An IoT electric energy meter with backflow prevention and energy scheduling functions

Abstract

The present application discloses an IoT electric energy meter with anti-backflow and energy scheduling functions, comprising: a current transformer module for detecting the magnitude and direction of the current generated by the power grid and the inverter in real time; a voltage detection module for detecting the voltage of the power grid in real time; an electric energy measurement module for calculating electric energy data based on the magnitude and direction of the current and the voltage; a processor module for analyzing the magnitude and direction of the electric energy data, voltage, and current; a Sub‑G communication module for communicating with the inverter in a network; an anti-backflow control module for sending anti-backflow control instructions to the inverter through the Sub‑G communication module to adjust the inverter's power generation; and an energy scheduling module for implementing an energy scheduling strategy based on the analysis results. The present application can directly perform anti-backflow control on the inverter, thereby improving the timeliness and effectiveness of anti-backflow and ensuring the stability and security of the power grid; and can also implement an energy scheduling strategy based on the data of the energy node.

Description

Technical Field

[0001] The present application relates to the technical field of electric energy meters, and in particular to an Internet of Things electric energy meter with anti-backflow and energy scheduling functions. Background Art

[0002] With the transformation of energy structures and the development of new energy technologies, particularly the widespread adoption of solar photovoltaic power generation and energy storage, the functional and performance requirements of electricity meters, as key components of energy management systems, have significantly changed. However, existing electricity meter technology has several significant shortcomings and limitations. First, in terms of energy data collection, most existing meters only support single-phase or three-phase measurement. This means that to simultaneously measure energy parameters on the inverter and grid sides, multiple meters are often required. This approach not only increases the labor burden for installation, configuration, and subsequent maintenance, but also increases the complexity of data transmission and processing, raising overall system operation and maintenance costs. Second, traditional backflow prevention functions primarily rely on inverters, EMS systems, or distributed energy gateways for control. However, this control approach suffers from long data acquisition and control paths, reducing the efficiency of backflow prevention and affecting the timeliness and effectiveness of backflow prevention. Furthermore, traditional electricity meters lack energy dispatch capabilities. Existing energy dispatch relies on EMS systems or distributed energy gateways. While powerful, this deployment cost is high, limiting their widespread adoption. Summary of the Invention

[0003] The main purpose of this application is to overcome the shortcomings and deficiencies of the existing technology and provide an Internet of Things electricity meter with anti-backflow and energy scheduling functions, which can directly perform anti-backflow control on the inverter, improve the timeliness and effectiveness of anti-backflow, and ensure the stability and security of the power grid; at the same time, it can implement energy scheduling strategies based on the data of energy nodes.

[0004] In order to achieve the above objectives, this application adopts the following technical solutions:

[0005] In a first aspect, the present application provides an IoT electric energy meter with backflow prevention and energy scheduling functions, comprising: a current transformer module, a voltage detection module, an electric energy measurement module, a Sub-G communication module, a processor module, a backflow prevention control module, and an energy scheduling module;

[0006] The current transformer module is used to detect the magnitude and direction of the current at the grid access point and the magnitude and direction of the current generated by the inverter in real time;

[0007] The voltage detection module is used to detect the voltage of the grid access point in real time;

[0008] The electric energy measurement module is used to calculate the electric energy data according to the magnitude and direction of the current and the voltage;

[0009] The processor module is used to analyze and process the electric energy data, the voltage, and the magnitude and direction of the current;

[0010] The Sub-G communication module is used to communicate with the inverter in a network;

[0011] An anti-backflow control module is used to send an anti-backflow control instruction to the inverter through the Sub-G communication module to adjust the inverter power generation to achieve anti-backflow;

[0012] The energy scheduling module is used to implement an energy scheduling strategy based on the results of the analysis and processing.

[0013] As a preferred technical solution, the current transformer module includes multiple current transformers.

[0014] As a preferred technical solution, the electric energy data includes voltage, current, forward active power, reverse active power, forward active energy, reverse active energy, power factor, and harmonic content.

[0015] As a preferred technical solution, the Sub-G communication module further includes:

[0016] Used to achieve networking communication with multiple inverters.

