A blockchain-based electric carbon data processing method, device and medium

Abstract

The application discloses a kind of electric carbon data processing method, equipment and medium based on blockchain, the method comprises: obtaining the electric power data of target object, electric power data includes the power generation related data corresponding to target object, load related data, transaction related data;Green electricity traceability smart contract is used to determine the green electricity use of target object according to the power generation related data corresponding to target object, load related data, transaction related data;The carbon emission of target object is determined according to green electricity use by using electric carbon conversion smart contract, the scheme described above, from the point of view of power generation, use and transaction, the green electricity traceability of target object is carried out, so as to accurately determine the green electricity use of target object, further based on the correlation between green electricity use and carbon emission, the carbon emission of target object can be accurately obtained.

Description

Technical Field

[0001] This application relates to the field of blockchain technology, and in particular to a blockchain-based method, device, and medium for processing carbon data. Background Technology

[0002] Green electricity is electricity generated with zero or near-zero emissions of harmful pollutants. Because electricity and carbon emissions are closely linked, there is a natural connection between the green electricity trading and carbon trading markets. Currently, barriers exist between my country's green electricity trading and carbon trading mechanisms. On the supply side, there is a problem of overlapping incentives, while on the demand side, entities bear the dual constraints of green electricity consumption and carbon reduction.

[0003] However, the market currently lacks solutions that can achieve coordinated management of green electricity trading, source tracing, and carbon emissions, and the data on the main body's consumption of green electricity and related carbon emissions lack credibility. Summary of the Invention

[0004] The main technical problem addressed in this application is to provide a blockchain-based method, device, and medium for processing electricity carbon data, which can accurately determine the green electricity usage and related carbon emissions of a target object.

[0005] To address the aforementioned technical issues, this application adopts the following technical solution: providing a blockchain-based method for processing electricity carbon data. This method includes: acquiring electricity data of a target object, including power generation-related data, load-related data, and transaction-related data corresponding to the target object; using a green electricity traceability smart contract to determine the target object's green electricity usage based on the corresponding power generation-related data, load-related data, and transaction-related data; and using an electricity carbon conversion smart contract to determine the target object's carbon emissions based on the green electricity usage.

[0006] Among them, using green electricity traceability smart contracts to determine the green electricity usage of the target object based on the corresponding power generation-related data, load-related data, and transaction-related data includes: comparing the power generation-related data, load-related data, and transaction-related data with the green electricity usage reported by the target object to determine the actual green electricity usage of the target object.

[0007] Specifically, comparing power generation-related data and transaction-related data with the reported green electricity usage of the target entity to determine the target entity's actual green electricity usage includes: determining whether the power generation-related data, load-related data, and transaction-related data are greater than or equal to the reported green electricity usage; if all are yes, then the target entity's actual green electricity usage is determined to be equal to the reported green electricity usage; if none exist, then the target entity's actual green electricity usage is determined based on the power generation-related data.

[0008] The carbon emission situation includes carbon emission reduction data and carbon emission data. The carbon emission situation of the target object is determined by the electricity carbon conversion smart contract based on the green electricity usage, including: calculating the carbon emission reduction data corresponding to the target object's use of green electricity based on the green electricity usage and the electricity carbon emission factor.

[0009] Among them, using smart contracts for electricity carbon conversion to determine the carbon emissions of a target object based on its green electricity usage includes: calculating the target object's carbon emissions data based on electricity data, green electricity usage, electricity carbon emission factors, and other types of energy variables of the target object.

[0010] The calculation of carbon emission data for the target object, based on electricity data, green electricity usage, electricity carbon emission factors, and other types of energy variables, includes: calculating the target object's electricity carbon emission data based on electricity data, green electricity usage, and electricity carbon emission factors; calculating other carbon emission data for the target object based on other types of energy variables; and adding the electricity carbon emission data and other carbon emission data to obtain the target object's carbon emission data.

[0011] The carbon emission situation includes carbon emission data, and the method also includes sending adjustment prompts to the target object based on the relationship between the carbon emission data and the target object's carbon quota.

