Data acquisition device, method, equipment and storage medium for smart energy meters for carbon metering

Abstract

This invention discloses a smart energy meter data acquisition device, method, equipment, and storage medium for carbon emission metering, relating to the fields of power system and carbon emission management technology. It includes a carbon emission hardware calculation circuit module that verifies frozen data and regional-level carbon emission factors and line loss power from the upper-level node to generate carbon emission data; a first non-volatile processor that stores the carbon emission data; and a second non-volatile processor that serves as a backup for the first non-volatile processor and stores frozen electricity data. The device of this invention expands the carbon emission metering function at low cost through the idle RS485 ports of existing smart energy meters, generates dynamic carbon emission factors through local calculation, accurately calculates carbon emission data, improves data accuracy, real-time performance, and reliability, reduces the burden of centralized calculation, lowers system transformation costs, supports large-scale application, and effectively promotes low-carbon transformation and green power management.

Description

Technical Field

[0001] This invention relates to the field of power system and carbon emission management technology, specifically to a smart energy meter data acquisition device, method, equipment, and storage medium for electricity carbon metering. Background Technology

[0002] The existing power system faces two main problems: the proportion of renewable energy is gradually increasing, and the carbon emission structure of the power grid is becoming more dynamic. The static carbon emission factor cannot adapt to this change. The existing carbon emission factor is calculated based on average values ​​and cannot reflect the carbon emission differences caused by the fluctuation of the proportion of renewable energy such as wind and solar power in the power grid in real time, resulting in insufficient accuracy of carbon emission data.

[0003] Meanwhile, the carbon emission accounting of electricity users still relies on extensive statistical methods and lacks refined metering methods that are directly related to actual electricity consumption behavior. Most smart meters only provide electricity consumption data and cannot directly calculate carbon emissions. Although some systems have attempted to link electricity consumption with carbon emissions, the accuracy and operability of the data are limited due to the lack of real-time adjusted carbon factors. Existing smart meters generally do not have carbon emission metering functions, and replacing them all with meters that have this function would be too costly and would result in a waste of resources.

[0004] Current electricity carbon metering networks integrate smart meters, IoT terminals, and carbon flow tracking technology to some extent. However, the vast majority of devices lack carbon emission metering capabilities. A complete replacement with meters that have carbon metering functions would not only be a huge economic burden but would also increase the operating costs of the power system, making it difficult to achieve in the short term. Traditional power systems have a heavy computational burden, relying on centralized computing to process carbon emission data. This would lead to an increased system burden, and computational delays would affect real-time performance. Existing technologies have failed to effectively resolve the contradiction between computational accuracy and efficiency, making it difficult to provide real-time and accurate carbon emission data. Consequently, the real-time performance and accuracy of carbon emission monitoring cannot meet the increasingly stringent carbon emission management requirements. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by this invention is that: existing technologies, such as traditional smart meters, cannot measure carbon emissions, resulting in inaccurate carbon emission data. Carbon emission factors are static and cannot reflect changes in the power grid in real time. Carbon emission accounting for power users relies on extensive statistics, lacks refined measurement methods, and has high replacement costs and serious resource waste. The existing power system relies on centralized computing, which has a heavy computational burden, data transmission delays, and low real-time performance and accuracy of carbon emission monitoring. The question is how to achieve low-cost carbon emission measurement functions and improve the real-time performance and accuracy of data calculation without disrupting the existing power network operation architecture.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a smart energy meter data acquisition device for carbon metering, including a carbon emission hardware calculation circuit module, which verifies the frozen data and the regional-level carbon factor and line loss power of the upper-level node to generate carbon emission data; a first non-volatile processor for storing carbon emission data; and a second non-volatile processor, which serves as a backup for the first non-volatile processor, for storing frozen energy data.

