Carbon emission data determination method and device, equipment, storage medium and product

Abstract

The invention provides a carbon emission data determination method and device, equipment, a storage medium and a product. The method comprises the following steps: sending an identity authentication request to a block chain server; under the condition that the authentication information of the block chain server is obtained, generating a corresponding public key and a private key through a preset encryption algorithm; encrypting the carbon emission data through the private key to obtain encrypted data; sending the public key and the encrypted data to the block chain server, so that the block chain server combines the public key and the encrypted data to generate a block; decrypting the encrypted data through the public key, and writing the corresponding carbon emission data into the block chain according to the block; and comparing the carbon emission data in the block chain with a preset carbon emission limit, and determining a corresponding carbon emission judgment result.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, equipment, storage medium and product for determining carbon emission data. Background Art

[0002] In order to cope with global climate change, issues such as carbon emissions and carbon monitoring are attracting more and more attention. Among them, carbon monitoring is a comprehensive process that uses a variety of means such as comprehensive observation, numerical simulation and statistical analysis to obtain information on greenhouse gas emission intensity, environmental concentration, ecosystem carbon sinks, and the impact on the ecosystem, as well as the carbon source and sink conditions and their changing trends. This information is crucial for research and management work on climate change.

[0003] Relevant existing technologies mainly focus on data collection and recording. Although they have achieved real-time collection, recording and entry of key information data on carbon emissions, ensuring the timeliness and authenticity of data records, they are insufficient in data integration and analysis. It is impossible to effectively combine energy consumption data and production activity data, and it is impossible to judge the effectiveness of energy conservation and emission reduction. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment, storage medium and product for determining carbon emission data, which can accurately judge the effectiveness of energy conservation and emission reduction.

[0005] In a first aspect, the present application provides a method for determining carbon emission data, the method comprising:

[0006] Send an identity authentication request to the blockchain server;

[0007] When the authentication information of the blockchain server is obtained, a corresponding public key and a private key are generated by a preset encryption algorithm;

[0008] Encrypting the carbon emission data by using the private key to obtain encrypted data;

[0009] The public key and the encrypted data are sent to the blockchain server so that the blockchain server combines the public key and the encrypted data to generate a block; the encrypted data is decrypted by the public key, and the corresponding carbon emission data is written into the blockchain according to the block; the carbon emission data in the blockchain is compared with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

[0010] In some possible implementations, before encrypting the carbon emission data using the private key to obtain the encrypted data, the method further includes:

[0011] Obtain production statistics;

[0012] The corresponding carbon emission data is calculated based on the production statistical data.

[0013] In some possible implementations, the production statistical data includes electricity consumption data, natural gas consumption data, and oil consumption data, and the corresponding carbon emission data is calculated based on the production statistical data, including:

[0014] Extracting electricity consumption data, natural gas consumption data and oil consumption data from the production statistical data;

[0015] The corresponding carbon emission data is calculated based on the electricity consumption data, the natural gas consumption data, the oil consumption data, and the corresponding carbon emission coefficient.

[0016] In some possible implementations, after calculating the corresponding carbon emission data according to the production statistical data, the method further includes:

[0017] When the acquired carbon emission data reaches the preset quantity requirement, the volatility index of the carbon emission data is determined based on the existing carbon emission data;

[0018] Based on the volatility index, the comprehensive carbon emissions are predicted.

[0019] In some possible implementations, after predicting the comprehensive carbon emissions based on the volatility index, the method further includes:

[0020] Determine the subsequent carbon emission cap based on the comprehensive carbon emission;

[0021] When the carbon emission data exceeds the subsequent carbon emission upper limit, a carbon emission excess reminder is issued.

[0022] In some possible implementations, before encrypting the carbon emission data using the private key to obtain the encrypted data, the method further includes:

[0023] Obtain raw material consumption;

[0024] The corresponding carbon emission data is calculated based on the raw material consumption and the corresponding carbon emission coefficient.

[0025] In a second aspect, the present application provides a method for determining carbon emission data, the method comprising:

[0026] Upon receiving an identity authentication request sent by a carbon emission calculation node, sending authentication information to the carbon emission calculation node so that the emission calculation node generates a corresponding public key and a private key through a preset encryption algorithm; encrypting the carbon emission data through the private key to obtain encrypted data; and sending the public key and the encrypted data to a blockchain server;

[0027] Combining the public key and the encrypted data to generate a block;

[0028] Decrypting the encrypted data by using the public key, and writing the corresponding carbon emission data into the blockchain according to the block;

[0029] Compare the carbon emission data in the blockchain with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

[0030] In some possible implementations, decrypting the encrypted data by using the public key and writing the corresponding carbon emission data into the blockchain according to the block includes:

[0031] Decrypting the encrypted data using the public key to obtain carbon emission data;

[0032] Combining the hash value corresponding to the public key with the hash value corresponding to the previous block of the block to determine the hash value corresponding to the current block;

[0033] The carbon emission data is written into the blockchain according to the hash value corresponding to the current block.