[0017] As a preferred technical solution, the anti-backflow control module is used to send an anti-backflow control instruction to the inverter through the Sub-G communication, and adjust the inverter power generation to achieve anti-backflow, including:

[0018] Acquire the magnitude and direction of the current generated by the grid access point and the inverter through the current transformer module, and transmit them to the processor module;

[0019] The processor module transmits the magnitude and direction of the current generated by the grid access point and the inverter, as well as the electric energy data, to the anti-backflow control module;

[0020] The anti-backflow control module analyzes the magnitude and direction of the current generated by the grid access point and the inverter, as well as the electric energy data. If a reverse current is found flowing from the grid access point to the grid, the module calculates the target power reduction value required for each inverter based on the number of currently online inverters, the power generated by the inverters, and the reverse power at the grid access point.

[0021] When it is detected that the forward power of the grid access point is greater than the preset value, the target power value required for each inverter is calculated based on the number of current online inverters, the power generated by the inverters, and the forward power of the grid access point;

[0022] The anti-backflow control module generates an anti-backflow control instruction according to the downward target power value or the upward target power value;

[0023] Transmitting the anti-backflow control instruction to the inverter via the Sub-G communication module;

[0024] The inverter adjusts the power generation of the inverter according to the received anti-backflow control instruction until the rising target or the falling target is reached, so as to realize anti-backflow control.

[0025] As a preferred technical solution, the energy scheduling module is used to implement an energy scheduling strategy including a peak shaving and valley filling strategy based on the results of the analysis and processing. Specifically:

[0026] Through the current transformer module and Sub-G communication module, real-time data is collected from various energy nodes such as inverters, energy storage systems, and power-consuming equipment;

[0027] The processor module analyzes and processes the real-time data to identify peak and low periods of energy usage;

[0028] Based on the peak period and the off-peak period, the energy scheduling module determines a peak-shaving and valley-filling strategy; wherein the peak-shaving and valley-filling strategy includes a charge and discharge plan of the energy storage system and adjustment of the load of the electrical equipment;

[0029] The peak shaving and valley filling strategy is sent to each energy node of the inverter, energy storage system and power-consuming equipment to perform energy scheduling.

[0030] As a preferred technical solution, the energy scheduling module also includes implementing an off-grid backup power strategy, specifically:

[0031] Through the current transformer module and Sub-G communication module, real-time data is collected from various energy nodes such as inverters, energy storage systems, and power-consuming equipment;

[0032] The processor module determines whether the power grid is stable based on the real-time data of the power grid;

[0033] If the power grid is unstable, the energy dispatch module checks whether the energy storage system has sufficient power based on the real-time data of the energy storage system;

[0034] If the amount of electricity is sufficient, the energy scheduling module starts the off-grid backup mode and issues a control instruction to disconnect the energy storage system from the power grid; otherwise, the energy scheduling module issues a charging instruction to the energy storage system and waits for charging to be completed.

[0035] As a preferred technical solution, in the off-grid backup power mode, the electric energy meter also adjusts power distribution according to the priority and actual demand of the load of the electrical equipment to ensure that the load of the electrical equipment is stably powered.

[0036] As a preferred technical solution, the processor module in the electricity meter continuously monitors the stability of the power grid and the power of the energy storage device. If the stability of the power grid improves or the power of the energy storage device continues to decrease, it evaluates whether the conditions for restoring grid connection are met. If so, the energy scheduling module issues a grid connection command to reconnect the energy storage system to the power grid.

[0037] As a preferred technical solution, the electric energy meter also includes an AC-to-DC conversion module, a communication interface module and an AD sampling module; the AC-to-DC conversion module is used to convert AC power into DC power to provide internal power supply for the electric energy meter; the communication interface module is used to connect to a cloud platform or EMS system; the AD sampling module is used to sample current signals and voltage signals at a preset period.

[0038] In summary, compared with the prior art, the effective effects brought about by the technical solution provided by this application include at least:

[0039] The present application proposes an Internet of Things electricity meter with anti-backflow and energy scheduling functions. The electricity meter integrates a current transformer module, a voltage detection module, an electricity measurement module, a Sub-G communication module, a processor module, an anti-backflow control module and an energy scheduling module. It can directly perform anti-backflow control on the inverter without relying on the inverter, EMS system or distributed energy gateway, thereby shortening the data acquisition and control path, improving the timeliness and effectiveness of anti-backflow, and ensuring the stability and security of the power grid; at the same time, the energy scheduling module can implement intelligent energy scheduling strategies based on the analysis and processing results of the electricity data, voltage and current by the processor module, realize the rational use of energy, and solve the problem that the existing energy scheduling relies on the EMS system or distributed energy gateway to be implemented, and the deployment cost is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0041] Figure 1 A structural diagram of an IoT electricity meter with backflow prevention and energy scheduling functions provided for one embodiment of the present application. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0043] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0044] Example:

[0045] See also Figure 1 , in one embodiment of the present application, an IoT electric energy meter with backflow prevention and energy scheduling functions is provided, comprising: a current transformer module, a voltage detection module, an electric energy measurement module, a Sub-G communication module, a processor module, a backflow prevention control module, and an energy scheduling module;

[0046] The current transformer module is used to detect the magnitude and direction of the current at the grid access point and the magnitude and direction of the current generated by the inverter in real time;

[0047] The voltage detection module is used to detect the voltage of the grid access point in real time;

[0048] The electric energy measurement module is used to calculate the electric energy data according to the magnitude and direction of the current and the voltage;

[0049] The processor module is used to analyze and process the electric energy data, the voltage, and the magnitude and direction of the current;

[0050] The Sub-G communication module is used to communicate with the inverter in a network;

[0051] An anti-backflow control module is used to send an anti-backflow control instruction to the inverter through the Sub-G communication module to adjust the inverter power generation to achieve anti-backflow;

[0052] The energy scheduling module is used to implement an energy scheduling strategy based on the results of the analysis and processing.

[0053] In addition, the electric energy meter in this application also includes an AC-to-DC conversion module, a communication interface module, a human-computer interaction module, a memory module, an RTC module and an AD sampling module; wherein the AC-to-DC conversion module is used to convert AC power into DC power to provide internal power supply for the electric energy meter; the communication interface module is used to connect to the cloud platform or EMS system; the human-computer interaction module includes a display screen and operation buttons for on-site viewing of real-time electric energy parameters and operations; the memory module is used to store electric energy data; the RTC module is used to provide time information; the AD sampling module is used to sample current signals and voltage signals at a preset period, for example, sampling current signals and voltage signals at a period of 10ms.

[0054] Specifically, the communication interface module includes an Ethernet interface, a USB debug serial port, BLE (Bluetooth Low Energy), and Wi-Fi. BLE enables the energy meter to have near-field BLE configuration capabilities, which can be configured by connecting the device to the BLE via a mobile phone Bluetooth connection. Wi-Fi enables the energy meter to support Wi-Fi network configuration, which allows convenient access to the Internet and data exchange via mobile phone Bluetooth network configuration. This application can exchange data and coordinate communications with external devices such as cloud platforms or EMS systems through various communication methods such as Wi-Fi, BLE, or Ethernet.

[0055] As one of the implementation methods, the current transformer module is installed at the grid access point. In order to simultaneously obtain the power parameters of the inverter side and the grid side, the current transformer module in this application includes multiple current transformers, such as two current transformers or six current transformers, so that a single-phase electric energy meter can measure at least two electric energy parameters, and a three-phase electric energy meter can measure at least six electric energy parameters, thereby optimizing the hardware connection solution of the photovoltaic power generation and energy storage system and reducing the overall deployment cost.

[0056] As one of the implementation methods, the electric energy data includes multiple parameters such as voltage, current, frequency, forward active power, reverse active power, forward active energy, reverse active energy, forward reactive power, reverse reactive power, forward reactive energy, reverse reactive energy, apparent power, apparent energy, power factor, harmonic content, etc.

[0057] Specifically, active power refers to the power actually used to perform work in the power grid. It is calculated by the phase relationship between the current detected by the current transformer module and the voltage detected by the voltage detection module, as well as the effective values of the current and voltage. Active energy refers to the total amount of electrical energy actually consumed by the power grid over a period of time. It is calculated by integrating the active power. Power factor, the ratio of active power to apparent power in the power grid, reflects the efficiency of energy utilization in the grid and can be calculated by the phase difference between current and voltage.

[0058] The processor module is also responsible for processing human-computer interaction information from the display screen and buttons, displaying real-time power parameters, and receiving user configuration and operation instructions.

[0059] As one of the implementation methods, through the Sub-G communication module, the electricity meter supports point-to-point and one-to-many networking functions, realizing networking communication with multiple (up to 80) inverters.