[0008] As a preferred embodiment of the smart energy meter data acquisition device for carbon emission metering according to the present invention, the carbon emission hardware calculation circuit module includes an MCU processing module, which includes a factor generation submodule and a coupling operation submodule; the MCU processing module is connected to an RS485 interface, and communicates with the sub-node smart energy meter through the RS485 interface to establish meter files and configure acquisition tasks, performs secondary verification and point-to-point comparison on the acquired frozen data, and interacts with the regional-level carbon emission factor and line loss power obtained by the upper-level node; the frozen data includes minute-level frozen data and hourly frozen data.

[0009] As a preferred embodiment of the smart energy meter data acquisition device for carbon metering according to the present invention, the factor generation submodule includes: generating a local hourly dynamic carbon factor based on the hourly carbon factor, and obtaining the real-time carbon emission, expressed as:

[0010] ,

[0011] in, This represents the dynamic carbon emission calculation result, i.e., the final carbon emission amount, reflecting the impact of electricity consumption and energy storage regulation in each region on total carbon emissions. This represents the coefficient for the current time period. This represents the regional-level carbon emission factor received from the higher-level node. This indicates the electrical energy released and stored by a user's power storage equipment within one hour, determined based on the equipment's power and energy efficiency. When a user is in a high-carbon emission factor phase, the energy stored in the power storage system will be released. A negative value indicates the user is in a period of low carbon emission factors; conversely, a positive value indicates the user is in a period of low carbon emission factors. A positive value indicates that the user has not installed or activated any energy storage devices. The value is zero. Indicates the number of collectors. The user's hourly frozen difference, which is the increase in energy consumption of the smart meter every hour. This refers to the difference between the frozen amount in the 15th minute after each hour in a smart energy meter. , , They occurred in the 15th minute, 45th minute, and 60th minute, respectively. This indicates the current line loss power.

[0012] As a preferred embodiment of the smart energy meter data acquisition device for carbon metering according to the present invention, the coupling operation submodule includes coupling the frozen data and the local hourly dynamic carbon factor to generate carbon emission data.

[0013] As a preferred embodiment of the smart energy meter data acquisition device for carbon metering according to the present invention, the first non-volatile processor includes an EEPROM and a ferroelectric memory, which store carbon emission data including local hourly dynamic carbon factor and carbon emission amount; the second non-volatile processor includes a Flash memory, which stores power freeze data; the first non-volatile processor and the second non-volatile processor are connected to the MCU processing module through a bus.

[0014] In a preferred embodiment of the smart energy meter data acquisition device for carbon metering according to the present invention, the first non-volatile processor and the second non-volatile processor are configured to perform data storage on the first and second non-volatile processors in the event of a power outage, based on a supercapacitor backup power supply. The charging and discharging circuit is connected through a power resistor to limit the peak current. The supercapacitor backup power supply includes a 10F backup power supply and a 1F backup power supply, and the charging and discharging circuit uses a 50Ω power resistor to limit the peak current during charging and discharging.

[0015] As a preferred embodiment of the smart energy meter data acquisition device for carbon metering according to the present invention, the data acquisition device further includes: an infrared communication interface, an AC-DC power module, a first indicator light and a second indicator light, and a first LDO and a second LDO that support local data interaction when the uplink communication is abnormal, providing operating voltage for the RS485 interface, the carbon emission hardware calculation circuit module, the ESAM encryption module, and the uplink communication module; the infrared communication interface includes features that support direct acquisition of local data by an infrared handheld device under extreme conditions, such as when the uplink communication module is damaged; the AC-DC power module includes features that convert 220V AC voltage to 15V DC voltage via an AC-DC converter. Voltage; the first indicator light includes a device power indicator light, which is solid green when the power supply is normal during normal operation of each module; the second indicator light includes a device data communication indicator light, which flashes when the collector communicates with the upper-level equipment and the master station system, and turns off when the uplink communication module is idle; the first LDO includes a function to convert 15V DC voltage to 5V to power the carrier circuit; the second LDO includes a function to convert 15V DC voltage to 3.3V to power the entire carbon emission calculation circuit; the ESAM encryption module includes a function to encrypt the carbon emission data; the uplink communication module includes a function to interact with the Type I concentrator through carrier communication and dual-mode communication.

