Internet of Things electric energy meter with countercurrent prevention and energy scheduling functions

Abstract

The invention discloses an Internet of Things electric energy meter with countercurrent prevention and energy scheduling functions, and the electric energy meter comprises a current transformer module which is used for detecting the size and direction of the power generation current of a power grid and an inverter in real time; the voltage detection module is used for detecting the voltage of the power grid in real time; the electric energy measuring module is used for calculating electric energy data according to the magnitude and direction of the current and the voltage; the processor module is used for analyzing the magnitude and the direction of the electric energy data, the voltage and the current; the Sub-G communication module is used for carrying out networking communication with an inverter; the anti-countercurrent control module is used for sending an anti-countercurrent control instruction to the inverter through the Sub-G communication module and adjusting the power generation power of the inverter; and the energy scheduling module is used for implementing an energy scheduling strategy according to the analysis result. According to the invention, countercurrent prevention control can be directly carried out on the inverter, the timeliness and effectiveness of countercurrent prevention are improved, and the stability and safety of a power grid are guaranteed; meanwhile, an energy scheduling strategy can be implemented according to the data of the energy nodes.

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 backflow prevention and energy scheduling functions. Background Art

[0002] With the transformation of energy structure and the development of new energy technology, especially the widespread application of solar photovoltaic power generation and energy storage technology, the functions and performance requirements of electric energy meters as key components of energy management systems have also changed significantly. However, the existing electric energy meter technology has some obvious shortcomings and limitations. First, in terms of electric energy data collection, most of the existing electric energy meters only support one single-phase or three-phase metering, which means that in order to simultaneously measure the electric energy parameters on the inverter side and the grid side, multiple electric energy meters often need to be installed. This practice not only increases the manpower burden of installation, configuration and subsequent maintenance, but also increases the complexity of data transmission and processing, and increases the overall operation and maintenance cost of the system. Secondly, the traditional anti-backflow function mainly relies on the inverter, EMS system or distributed energy gateway to achieve control; however, this control method has the problem of long data acquisition path and control path, which reduces the efficiency of processing the backflow phenomenon and affects the timeliness and effectiveness of anti-backflow. In addition, the traditional electric energy meter does not have the ability to dispatch energy. The existing energy dispatch relies on the EMS system or distributed energy gateway to achieve it. Although it is powerful, the deployment cost is high, which limits its wide application. Summary of the invention

[0003] The main purpose of this application is to overcome the shortcomings and deficiencies of the prior art and to provide an Internet of Things electricity meter with anti-backflow and energy scheduling functions, which 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; 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 the first aspect, the present application provides an IoT electric energy meter with anti-backflow and energy scheduling functions, including: a current transformer module, a voltage detection module, an electric energy measurement module, a Sub-G communication module, a processor module, an anti-backflow 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 networking manner;

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

[0012] The energy scheduling module is used to implement an energy scheduling strategy based on the result 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] The magnitude and direction of the current generated by the grid access point and the inverter are obtained through the current transformer module, and transmitted 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, and the electric energy data to the anti-backflow control module;

[0020] The anti-reverse flow 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-reverse flow control module calculates the target power reduction value required for each inverter according to the current number of online inverters, the magnitude of the inverter power generation, and the magnitude of 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 descending target power value or the ascending target power value;

[0023] Transmitting the anti-backflow control instruction to the inverter through 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 to realize the anti-backflow control.

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

[0026] Collect real-time data from various energy nodes such as inverters, energy storage systems and power-consuming equipment through current transformer modules and Sub-G communication modules;

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

[0028] Based on the peak period and the valley period, the energy scheduling module determines a peak-shaving and valley-filling strategy; wherein the peak-shaving and valley-filling strategy includes a charging and discharging plan of the energy storage system and adjusting 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 execute energy scheduling.

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

[0031] Collect real-time data from various energy nodes such as inverters, energy storage systems and power-consuming equipment through current transformer modules and Sub-G communication modules;

[0032] The processor module determines whether the power grid is stable according to 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 dispatching module starts the off-grid backup mode and issues a control command to disconnect the energy storage system from the power grid; otherwise, the energy dispatching module issues a charging command 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 electric energy meter continuously monitors the stability of the power grid and the power of the energy storage device. If the stability of the power grid is improved or the power of the energy storage device is constantly decreasing, it evaluates whether the conditions for restoring grid connection are met. If so, the energy dispatching module issues a grid connection command to reconnect the energy storage system to the 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 an 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 IoT electric energy meter with anti-backflow and energy scheduling functions. The electric energy meter integrates a current transformer module, a voltage detection module, an electric energy 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 according to the analysis and processing results of the electric energy data, voltage and current by the processor module, so as to 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 has high deployment costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. 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 paying any creative work.

