Carbon accounting data quality control method and device based on block chain, equipment, medium and product

Abstract

The invention discloses a carbon accounting data quality control method and device based on a block chain, equipment, a medium and a product, and relates to the technical field of carbon neutralization, and the method comprises the steps: processing each data in a carbon data set, and obtaining a hash value and a signature of each data; performing verification processing on the carbon data set to obtain a deleted carbon data set; performing threshold verification and marking on the carbon data set to obtain a marked set; performing correlation degree verification and carbon emission accounting on the deleted carbon data set, and marking a carbon emission accounting result according to a correlation degree verification result; carrying out regression analysis data verification on the carbon emission accounting result, carrying out secondary marking on the carbon emission accounting result according to the regression analysis data verification, and uploading a marking set, the carbon emission accounting result, a marking result, carbon data, a hash value and a signature to a block chain for storage. According to the invention, the problems of insufficient accuracy of carbon accounting data, data collection lagging and incomplete carbon data statistics can be solved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of carbon neutralization, in particular to a carbon accounting data quality control method and device based on a blockchain, equipment, medium and product. BACKGROUND

[0002] Due to the complex source caliber and multiple statistical links of enterprise carbon emission basic data, the data is mainly manually entered after instrument monitoring, and the data authenticity and consistency are poor and difficult to trace. In the development of carbon trading and carbon neutralization management, there are many challenges such as carbon accounting fraud and weak carbon data flow communication.

[0003] In summary, the existing carbon accounting data accuracy is not enough, data collection is lagging behind, and carbon data statistics are not comprehensive. SUMMARY

[0004] The purpose of the application is to provide a carbon accounting data quality control method and device based on a blockchain, equipment, medium and product, which can solve the problems of insufficient carbon accounting data accuracy, data collection lag and incomplete carbon data statistics.

[0005] To achieve the above purpose, the application provides the following solutions:

[0006] In a first aspect, the application provides a carbon accounting data quality control method based on a blockchain, comprising:

[0007] obtaining a carbon data set of a target enterprise;

[0008] processing each data in the carbon data set using a hash function and an asymmetric encryption algorithm to obtain a hash value and a signature of each data;

[0009] performing verification processing on the carbon data set to obtain a reduced carbon data set;

[0010] performing threshold verification processing and marking on the carbon data set to obtain a marked set;

[0011] According to the smart contract, the correlation degree of each data in the reduced carbon data set is checked and carbon emission accounting is performed, and the carbon emission accounting result is marked according to the correlation degree checking result to obtain a first marking result corresponding to the carbon emission accounting result;

[0012] Performing regression analysis data verification on the carbon emission accounting result, performing secondary marking on the carbon emission accounting result according to the regression analysis data verification, obtaining a secondary marking result corresponding to the carbon emission accounting result, and uploading the marked set, the carbon emission accounting result, the first marking result corresponding to the carbon emission accounting result, the secondary marking result corresponding to the carbon emission accounting result, each data in the carbon data set, and the hash value and signature of each data to the blockchain for storage according to the time stamp.

[0013] Optionally, the carbon data set comprises: sensor data, gateway type data and test type data of each time of each day within a year of a preset year; the sensor data comprises: coal quantity into a furnace measured by a belt scale or a coal feeder, hot water flow purchased, fuel consumption collected by a flow meter, power supply collected by a power meter, power generation collected by a power meter, power consumption collected by a power meter, power supply of a pure condensing unit, heat supply of a cogeneration unit and power generation of a pure condensing unit; the gateway type data comprises: fuel consumption recorded by an internal system of an enterprise, coal quantity into a plant, running hours of starting, running hours of stopping, heat supply of a cogeneration unit and heat supply of a pure condensing unit; the fuel consumption comprises: fuel consumption of a cogeneration unit and fuel consumption of a pure condensing unit; the test type data comprises: fuel air dry basis calorific value, fuel received basis moisture, fuel received basis low heat value calculated according to fuel air dry basis calorific value detected by a detection mechanism, sulfur content detected by the detection mechanism, carbon content detected by the detection mechanism, fuel received basis low heat value measured by an enterprise calorimeter experimental instrument and sulfur content measured by the enterprise calorimeter experimental instrument.

[0014] Optionally, the carbon data set is subjected to a verification process to obtain a reduced carbon data set, specifically comprising:

[0015] data verification is performed on the coal quantity into a plant, the coal quantity into a furnace measured by a belt scale or a coal feeder, fuel received basis low heat value calculated according to fuel air dry basis calorific value detected by a detection mechanism, sulfur content detected by the detection mechanism, fuel received basis low heat value measured by an enterprise calorimeter experimental instrument and sulfur content measured by the enterprise calorimeter experimental instrument to obtain a data verification result, and the carbon data set is reduced according to the verification result to obtain a reduced carbon data set.