[0034] In a third aspect, the present application provides a carbon emission data determination device, the device comprising:

[0035] A sending module, used to send an identity authentication request to a blockchain server;

[0036] A generation module, used to generate corresponding public keys and private keys through a preset encryption algorithm when the authentication information of the blockchain server is obtained;

[0037] An encryption module, used to encrypt the carbon emission data using the private key to obtain encrypted data;

[0038] The sending module is also used to send the public key and the encrypted data to the blockchain server, so that the blockchain server combines the public key and the encrypted data to generate a block; decrypt the encrypted data through the public key, and write the corresponding carbon emission data into the blockchain according to the block; compare the carbon emission data in the blockchain with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

[0039] In a fourth aspect, the present application provides a carbon emission data determination device, the device comprising: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the carbon emission data determination method as described above.

[0040] In a fifth aspect, the present application provides a computer-readable storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, the carbon emission data determination method as described above is implemented.

[0041] In a sixth aspect, the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the carbon emission data determination method as described above.

[0042] The carbon emission data determination method, device, equipment, storage medium and product provided in the embodiments of the present application establish a secure network through the carbon emissions generated by energy production and enterprise production processes, and write the carbon emission data into the blockchain through a data module, so as to achieve the security and traceability of carbon emission data, so that relevant organizations can grasp the real data in real time, and then make accurate judgments on the effectiveness of energy conservation and emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present application can be better understood from the following description of the specific embodiments of the present application in conjunction with the accompanying drawings, in which:

[0044] Other features, objects and advantages of the present application will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings, in which the same or similar reference numerals represent the same or similar features.

[0045] Figure 1 is a flow chart of a method for determining carbon emission data provided by an embodiment of the present application;

[0046] Figure 2 is a flow chart of a method for determining carbon emission data provided by another embodiment of the present application;

[0047] Figure 3 is a schematic diagram of a carbon emission data determination system provided by an embodiment of the present application;

[0048] Figure 4 It is a structural schematic diagram of a carbon emission data determination device provided by an embodiment of the present application;

[0049] Figure 5 It is a schematic diagram of the hardware structure of the carbon emission data determination device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0051] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0052] In order to solve the problems of the prior art, the embodiments of the present application provide a method, device, equipment, storage medium and product for determining carbon emission data. The following first introduces the method for determining carbon emission data provided by the embodiments of the present application.

[0053] Figure 1 FIG. 1 is a flow chart of a method for determining carbon emission data provided by an embodiment of the present application. The above method is applied to a carbon emission calculation node, such as Figure 1 As shown, the method includes the following steps: S101 to S104.

[0054] S101: Send an identity authentication request to the blockchain server.

[0055] In the specific implementation, the user's connection with the blockchain server is first verified, and an identity authentication request is sent to the blockchain server by using a predefined identity authentication protocol. The request may contain the user's credentials, authentication keys, etc. The blockchain server verifies the information and returns the authentication information. All communications should be conducted through encrypted channels to ensure the security of the identity authentication request. The blockchain server determines whether the request is legitimate based on the received credential information and returns an authentication token or certificate.

[0056] S102: After obtaining the authentication information of the blockchain server, a corresponding public key and private key are generated by a preset encryption algorithm.

[0057] In the specific implementation, a common public-private key encryption algorithm is used. According to the selected encryption algorithm, the public key and private key are generated using the relevant encryption library. Among them, the private key is used to encrypt data and can only be used by the entity that owns the private key; the public key can be publicly used to decrypt data. Anyone can own and use the public key, but only the owner of the private key can encrypt data.

[0058] S103: Encrypt the carbon emission data using the private key to obtain encrypted data.

[0059] In the specific implementation, carbon emission data is collected, encrypted using a private key and encryption algorithm, and the encrypted data generates a ciphertext, i.e., encrypted data. The encrypted data will be packaged in the format required by the blockchain and prepared to be sent to the blockchain server.

[0060] S104: Send the public key and the encrypted data to the blockchain server, so that the blockchain server combines the public key and the encrypted data to generate a block. Decrypt the encrypted data using the public key, and write the corresponding carbon emission data into the blockchain according to the block. Compare the carbon emission data in the blockchain with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

[0061] In the specific implementation, the encrypted data and public key are packaged and sent to the blockchain server. After receiving the public key and encrypted data, the blockchain server may execute a smart contract. The function of the contract is to combine the data and the public key to generate a new block and add this block to the blockchain. The logic in the smart contract will verify the integrity of the encrypted data and the legitimacy of the public key. The public key and encrypted data will be stored in the newly generated block and connected to the existing blockchain.

[0062] The carbon emission data determination method provided in the embodiment of the present application establishes a secure network through the carbon emissions generated by energy production and enterprise production processes, and writes the carbon emission data into the blockchain through a data module, thereby achieving the security and traceability of the carbon emission data, allowing relevant organizations to grasp the real data in real time, and then make accurate judgments on the effectiveness of energy conservation and emission reduction.

[0063] In order to accurately obtain carbon emission data, in some embodiments, before the above S103, the above method may further include the following steps: S1031 to S1032.

[0064] S1031: Obtain production statistics.

