seconds. After the electric energy meter receives the shedding instruction, it starts the internal circuit breaker control module and automatically cuts off the load power supply according to the shedding response time set by the system. The distributed ledger records the data during the shedding process, including load parameters, time and operation status.

6. The remote load shedding and resetting method of the electric energy meter with built-in large current switch according to claim 5, characterized in that: The detection of load stability includes monitoring the load state of the electric energy meter every 5 seconds after the load is removed, recording whether the current fluctuation is within a preset threshold of 10% and the voltage fluctuation is within a preset limit of 8% within 10 consecutive seconds, as a stability standard for judging whether the load has been restored, and detecting the external temperature and humidity conditions through the built-in environmental sensor module of the electric energy meter to ensure that the environmental conditions meet the reset requirements. When the stable state and environmental conditions are met at the same time, a reset instruction is generated and reported to the main control node.

7. The remote load shedding and resetting method of the electric energy meter with built-in large current switch according to claim 6, characterized in that: The remote reset after the reset condition is met includes that after receiving the reset command of the master control node, the electric energy meter gradually restores the load power supply within 3 seconds, gradually increases the power supply load through the slow start module to prevent instantaneous power shock, and when the power supply load is restored to 95% of the preset current, detects the real-time data of the temperature sensor to confirm that there is no temperature overload during the power supply process. When a sudden temperature increase occurs, the reset is immediately suspended and the load detection is re-triggered. Otherwise, normal power supply is restored and operation data is recorded in the absence of abnormalities to complete the reset process; Exception handling during the reset process includes when a slave node is disconnected or abnormal fluctuations are detected during the removal or reset process, the master control node quickly switches to the backup node through the multipath protocol, records the load data of the faulty node, and predicts the impact that the reset may have on the system based on the load history data. When the reset risk exceeds the set value, the master control node delays the reset operation or continues to maintain the removal state. When the load meets the reset conditions, the master control node regenerates the reset instruction and performs secondary verification.

8. A system using a remote load shedding and resetting method of a large current switch built-in electric energy meter as claimed in any one of claims 1 to 7, characterized in that: Including monitoring and early warning module, synchronous control module, and remote reset module; The monitoring and early warning module is used to collect current data and voltage data in real time through the dynamic load monitoring module, and generate an early warning signal when the load threshold is exceeded; The synchronization control module is used to synchronize load data in the distributed network, and the master control node issues instructions to control the load shedding of the energy meter; The remote reset module is used to detect the stable state of the load and perform remote reset after the reset condition is met.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the remote load shedding and resetting method of the large current switch built-in electric energy meter according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the remote load shedding and resetting method of the large current switch built-in electric energy meter according to any one of claims 1 to 7 are implemented.

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