[0060] In one embodiment, the anti-backflow control module is configured to send an anti-backflow control instruction to the inverter via the Sub-G communication to adjust the inverter power generation to achieve anti-backflow, and the steps include:

[0061] Acquire the magnitude and direction of the current generated by the grid access point and the inverter through the current transformer module, and transmit them to the processor module;

[0062] The processor module transmits the magnitude and direction of the current generated by the grid access point and the inverter, as well as the electric energy data, to the anti-backflow control module;

[0063] The anti-backflow control module analyzes the magnitude and direction of the current generated by the grid access point and the inverter, as well as the electric energy data. If a reverse current is found flowing from the grid access point to the grid, the module calculates the target power reduction value required for each inverter based on the number of currently online inverters, the power generated by the inverters, and the reverse power at the grid access point.

[0064] When it is detected that the forward power of the grid access point is greater than the preset value, the target power value required for each inverter is calculated based on the number of current online inverters, the power generated by the inverters, and the forward power of the grid access point;

[0065] The anti-backflow control module generates an anti-backflow control instruction according to the downward target power value or the upward target power value;

[0066] Transmitting the anti-backflow control instruction to the inverter via the Sub-G communication module;

[0067] The inverter rapidly responds to the received anti-backflow control command and adjusts the inverter's generated power until it reaches the target increase or decrease, ensuring that the power flowing from the photovoltaic power station to the grid remains close to or above 0W, thereby achieving anti-backflow control. Furthermore, the economic benefits of the inverter's power generation are maximized without backflow. Specifically, to achieve the aforementioned anti-backflow control goal, the energy meter utilizes an AD sampling module with an accuracy greater than or equal to 24 bits and a refresh rate greater than or equal to 64 kilohertz (kHz). This AD sampling module performs high-precision sampling of the current and voltage signals at the grid access point at a fixed period of 10 milliseconds (ms). Based on the sampled data, the active power at the grid access point is calculated in real time. The sampling and calculation steps are executed in a loop every 10 ms, forming a continuous monitoring and adjustment process. The energy meter continuously evaluates whether the forward power at the grid access point is stable within a preset power range (i.e., between a preset value and 0 watts (W)) based on the latest active power calculation results. If the forward power exceeds the preset power range, the inverter continues to adjust its power generation according to the anti-backflow control instruction until the forward power stabilizes back to the preset power range.

[0068] Continuously monitor the effectiveness of backflow prevention to ensure that the inverter output power is adjusted to the desired target. If the anti-backflow prevention effect fails to achieve the desired target, the anti-backflow control module will provide relevant information to the processor, and the inverter output power will be adjusted multiple times based on actual conditions until it approaches the desired target, thereby maximizing power generation revenue. In addition, when the power generation is less than or equal to the load demand of the power device, the inverter supplies power to the power device load at maximum power along with the grid. In this case, no backflow prevention operation is required, and the energy meter enters a continuous monitoring state, awaiting the next anti-backflow operation request.

[0069] As one implementation manner, the energy scheduling module is used to implement an energy scheduling strategy including a peak shaving and valley filling strategy based on the results of the analysis and processing, specifically:

[0070] (1) Collect real-time data from various energy nodes such as inverters, energy storage systems, and power-consuming devices through current transformer modules and Sub-G communication modules;

[0071] Furthermore, the real-time data of the inverter includes the current size and direction; the real-time data of the energy storage system includes the power and charging and discharging power; the real-time data of the electrical equipment includes real-time power consumption, operating status and other information.

[0072] (2) The processor module analyzes and processes the real-time data to identify peak and low periods of energy use and predict future energy demand trends;

[0073] Peak periods refer to time periods when energy demand increases significantly, while trough periods are time periods when energy demand is relatively low. The processor can use algorithms to perform statistical analysis on real-time data to accurately identify peak and trough periods.

[0074] (3) Based on the peak period and the valley period, the energy scheduling module determines a peak shaving and valley filling strategy;

[0075] Based on the peak and valley periods, the energy scheduling module formulates an energy scheduling strategy by combining factors such as the charging and discharging capacity of the energy storage system and user load characteristics.

[0076] The peak-shaving and valley-filling strategy involves scheduling the energy storage system's charge and discharge, and adjusting the load of electrical equipment. The energy storage system's charge and discharge schedule involves storing excess energy during periods of low energy demand and releasing it during peak periods to supplement the grid's energy deficit. Adjusting the load of electrical equipment involves adjusting the equipment's operating hours and power to balance energy demand. For example, this involves reducing the power consumption of non-essential equipment during peak periods and increasing its operating hours or power during off-peak periods.

[0077] (4) The peak shaving and valley filling strategy is sent to various energy nodes such as inverters, energy storage systems, and power-consuming equipment to perform energy scheduling.