[0065] In the specific implementation, in order to extract data from production equipment, enterprise resource planning (ERP) systems or other data sources into the system, it may be necessary to develop specific data interfaces (APIs). These interfaces will automatically capture data from various systems, or directly connect to the production monitoring system to transmit real-time data to the main system. Different data sources may use different formats, so format conversion may be required when extracting data to convert all data into a unified standard format. Check whether the extracted data is complete and whether there are missing values. For example, if the data of a production batch is missing, it needs to be marked or supplemented. Outliers may appear in the production process (such as equipment failure, recording errors, etc.), and these data should be detected and eliminated to ensure the accuracy of subsequent calculations. Data preprocessing also includes standardization (such as unit unification, time format standardization, etc.) to ensure that data from different sources can be seamlessly combined for further analysis and calculation.

[0066] S1032: Based on the above production statistical data, the corresponding carbon emission data is calculated.

[0067] In the specific implementation, each energy and raw material has a standard carbon emission factor, which represents the carbon emission per unit consumption. Different production processes will have different carbon emission factors. Therefore, in the process of carbon emission calculation, it is necessary to select appropriate emission factors according to different production lines or production links. According to the preset carbon emission factors, the carbon emissions of each type of production activity are calculated item by item. All calculated carbon emission data are aggregated into a comprehensive data set, which may be classified and aggregated according to dimensions such as various production links, equipment, time periods, etc., so as to calculate the corresponding carbon emission data.

[0068] The above implementation of the embodiment of the present application is the basis of the entire process by obtaining accurate production statistical data. Next, by selecting appropriate carbon emission factors and calculation models, these production data are converted into specific carbon emission data, thereby accurately obtaining carbon emission data.

[0069] In order to calculate the result accurately, in some embodiments, the above production statistics include electricity consumption data, natural gas consumption data and oil consumption data, and the above S1032 may include the following steps: S10321 to S10322.

[0070] S10321: Extract electricity consumption data, natural gas consumption data and oil consumption data from the above production statistics.

[0071] In the specific implementation, first, you need to establish a connection with the source of production statistics. Get the raw data through the interface. For electricity consumption data, the interface may need to obtain it from the meter data of the production equipment, sensors, or the energy management module in the enterprise resource planning system. For natural gas and oil consumption, the data source may be through reading the natural gas flow meter of the production equipment, the oil and gas monitoring system, or manual reports. It may be necessary to convert the data into a unified unit.

[0072] S10322: Calculate the corresponding carbon emission data based on the above electricity consumption data, the above natural gas consumption data, the above oil consumption data, and the corresponding carbon emission coefficient.

[0073] In specific implementations, the carbon emission factor refers to the carbon emissions generated per unit of energy consumption. The carbon emission factors of different energy sources may be different. Based on the above electricity consumption data, the above natural gas consumption data, and the above oil consumption data, as well as the corresponding carbon emission coefficients, the carbon emissions of all energy sources are aggregated to obtain the total carbon emissions.

[0074] The above implementation of the embodiment of the present application ensures the integrity and accuracy of production statistics through data extraction and cleaning, and extracts energy usage information from multiple data sources. Next, the extracted data is converted and calculated using carbon emission factors to ultimately generate carbon emission data. The entire process ensures that the calculation results are accurate through rigorous data verification and standardization.

[0075] In order to analyze the carbon emission data more accurately, in some embodiments, after the above S1032, the above method may further include the following steps: S10321 to S10322.

[0076] S10321: When the acquired carbon emission data reaches a preset quantity requirement, determine a volatility index of the carbon emission data based on the existing carbon emission data.

[0077] In the specific implementation, it is necessary to verify whether the acquired carbon emission data meets the preset quantity requirement. This quantity requirement may be set according to the time period, collection frequency or data collection cycle. Assuming that the system obtains carbon emission data every week, it may require at least one month of data to start calculating the volatility index. Once the data volume meets the requirement, the system can start calculating the volatility index of carbon emission data. The volatility index is usually an indicator to measure the degree of data volatility. The most commonly used method to calculate the volatility index is the standard deviation. The standard deviation can measure the degree of dispersion of a set of data relative to the mean. The larger the standard deviation, the more drastic the data fluctuation.

[0078] S10322: Based on the above volatility index, the comprehensive carbon emissions are predicted.

[0079] In the specific implementation, different prediction methods can be selected according to the volatility index. Common prediction models include linear regression, time series prediction, etc. The volatility index essentially reflects the volatility of carbon emission data, so it can be combined with time series data as part of the prediction model. The volatility index can be added to the prediction model as an external variable to help the model adjust the prediction value. For example, if the volatility index is very high, it means that the uncertainty of carbon emission data is large. The model can appropriately increase the confidence interval of the prediction or adjust the prediction results to predict the comprehensive carbon emissions.

[0080] The above implementation of the embodiment of the present application ensures that a sufficient amount of carbon emission data is obtained, and then calculates the volatility index through methods such as standard deviation or coefficient of variation to indicate the degree of volatility of the data. Based on the volatility index, the system uses a suitable prediction model to predict future carbon emissions and adjusts the credibility of the prediction results according to the volatility index. This series of processes helps to analyze and manage carbon emission data more accurately.

[0081] In order to achieve dynamic control of carbon emissions, in some embodiments, after the above S10322, the above method may further include the following steps: S103221 to S103222.