[0012] Before obtaining the power data of the target object, the method further includes: obtaining source business data from the business system, processing the source business data to obtain the power data of the target object; and putting the power data of the target object on the blockchain. Obtaining the power data of the target object includes: obtaining the power data of the target object from the blockchain-on-chain data. The business system includes a power data platform and a power trading platform. The power company's data platform is connected to the user electricity information collection system and the power marketing system, respectively.

[0013] The method further includes: in response to a user's visualization request, visualizing at least one of the following: electricity data, green electricity usage, and carbon emissions.

[0014] To solve the above-mentioned technical problems, another technical solution adopted in this application is to provide an electronic device, which includes a processor and a memory, wherein the memory is used to store program data and the processor is used to execute the program data to implement any of the above methods.

[0015] To solve the above-mentioned technical problems, another technical solution adopted in this application is to provide a computer-readable storage medium for storing program data, which can be executed to implement any of the above methods.

[0016] In the above scheme, based on the power generation-related data, load-related data, and transaction-related data of the target object, green electricity traceability can be performed on the target object from the perspectives of power generation, use, and transaction, thereby accurately determining the target object's green electricity usage. Furthermore, based on the correlation between green electricity usage and carbon emissions, the carbon emission situation of the target object can be accurately obtained, thus accurately determining the target object's green electricity usage and related carbon emissions. Attached Figure Description

[0017] Figure 1 This is a schematic flowchart of an embodiment of a blockchain-based carbon data processing method according to this application;

[0018] Figure 2 This is a schematic flowchart of another embodiment of a blockchain-based carbon data processing method of this application;

[0019] Figure 3 This is a flowchart illustrating another embodiment of step S240 of this application;

[0020] Figure 4 This is a flowchart illustrating another embodiment of step S250 in this application;

[0021] Figure 5 This is a schematic diagram of the framework of an embodiment of the electronic device of this application;

[0022] Figure 6 This is a schematic diagram of a framework of an embodiment of the computer-readable storage medium of this application. Detailed Implementation

[0023] To make the purpose, technical solution and effects of this application clearer and more explicit, the following describes this application in further detail with reference to the accompanying drawings and embodiments.

[0024] In this article, the term "and / or" simply describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, "more" in this article means two or more objects.

[0025] It is understood that the methods of this application may include the methods provided by any of the following method embodiments and any combination of the following method embodiments that do not conflict.

[0026] It is understood that the relevant steps of the method in this application can be performed by an electronic device, which can be any device with computing capabilities, such as a computer, tablet computer, mobile phone, etc.

[0027] In this embodiment, the blockchain can deploy multiple smart contracts. Each blockchain node deploys a smart contract, and all nodes determine whether the current state meets the triggering conditions of the smart contract. If so, the smart contract is executed. After execution, the result is pushed to a verification queue. The calculation results in the verification queue are then sequentially distributed to each node of the blockchain for signature verification. Consensus is reached on the results and uploaded to the blockchain, thus realizing the smart contract. The aforementioned execution electronic device serves as a node in the blockchain, and this embodiment uses the steps of the aforementioned execution electronic device as an example.

[0028] Please see Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of a blockchain-based carbon data processing method according to this application. Specifically, it may include the following steps:

[0029] Step S110: Obtain the power data of the target object.

[0030] The target entity can be a subject responsible for green energy consumption and carbon reduction, such as an electricity-consuming enterprise. The target entity's electricity data includes generation-related data, load-related data, and transaction-related data, corresponding to the generation, consumption, and transaction data related to the green energy used by the target entity, respectively. For example, generation-related data can include the generation data of the power generators supplying the green energy used by the target entity; the power generation-related data corresponding to the target entity can be determined by the power generator's supply direction. Transaction-related data can include data related to the target entity's purchase of green energy, etc.

[0031] Specifically, the aforementioned electronic device, acting as a blockchain node, can obtain the power data of the target object in the blockchain's on-chain data. Thus, when the triggering conditions of the green electricity traceability smart contract are met, step S120 is executed, and when the triggering conditions of the electricity-carbon conversion smart contract are met, step S130 is executed.

[0032] Step S120: Use the green electricity traceability smart contract to determine the green electricity usage of the target object based on the power generation-related data, load-related data, and transaction-related data corresponding to the target object.

[0033] The green electricity usage of the target entity can include whether the target entity uses green electricity and the amount of green electricity used.