[0078] In addition, the electricity meter will continuously monitor changes in grid load and electrical equipment. If it finds that the adjustment effect is poor or there are abnormal conditions, the electricity meter will adjust the strategy in time to ensure the effect of peak shaving and valley filling.

[0079] As one implementation method, the energy scheduling module further includes implementing an off-grid backup power strategy, specifically:

[0080] Through the current transformer module and Sub-G communication module, real-time data is collected from various energy nodes such as inverters, energy storage systems, and power-consuming equipment;

[0081] The processor module determines whether the power grid is stable based on the real-time data of the power grid; if the power grid is stable, the monitoring continues;

[0082] If the power grid is unstable, the energy dispatch module checks whether the energy storage system has sufficient power based on the real-time data of the energy storage system;

[0083] If the amount of electricity is sufficient, the energy dispatch module activates the off-grid backup mode and issues a control command to disconnect the energy storage system from the grid. Otherwise, the energy dispatch module issues a charging command to the energy storage system and waits for charging to complete. The inverter is used to generate electricity.

[0084] In off-grid mode, the energy meter adjusts power distribution based on the priority and actual demand of the power equipment load, ensuring stable power supply to critical loads (high-priority power equipment). The energy meter continuously monitors the energy storage device's power level, discharge rate, and load demand. If the energy storage device's power level is too low or the load demand is too high, an alarm will be issued, prompting the operator to take action.

[0085] As one of the implementation methods, the processor module in the electricity meter continuously monitors the stability of the power grid and the power of the energy storage device. If the stability of the power grid improves or the power of the energy storage device continues to decrease, it evaluates whether the conditions for restoring grid connection are met. If so, the energy scheduling module issues a grid connection command to reconnect the energy storage system to the grid.

[0086] This application integrates some functions of the energy gateway into the electricity meter, which can realize energy scheduling and effectively reduce the dependence on external EMS systems or distributed energy gateways. It not only simplifies the system architecture, but also brings lower deployment costs and return on investment to users.

[0087] The high-precision AD sampling circuit and high-performance processor integrated inside the electric energy meter in this application directly calculate the active power through half-wave sampling, realize the half-cycle detection of reverse active power and reverse current, get rid of the constraints of the metering chip performance on the refresh rate, and ensure the real-time data collection on the inverter side and the grid side; realize the autonomous control and significant improvement of data refresh, so as to get rid of the traditional electric energy meter's dependence on the metering chip refresh rate.

[0088] In summary, this application realizes direct networking communication with multiple inverters through the built-in anti-backflow control module and Sub-G communication module, can quickly respond to the backflow phenomenon, and intelligently adjust the inverter power generation to achieve backflow prevention; this control method improves the efficiency of handling the backflow phenomenon and ensures the stable operation of the power grid; it solves the problem that traditional anti-backflow electricity meters rely on inverters, EMS systems or distributed energy gateways for control, and have long data acquisition and control paths. Secondly, this application optimizes energy utilization efficiency and reduces power grid load pressure by collecting data from various energy nodes of the power grid, energy storage system and electrical equipment in real time; in addition, the energy scheduling module also has an off-grid backup power function, which can automatically switch to the energy storage system for power supply when the power grid is unstable to ensure the normal operation of key equipment.

[0089] It should be noted that, for the sake of convenience, the aforementioned embodiments are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited to the described order of actions, because according to this application, certain steps can be performed in other orders or simultaneously.

[0090] Those skilled in the art will appreciate that all or part of the processes in the above embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0091] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0092] The above embodiments are preferred implementation modes of the present application, but the implementation modes of the present application are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present application should be considered as equivalent replacement methods and are included in the scope of protection of the present application.