[0082] S103221: Based on the above comprehensive carbon emissions, determine the subsequent carbon emissions cap.

[0083] In a specific implementation, using the comprehensive carbon emission prediction result obtained in step S10322, an upper limit can be obtained according to the selected calculation standard to determine the subsequent carbon emission upper limit.

[0084] S103222: When the carbon emission data exceeds the above-mentioned subsequent carbon emission upper limit, a carbon emission excess reminder will be issued.

[0085] In the specific implementation, whenever new carbon emission data is collected, the current carbon emission is automatically compared with the set upper limit. When it is detected that the carbon emission exceeds the upper limit, a reminder mechanism will be triggered to record the excess event for further processing.

[0086] The above implementation of the embodiment of the present application calculates a reasonable upper limit of carbon emissions based on the predicted carbon emissions and their fluctuation index. This upper limit is used for subsequent carbon emissions monitoring. Real-time monitoring is performed to determine whether the current carbon emissions exceed the upper limit. If the upper limit is exceeded, a reminder mechanism is triggered, such as an email or SMS notification, and the exceeding event is recorded. This process helps to achieve dynamic control of carbon emissions.

[0087] In order to effectively manage and monitor the carbon emission data of raw materials, in some embodiments, before the above S103, the above method may further include the following steps: S1031 to S1032.

[0088] S1031: Obtain raw material consumption.

[0089] In specific implementation, raw material consumption is obtained through ERP system, production equipment or sensors or manual input.

[0090] S1032: Calculate the corresponding carbon emission data based on the above raw material consumption and the corresponding carbon emission coefficient.

[0091] In specific implementation, the production and consumption process of each raw material will generate a certain amount of carbon emissions. This emission is usually expressed as a carbon emission coefficient, and the unit is usually "carbon emissions per unit of raw material". After obtaining the consumption of raw materials and the corresponding carbon emission coefficient, the carbon emissions of each raw material can be calculated through simple multiplication operations to obtain the corresponding carbon emission data.

[0092] The above implementation of the embodiment of the present application obtains the consumption data of raw materials from different data sources and stores it in a database. Then, the carbon emission coefficient of the raw materials is read and combined with the consumption data to calculate the carbon emission of each raw material. Finally, these calculation results are stored in the database for subsequent analysis, report generation or other decision support. Through these steps, the system can effectively manage and monitor the carbon emission data of raw materials.

[0093] As another embodiment, the above method is applied to a blockchain server, such as Figure 2 As shown, the method includes the following steps: S201 to S204.

[0094] S201: Upon receiving an identity authentication request from a carbon emission calculation node, send authentication information to the carbon emission calculation node so that the emission calculation node generates a corresponding public key and private key through a preset encryption algorithm. Encrypt the carbon emission data through the private key to obtain encrypted data. Send the public key and the encrypted data to a blockchain server.

[0095] In the specific implementation, when the carbon emission calculation node issues an identity authentication request, it needs to be able to receive this request and process the authentication information. After receiving the request, the identity information of the request needs to be verified. Once the identity authentication is successful, the authentication information will be sent to the calculation node, and the public key and private key pair will be generated using the preset encryption algorithm. Then, the carbon emission data will be encrypted using the generated private key. The private key will encrypt the carbon emission data into encrypted text.

[0096] S202: Combining the public key and the encrypted data to generate a block.

[0097] In the specific implementation, once the public key and encrypted data are received, they will be stored as a transaction in the blockchain. These data are encapsulated into a block and the hash of the block is calculated. The blockchain uses a hash algorithm to ensure the data integrity and immutability of the block. Calculating the hash is to hash the data of the block to generate a unique identifier.

[0098] S203: Decrypt the encrypted data using the public key, and write the corresponding carbon emission data into the blockchain according to the block.

[0099] In the specific implementation, the encrypted data can be decrypted using the public key. The decryption process uses the same algorithm as the encryption. The decrypted data can be written to the blockchain, which ensures the integrity of the carbon emission data, and each data block on the blockchain has corresponding signatures and verification information.

[0100] S204: Compare the carbon emission data in the above blockchain with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

[0101] In the specific implementation, the carbon emission data in the above-mentioned blockchain is compared with the preset carbon emission quota, and the data extracted from the blockchain is compared with the preset carbon emission quota to determine whether it meets the carbon emission requirements and determine the corresponding carbon emission judgment result.

[0102] The above implementation of the embodiment of the present application sends authentication information to the above carbon emission calculation node when receiving the identity authentication request sent by the carbon emission calculation node, and combines the above public key and the above encrypted data to generate a block. The above encrypted data is decrypted by the above public key, and the corresponding carbon emission data is written into the blockchain according to the above block. The carbon emission data in the above blockchain is compared with the preset carbon emission quota to determine the corresponding carbon emission judgment result. A complete process from identity authentication, data encryption, blockchain storage to carbon emission judgment is realized. Each step involves encryption and decryption of data and ensures the security and integrity of data through the tamper-proof nature of the blockchain.

[0103] In order to ensure the integrity and traceability of carbon emission data, in some embodiments, the above S203 may include the following steps: S2031 to S2033.

[0104] S2031: Decrypt the encrypted data using the public key to obtain carbon emission data.