[0016] Another objective of this invention is to provide a data acquisition method for smart energy meters that measures carbon emissions. This method can calculate and store carbon emission data locally by using the RS485 communication interface of existing smart energy meters in conjunction with a carbon emission hardware calculation circuit module. This solves the problems of current smart energy meters lacking carbon emission measurement functions and relying on centralized processing for data calculation, which leads to computational burden and latency. It also reduces system upgrade costs and resource waste.

[0017] As a preferred embodiment of the smart energy meter data acquisition method for carbon metering described in this invention, the method includes: establishing a meter file through communication with the sub-node smart energy meter via an RS485 interface; configuring acquisition tasks; acquiring minute-freeze and hour-freeze data and performing secondary verification and point-to-point comparison; acquiring the regional-level carbon factor and line loss power of the upper-level node, inputting them to the factor generation submodule to generate the local hour-level real-time carbon factor; inputting the frozen data and the local hour-level real-time carbon factor into the coupling calculation submodule to generate carbon emission data; encrypting the carbon emission data through the ESAM encryption module and writing it into the first non-volatile memory and the second non-volatile memory respectively, and uploading it through the uplink communication module.

[0018] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of a smart energy meter data acquisition device for carbon metering.

[0019] A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of a smart energy meter data acquisition device for measuring carbon dioxide are disclosed.

[0020] The beneficial effects of this invention are as follows: The smart energy meter data acquisition device for carbon emission metering provided by this invention extends the carbon emission metering function through the idle RS485 communication port of the existing energy meter, without the need to replace the energy meter or carry out power outage modifications, thus reducing implementation costs and avoiding interference with the existing power system. By generating hourly dynamic carbon emission factors locally in real time through the factor generation submodule, it avoids the problem that traditional static carbon emission factors cannot reflect dynamic changes in the power grid. Real-time adjustment of the carbon emission factors accurately reflects changes in the absorption of renewable energy in the power grid and fluctuations in user electricity consumption behavior. By transferring the calculation and storage tasks of carbon emission data from the centralized computing system to local processing, the computational burden of the main station system is reduced. Edge computing improves data processing efficiency. Local storage and computation provide efficient, real-time processing and historical traceability functions for carbon emission data, effectively supporting carbon market settlement. This invention achieves better results in reducing costs, improving real-time performance and accuracy, and reducing computational burden, greatly improving the accuracy and efficiency of carbon emission metering in the power system and providing reliable data support for low-carbon transformation and green power management. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is an overall schematic diagram of the smart energy meter data acquisition device for carbon metering provided in Embodiment 1 of the present invention.

[0023] Figure 2 This is a system architecture diagram of the smart energy meter data acquisition device for carbon metering provided in Embodiment 1 of the present invention.

[0024] Figure 3 The flowchart shows the carbon data coupling process of the smart energy meter data acquisition device for carbon metering provided in Embodiment 1 of the present invention.

[0025] Figure 4 This is an application architecture diagram of the smart energy meter data acquisition device for carbon metering provided in Embodiment 1 of the present invention.

[0026] Figure 5This is an external structural diagram of the smart energy meter data acquisition device for carbon metering provided in Embodiment 2 of the present invention. Detailed Implementation

[0027] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0028] Example 1, referring to Figure 1-4 According to one embodiment of the present invention, a smart energy meter data acquisition device for carbon metering is provided, comprising:

[0029] For reference Figure 1 As shown, the carbon emission hardware calculation circuit module 100 verifies the frozen data and the regional-level electric carbon factor and line loss power of the upper-level node to generate carbon emission data.

[0030] The carbon emission hardware calculation circuit module 100 includes an MCU processing module 101, which includes a factor generation submodule 102 and a coupling operation submodule 103. The MCU processing module 101 is connected to an RS485 interface 10, and communicates with the smart energy meters of the sub-nodes through the RS485 interface 10 to establish meter files and configure data acquisition tasks. It performs secondary verification and point-to-point comparison on the collected frozen data, and exchanges data with the regional-level carbon factor and line loss power obtained by the upper-level node. The frozen data includes minute-level frozen data and hourly frozen data.