[0041] Figure 1 A structural diagram of an Internet of Things electric energy meter with anti-backflow 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 application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0043] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood 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 anti-backflow and energy scheduling functions is provided, including: a current transformer module, a voltage detection module, an electric energy measurement module, a Sub-G communication module, a processor module, an anti-backflow 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 networking manner;

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

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

[0053] In addition, the electric energy meter in the present 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 a cloud platform or an EMS system; the human-computer interaction module includes a display screen and operation buttons for viewing real-time electric energy parameters and performing operations on site; 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 Ethernet interface, USB debugging serial port, BLE (Bluetooth LowEnergy), Wi-Fi, etc.; BLE enables the energy meter to have near-field BLE configuration function, and configure it through the mobile phone Bluetooth connection device BLE; Wi-Fi enables the energy meter to support Wi-Fi network configuration function, through the mobile phone Bluetooth network configuration, convenient access to the Internet for data interaction. This application can interact with data and coordinate communications with external devices such as cloud platforms or EMS systems through multiple communication methods such as Wi-Fi, BLE or Ethernet.

[0055] As one of the implementation modes, the current transformer module is installed at the grid access point. In order to simultaneously obtain the electric energy parameters of the inverter side and the grid side, the current transformer module in the present 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 modes, 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 do work in the power grid, which is calculated by the phase relationship between the current obtained 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 electric energy refers to the total amount of electric energy actually consumed in the power grid over a period of time, which is calculated by integrating the active power. Power factor refers to the ratio of active power to apparent power in the power grid. It reflects the efficiency of electric energy utilization in the power grid. The power factor 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 electric energy meter supports point-to-point and one-to-many networking functions, and realizes networking communication with multiple (up to 80) inverters.

[0060] As one implementation mode, 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, and the steps include:

[0061] The magnitude and direction of the current generated by the grid access point and the inverter are obtained through the current transformer module, and transmitted 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, and the electric energy data to the anti-backflow control module;

[0063] The anti-reverse flow 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-reverse flow control module calculates the target power reduction value required for each inverter according to the current number of online inverters, the magnitude of the inverter power generation, and the magnitude of 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 descending target power value or the ascending target power value;

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

[0067] The inverter responds quickly according to the received anti-backflow control instruction, adjusts the inverter's power generation until the rising target or the falling target is reached, so that the power flowing from the photovoltaic power station to the grid is always kept close to 0W and higher than 0W, so as to achieve anti-backflow control; and under the premise of no backflow, the economic benefits of inverter power generation are improved as much as possible. Specifically, in order to achieve the above anti-backflow control goal, the electric energy meter adopts an AD sampling module with an accuracy greater than or equal to 24 bits (bits) and a refresh rate greater than or equal to 64 kilohertz (KHz). The AD sampling module performs high-precision sampling of the current and voltage signals of the grid access point with a fixed period of 10 milliseconds (ms), and calculates the active power of the grid access point in real time based on the sampled data. The above sampling and calculation steps are executed once every 10ms to form a continuous monitoring and adjustment process; the electric energy meter continuously evaluates whether the forward power of the grid access point is stable in the preset power range (i.e., between the preset value and 0 watts (W)) according to 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-reverse flow control instruction until the forward power stabilizes back to the preset power range.

[0068] Continuously monitor the anti-backflow effect to ensure that the inverter output power adjustment reaches the expected target. If the anti-backflow effect does not reach the expected target, the anti-backflow control module will feedback relevant information to the processor and adjust the inverter output power multiple times according to the actual situation until it approaches the expected target, maximizing the power generation revenue. In addition, when the power generation is less than or equal to the load demand of the power equipment, the inverter supplies power to the power equipment load at maximum power together with the power grid. At this time, there is no need to perform anti-backflow operation, and the energy meter enters the continuous monitoring state, waiting for the next anti-backflow operation demand.

[0069] As one implementation mode, the energy scheduling module is used to implement an energy scheduling strategy including a peak shaving and valley filling strategy based on the result 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 equipment 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, charging and discharging power; the real-time data of the electrical equipment includes the real-time power consumption, operating status and other information.

[0072] (2) the processor module analyzes and processes the real-time data, identifies peak and trough periods of energy use, and predicts future energy demand trends;

[0073] Peak period refers to the time period when energy demand increases significantly, while trough period refers to the time period when energy demand is relatively low. The processor can perform statistical analysis on real-time data through algorithms 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 period and the trough period, the energy dispatching module formulates an energy dispatching strategy in combination with factors such as the charging and discharging capacity of the energy storage system and the user load characteristics.

[0076] The peak-shaving and valley-filling strategy includes the charging and discharging plan of the energy storage system and the adjustment of the load of the electrical equipment. The charging and discharging plan of the energy storage system is to use the energy storage system to store excess energy during the low energy demand period; during the peak period, the energy in the energy storage system is released to supplement the shortage of the power grid. Adjusting the load of electrical equipment is to adjust the operating time and power of electrical equipment to balance energy demand, for example, reducing the power consumption of non-essential equipment during peak periods and increasing the operating time or power of equipment during valley 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 is found that the adjustment effect is not good 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 also includes implementing an off-grid backup power strategy, specifically:

[0080] Collect real-time data from various energy nodes such as inverters, energy storage systems and power-consuming equipment through current transformer modules and Sub-G communication modules;

[0081] The processor module determines whether the power grid is stable according to 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 starts 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 be completed. The inverter is used to generate electricity.