[0105] In the specific implementation, the public key is provided by the sender when the data is encrypted and stored in the blockchain along with the encrypted data. The decryption process needs to extract the public key from the blockchain and use it as the decryption key to decrypt the carbon emission data.

[0106] S2032: Combine the hash value corresponding to the above public key with the hash value corresponding to the previous block of the above block to determine the hash value corresponding to the current block.

[0107] In the specific implementation, the blockchain connects the hash of the current block with the hash value of the previous block by means of a hash chain. This ensures that if the data of any block is modified, the hash value of the entire chain will change, so that tampering can be easily detected. The hash value of the current block consists of the following parts: the carbon emission data of the current block (decrypted data); the public key of the current block; the hash value of the previous block. Specifically, the public key of the current block, the decrypted carbon emission data, and the hash value of the previous block are concatenated into a string or binary data. The concatenated data is hashed. This hash value will be used as the hash value of the current block to ensure the integrity of the data and the connectivity of the chain.

[0108] S2033: Write the above carbon emission data into the blockchain according to the hash value corresponding to the above current block.

[0109] In the specific implementation, the hash value of the current block is generated by the decrypted data and the hash value of the previous block, and the relevant data of the current block (including carbon emission data, current block hash and timestamp, etc.) is written into the blockchain.

[0110] The above-mentioned implementation method of the embodiment of the present application decrypts the above-mentioned encrypted data through the above-mentioned public key to obtain carbon emission data, and then combines the hash value corresponding to the above-mentioned public key with the hash value corresponding to the previous block of the above-mentioned block to determine the hash value corresponding to the current block, and then writes the above-mentioned carbon emission data into the blockchain according to the hash value corresponding to the above-mentioned current block. Through these three steps, the carbon emission data is decrypted from an encrypted state into usable plaintext data, and combined with the hash value of the previous block to generate the hash value of the current block, and finally the decrypted data and hash value are written into the blockchain, thereby ensuring the security, transparency and non-tamperability of the data, and ensuring the integrity and traceability of the carbon emission data.

[0111] In one embodiment of the present application, first, reference may be made to Figure 3This embodiment constructs an intelligent blockchain-based energy consumption and carbon emission data collection system, including: a blockchain server, at least one carbon emission calculation node distributedly connected to the blockchain server, and an energy consumption collection device connected to the carbon emission calculation node; the carbon emission calculation node connects the data transmission between the enterprise and the blockchain server.

[0112] The energy consumption collection device is used to collect the daily energy consumption of the current enterprise, which includes the daily electricity consumption, the daily natural gas consumption and the daily oil consumption; the carbon emission calculation node is used to calculate the daily comprehensive carbon emissions of the current enterprise; the blockchain server is used to encrypt and write the daily comprehensive carbon emissions into the blockchain. The energy consumption collection device includes an electricity consumption collection module, a gas consumption collection module and an oil consumption collection module; the electricity consumption collection module is used to collect the daily electricity consumption, the gas consumption collection module is used to collect the daily natural gas consumption, and the oil consumption collection module is used to collect the daily oil consumption.

[0113] The carbon emission calculation node includes an input unit, a processing unit, a storage unit, a display unit, and an output unit; the input unit is used to record the production statistics data during the production activities of the enterprise and send it to the processing unit; the production statistics data include raw material inventory data and raw material carbon emission coefficients, and the raw material inventory data include material requisition forms, material return forms, transfer forms, warehouse entry forms, and warehouse exit forms; the raw material inventory data is related to carbon emissions, and the raw material carbon emission coefficient is obtained by statistical calculation by technical personnel in this field; the daily production carbon emissions include the carbon emissions released during the conversion of raw materials in the process of producing products; the processing unit is used to output daily energy consumption carbon emissions according to daily energy consumption, and predict the carbon emissions generated during production activities according to production statistics. The daily production carbon emissions are calculated, and the daily energy consumption carbon emissions and the daily production carbon emissions are combined to generate the daily comprehensive carbon emissions, and sent to the storage unit, the display unit and the output unit; the storage unit is used to store the monthly allocated carbon emission quota, generate the monthly comprehensive carbon emissions by statistically analyzing the monthly comprehensive carbon emissions, and compare the monthly comprehensive carbon emissions with the monthly allocated carbon emission quota to analyze the energy conservation and emission reduction results of the month; the display unit is used to display the comparison result of the daily comprehensive carbon emissions and the storage unit; the output unit is used to package the daily comprehensive carbon emissions by date to generate daily comprehensive carbon emissions data, generate a key pair with a common hash value: a public key and a private key, and encrypt the daily comprehensive carbon emissions data with the private key, and send the daily comprehensive carbon emissions data and the public key to the blockchain server.

[0114] The blockchain server includes a consensus module, a network module, a data module, and an application module; the consensus module is used to establish a secure network through mutual authentication with the output unit and receive the public key; the network module is connected to the output unit and the consensus module, and is used to combine the daily comprehensive carbon emission data and the public key to generate a block; the data module decrypts the daily comprehensive carbon emission data through the public key, writes the decrypted daily comprehensive carbon emission data into the blockchain, and combines the hash value on the public key with the hash value on the previous block to obtain the hash value of the current block; the application module is connected to the data module, and is used to take stock of the annual comprehensive carbon emission data of at least one carbon emission calculation node, and reward or punish the current enterprise on the carbon emission calculation node in combination with the annual allocated carbon emission quota analysis.