[0031] Factor generation submodule 102 includes generating a local hourly dynamic electric carbon factor based on the hourly electric carbon factor, and obtaining the real-time carbon emissions, represented as:

[0032] ,

[0033] in, This represents the dynamic carbon emission calculation result, i.e., the final carbon emission amount, reflecting the impact of electricity consumption and energy storage regulation in each region on total carbon emissions. This represents the coefficient for the current time period. This represents the regional-level carbon emission factor received from the higher-level node. This indicates the electrical energy released and stored by a user's power storage equipment within one hour, determined based on the equipment's power and energy efficiency. When a user is in a high-carbon emission factor phase, the energy stored in the power storage system will be released. A negative value indicates the user is in a period of low carbon emission factors; conversely, a positive value indicates the user is in a period of low carbon emission factors. A positive value indicates that the user has not installed or activated any energy storage devices. The value is zero. Indicates the number of collectors. The user's hourly frozen difference, which is the increase in energy consumption of the smart meter every hour. This refers to the difference between the frozen amount in the 15th minute after each hour in a smart energy meter. , , They occurred in the 15th minute, 45th minute, and 60th minute, respectively. This indicates the current line loss power.

[0034] The coupling operation submodule 103 includes coupling the frozen data and the local hourly dynamic electric carbon factor to generate carbon emission data.

[0035] The first non-volatile processor 200 stores carbon emission data; the second non-volatile processor 300, which serves as a backup for the first non-volatile processor 200, stores power freeze data.

[0036] The first non-volatile processor 200 includes an EEPROM and a ferroelectric memory, which store carbon emission data including local hourly dynamic electrocarbon factor and carbon emission amount; the second non-volatile processor 300 includes a Flash memory, which stores power freeze data; the first non-volatile processor 200 and the second non-volatile processor 300 are connected to the MCU processing module via a bus.

[0037] The first non-volatile processor 200 and the second non-volatile processor 300 include data saving of the first non-volatile processor 200 and the second non-volatile processor 300 in the event of power failure, based on a supercapacitor backup power supply C, and the charging and discharging circuit is connected through a power resistor to limit the current peak.

[0038] The supercapacitor backup power supply C includes a backup power supply with a capacity of 10F and a backup power supply with a capacity of 1F. The charging and discharging circuit uses a 50Ω power resistor to limit the peak current of charging and discharging.

[0039] For reference Figure 2As shown, the data acquisition device further includes an infrared communication interface 20, an AC-DC power module AC, a first indicator light T and a second indicator light T', a first LDO and a second LDO that support local data interaction when uplink communication is abnormal, and provide operating voltage for the RS485 interface 10, the carbon emission hardware calculation circuit module 100, the ESAM encryption module 400 and the uplink communication module 500; the infrared communication interface 20 includes features that support direct acquisition of local data by an infrared handheld device in extreme conditions, such as when the uplink communication module 500 is damaged; the AC-DC power module AC includes features that convert 220V AC voltage to 15V DC voltage via an AC-DC converter; the first indicator light T includes features that support local data interaction ... first LDO includes features that support local data interaction in extreme conditions, such as when the uplink communication module 500 is damaged; the second LDO includes features that support local data interaction in extreme conditions, such as when the uplink communication module 500 is damaged; the third LDO includes features that support local data interaction in extreme conditions, such as when the uplink communication module 500 is damaged; the fourth LDO includes features that support local data interaction in extreme conditions, such as when the uplink communication module 500 is damaged; the fifth LDO includes features that support local data interaction in extreme conditions, such as when the uplink communication module 500 is damaged; the sixth LDO includes features that support local data interaction in extreme conditions, such as when the uplink communication module 500 is damaged; the seventh LDO includes features that support local data interaction in extreme conditions, such as when the uplink communication module 500 is damaged; the eighth LDO includes features that support local data interaction in extreme conditions, such as when the uplink communication module 500 The device includes a power indicator light, which is solid green when the power supply is normal for each module; a second indicator light T', which is a data communication indicator light, which flashes when the collector communicates with the upstream equipment and the main station system, and turns off when the uplink communication module 500 is idle; a first LDO, which converts 15V DC voltage to 5V to power the carrier circuit; a second LDO, which converts 15V DC voltage to 3.3V to power the entire carbon emission calculation circuit; an ESAM encryption module 400, which encrypts the carbon emission data; and an uplink communication module 500, which interacts with the Type I concentrator via carrier communication and dual-mode communication.