[0034] Through the aforementioned green electricity traceability smart contract, it is possible to determine whether a target entity uses green electricity and the amount of green electricity used based on the perspectives of power generation, trading, and electricity consumption, thereby enabling green electricity traceability for the target entity and accurately verifying the target entity's green electricity usage.

[0035] Step S130: Use the electric carbon conversion smart contract to determine the carbon emissions of the target object based on the use of green electricity.

[0036] It is understandable that the use of green electricity can be considered as zero carbon emissions. Therefore, whether the electricity used by the target entity includes green electricity, and how much green electricity it includes, will affect the determination of the target entity's carbon emissions. Thus, after tracing the source of green electricity for the target entity, the green electricity usage of the target entity can be accurately determined, and on this basis, the carbon emissions of the target entity can be further accurately determined.

[0037] The carbon emission situation of the target entity can include carbon emission reduction data and carbon emission data. The carbon emission reduction data reflects the amount of carbon dioxide emission reduction brought about by the use of green electricity, while the carbon emission data reflects the overall carbon emission of the target entity, including the carbon emission corresponding to the use of non-green electricity and the carbon emission corresponding to the use of other energy sources.

[0038] The aforementioned carbon emission reduction data can be used to reflect the environmental contributions of the target entity. Carbon emission data helps the target entity and regulatory authorities accurately understand its carbon emission situation, facilitating oversight by regulatory authorities and enabling the target entity to plan and arrange its production and other activities. By determining the target entity's carbon emission situation, and based on the relationship between carbon emission data and the target entity's carbon quotas, information can be used as a reference for adjusting production activities. It is understood that in some embodiments, the target entity can be an electricity-consuming enterprise or a power-generating enterprise. Furthermore, the target entity can be a single enterprise or multiple enterprises, facilitating analysis of a single enterprise or analysis of multiple enterprises within a certain region.

[0039] The above scheme, based on the power generation-related data, load-related data, and transaction-related data of the target object, can trace the source of green electricity from the perspectives of power generation, use, and transaction, thereby accurately determining the target object's green electricity usage. Furthermore, based on the correlation between green electricity usage and carbon emissions, it can accurately obtain the target object's carbon emissions, thus accurately determining the target object's green electricity usage and related carbon emissions.

[0040] Please see Figure 2 , Figure 2 This is a schematic flowchart of another embodiment of a blockchain-based method for processing carbon data. Specifically, it may include the following steps:

[0041] Step S210: Obtain source business data from the business system, process the source business data to obtain the power data of the target object.

[0042] It should be noted that the execution electronic device in this embodiment can act as a blockchain node to participate in the execution of blockchain-related steps, such as the triggering and execution of smart contracts. It can also act as a regular execution device to execute non-blockchain-related steps, such as data preprocessing and visualization.

[0043] The power data of the target object is obtained by processing the source business data in the business system. The preprocessing steps of this data can be performed by the execution electronic device in this application or by other devices. In this embodiment, the former is used as an example.

[0044] Specifically, the business system may include a power company data platform and a power trading platform. The power company data platform is connected to the user electricity consumption information collection system and the power marketing system, respectively. The source business data includes electricity customer information, daily frozen electricity consumption information, enterprise electricity consumption information, electricity bill settlement information, and electricity trading information. Among them, the daily frozen electricity consumption information can be obtained by the power company data platform from the user electricity consumption information collection system; the power company data platform can provide electricity customer information and electricity bill settlement information; enterprise electricity consumption information can be obtained from the power marketing system; and electricity trading information can be obtained through the power trading platform.

[0045] The device can adapt to and connect to the interface of external business systems, and acquire source business data through the interface. Based on the type of the acquired source business data, it inputs the data into a corresponding preset algorithm for calculation to obtain the corresponding power data. For example, power data includes power generation-related data, load-related data, and transaction-related data. In some embodiments, it may also include electricity settlement information data, non-electric energy information, etc.

[0046] Step S220: Upload the power data of the target object to the blockchain.