[0115] Correspondingly, this embodiment also provides an implementation method, first, the output unit sends an identity authentication request to the consensus module, and after obtaining the feedback authentication of the consensus module, generates the public key and the private key through an encryption algorithm, and uses the private key to encrypt the daily comprehensive carbon emission data. After that, the output unit sends the public key to the consensus module, and sends the daily comprehensive carbon emission data to the network module under the encryption of the private key. The network module combines the public key and the daily comprehensive carbon emission data to generate a block, and sends it to the data module. After receiving the block, the data module decrypts the daily comprehensive carbon emission data through the public key, writes the decrypted daily comprehensive carbon emission data into the blockchain, and combines the hash value on the public key with the hash value on the previous block to obtain the hash value of the current block. The application module counts the annual comprehensive carbon emissions of at least one carbon emission calculation node of the data module and compares it with the annual allocated carbon emission quota: if the annual comprehensive carbon emissions are lower than the annual allocated carbon emission quota, the current enterprise of the carbon emission calculation node will be given tax reduction benefits according to the saved carbon emissions; if the annual comprehensive carbon emissions are higher than the annual allocated carbon emission quota, the current enterprise of the carbon emission calculation node will be punished according to the excess carbon emissions.

[0116] Specifically, in the process of calculating the comprehensive carbon emission data of the carbon emission calculation node, the input unit records the production statistical data during the production activity and sends it to the processing unit. The processing unit predicts the daily production carbon emissions generated during the production activity based on the production statistical data.

[0117] The processing unit receives the energy consumption collected by the energy consumption collection device and converts the energy consumption into daily energy consumption carbon emissions, and the formula is as follows:

[0118] E=A*F=A1*F1+A2*F2+A3*F3

[0119] Among them, E represents daily energy consumption and carbon emissions; A represents energy consumption, A1 is the daily electricity consumption, A2 is the daily natural gas consumption, and A3 is the daily oil consumption; F is the carbon emission coefficient, F1 is the carbon emission coefficient of electricity, F1=0.714kg / (kw*h), F2 is the carbon emission coefficient of natural gas, F2=56.1kg / GJ, and F3 is the carbon emission coefficient of oil, F3=63.1kg / GJ.

[0120] The processing unit combines the daily energy consumption carbon emissions and the daily production carbon emissions to generate comprehensive carbon emissions, and packages the generated daily comprehensive carbon emissions by date, and sends them to the storage unit, the display unit and the output unit.

[0121] The storage unit generates monthly comprehensive carbon emissions from daily comprehensive carbon emissions statistics, and compares the monthly comprehensive carbon emissions with the stored monthly allocated carbon emissions quota: if the monthly comprehensive carbon emissions are greater than the monthly allocated carbon emissions quota, information is sent to the display unit to prompt that the carbon emissions for that month have exceeded the quota, reminding the company to promptly strengthen energy conservation and emission reduction efforts; the monthly comprehensive carbon emissions are real-time data. When half of the month is over, the processing unit can predict whether the comprehensive carbon emissions for that month will exceed the allocated carbon emissions quota based on current data, and calculate the comprehensive carbon emissions limit for the day. When the collected daily comprehensive carbon emissions value exceeds the calculated limit, a reminder is issued to the company.

[0122] The daily comprehensive carbon emissions of the month are represented by C(day), where day represents the number of days and has a value range of [1, 2, 3, ..., Now], where Now represents the number of days of the day. The processing unit calculates the fluctuation index P according to the following formula:

[0123]

[0124] Among them, i is a variable representing day.

[0125] The processing unit predicts whether the comprehensive carbon emissions for the month will exceed the allocated carbon emission quota according to the following formula:

[0126]

[0127] Among them, Max is the maximum number of days in the month, and C (Month) represents the real-time monthly comprehensive carbon emissions.

[0128] When the inequality holds true, it is predicted that the allocated carbon emission quota will be exceeded, and the processing unit calculates the limit value CY(Now) for the day according to the following formula:

[0129]

[0130] If the monthly comprehensive carbon emissions are less than the monthly allocated carbon emissions quota, information is sent to the display unit to prompt that the carbon emissions for the month are within the quota range and the energy conservation and emission reduction work for the month is effective.

[0131] In some embodiments, the carbon emission calculation node includes an input unit, a processing unit, a storage unit, a display unit, and an output unit; the input unit is used to record production statistical data during the production activities of the enterprise; the processing unit is used to output the daily energy consumption recorded by the energy consumption collection device as daily energy consumption carbon emissions, predict the daily production carbon emissions generated during the production activities based on the production statistical data, and combine the daily energy consumption carbon emissions and the daily production carbon emissions to generate a daily comprehensive carbon emissions, and send it to the storage unit, the display unit, and the output unit; the storage unit is used to store the monthly allocated carbon emission quota, generate the monthly comprehensive carbon emissions by statistically analyzing the daily comprehensive carbon emissions, and compare the monthly comprehensive carbon emissions with the monthly allocated carbon emission quota to analyze the energy conservation and emission reduction results of the month; the display unit is used to display the comparison result of the daily comprehensive carbon emissions and the storage unit, that is, the energy conservation and emission reduction results of the month, and the output unit is used to package the comprehensive carbon emissions by date to generate daily comprehensive carbon emission data, and encrypt and send it to the blockchain server.