[0040] For reference Figure 3 As shown, the process begins with Task 1. After power-on, the invention broadcasts communication to all connected smart meters in the sub-nodes. Based on the connection between the MCU processing module 101 and the RS485 interface 10, the system establishes meter files and configures data acquisition tasks through communication with the smart meters in the sub-nodes via the RS485 interface 10. Furthermore, the system configures data acquisition tasks according to the carbon metering requirements. The data to be collected includes the corresponding meter number, communication address, time period, rate, minute freeze, and hour freeze data for each smart meter. For the freeze data, the system will individually determine whether there are any anomalies. If there is a sudden change in energy, and the change value exceeds a user-defined preset threshold, the device will trigger a secondary verification. The MCU processing module 101 first performs a secondary verification to ensure that the data is not distorted or lost during transmission. After the secondary verification is successful, a secondary data reading is performed to verify the accuracy of the data. If the comparison is successful, the data will be retained and enter the carbon data coupling stage for further processing. If the data reading comparison fails, it is determined to be a sudden change in energy, which is identified as a fault in the smart meter's metering chip or memory. The error is then reported, and maintenance personnel are notified in a timely manner to conduct an inspection.

[0041] Furthermore, starting from Task 2, the regional-level electric carbon factor is obtained from the superior. After obtaining the regional-level electric carbon factor through the factor generation submodule 102 in the carbon emission hardware calculation circuit module 100, it is first judged. If the judgment is valid, it enters the electric carbon data coupling link. If it is invalid, the regional-level electric carbon factor needs to be obtained again to ensure that the electric carbon factor used complies with the latest standards.

[0042] Furthermore, line loss data is obtained from the coupling operation submodule 103 in the carbon emission hardware calculation circuit module 100 of Task 3. After obtaining the line loss data, it first enters the judgment stage. If the data meets the expectations, it enters the electric carbon data coupling stage. If the data does not meet the expectations or is illegal data, it is discarded and the line loss data is obtained again.

[0043] It should be noted that once Task 1, Task 2, and Task 3 have entered the electric carbon data coupling stage, they begin to produce local hourly dynamic electric carbon factors. After generating the dynamic electric carbon factors, they are again calculated with minute-freeze and hourly frozen data parameters to produce carbon emission data. After the carbon emission data is generated, it is compressed and packaged together with the frozen data and communicated through the uplink channel. The corresponding electric carbon data generated is stored locally in the first and second storage. This local storage facilitates the historical tracing and local querying of carbon emission data in the future.

[0044] The downlink communication channel of the data acquisition device Q adopts wired RS485 communication, avoiding the mainstream channels of traditional electricity meters, thus maximizing data independence and reliability, and effectively avoiding conflicts between the acquisition topology and the power supply topology. Each data acquisition device can connect to dozens or hundreds of smart electricity meters through the RS485 bus. After the data acquisition device connects to the smart electricity meters, it first conducts broadcast communication, and then establishes a file and configures the data acquisition task based on the data replied by the meters. It periodically polls the smart electricity meters connected to the data acquisition device. When a smart electricity meter in the file is found to be offline, it then performs point-to-point reading. If the point reading fails, it actively reports the smart electricity meter communication failure.