[0047] Through step S220, electricity data can be uploaded to the blockchain. This operation can trigger the green electricity traceability smart contract and the electricity carbon conversion smart contract to determine the green electricity usage and carbon emission status of the target object. After the smart contract is executed, the execution result of the smart contract and the electricity data will be stored in the blockchain, so that they cannot be tampered with.

[0048] In some embodiments, steps S210 and S220 may also be performed by other devices. If performed by other devices, after the other devices have finished performing their tasks, the electronic device in this application may perform blockchain-related steps to determine the green electricity usage and carbon emissions of the target object.

[0049] Step S230: Obtain the power data of the target object from the blockchain on-chain data.

[0050] Step S110 can be implemented by step S230. The operation of putting the power data of the target object on the blockchain does not mean that the power data has been stored in the blockchain. Rather, it means that each node of the blockchain can obtain the data put on the blockchain and trigger the smart contract after the triggering conditions of the smart contract are met.

[0051] For example, the triggering condition for the green electricity traceability smart contract can be that power generation-related data, load-related data, and transaction-related data are uploaded to the blockchain, thereby triggering the execution of the green electricity traceability smart contract, including obtaining power generation-related data, load-related data, transaction-related data, and determining the green electricity usage of the target object based on the obtained data.

[0052] Step S240: Compare the power generation-related data, load-related data, and transaction-related data with the green electricity usage reported by the target entity to determine the actual green electricity usage of the target entity.

[0053] Step S120 can be implemented through step S240, which also utilizes the green electricity traceability contract. The details of contract execution and verification will not be elaborated further. It should be noted that the green electricity usage reported by the target object is self-reported, representing its perceived green electricity usage, and this reported usage will also be recorded on the blockchain. Green electricity traceability for the target object determines whether it uses green electricity and verifies the accuracy of its reported green electricity usage based on electricity data.

[0054] The target entity's electricity data includes generation-related data, load-related data, and transaction-related data, representing the target entity's green electricity generation data, electricity consumption data, and green electricity transaction data. By comparing the reported green electricity consumption with the generation-related data, the generation of the aforementioned green electricity can be determined from a generation perspective. Furthermore, it can also be used to determine where the generated green electricity flows to the target entity. By comparing the transaction-related data with the reported green electricity consumption, it can be verified from a transaction perspective that the target entity has purchased green electricity. By comparing the load-related data with the reported green electricity consumption, it can be verified from an electricity consumption perspective that the target entity has used green electricity.

[0055] By utilizing smart contracts for green electricity traceability, it is possible to determine whether a target entity uses green electricity and the actual amount of green electricity used in multiple stages, including power generation, trading, and consumption. This enables full-process traceability of green electricity, and the relevant information is stored on the blockchain in an immutable manner. As a result, it is possible to accurately trace green electricity, accurately determine the green electricity usage of the target entity, and improve the credibility of green electricity usage.

[0056] Please refer to the reference. Figure 3 , Figure 3This is a flowchart illustrating another embodiment of step S240 of this application. Specifically, step S240 may include the following steps:

[0057] Step S341: Determine whether the power generation-related data is greater than or equal to the reported green electricity usage.

[0058] Step S342: Determine whether the load-related data is greater than or equal to the reported green electricity usage.

[0059] Step S343: Determine whether the transaction-related data is greater than or equal to the reported green electricity usage.

[0060] It is understandable that the execution order of steps S341-S343 is not restricted; they can be executed sequentially or synchronously, and the order of execution can also be changed.

[0061] If the judgment results obtained from steps S341 to S343 are all yes, then step S344 is executed; if there is no judgment result, then step S345 is executed.

[0062] Step S344: Determine that the actual green electricity usage of the target object is equal to the reported green electricity usage.

[0063] If all the above judgment results are yes, then it can be considered that the target object used green electricity and the reported green electricity usage is true. The actual green electricity usage can be determined to be equal to the reported green electricity usage.

[0064] It is understandable that the green electricity usage reported by the target entity may not necessarily equal its actual green electricity usage. However, during the green electricity traceability process, only the reported green electricity usage is traced and verified. For example, if the target entity uses 200 kWh of electricity, of which 120 kWh is green electricity, and the target entity reports 100 kWh of green electricity usage, then the actual green electricity usage obtained from the green electricity traceability will be 100 kWh, which may differ from the actual 120 kWh of green electricity used.