[0132] The input unit is used to connect with an equipment management device in an enterprise; the equipment management device includes an inventory counting unit and a product counting unit.

[0133] The inventory counting unit is used to record the daily input of raw materials in the production process, and the product counting unit is used to monitor the daily production quantity of products in the production process.

[0134] The processing unit receives the raw material input and the daily production quantity in the equipment management device, and generates the daily production carbon emission based on the following formula:

[0135] X i =K 1 ×i (i=1,2,…n)

[0136] F i =K 2 X i

[0137] Where X i is the raw material consumption of producing product i, K1 and K2 are the raw material consumption coefficient and daily production carbon emission coefficient, respectively, which are obtained by technicians in this field through limited experiments; F i is the daily production carbon emission corresponding to the raw material consumption for producing product i.

[0138] The present invention uses an energy consumption collection device to monitor the energy consumption of electricity, natural gas, oil and other energy sources in real time, effectively tracks the carbon emissions generated by energy production and enterprise production processes, and effectively calculates the carbon emissions of the current carbon emission calculation node. The carbon emissions generated during production activities are also predicted through carbon emission calculation nodes, and comprehensive carbon emissions are generated by combining energy consumption carbon emissions and production carbon emissions, effectively calculating the total carbon emissions of the current carbon emission calculation node, which is conducive to the promotion of energy conservation and emission reduction. The consensus module and the output unit mutually authenticate and establish a secure network, and the carbon emission data is written into the blockchain through the data module to achieve the security and traceability of the carbon emission data. The present invention effectively improves the level of intelligence in verifying enterprise carbon emission data in this field.

[0139] Based on the carbon emission data determination method provided in the above embodiment, the present application also provides a specific implementation of the carbon emission data determination device. Please refer to the following embodiment.

[0140] See first Figure 4 The carbon emission data determination device 400 provided in the embodiment of the present application includes the following modules:

[0141] The sending module 401 is used to send an identity authentication request to the blockchain server.

[0142] The generation module 402 is used to generate corresponding public keys and private keys through a preset encryption algorithm when the authentication information of the above-mentioned blockchain server is obtained.

[0143] The encryption module 403 is used to encrypt the carbon emission data using the private key to obtain encrypted data.

[0144] The sending module 401 is also used to send the public key and the encrypted data to the blockchain server, so that the blockchain server combines the public key and the encrypted data to generate a block. The encrypted data is decrypted by the public key, and the corresponding carbon emission data is written into the blockchain according to the block. The carbon emission data in the blockchain is compared with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

[0145] The carbon emission data determination device provided in the embodiment of the present application establishes a secure network through the carbon emissions generated by energy production and enterprise production processes, and writes the carbon emission data into the blockchain through a data module, thereby achieving the security and traceability of the carbon emission data, allowing relevant organizations to grasp the real data in real time, and then make accurate judgments on the effectiveness of energy conservation and emission reduction.

[0146] As an implementation of the present application, a carbon emission data determination device 400 includes:

[0147] The acquisition module is used to obtain production statistics.

[0148] The calculation module is used to calculate the corresponding carbon emission data based on the above production statistical data.

[0149] As an implementation of the present application, the computing module includes:

[0150] The extraction unit is used to extract the electricity consumption data, natural gas consumption data and oil consumption data from the above production statistical data.

[0151] The calculation unit is used to calculate the corresponding carbon emission data according to the above electricity consumption data, the above natural gas consumption data and the above oil consumption data, and the corresponding carbon emission coefficient.

[0152] As an implementation of the present application, a carbon emission data determination device 400 includes:

[0153] The determination module is used to determine the fluctuation index of the carbon emission data based on the existing carbon emission data when the acquired carbon emission data reaches a preset quantity requirement.

[0154] The prediction module is used to predict the comprehensive carbon emissions based on the above fluctuation index.

[0155] As an implementation of the present application, a carbon emission data determination device 400 includes:

[0156] The determination module is used to determine the subsequent carbon emission upper limit based on the above comprehensive carbon emissions.

[0157] The reminder module is used to issue a carbon emission excess reminder when the carbon emission data exceeds the above-mentioned subsequent carbon emission upper limit.

[0158] As an implementation of the present application, a carbon emission data determination device 400 includes:

[0159] The acquisition module is used to obtain the raw material consumption.

[0160] The calculation module is used to calculate the corresponding carbon emission data according to the above raw material consumption and the corresponding carbon emission coefficient.

[0161] Each module in the carbon emission data determination device provided in the embodiment of the present application can implement each step in the above-mentioned carbon emission data determination method and achieve the corresponding effect. For the sake of concise description, it will not be repeated here.

[0162] Figure 5 A schematic diagram of the structure of the carbon emission data determination hardware provided in an embodiment of the present application is shown.