Claims

1. An IoT electric energy meter with backflow prevention and energy scheduling functions, characterized in that: include: Current transformer module, voltage detection module, electric energy measurement module, Sub-G communication module, processor module, anti-backflow control module, energy scheduling module; The current transformer module is used to detect the magnitude and direction of the current at the grid access point and the magnitude and direction of the current generated by the inverter in real time; The voltage detection module is used to detect the voltage of the grid access point in real time; The electric energy measurement module is used to calculate the electric energy data according to the magnitude and direction of the current and the voltage; The processor module is used to analyze and process the electric energy data, the voltage, and the magnitude and direction of the current; The Sub-G communication module is used to communicate with the inverter in a network; The anti-backflow control module is used to send an anti-backflow control instruction to the inverter through the Sub-G communication module, adjust the inverter power generation to achieve anti-backflow; specifically, it is used to obtain the magnitude and direction of the current generated by the grid access point and the inverter through the current transformer module, and transmit it to the processor module. The processor module transmits the magnitude and direction of the current generated by the grid access point and the inverter, and the electric energy data to the anti-backflow control module. The anti-backflow control module analyzes the magnitude and direction of the current generated by the grid access point and the inverter, and the electric energy data. If it is found that there is a reverse current flowing to the grid at the grid access point, the anti-backflow control module adjusts the reverse current according to the current number of online inverters, the magnitude of the inverter power generation, and the grid The reverse power of the access point is detected, and the target power reduction value required for each inverter is calculated. When it is detected that the forward power of the grid access point is greater than a preset value, the target power increase value required for each inverter is calculated based on the number of current online inverters, the power generation power of the inverter, and the forward power of the grid access point. The anti-backflow control module generates an anti-backflow control instruction based on the downward target power value or the upward target power value, and transmits the anti-backflow control instruction to the inverter through the Sub-G communication module. The inverter adjusts the power generation power of the inverter according to the received anti-backflow control instruction until the upward target or the downward target is reached, thereby realizing anti-backflow control. The energy scheduling module is used to implement an energy scheduling strategy based on the results of the analysis and processing; the energy scheduling module is also used to implement an off-grid backup power strategy, specifically by collecting real-time data from various energy nodes such as the inverter, energy storage system, and electrical equipment through the current transformer module and the Sub-G communication module; the processor module determines whether the power grid is stable based on the real-time data of the power grid; if the power grid is unstable, the energy scheduling module checks whether the energy storage system has sufficient power based on the real-time data of the energy storage system; if the power is sufficient, the energy scheduling module starts the off-grid backup power mode and issues a control instruction to disconnect the energy storage system from the power grid; otherwise, the energy scheduling module issues a charging instruction to the energy storage system and waits for charging to be completed.

2. The IoT electric energy meter with backflow prevention and energy scheduling functions according to claim 1, characterized in that: The current transformer module includes multiple current transformers.

3. The IoT electric energy meter with backflow prevention and energy scheduling functions according to claim 1, characterized in that: The electric energy data includes voltage, current, forward active power, reverse active power, forward active energy, reverse active energy, power factor, and harmonic content.

4. The Internet of Things electric energy meter with backflow prevention and energy scheduling functions according to claim 1, characterized in that: The Sub-G communication module further includes: Used to achieve networking communication with multiple inverters.

5. The Internet of Things electric energy meter with backflow prevention and energy scheduling functions according to claim 1, characterized in that: The energy scheduling module is used to implement energy scheduling strategies based on the results of the analysis and processing, including implementing peak shaving and valley filling strategies, specifically: Through the current transformer module and Sub-G communication module, real-time data is collected from various energy nodes such as inverters, energy storage systems, and power-consuming equipment; The processor module analyzes and processes the real-time data to identify peak and low periods of energy usage; Based on the peak period and the off-peak period, the energy scheduling module determines a peak-shaving and valley-filling strategy; wherein the peak-shaving and valley-filling strategy includes a charge and discharge plan of the energy storage system and adjustment of the load of the electrical equipment; The peak shaving and valley filling strategy is sent to each energy node of the inverter, energy storage system and power-consuming equipment to perform energy scheduling.

6. The Internet of Things electric energy meter with backflow prevention and energy scheduling functions according to claim 1, characterized in that: In the off-grid backup power mode, the IoT electricity meter also adjusts power distribution according to the priority and actual demand of the power equipment load to ensure that the power equipment load is stably powered.

7. The Internet of Things electric energy meter with backflow prevention and energy scheduling functions according to claim 1, characterized in that: The processor module in the IoT electricity meter continuously monitors the stability of the power grid and the power of the energy storage device. If the stability of the power grid improves or the power of the energy storage device continues to decrease, it evaluates whether the conditions for restoring grid connection are met. If so, the energy scheduling module issues a grid connection command to reconnect the energy storage system to the grid.

8. The Internet of Things electric energy meter with backflow prevention and energy scheduling functions according to claim 1, characterized in that: The IoT electricity meter also includes an AC-to-DC conversion module, a communication interface module and an AD sampling module; the AC-to-DC conversion module is used to convert AC power into DC power to provide internal power supply for the electricity meter; the communication interface module is used to connect to a cloud platform or EMS system; the AD sampling module is used to sample current signals and voltage signals at a preset period.

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