[0065] Step S345: Determine the actual green electricity usage of the target object based on power generation-related data.

[0066] If any of the above judgment results are negative, then the reported green electricity usage is considered inaccurate, and the actual green electricity usage of the target entity can be determined based on power generation-related data. Specifically, power generation-related data may include the amount of green electricity generated and supplied to the target entity, which can be used to determine the actual green electricity usage.

[0067] Step S250: Use the electric carbon conversion smart contract to determine the carbon emissions of the target object based on the use of green electricity.

[0068] Among them, carbon emission status can include carbon emission reduction data. Compared with electricity generated from traditional energy sources, using green electricity reduces carbon emissions. Based on the green electricity usage of the target object, the carbon emission reduction data brought about by using green electricity can be determined.

[0069] Carbon emission data can also include carbon emission statistics. The target entity can use green electricity, non-green electricity, and other energy sources. Using green electricity results in zero carbon emissions. Based on the target entity's green electricity usage and other relevant electricity data, the carbon emissions from non-green electricity can be determined. By combining the carbon emissions from other non-electric energy sources, the overall carbon emissions of the target entity can be determined. The electricity-carbon conversion smart contract can be compiled from an electricity-carbon conversion model and used to determine carbon reduction and carbon emission data. This model uses blockchain-based data as model variables, combined with electricity carbon emission factors and other energy type variables of the target entity, to calculate the user's carbon reduction data through the electricity-carbon conversion model.

[0070] Please refer to the following: Figure 4 , Figure 4 This is a flowchart illustrating another embodiment of step S250 in this application. Specifically, step S250 may include at least one of the following steps:

[0071] It is understood that step S250 may include steps S451 and S452, or may include only step S451, or may include only step S452.

[0072] Step S451: Based on the green electricity usage and the electricity carbon emission factor, calculate the carbon emission reduction data corresponding to the target object's use of green electricity.

[0073] Among them, the green electricity usage includes the actual amount of green electricity used. By using the actual amount of green electricity used and the electricity carbon emission factor, the carbon emission reduction of the target entity based on the actual amount of green electricity used can be calculated, which is the carbon emission reduction data, thus reflecting the environmental contribution of the target entity.

[0074] Step S452: Calculate the carbon emission data of the target object based on electricity data, green electricity usage, electricity carbon emission factor, and other types of energy variables of the target object.

[0075] Among them, other types of energy variables of the target object represent the non-electric energy used by the target object, such as natural gas. This data can be provided by the target object and put on the blockchain, specifically as electricity data.

[0076] Specifically, step S452 may include the following steps: calculating the target object's electricity carbon emission data based on electricity data, green electricity usage, and electricity carbon emission factors; calculating other carbon emission data of the target object based on other types of energy variables; and adding the electricity carbon emission data and other carbon emission data to obtain the target object's carbon emission data.

[0077] It should be noted that the electricity usage of the target object can be determined based on the load-related data in the user's electricity data, including green electricity and non-green electricity. Based on this electricity usage and the determined actual amount of green electricity used, the user's non-green electricity usage can be determined. Combined with the electricity carbon emission factor, the electricity carbon emission data caused by the target object's use of non-green electricity can be calculated.

[0078] In addition to electricity, the target entity may also generate carbon emissions from non-electric energy sources. Based on other energy types provided by the target entity, we can determine other carbon emissions resulting from their use. Adding these other carbon emission data to the electricity carbon emission data yields the overall carbon emission data for the target entity.

[0079] In some embodiments, after obtaining the overall carbon emission data of the target object, the target object's carbon allowances can also be obtained through a smart contract. Based on the relationship between the carbon emission data and the carbon allowances, an adjustment prompt can be sent to the target object, prompting it to adjust its production and electricity consumption plans according to the relationship between the carbon emission data and the carbon allowances. For example, if the carbon emission data is compared with the carbon allowances and there is a surplus or shortage, the target object can be prompted to adjust its production and electricity consumption plans, such as adjusting the proportion of green electricity use, increasing / decreasing electricity consumption, or buying / selling carbon allowances.

[0080] Step S260: In response to the user's visualization request, visualize at least one of the following: electricity data, green electricity usage, and carbon emissions.