[0163] The carbon emission data determination device may include a processor 501 and a memory 502 storing computer program instructions.

[0164] Specifically, the processor 501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0165] The memory 502 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 502 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 502 is a non-volatile solid-state memory.

[0166] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the carbon emission data determination method according to any one embodiment of the present disclosure.

[0167] The processor 501 implements any one of the carbon emission data determination methods in the above embodiments by reading and executing computer program instructions stored in the memory 502 .

[0168] In one example, the carbon emission data determination device may further include a communication interface 503 and a bus 510. Figure 5 As shown, the processor 501, the memory 502, and the communication interface 503 are connected via a bus 510 and communicate with each other.

[0169] The communication interface 503 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0170] Bus 510 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 510 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0171] In addition, in combination with the method for determining carbon emission data in the above embodiments, the present application embodiment may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the methods for determining carbon emission data in the above embodiments is implemented.

[0172] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements any one of the methods for determining carbon emission data in the above embodiments.

[0173] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0174] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0175] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0176] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0177] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for determining carbon emission data, characterized in that: The method is applied to a carbon emission calculation node, and the method comprises: Send an identity authentication request to the blockchain server; When the authentication information of the blockchain server is obtained, a corresponding public key and a private key are generated by a preset encryption algorithm; Encrypting the carbon emission data using the private key to obtain encrypted data; The public key and the encrypted data are sent to the blockchain server so that the blockchain server combines the public key and the encrypted data to generate a block; the encrypted data is decrypted by the public key, and the corresponding carbon emission data is written into the blockchain according to the block; the carbon emission data in the blockchain is compared with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

2. The carbon emission data determination method according to claim 1, characterized in that: Before encrypting the carbon emission data by using the private key to obtain the encrypted data, the method further includes: Obtain production statistics; The corresponding carbon emission data is calculated based on the production statistical data.

3. The method for determining carbon emission data according to claim 2, characterized in that: The production statistical data includes electricity consumption data, natural gas consumption data and oil consumption data. The corresponding carbon emission data is calculated based on the production statistical data, including: Extracting electricity consumption data, natural gas consumption data and oil consumption data from the production statistical data; The corresponding carbon emission data is calculated based on the electricity consumption data, the natural gas consumption data, the oil consumption data, and the corresponding carbon emission coefficient.

4. The method for determining carbon emission data according to claim 2, characterized in that: After the corresponding carbon emission data is calculated based on the production statistical data, the method further includes: When the acquired carbon emission data reaches the preset quantity requirement, the volatility index of the carbon emission data is determined based on the existing carbon emission data; Based on the volatility index, the comprehensive carbon emissions are predicted.

5. The method for determining carbon emission data according to claim 4, characterized in that: After predicting the comprehensive carbon emissions based on the volatility index, the method further includes: Determine the subsequent carbon emission cap based on the comprehensive carbon emission; When the carbon emission data exceeds the subsequent carbon emission upper limit, a carbon emission excess reminder is issued.

6. The method for determining carbon emission data according to claim 1, characterized in that: Before encrypting the carbon emission data by using the private key to obtain the encrypted data, the method further includes: Obtain raw material consumption; The corresponding carbon emission data is calculated based on the raw material consumption and the corresponding carbon emission coefficient.

7. A method for determining carbon emission data, characterized in that: The method is applied to a blockchain server, and the method includes: Upon receiving an identity authentication request sent by a carbon emission calculation node, sending authentication information to the carbon emission calculation node so that the emission calculation node generates a corresponding public key and a private key through a preset encryption algorithm; encrypting the carbon emission data through the private key to obtain encrypted data; and sending the public key and the encrypted data to a blockchain server; Combining the public key and the encrypted data to generate a block; Decrypting the encrypted data by using the public key, and writing the corresponding carbon emission data into the blockchain according to the block; Compare the carbon emission data in the blockchain with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

8. The method for determining carbon emission data according to claim 7, characterized in that: The decrypting the encrypted data by the public key and writing the corresponding carbon emission data into the blockchain according to the block includes: Decrypting the encrypted data using the public key to obtain carbon emission data; Combining the hash value corresponding to the public key with the hash value corresponding to the previous block of the block to determine the hash value corresponding to the current block; The carbon emission data is written into the blockchain according to the hash value corresponding to the current block.

9. A device for determining carbon emission data, characterized in that: The device comprises: A sending module, used to send an identity authentication request to a blockchain server; A generation module, used to generate corresponding public keys and private keys through a preset encryption algorithm when the authentication information of the blockchain server is obtained; An encryption module, used to encrypt the carbon emission data using the private key to obtain encrypted data; The sending module is also used to send the public key and the encrypted data to the blockchain server, so that the blockchain server combines the public key and the encrypted data to generate a block; decrypt the encrypted data through the public key, and write the corresponding carbon emission data into the blockchain according to the block; compare the carbon emission data in the blockchain with the preset carbon emission quota to determine the corresponding carbon emission judgment result.

10. A carbon emission data determination device, characterized in that: The device comprises: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the carbon emission data determination method according to any one of claims 1-8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the carbon emission data determination method according to any one of claims 1 to 8 is implemented.

12. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the carbon emission data determination method as described in any one of claims 1-8.

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