[0016] Optionally, data verification is performed on the coal quantity into a plant, the coal quantity into a furnace measured by a belt scale or a coal feeder, fuel received basis low heat value calculated according to fuel air dry basis calorific value detected by a detection mechanism, sulfur content detected by the detection mechanism, fuel received basis low heat value measured by an enterprise calorimeter experimental instrument and sulfur content measured by the enterprise calorimeter experimental instrument to obtain a data verification result, and the carbon data set is reduced according to the verification result to obtain a reduced carbon data set, specifically comprising:

[0017] a sum of the coal quantity into a furnace measured by a belt scale or a coal feeder within a year within a preset year is calculated;

[0018] a sum of the coal quantity into a plant within a year within a preset year is calculated;

[0019] If the sum of the coal quantity measured by the belt scale or the coal feeder in a year within the preset year and the sum of the coal quantity in the plant in a year within the preset year differ by a preset quantity, the coal quantity in the plant in a year within the preset year is marked as warning data;

[0020] For any time in any day in a year within the preset year, if the received basis low calorific value of the fuel calculated according to the low calorific value of the fuel detected by the time detection mechanism and the received basis low calorific value of the fuel measured by the enterprise calorimeter experimental instrument at the time differ by a preset quantity, the received basis low calorific value of the fuel measured by the enterprise calorimeter experimental instrument at the time is marked as warning data, and the received basis low calorific value of the fuel measured by the enterprise calorimeter experimental instrument at the time is deleted;

[0021] If the sulfur content detected by the time detection mechanism and the sulfur content measured by the enterprise calorimeter experimental instrument at the time differ by a preset quantity, the sulfur content measured by the enterprise calorimeter experimental instrument at the time is marked as warning data, and the sulfur content measured by the enterprise calorimeter experimental instrument at the time is deleted.

[0022] Optionally, the correlation degree verification and carbon emission accounting of each data in the reduced carbon data set are performed according to the smart contract, and a first marking result corresponding to the carbon emission accounting result is obtained according to the correlation degree verification result, specifically including:

[0023] For any time in any day in a year within the preset year, if the coal quantity measured by the belt scale or the coal feeder at the time is greater than or equal to the coal quantity in the plant at the time, the carbon emission accounting result at the time is marked as unqualified, otherwise as qualified;

[0024] If the result of the low calorific value of the fuel on an empty dry basis / the elemental carbon content of the fuel on an empty dry basis at the time is not within the preset received basis elemental carbon content range of the coal, the carbon emission accounting result at the time is marked as unqualified, otherwise as qualified; the elemental carbon content of the fuel on an empty dry basis at the time is obtained according to the carbon content detected by the detection mechanism and the water content measured by the enterprise;

[0025] If the elemental carbon content of the fuel on an empty dry basis at the time is not within the preset carbon content threshold, the carbon emission accounting result at the time is marked as unqualified, otherwise as qualified;

[0026] If the power generation quantity collected by the electric meter at the time ≤ the installed capacity reported by the enterprise at the time × 8760 × the load output coefficient reported by the enterprise at the time, or the power supply quantity collected by the electric meter at the time < the power generation quantity collected by the electric meter at the time is not true, the carbon emission accounting result at the time is marked as unqualified, otherwise as qualified;

[0027] If the heat supply of the cogeneration unit at the moment + the power generation of the cogeneration unit at the moment * 3.6 / (the fuel consumption of the cogeneration unit at the moment * the low-heat value of the coal quantity fed into the furnace of the cogeneration unit at the moment) < 1, the carbon emission accounting result at the moment is marked as unqualified, otherwise as qualified;

[0028] For the condensing unit, the power generation efficiency of the condensing unit at the moment is calculated according to the power generation of the condensing unit at the moment and the power supply of the condensing unit at the moment, and if the power generation efficiency of the condensing unit at the moment is not less than the preset power generation efficiency threshold, the carbon emission accounting result at the moment is marked as unqualified, otherwise as qualified;

[0029] If the on-machine running hours in a year of the preset year are not less than the preset running time threshold, the carbon emission accounting result at the moment is marked as unqualified, otherwise as qualified;

[0030] For the cogeneration unit, the power supply coal consumption of the cogeneration unit at the moment is calculated according to the fuel consumption of the cogeneration unit at the moment and the power generation of the cogeneration unit at the moment, and if the power supply coal consumption of the cogeneration unit at the moment is not greater than the first preset power supply coal consumption threshold, the carbon emission accounting result at the moment is marked as unqualified, otherwise as qualified;

[0031] For the condensing unit, the power supply coal consumption of the condensing unit at the moment is calculated according to the fuel consumption of the condensing unit at the moment and the power generation of the condensing unit at the moment, and if the power supply coal consumption of the condensing unit at the moment is not greater than the second preset power supply coal consumption threshold, the carbon emission accounting result at the moment is marked as unqualified, otherwise as qualified;

[0032] The total power supply coal consumption at the moment is calculated according to the fuel consumption of the cogeneration unit at the moment, the fuel consumption of the condensing unit at the moment, the heat supply of the cogeneration unit at the moment and the heat supply of the condensing unit at the moment, and if the total heat supply coal consumption at the moment is not within the total power supply coal consumption preset range, the carbon emission accounting result at the moment is marked as unqualified, otherwise as qualified.

[0033] Optionally, the carbon emission accounting result is subjected to regression analysis data verification, specifically including:

[0034] The regression model is adopted to perform regression analysis data verification on the carbon emission accounting result.

[0035] In a second aspect, the present application provides a carbon accounting data quality control device based on a block chain, comprising:

[0036] An acquisition module is configured to acquire a carbon data set of a target enterprise;

[0037] An encryption module is configured to process each data in the carbon data set by using a hash function and an asymmetric encryption algorithm to obtain a hash value and a signature of each data;

[0038] A verification module is configured to perform verification processing on the carbon data set to obtain a pruned carbon data set;

[0039] A verification and marking module is configured to perform threshold verification processing and marking on the carbon data set to obtain a marked set;

[0040] A first marking module is configured to perform correlation degree verification and carbon emission accounting on each data in the pruned carbon data set according to a smart contract, mark the carbon emission accounting result according to the correlation degree verification result, and obtain a first marking result corresponding to the carbon emission accounting result;

[0041] A second marking and storage module is configured to perform regression analysis data verification on the carbon emission accounting result, mark the carbon emission accounting result twice according to the regression analysis data verification, obtain a second marking result corresponding to the carbon emission accounting result, and upload the marked set, the carbon emission accounting result, the first marking result corresponding to the carbon emission accounting result, the second marking result corresponding to the carbon emission accounting result, each data in the carbon data set, the hash value and the signature of each data to a blockchain for storage according to a time stamp.