[0081] Step S260 can be performed by the execution electronic device in this application or by other devices.

[0082] For example, the device can provide users with visual buttons to issue visualization requests. In response to the user's visualization requests, it can visualize data such as the target object's power data, green electricity usage, carbon emissions, target object information, and green electricity settlement information.

[0083] It should be noted that for enterprises within a certain range, each enterprise can be processed individually as a target object to obtain corresponding data for each enterprise. When visualizing the data, each enterprise's data can be visualized separately, or several enterprises in the same region or industry can be visualized together, allowing users to intuitively understand the relevant carbon information from multiple perspectives.

[0084] In some embodiments, the electronic device can also input green electricity usage data, carbon emission reduction data, and green electricity consumption data into a proof generator to generate corresponding proofs. Specifically, the proof generator can generate proofs by the following steps: generating a proof page that can only be accessed through a dedicated link, the proof page containing proof content; generating an original QR code storing a dedicated link address, in this embodiment, the dedicated link address that can jump to the proof page can only be obtained by parsing the original QR code; obtaining the user's historical electricity data through the blockchain, reconstructing the original QR code based on the user's historical electricity data, and using the reconstructed QR code as the proof QR code.

[0085] Furthermore, the original QR code is reconstructed based on the user's historical electricity data, specifically including the following steps: selecting a certain type of data from the user's historical electricity data, plotting the trend curve of the selected data, calculating the curvature of each point on the trend curve, and taking the median value of the curvature at each point as the curvature calculation result. For example, a certain type of data from the user's historical electricity flow information data can be selected randomly or specified by the user; selecting the corresponding reconstruction mode from the reconstruction mode set according to the numerical range corresponding to the curvature calculation result; and reconstructing the original QR code according to the selected reconstruction mode.

[0086] In this embodiment, multiple reconstruction modes are preset. Different reconstruction modes represent different reconstruction operations performed on the original QR code image, such as mirror flipping and axial symmetry flipping. Based on the total number of reconstruction modes, the interval between the minimum and maximum possible values ​​of the curvature calculation result is divided into several smaller intervals of the same number. The reconstruction mode is determined according to the order of the intervals in which the curvature calculation result falls. For example, if the curvature calculation result is in the third interval, the third reconstruction mode is selected. The original QR code containing the proof page link address is reconstructed based on the user's historical electricity data change trend. This ensures that if others obtain the reconstructed QR code but are unaware of the corresponding reconstruction mode, they cannot reconstruct the correct original QR code, thus improving the security of the proof content.

[0087] Please see Figure 5 , Figure 5 This is a schematic diagram of the framework of an embodiment of the electronic device of this application.

[0088] In this embodiment, the electronic device 50 includes a memory 51 and a processor 52, wherein the memory 51 is coupled to the processor 52. Specifically, the various components of the electronic device 50 can be coupled together via a bus, or the processor 52 of the electronic device 50 can be connected to each other component individually. The electronic device 50 can be any device with processing capabilities, such as a computer, tablet computer, mobile phone, etc.

[0089] The memory 51 is used to store program data executed by the processor 52, as well as data generated by the processor 52 during processing. Examples include electricity data, carbon reduction data, and carbon emission data. The memory 51 includes a non-volatile storage portion for storing the aforementioned program data.

[0090] Processor 52 controls the operation of electronic device 50. Processor 52 can also be referred to as CPU (Central Processing Unit). Processor 52 may be an integrated circuit chip with signal processing capabilities. Processor 52 can also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. The general-purpose processor can be a microprocessor or any conventional processor. In addition, processor 52 can be implemented by multiple integrated circuit chips.

[0091] The processor 52 executes instructions to implement any of the above-mentioned blockchain-based carbon data processing methods by calling the program data stored in the memory 51.

[0092] In the above scheme, based on the power generation-related data, load-related data, and transaction-related data of the target object, green electricity traceability can be performed on the target object from the perspectives of power generation, use, and transaction, thereby accurately determining the target object's green electricity usage. Furthermore, based on the correlation between green electricity usage and carbon emissions, the carbon emission situation of the target object can be accurately obtained, thus accurately determining the target object's green electricity usage and related carbon emissions.