[0045] For reference Figure 4 As shown, the uplink communication of this invention can use HPLC carrier communication and dual-mode communication to communicate with the Type I concentrator. For the Type I concentrator and the master station, only one or several communication addresses need to be allocated, and the management method is consistent with that of traditional smart meters.

[0046] Different data acquisition devices can be connected directly via the 485 channel or via other channels. After connection, data from adjacent carbon metering devices can be transparently forwarded. The uplink communication data of the carbon data acquisition device has a lower communication priority than the uplink communication data of the smart energy meter, which can effectively avoid data overload or information congestion on the power line carrier channel. Dual-mode communication can be added according to the communication quality requirements based on the on-site communication environment.

[0047] Example 2, refer to Figure 5 According to one embodiment of the present invention, a smart energy meter data acquisition device for carbon metering is provided, comprising:

[0048] The data acquisition device is compact and flexible in installation. Users can easily connect the device to their existing electricity meters. During installation, no power outage or modification is required. Users only need to install the device on an unused RS485 port of the smart electricity meter to achieve carbon emission metering.

[0049] After installation, the system automatically detects and establishes meter files, configures data acquisition tasks, and communicates with the superior node to obtain regional-level carbon emission factors and line loss power. Through the data acquisition tasks, the system automatically collects the required data and performs verification. After the data verification is correct, it enters the data processing and carbon emission factor generation stage to ensure the accuracy of the data.

[0050] During system operation, this device periodically updates the carbon emission factor, calculates carbon emissions in real time, and uploads the data to the concentrator via the uplink communication module. In the event of a communication failure, the device provides a local infrared communication interface to directly acquire data via infrared devices under extreme operating conditions.

[0051] Example 3, an embodiment of the present invention, provides a data acquisition method for a smart energy meter for carbon metering, comprising:

[0052] Meter files are established by communicating with sub-node smart energy meters via RS485 interface, data acquisition tasks are configured, minute-freeze and hour-freeze data are obtained, and secondary verification and point-to-point measurement comparison are performed.

[0053] The regional-level electric carbon factor and line loss power of the upper-level node are obtained and input into the factor generation submodule to generate the local hourly real-time electric carbon factor. The frozen data and the local hourly real-time electric carbon factor are input into the coupling calculation submodule to generate carbon emission data.

[0054] Carbon emission data is encrypted by the ESAM encryption module and then written into the first non-volatile memory and the second non-volatile memory respectively, and then uploaded through the uplink communication module.

[0055] If a function is implemented as 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 this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0056] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0057] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0058] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0059] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An intelligent electric energy meter data acquisition device for electric carbon metering, characterized in that, The application relates to a carbon emission data acquisition device. The carbon emission hardware calculation circuit module (100) is used for checking frozen data and regional-level electric carbon factors and line loss power of a superior node to generate carbon emission data. The first nonvolatile processor (200) is used for storing the carbon emission data. The second nonvolatile processor (300) is used for storing electric quantity frozen data and is a backup of the first nonvolatile processor (200). The carbon emission hardware calculation circuit module (100) comprises an MCU processing module (101). The MCU processing module (101) comprises a factor generation submodule (102) and a coupling operation submodule (103). The MCU processing module (101) is connected with an RS485 interface (10) and communicates with a child node intelligent electric energy meter through the RS485 interface (10) to establish a meter file and configure a collection task, executes secondary verification and point copying comparison on collected frozen data, and performs data interaction with regional-level electric carbon factors and line loss power obtained by a superior node. The frozen data comprises minute frozen data and hour frozen data. The factor generation submodule (102) is used for generating local hour-level dynamic electric carbon factors according to hour-level electric carbon factors, and obtaining real-time carbon emission, which is expressed as: C = F * P. ， Wherein, represents the dynamic carbon emission calculation result, that is, the final carbon emission, which reflects the influence of power consumption and energy storage adjustment of each region on the total carbon emission, represents the current time period coefficient, represents the carbon emission factor of the region level received from the upper node, represents the electric energy released and stored by the user's electric energy storage device in one hour, which is determined according to the device power and energy efficiency value, when the user is in the high carbon emission factor stage, the release of the electric energy storage is carried out value is negative, otherwise the user is in the low carbon emission factor period value is positive, the user does not install the electric energy storage device, and the energy storage device is not enabled value is zero, represents the first hourly frozen difference value of the user, that is, the electric energy increment of the smart electric energy meter per 1 hour, the difference value between the frozen amount of the smart electric energy meter at each whole point and the 15th minute, so as to , , 15 minutes, 45 minutes and 60 minutes respectively, represents the current line loss power; The coupling operation submodule (103) is used for coupling the frozen data and the local hour-level dynamic electric carbon factors to generate carbon emission data.