[0042] In a third aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the carbon accounting data quality control method based on a blockchain according to any one of the above.

[0043] In a fourth aspect, the present application provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the carbon accounting data quality control method based on a blockchain according to any one of the above.

[0044] In a fifth aspect, the present application provides a computer program product comprising a computer program, wherein the computer program is executed by a processor to implement the carbon accounting data quality control method based on a blockchain according to any one of the above.

[0045] According to the embodiments provided in the present application, the following technical effects are disclosed:

[0046] The application provides a blockchain-based carbon accounting data quality control method, device, equipment, medium and product. As a rule-based digital technology, the blockchain has the characteristics of multi-party consensus, openness and transparency, tamper resistance and traceability, and is naturally suitable for scenarios with strong dependence on rules such as carbon monitoring and accounting. It can realize credible recording of the whole life cycle of carbon footprint and credible circulation of all factors of carbon emission, and support the improvement of carbon emission data quality. The application integrates the blockchain and carbon accounting data quality control technology, which can improve the authenticity and accuracy of carbon accounting data, and solve the problems of insufficient accuracy of carbon accounting data, lagging data collection and incomplete carbon data statistics. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0048] Figure 1 A flowchart of a blockchain-based carbon accounting data quality control method provided by an embodiment of the present application is provided.

[0049] Figure 2 A principle diagram of a blockchain-based carbon accounting data quality control method provided by an embodiment of the present application is provided.

[0050] Figure 3 A structural schematic diagram of a computer device provided by an embodiment of the present application is provided. DETAILED DESCRIPTION

[0051] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0052] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0053] In an exemplary embodiment, as shown in Figure 1 A blockchain-based carbon accounting data quality control method is provided, including the following steps:

[0054] Step 201: Obtain a carbon data set of a target enterprise.

[0055] Step 202: Process each data in the carbon data set using a hash function and an asymmetric encryption algorithm to obtain the hash value and signature of each data. The collected carbon data needs to be hashed, and the data hash value is used as the unique identifier of the data. At the same time, in order to ensure the credibility of the data source, the data needs to be digitally signed by the private key of the enterprise. This step can be implemented using a hash function and an asymmetric encryption algorithm. The hash and signature process ensures the integrity and authenticity of the data when it is chained.

[0056] Step 203: Verify the carbon data set to obtain the reduced carbon data set.

[0057] Step 204: Threshold verification and labeling of the carbon data set.

[0058] Step 205: According to the smart contract, the correlation degree of each data in the reduced carbon data set is checked and the carbon emission accounting is performed, and the carbon emission accounting result is marked according to the correlation degree checking result to obtain the first marking result corresponding to the carbon emission accounting result.

[0059] Step 206: Regression analysis data verification of carbon emission accounting result, secondary marking of carbon emission accounting result according to regression analysis data verification, and secondary marking result corresponding to carbon emission accounting result, and uploading the marking set, carbon emission accounting result, carbon emission accounting result corresponding to the first marking result, carbon emission accounting result corresponding to the secondary marking result, each data in the carbon data set, and the hash value and signature of each data to the blockchain for storage according to the timestamp.

[0060] In another exemplary embodiment of the present application, a carbon data collection device is used to collect multi-source data of the target enterprise, i.e. carbon data set. Step 201 is specifically:

[0061] 1) The sensor obtains the amount of coal entering the furnace measured by the belt scale or coal feeder, the gas consumption collected by the flow meter, the hot water flow purchased, the power supply of the pure condensing unit, the power generation of the cogeneration unit and the pure condensing unit, the power supply collected by the electric meter, the power generation and the power consumption. The hot water flow purchased and the power consumption collected by the electric meter are subsequently used for carbon emission accounting.

[0062] 2) The gateway type collection device collects the fuel consumption, coal entering the plant, heat supply of the cogeneration unit, heat supply of the pure condensing unit, running hours, and shutdown hours recorded by the internal system of the enterprise.

[0063] 3) collecting the fuel air dry basis heat value, the fuel received basis moisture, the fuel received basis low heat value calculated by the fuel low heat value detected by the detection institution, the sulfur content detected by the detection institution, and the carbon content detected by the detection institution through the test protocol; the fuel received basis low heat value measured by the enterprise calorimeter experimental instrument and the sulfur content measured by the enterprise calorimeter experimental instrument.

[0064] In another example embodiment of the present application, the blockchain-based carbon accounting data quality control method further comprises: collecting data monitored by the flue gas emission continuous monitoring system through the metering acquisition device. The flue gas emission continuous monitoring system monitors carbon dioxide emission values, which are used for comparison with carbon dioxide emission values obtained through carbon emission accounting.

[0065] The temperature is collected by the temperature sensor and used for subsequent carbon accounting steps.

[0066] In another example embodiment of the present application, step 203 specifically comprises:

[0067] The data verification result is obtained by data verification on the amount of coal entering the factory, the amount of coal entering the furnace measured by the belt scale or the coal feeder, the fuel received basis low heat value calculated according to the fuel low heat value detected by the detection institution, the sulfur content detected by the detection institution, the fuel received basis low heat value measured by the enterprise calorimeter experimental instrument, and the sulfur content measured by the enterprise calorimeter experimental instrument, and the carbon data set is pruned according to the verification result to obtain a pruned carbon data set.