[0093] Please see Figure 6 , Figure 6 This is a schematic diagram of a framework of an embodiment of the computer-readable storage medium of this application.

[0094] In this embodiment, the computer-readable storage medium 60 stores processor-executable program data 61, which can be executed to implement any of the above-described blockchain-based carbon data processing methods.

[0095] The computer-readable storage medium 60 can be a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, or it can be a server storing the program data. The server can send the stored program data to other devices for execution, or it can run the stored program data itself.

[0096] In some embodiments, the computer-readable storage medium 60 may also be such as Figure 5 The memory shown.

[0097] In the above scheme, based on the power generation-related data, load-related data, and transaction-related data of the target object, green electricity traceability can be performed on the target object from the perspectives of power generation, use, and transaction, thereby accurately determining the target object's green electricity usage. Furthermore, based on the correlation between green electricity usage and carbon emissions, the carbon emission situation of the target object can be accurately obtained, thus accurately determining the target object's green electricity usage and related carbon emissions.

[0098] The above description is merely an embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A blockchain-based electric-carbon data processing method, characterized by, The method includes: acquiring power data of a target object, wherein the power data includes power generation-related data, load-related data, and transaction-related data corresponding to the target object; The green electricity usage of the target object is determined by using a green electricity traceability smart contract based on the target object's power generation-related data, load-related data, and transaction-related data. The carbon emissions of the target entity are determined based on the green electricity usage using a smart contract for electricity conversion. The carbon emission situation includes carbon reduction data and carbon emission data. The process of determining the carbon emission situation of the target object based on the green electricity usage using the electricity-carbon conversion smart contract includes: Based on the green electricity usage and the electricity carbon emission factor, the carbon emission reduction data corresponding to the green electricity usage of the target object is calculated, and / or, based on the electricity data, the green electricity usage, the electricity carbon emission factor, and other types of energy variables of the target object, the carbon emission data of the target object is calculated; specifically, this includes: calculating the electricity carbon emission data of the target object based on the electricity data, the green electricity usage, and the electricity carbon emission factor; calculating other carbon emission data of the target object based on the other types of energy variables; and adding the electricity carbon emission data and the other carbon emission data to obtain the carbon emission data of the target object; Based on the relationship between the carbon emission data and the carbon quota of the target entity, an adjustment prompt is sent to the target entity, thereby prompting the target entity to adjust its production and electricity consumption plans.

2. The method of claim 1, wherein, The step of using a green electricity traceability smart contract to determine the green electricity usage of the target object based on the power generation-related data, load-related data, and transaction-related data corresponding to the target object includes: comparing the power generation-related data, load-related data, and transaction-related data with the green electricity usage reported by the target object to determine the actual green electricity usage of the target object.

3. The method of claim 2, wherein, The step of comparing the power generation-related data, load-related data, and transaction-related data with the reported green electricity usage of the target object to determine the actual green electricity usage of the target object includes: determining whether the power generation-related data is greater than or equal to the reported green electricity usage, whether the load-related data is greater than or equal to the reported green electricity usage, and whether the transaction-related data is greater than or equal to the reported green electricity usage; If both are yes, then the actual green electricity usage of the target object is determined to be equal to the reported green electricity usage. If not, the actual green electricity usage of the target object is determined based on the power generation-related data.

4. The method of claim 1, wherein, Before obtaining the power data of the target object, the method further includes: obtaining source business data from the business system, and processing the source business data to obtain the power data of the target object; Upload the power data of the target object to the blockchain; The acquisition of the target object's power data includes: acquiring the target object's power data from the blockchain's on-chain data; And / or, the business system includes a power data platform and a power trading platform, wherein the power data platform is connected to the user electricity consumption information collection system and the power marketing system, respectively.

5. The method of claim 1, wherein, The method further includes: in response to a user's visualization request, visualizing at least one of the electricity data, the green electricity usage, and the carbon emissions.

6. An electronic device, comprising: The electronic device includes a processor and a memory, the memory being used to store program data, and the processor being used to execute the program data to implement the method as described in any one of claims 1-5.

7. A computer readable storage medium characterized in that, The computer-readable storage medium is used to store program data that can be executed to implement the method as described in any one of claims 1-5.

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