2. The electric carbon metering smart electric meter data acquisition device of claim 1, wherein: The first nonvolatile processor (200) comprises an EEPROM and a ferroelectric memory. The second nonvolatile processor (300) comprises a flash memory. The first nonvolatile processor (200) and the second nonvolatile processor (300) are connected with the MCU processing module through a bus. The first nonvolatile processor (200) and the second nonvolatile processor (300) comprise a super capacitor backup power supply (C) which is used for executing data saving on the first nonvolatile processor (200) and the second nonvolatile processor (300) in a power failure case.

3. The electric carbon metering smart meter data acquisition device according to claim 1 or 2, characterized in that: The super capacitor backup power supply (C) comprises a backup power supply with a power supply capacity of 10F and a backup power supply with a power supply capacity of 1F. The data acquisition device further comprises an infrared communication interface (20) and an AC-DC power module (AC), first and second indicator lamps (T and T'), first and second LDOs (L and L') which support local data interaction when uplink communication is abnormal, and provide working voltages for the RS485 interface (10), the carbon emission hardware calculation circuit module (100), an ESAM encryption module (400) and an uplink communication module (500). The infrared communication interface (20) is used for supporting local data acquisition by an infrared palm machine in an extreme working condition and in a working condition where the uplink communication module (500) is damaged.

4. The electric carbon metering smart meter data acquisition device of claim 3, wherein: ​ ​ ​ The AC-DC power module (AC) comprises AC 220V voltage converted into 15V DC voltage by an AC-DC converter; The first indicator light (T) comprises a device power supply indicator, which is green and constantly on when each module is normally operated and the power supply is normal; The second indicator light (T') comprises a device data communication indicator, which enters a flashing state when the collector and the superior equipment and the main station system communicate, and is turned off when the uplink communication module (500) is idle; The first LDO (L) comprises converting 15V DC voltage into 5V to supply power to the carrier circuit; The second LDO (L') comprises converting 15V DC voltage into 3.3V to supply power to the entire carbon emission operation calculation circuit; The ESAM encryption module (400) comprises encrypting the carbon emission data; The uplink communication module (500) comprises data interaction with the I-type concentrator through carrier communication and dual-mode communication.

5. The data acquisition method of the smart electric energy meter for electric carbon metering, using the data acquisition device of the smart electric energy meter for electric carbon metering according to any one of claims 1 to 4, characterized in that, It comprises: Through the RS485 interface and the communication of the child node intelligent electric energy meter, the meter file is established, the acquisition task is configured, the minute frozen and hour frozen data are obtained, the secondary verification and point copying comparison are executed; The regional level electric carbon factor and line loss power of the superior node are obtained, input into the factor generation sub-module, and the local hour level real-time electric carbon factor is generated, the frozen data and the local hour level real-time electric carbon factor are input into the coupling operation sub-module, and the carbon emission data is generated; The carbon emission data is encrypted by the ESAM encryption module and written into the first non-volatile memory and the second non-volatile memory respectively, and uploaded by the uplink communication module. 6.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-5 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the electric carbon metering intelligent electric energy meter data acquisition method in claim 5.

7. A computer readable storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to realize the steps of the electric carbon metering intelligent electric energy meter data acquisition method in claim 5.

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