[0084] In off-grid mode, the energy meter will adjust power distribution according to the priority and actual demand of the load of the power equipment to ensure that the critical load (high-priority power equipment) is stably powered. The energy meter continuously monitors the power of the energy storage device, the discharge rate, and the load demand of the power equipment. If the power of the energy storage device is too low or the load demand is too high, an alarm will be issued to prompt the operator to take measures.

[0085] As one of the implementation modes, the processor module in the electric energy meter continuously monitors the stability of the power grid and the power of the energy storage device. If the stability of the power grid is improved or the power of the energy storage device is continuously reduced, it evaluates whether the conditions for restoring grid connection are met. If so, the energy dispatching module issues a grid connection command to reconnect the energy storage system to the power 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 half-cycle detection of reverse active power and reverse current, get rid of the constraints of metering chip performance on refresh rate, and ensure the real-time data collection on the inverter side and the grid side; realize autonomous control and significant improvement of data refresh, so as to get rid of the dependence of traditional electric energy meters on the refresh rate of metering chips.

[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 the traditional anti-backflow energy meter relies on the inverter, EMS system or distributed energy gateway for control, and has a long data acquisition and control path. Secondly, in this application, by collecting data from each energy node of the power grid, energy storage system and electrical equipment in real time, the energy utilization efficiency is optimized and the load pressure of the power grid is reduced; 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 of description, the aforementioned embodiments are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited to the described order of actions, because according to the present 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, and 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 the present application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many 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 may 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 equivalent replacement methods and are included in the protection scope of the present application.

Claims

1. An IoT electric energy meter with backflow prevention and energy dispatching 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 networking manner; An anti-backflow control module, used to send an anti-backflow control instruction to the inverter through the Sub-G communication module, and adjust the power generation of the inverter to achieve anti-backflow; The energy scheduling module is used to implement an energy scheduling strategy based on the result of the analysis and processing.

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

3. According to claim 1, an IoT electric energy meter with backflow prevention and energy dispatching functions is 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. According to claim 1, an IoT electric energy meter with backflow prevention and energy dispatching functions is characterized in that: The Sub-G communication module further includes: Used to achieve networking communication with multiple inverters.

5. According to claim 1, an IoT electric energy meter with backflow prevention and energy dispatching functions is characterized in that: 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: The magnitude and direction of the current generated by the grid access point and the inverter are obtained through the current transformer module, and transmitted 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-reverse flow 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-reverse flow control module calculates the target power reduction value required for each inverter according to the current number of online inverters, the magnitude of the inverter power generation, and the magnitude of the reverse power at the grid access point; 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; The anti-backflow control module generates an anti-backflow control instruction according to the descending target power value or the ascending target power value; Transmitting the anti-backflow control instruction to the inverter through the Sub-G communication module; 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 to realize the anti-backflow control.

6. According to claim 1, an IoT electric energy meter with backflow prevention and energy dispatching functions is characterized in that: The energy scheduling module is used to implement energy scheduling strategies including peak shaving and valley filling strategies based on the results of the analysis and processing, specifically: Collect real-time data from various energy nodes such as inverters, energy storage systems and power-consuming equipment through current transformer modules and Sub-G communication modules; The processor module analyzes and processes the real-time data to identify peak and low periods of energy use; Based on the peak period and the valley period, the energy scheduling module determines a peak-shaving and valley-filling strategy; wherein the peak-shaving and valley-filling strategy includes a charging and discharging plan of the energy storage system and adjusting 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 execute energy scheduling.

7. According to claim 1, an IoT electric energy meter with backflow prevention and energy dispatching functions is characterized in that: The energy scheduling module also includes implementing off-grid backup power strategies, specifically: Collect real-time data from various energy nodes such as inverters, energy storage systems and power-consuming equipment through current transformer modules and Sub-G communication modules; The processor module determines whether the power grid is stable according to the real-time data of the power grid; 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; If the amount of electricity is sufficient, the energy dispatching module starts the off-grid backup mode and issues a control command to disconnect the energy storage system from the power grid; otherwise, the energy dispatching module issues a charging command to the energy storage system and waits for charging to be completed.

8. The IoT electric energy meter with backflow prevention and energy dispatching functions according to claim 7, characterized in that: In the off-grid backup power mode, the electric energy meter also adjusts the power distribution according to the priority and actual demand of the load of the power equipment to ensure that the load of the power equipment is stably powered.

9. The IoT electric energy meter with backflow prevention and energy dispatching functions according to claim 7, characterized in that: The processor module in the electric energy meter continuously monitors the stability of the power grid and the power of the energy storage device. If the stability of the power grid is improved or the power of the energy storage device is constantly decreasing, it evaluates whether the conditions for restoring grid connection are met. If so, the energy dispatching module issues a grid connection command to reconnect the energy storage system to the grid.

10. The IoT electric energy meter with backflow prevention and energy dispatching functions according to claim 1, characterized in that: 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 an EMS system; the AD sampling module is used to sample current signals and voltage signals at a preset period.

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