[0068] In another example embodiment of the present application, the data verification result is obtained by data verification on the amount of coal entering the factory, the amount of coal entering the furnace measured by the belt scale or the coal feeder, the fuel received basis low heat value calculated according to the fuel low heat value detected by the detection institution, the sulfur content detected by the detection institution, the fuel received basis low heat value measured by the enterprise calorimeter experimental instrument, and the sulfur content measured by the enterprise calorimeter experimental instrument, and the carbon data set is pruned according to the verification result to obtain a pruned carbon data set, specifically comprising:

[0069] The sum of the amount of coal entering the furnace measured by the belt scale or the coal feeder in a year within a preset year is calculated; the amount of coal entering the furnace measured by the belt scale or the coal feeder is summed up in units of years.

[0070] The sum of the amount of coal entering the factory in a year within a preset year is calculated to obtain the annual amount of coal entering the factory.

[0071] If the sum of the coal into the furnace measured by the belt scale or the coal feeder in a year of the preset year and the sum of the coal into the plant in a year of the preset year differ by a preset amount (5% of the sum of the coal into the furnace measured by the belt scale or the coal feeder in a year of the preset year), the sum of the coal into the plant in a year of the preset year is marked as warning data.

[0072] For any time in any day in a year of the preset year, if the received base low heat value of the fuel calculated according to the low heat value of the fuel on an empty dry basis detected by the time detection mechanism and the received base low heat value of the fuel measured by the enterprise calorimeter experimental instrument at the time differ by a preset amount (5% of the received base low heat value of the fuel calculated according to the low heat value of the fuel on an empty dry basis detected by the time detection mechanism), the received base low heat value of the fuel measured by the enterprise calorimeter experimental instrument at the time is marked as warning data, and the received base low heat value of the fuel measured by the enterprise calorimeter experimental instrument at the time is deleted.

[0073] If the sulfur content detected by the time detection mechanism and the sulfur content measured by the enterprise calorimeter experimental instrument at the time differ by a preset amount (5% of the sulfur content detected by the time detection mechanism), the sulfur content measured by the enterprise calorimeter experimental instrument at the time is marked as warning data, and the sulfur content measured by the enterprise calorimeter experimental instrument at the time is deleted.

[0074] In another exemplary embodiment of the present application, threshold checking and marking are performed on the carbon data set to obtain a marked set, specifically:

[0075] According to the carbon accounting standard conversion formula of the low heat value of the fuel on an empty dry basis and the received base moisture of the fuel: the low heat value of the fuel is calculated;

[0076] According to the low heat value of the fuel calculated in the previous step and the collected carbon content of the fuel elements, the carbon accounting standard is: the unit heat value carbon content of the fuel is calculated;

[0077] It is determined whether the low heat value of the fuel and the unit heat value carbon content of the fuel are within a reasonable threshold range, and if not, the calculated low heat value of the fuel and the unit heat value carbon content of the fuel and the low heat value of the fuel on an empty dry basis and the received base moisture of the fuel in the carbon data set are marked as unqualified to obtain a marked set.

[0078] The reasonable threshold range is shown in Table 1 and Table 2:

[0079] Table 1 Reasonable threshold range of low heat value of fuel

[0080] Fuel type Reference threshold interval Unit Coal 5.5-32.2 GJ / t Crude oil 40.1-44.8 GJ / t Fuel oil 39.8-41.7 GJ / t Diesel 41.4-43.3 GJ / t Liquefied petroleum gas 44.8-52.2 GJ / t Refinery dry gas 47.5-50.6 GJ / t Natural gas 355.44-397.75 GJ / 10 4 Nm 3 ]]>

[0081] Table 2 reasonable threshold range of carbon content of fuel unit heat value

[0082]

[0083] In another exemplary embodiment of the present application, the correlation verification and carbon emission accounting of each data in the pruned carbon data set are performed according to the smart contract, and the carbon emission accounting result is marked according to the correlation verification result to obtain a primary marking result corresponding to the carbon emission accounting result, which specifically includes:

[0084] 1) Coal consumption.

[0085] The belt scale or coal feeder is used to obtain the amount of coal into the furnace and the amount of coal into the plant. If formula (4-1) is met, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified.

[0086] The amount of coal into the furnace < the amount of coal into the plant (4-1)

[0087] 2) Received base element carbon content of coal.

[0088] If the received base element carbon content of coal is within the range of 0.35-0.4, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified. The received base element carbon content of coal is the result of the detected fuel air-dry base fuel low-heat value / fuel air-dry base element carbon content detected by the detection agency; the fuel air-dry base element carbon content is obtained according to the carbon content detected by the detection agency and the water content measured by the enterprise.

[0089] If the fuel air-dry base element carbon content is not within the preset carbon content threshold, the carbon emission accounting result at the moment is marked as unqualified, otherwise it is marked as qualified. The reasonable threshold of fuel air-dry base element carbon content is set as follows: 60%-77% for lignite, 74%-92% for bituminous coal, and 90%-98% for anthracite.

[0090] 3) Power generation.

[0091] The power generation collected by the electric meter, the power supply collected by the electric meter, the installed capacity reported by the enterprise and the load capacity coefficient, if formula (4-2) and (4-3) are met, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified.

[0092] Power generation < installed capacity x 8760 x load capacity coefficient (4-2)

[0093] Power supply < power generation (4-3)

[0094] 4) Comprehensive thermal efficiency.

[0095] The comprehensive thermal efficiency data verification is mainly divided into two categories: cogeneration units and pure condensing units. For cogeneration units, the power generation, heat supply, fuel consumption and low heat value (which can be the fuel received base low heat value calculated according to the detection of the detection agency, or the fuel received base low heat value measured by the enterprise calorimeter experimental instrument) of the cogeneration unit are used. If formula (4-4) is met, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified.

[0096] (heat supply of the cogeneration unit at the moment + power generation of the cogeneration unit at the moment × 3.6) / (fuel consumption of the cogeneration unit at the moment × low heat value of the coal into the furnace of the cogeneration unit at the moment) < 1 (4-4)

[0097] For pure condensing units, the power generation efficiency is calculated according to the power generation and power supply of the pure condensing unit. If the power generation efficiency is less than 45%, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified.

[0098] 5) Annual operating hours.

[0099] The annual operating hours are collected by the carbon data collection device. If the annual operating hours are less than 8760 hours, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified.

[0100] 6) Coal consumption for power supply.

[0101] The coal consumption for power supply data verification is mainly divided into two categories: cogeneration units and pure condensing units. For cogeneration units, the fuel consumption and power generation of the cogeneration unit are used to calculate the coal consumption for power supply. If the coal consumption for power supply is greater than 0.1229 tce / MWh, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified. For pure condensing units, if the coal consumption for power supply is greater than 0.249 tce / MWh, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified.

[0102] 7) Coal consumption for heat supply.

[0103] The coal consumption for heat supply is calculated using the fuel consumption and heat supply of the cogeneration unit collected by the carbon data collection device and the fuel consumption and heat supply of the pure condensing unit. If the coal consumption for heat supply is between 0.03412-0.043 tce / MWh, the carbon emission accounting result is marked as qualified, otherwise the carbon emission accounting result is marked as unqualified.

[0104] In another exemplary embodiment of the present application, the carbon emission accounting result is subjected to regression analysis data verification, specifically including: using a regression model to perform regression analysis data verification on the carbon emission accounting result.

[0105] In another example embodiment of the present application, the data is carbon emission accounting according to the smart contract, specifically: the data is carbon emission accounting through the smart contract running on the blockchain network, and the smart contract carbon accounting step is calculated according to the "Greenhouse Gas Emission Accounting and Reporting Requirements" and "Enterprise Greenhouse Gas Emission Accounting and Reporting Guide for Power Generation Facilities". The smart contract contains an EmissionData structure for storing fossil fuel consumption, net purchased electricity and net purchased heat. By calling the setEmissionData function, these values can be set to trigger the process of calculating total carbon emissions. The specific emission factor values are example values, and in actual application, the parameters in the contract need to be increased and adjusted according to the specific industry accounting formula. Deploy the smart contract to the blockchain network, and the contract owner sets the carbon emission data of each stage by calling the setEmissionData function. The contract will automatically calculate the total carbon emission, and the value will be stored in totalCarbonEmission. Users on the blockchain can verify the value of totalCarbonEmission to ensure transparency and tamper resistance.

[0106] In another example embodiment of the present application, the carbon emission accounting result is subjected to regression analysis data verification, and the carbon emission accounting result is subjected to secondary marking according to the regression analysis data verification, specifically including:

[0107] The data is subjected to regression analysis data verification, and the data outside the distribution range is marked as warning data. The regression analysis data verification method is: by constructing a regression model of the verification item and the related data item, using Lasso regression, Ridge regression, regression decision tree, gradient boosting regression tree, random forest regression and other models to train and test the data, and complete the model optimization. Finally, the optimal model is verified to verify the effectiveness of the model result, and the model that passes the verification is used for regression analysis data verification of the data.

[0108] In another example embodiment of the present application, the data in the carbon data set is subjected to data regression analysis and verification before accounting.

[0109] In another example embodiment of the present application, the hash value and signature of each data are obtained by processing each data in the carbon data set using a hash function and an asymmetric encryption algorithm, and the method further includes:

[0110] The data is cleaned, aligned and encrypted.

[0111] In another example embodiment of the present application, the set of tokens, the carbon emission accounting result, the primary token result corresponding to the carbon emission accounting result, the secondary token result corresponding to the carbon emission accounting result, each data in the carbon data set, the hash value of each data, and the signature are uploaded to the blockchain according to the timestamp for storage, specifically including:

[0112] The set of tokens and the emission accounting result are encrypted to obtain the encrypted emission accounting result. For some sensitive data related to the core production and operation of the enterprise, privacy protection technologies such as homomorphic encryption, zero-knowledge proof, etc. can be used to protect the privacy of the enterprise data. Only specific legal parties can decrypt and verify the data to ensure that sensitive information is not leaked.

[0113] The encrypted set of tokens and the emission accounting result, the primary token result corresponding to the carbon emission accounting result, the secondary token result corresponding to the carbon emission accounting result, each data in the carbon data set, the hash value of each data, and the signature are uploaded to the blockchain according to the timestamp for storage. By calling the uploadEmissionData function in the smart contract, the enterprise uploads the hashed data and digital signature to the blockchain. This process requires the use of the enterprise's private key to sign the data to ensure that only the enterprise can upload the data and ensure the credibility of the data source. The verifyEmissionData function in the smart contract provides verification of the data, including verification of the hash value and digital signature. The data on the blockchain is public and any on-chain user can verify the carbon emission data of the enterprise. Of course, the data can also be accessed and verified under authorization through encryption algorithms. The hash value and digital signature of the data can be used to verify the integrity and source of the data. This provides transparency for third-party verification agencies, regulatory agencies, and the enterprise, and improves the credibility of the data. By designing a carbon data evidence smart contract for storing carbon emission data on the chain, the data structure, upload function, verification function, etc. are included. The contract needs to define the format of the stored data, including the hash value of the data, the digital signature, the timestamp, and other key information.

[0114] First, this application uses a carbon data collection device to collect carbon emission-related data to achieve real-time collection and transmission of carbon emission-related data; secondly, the collected data is pre-processed (data verification) and stored in the blockchain network, and the smart contract in the blockchain network is used to perform threshold verification, data correlation verification and data regression analysis verification on the collected data. After the data is cleaned and verified successfully, the erroneous data is eliminated to ensure the accuracy and credibility of the carbon emissions. Carbon verification and validation technology is applied to the original carbon accounting method, and combined with the advantages of blockchain's non-tamperability and distributed storage, the accuracy of corporate carbon emission accounting is effectively improved, and the accuracy of carbon accounting is improved through embedded verification methods. By utilizing smart contract technology, automated management is achieved, the efficiency and accuracy of carbon emission management are improved, and support is provided for trusted transactions of carbon emission rights.

[0115] like Figure 2 As shown, the principles of the blockchain-based carbon accounting data quality control method provided in this application are:

[0116] Step 1: Collect real-time data on the company’s carbon emissions from multiple sources.

[0117] IoT technology is used to collect carbon emission-related data. Specifically, carbon emission-related data is collected using carbon data collection devices. Metering-type collection devices include electricity meters, while gateway-type collection devices include data extraction devices for enterprise control systems. Carbon emission-related data includes various indicators such as fossil fuel energy consumption and electricity usage. Carbon data collection devices enable real-time data collection, facilitating real-time feedback on carbon emissions.

[0118] Step 2: Preprocess the collected multi-source data, eliminate erroneous data through threshold analysis, perform correlation verification and carbon accounting, and annotate the carbon accounting results.

[0119] The pre-processing of the data includes: pre-processing the data by the carbon data collection device; or pre-processing the data by the gateway where the carbon data collection device is located. The pre-processing includes data cleaning, alignment, encryption and the like, and then threshold analysis is performed on the pre-processed data. The data is stored on the blockchain after pre-processing, which can improve the accuracy of the data, and then the correlation verification is performed through the correlation verification model built in the smart contract, and then the carbon accounting is performed through the formula embedded in the smart contract. In the process of carbon accounting, the carbon accounting is performed according to the management of the carbon emission factor, wherein the power grid carbon emission factor is embedded into the smart contract according to the value specified by each country and region, and the selection of the carbon emission factor is performed according to the local situation in the process of carbon accounting. In addition, in the process of carbon accounting, the calculation model can be determined according to the needs of different industries, wherein the calculation model can include GHG protocol, ISO14064, and the standards issued by the country, so as to realize the calculation and analysis of the carbon emission data. The carbon accounting results that meet and do not meet the correlation relationship are marked.

[0120] Step 3: Regression analysis is performed on the carbon accounting results, and a warning is given to the values that do not meet the regression interval.

[0121] The carbon accounting results are analyzed in depth through the regression analysis model built in the smart contract, and the data that do not meet the regression interval is marked as warning data.

[0122] Step 4: The screened data is stored through the smart contract running on the blockchain.

[0123] For the data that meet the verification, the running smart contract automatically stores these data and the carbon accounting results. At the same time, enterprises, units or individuals can analyze and compare the data according to the analysis results, and optimize the carbon emission management scheme according to the analysis results, for example, the carbon emission in a period of time can be counted through the stored carbon data, and the trend analysis is performed according to the existing carbon emission data, so as to optimize the carbon emission control strategy.

[0124] Based on the same inventive concept, the embodiments of the present application also provide a blockchain-based carbon accounting data quality control device for implementing the above-mentioned blockchain-based carbon accounting data quality control method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more blockchain-based carbon accounting data quality control device embodiments provided below can refer to the limitations of the blockchain-based carbon accounting data quality control method described above, which will not be repeated here.

[0125] In one exemplary embodiment, a blockchain-based carbon accounting data quality control device is provided, comprising:

[0126] An acquisition module is configured to acquire a set of carbon data of a target enterprise.

[0127] an encryption module configured to process each data in the carbon data set by using a hash function and an asymmetric encryption algorithm to obtain a hash value and a signature of each data.

[0128] a verification module configured to perform verification processing on the carbon data set to obtain a pruned carbon data set.

[0129] a verification and marking module configured to perform threshold verification processing and marking on the carbon data set to obtain a marked set.

[0130] a first marking module configured to perform correlation verification and carbon emission accounting on each data in the pruned carbon data set according to a smart contract, and mark the carbon emission accounting result according to the correlation verification result to obtain a first marking result corresponding to the carbon emission accounting result.

[0131] a second marking and storage module configured to perform regression analysis data verification on the carbon emission accounting result, mark the carbon emission accounting result twice according to the regression analysis data verification to obtain a second marking result corresponding to the carbon emission accounting result, and upload the marked set, the carbon emission accounting result, the first marking result corresponding to the carbon emission accounting result, the second marking result corresponding to the carbon emission accounting result, each data in the carbon data set, and the hash value and the signature of each data to a block chain for storage according to a time stamp.

[0132] In an exemplary embodiment, a computer device, which can be a server or a terminal, can have an internal structure as shown in Figure 3 The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The database of the computer device is configured to store carbon accounting data quality control data based on a block chain. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through a network connection. The computer program is executed by the processor to implement a carbon accounting data quality control method based on a block chain.

[0133] Those skilled in the art can understand that, Figure 3The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application and does not constitute a limitation on the computer device to which the solution of the present application is applied. A specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the above-mentioned method embodiments when executing the computer program.

[0134] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the above-mentioned method embodiments when executed by a processor.

[0135] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the above method embodiments are implemented.

[0136] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0137] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0138] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0139] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the present application.

[0140] The principles and implementation modes of the present application are described by applying specific examples herein, and the above-mentioned embodiments are only used to help understand the method and its core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range can be changed. In conclusion, the content of the present application should not be understood as a limitation.

Claims

1. A carbon accounting data quality control method based on blockchain, characterized in that: The blockchain-based carbon accounting data quality control method includes: Obtain carbon data sets from target companies; Using a hash function and an asymmetric encryption algorithm to process each data in the carbon data set to obtain a hash value and a signature of each data; performing verification processing on the carbon data set to obtain a deleted carbon data set; performing threshold verification processing and marking on the carbon data set to obtain a marked set; According to the smart contract, each data in the deleted carbon data set is verified for correlation and carbon emissions are calculated, and the carbon emissions calculation result is marked according to the correlation verification result to obtain a primary marking result corresponding to the carbon emissions accounting result; Perform regression analysis data verification on the carbon emission accounting results, perform secondary marking on the carbon emission accounting results based on the regression analysis data verification, obtain the secondary marking results corresponding to the carbon emission accounting results, and upload the marking set, carbon emission accounting results, the primary marking results corresponding to the carbon emission accounting results, the secondary marking results corresponding to the carbon emission accounting results, each data in the carbon data set, the hash value of each data and the signature to the blockchain for storage according to the timestamp.

2. The blockchain-based carbon accounting data quality control method according to claim 1 is characterized in that: The carbon data set includes: sensor data, gateway data and test data at each time of each day in a preset year; the sensor data includes the amount of coal entering the furnace measured by the belt scale or coal feeder, the flow of hot water purchased, the gas consumption collected by the flow meter, the power supply collected by the electric meter, the power generation collected by the electric meter, the power consumption collected by the electric meter, the power supply of the pure condensing unit, the power generation of the cogeneration unit and the power generation of the pure condensing unit; the gateway data includes: the fuel consumption recorded by the enterprise's internal system, the amount of coal entering the factory, the number of hours of operation, and the number of hours of shutdown the heating value of the cogeneration unit and the heating value of the pure condensing unit; the fuel consumption includes the fuel consumption of the cogeneration unit and the fuel consumption of the pure condensing unit; the test data include: the air-dry basis calorific value of the fuel, the as-received basis moisture of the fuel, the as-received basis lower calorific value of the fuel calculated according to the air-dry basis lower calorific value of the fuel tested by the testing agency, the sulfur content tested by the testing agency, the carbon content tested by the testing agency, the as-received basis lower calorific value of the fuel measured by the enterprise's calorimeter experimental instrument, and the sulfur content measured by the enterprise's calorimeter experimental instrument.

3. The blockchain-based carbon accounting data quality control method according to claim 2 is characterized in that: Performing verification processing on the carbon data set to obtain a deleted carbon data set specifically includes: The amount of coal entering the factory, the amount of coal entering the furnace measured by the belt scale or coal feeder, the low calorific value of the fuel as received calculated according to the low calorific value of the fuel on an air-dry basis detected by the detection agency, the sulfur content detected by the detection agency, the low calorific value of the fuel as received measured by the enterprise's calorimeter experimental instrument, and the sulfur content measured by the enterprise's calorimeter experimental instrument are subjected to data verification to obtain a data verification result, and the carbon data set is deleted according to the verification result to obtain a deleted carbon data set.

4. The blockchain-based carbon accounting data quality control method according to claim 3 is characterized in that: The amount of coal entering the factory, the amount of coal entering the furnace measured by the belt scale or coal feeder, the low calorific value of the fuel as received calculated based on the low calorific value of the fuel on an air-dry basis detected by the detection agency, the sulfur content detected by the detection agency, the low calorific value of the fuel as received measured by the enterprise calorimeter laboratory instrument, and the sulfur content measured by the enterprise calorimeter laboratory instrument are subjected to data verification to obtain a data verification result, and the carbon data set is deleted according to the verification result to obtain a deleted carbon data set, specifically including: Calculate the sum of the amount of coal fed into the furnace measured by the belt scale or coal feeder within a preset year; Calculate the total coal quantity delivered to the plant within a preset year; If the sum of the coal quantity fed into the furnace measured by the belt scale or coal feeder within a preset year differs from the sum of the coal quantity fed into the factory within a preset year by a preset amount, the coal quantity fed into the factory within a preset year will be marked as warning data; For any time on any day within a preset year, if the low calorific value of the fuel as received calculated based on the low calorific value of the fuel on an air-dry basis detected by the detection mechanism at the time differs by a preset amount from the low calorific value of the fuel as received measured by the enterprise calorimeter laboratory instrument at the time, the low calorific value of the fuel as received measured by the enterprise calorimeter laboratory instrument at the time will be marked as warning data, and the low calorific value of the fuel as received measured by the enterprise calorimeter laboratory instrument at the time will be deleted; If the sulfur content detected by the detection mechanism at the moment differs from the sulfur content measured by the enterprise calorimeter experimental instrument at the moment by a preset amount, the sulfur content measured by the enterprise calorimeter experimental instrument at the moment is marked as warning data, and the sulfur content measured by the enterprise calorimeter experimental instrument at the moment is deleted.

5. The blockchain-based carbon accounting data quality control method according to claim 3 is characterized in that: According to the smart contract, the correlation verification and carbon emission accounting are performed on each data in the deleted carbon data set, and the carbon emission accounting results are marked according to the correlation verification results to obtain a primary marking result corresponding to the carbon emission accounting results, which specifically includes: For any time on any day within a preset year, if the amount of coal entering the furnace measured by the belt scale or coal feeder at that time is greater than or equal to the amount of coal entering the factory at that time, the carbon emission accounting result at that time will be marked as unqualified; otherwise, it will be marked as qualified; If the result of the fuel air-dry basis lower calorific value / fuel air-dry basis elemental carbon content detected by the detection mechanism at the time is not within the preset coal received elemental carbon content range, the carbon emission accounting result at the time is marked as unqualified, otherwise it is marked as qualified; the fuel air-dry basis elemental carbon content at the time is obtained based on the carbon content detected by the detection mechanism and the moisture content tested by the enterprise; If the air-dry element carbon content of the fuel at the time is not within the preset carbon content threshold, the carbon emission accounting result at the time is marked as unqualified, otherwise it is marked as qualified; If the power generation collected by the electric meter at the time is ≤ the installed capacity reported by the enterprise at the time × 8760 × the load output coefficient reported by the enterprise at the time, or the power supply collected by the electric meter at the time is < the power generation collected by the electric meter at the time, the carbon emission accounting result at the time is marked as unqualified; otherwise, it is marked as qualified; For cogeneration units, if the ratio (heat supply of the cogeneration unit at the time + power generation of the cogeneration unit at the time × 3.6) / (fuel consumption of the cogeneration unit at the time × low calorific value of the coal fed into the cogeneration unit at the time) is less than 1, the carbon emission accounting result at the time will be marked as unqualified; otherwise, it will be marked as qualified. For the pure condensing unit, the power generation efficiency of the pure condensing unit at that moment is calculated based on the power generation of the pure condensing unit at that moment and the power supply of the pure condensing unit at that moment. If the power generation efficiency of the pure condensing unit at that moment is not less than the preset power generation efficiency threshold, the carbon emission accounting result at that moment is marked as unqualified; otherwise, it is marked as qualified; If the number of operating hours in a preset year is not less than the preset operating time threshold, the carbon emission accounting result at that moment will be marked as unqualified, otherwise it will be marked as qualified; For a cogeneration unit, the power supply coal consumption of the cogeneration unit at that moment is calculated based on the fuel consumption of the cogeneration unit at that moment and the power generation of the cogeneration unit at that moment. If the power supply coal consumption of the cogeneration unit at that moment is not greater than a first preset power supply coal consumption threshold, the carbon emission accounting result at that moment is marked as unqualified; otherwise, it is marked as qualified. For the pure condensing unit, the power supply coal consumption of the pure condensing unit at that moment is calculated based on the fuel consumption of the pure condensing unit at that moment and the power generation of the pure condensing unit at that moment. If the power supply coal consumption of the pure condensing unit at that moment is not greater than the second preset power supply coal consumption threshold, the carbon emission accounting result at that moment is marked as unqualified; otherwise, it is marked as qualified. The total power supply coal consumption at that moment is calculated based on the fuel consumption of the cogeneration unit at that moment, the fuel consumption of the pure condensing unit at that moment, the heat supply of the cogeneration unit at that moment, and the heat supply of the pure condensing unit at that moment. If the total heating coal consumption at that moment is not within the preset range of the total power supply coal consumption, the carbon emission accounting result at that moment is marked as unqualified, otherwise it is marked as qualified.

6. The blockchain-based carbon accounting data quality control method according to claim 1 is characterized in that: Conduct regression analysis and data verification on carbon emission accounting results, including: A regression model is used to conduct regression analysis data verification on the carbon emission accounting results.

7. A carbon accounting data quality control device based on blockchain, characterized in that: The blockchain-based carbon accounting data quality control device includes: An acquisition module is used to obtain the carbon data set of the target enterprise; An encryption module, configured to process each data in the carbon data set using a hash function and an asymmetric encryption algorithm to obtain a hash value and a signature of each data; a verification module, configured to perform verification processing on the carbon data set to obtain a deleted carbon data set; A verification and marking module, configured to perform threshold verification processing and marking on the carbon data set to obtain a marking set; The first marking module is used to perform correlation verification and carbon emission accounting on each data in the deleted carbon data set according to the smart contract, and mark the carbon emission accounting result according to the correlation verification result to obtain the first marking result corresponding to the carbon emission accounting result; The second marking and storage module is used to perform regression analysis data verification on the carbon emission accounting results, perform secondary marking on the carbon emission accounting results based on the regression analysis data verification, obtain the secondary marking results corresponding to the carbon emission accounting results, and upload the marking set, carbon emission accounting results, the first marking results corresponding to the carbon emission accounting results, the secondary marking results corresponding to the carbon emission accounting results, each data in the carbon data set, the hash value of each data and the signature to the blockchain for storage according to the timestamp.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the blockchain-based carbon accounting data quality control method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the blockchain-based carbon accounting data quality control method according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the blockchain-based carbon accounting data quality control method according to any one of claims 1 to 6 is implemented.

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