Multi-energy system carbon emission accounting method and system based on block chain

Abstract

The invention discloses a multi-energy system carbon emission accounting method and system based on a block chain, and the method comprises the steps: obtaining multi-energy load data, and designing a multi-energy system frame according to the multi-energy load data; based on a multi-energy system framework, designing an emission model and a physical model of carbon emission of different energy sources on a user side, and obtaining carbon emission data of the different energy sources on the user side; a block chain technology is introduced to verify, consensus and store carbon emission data. According to the invention, the accuracy, real-time performance and transparency of carbon emission accounting are improved; and the credibility of the data is enhanced through the block chain technology. And important contributions are made for promoting global carbon emission reduction and sustainable development targets.

Description

Technical Field

[0001] The present invention relates to the field of carbon emission technology, and in particular to a blockchain-based carbon emission accounting method and system for a multi-energy system. Background Art

[0002] As global climate change becomes increasingly serious, carbon emission reduction and sustainable development have become the focus of global attention.

[0003] Traditional carbon emission accounting methods, such as emission factor methods and input-output analysis, primarily focus on the macro level and struggle to meet the needs of accurate and real-time user-side data. They also lack consideration for spatial heterogeneity, such as significant regional variations in energy structure, climate conditions, and user density. This makes it difficult for macro data to accurately guide localized emission reductions. These methods typically rely on macro-level consumption data and estimation factors, lacking sufficient temporal accuracy and data granularity, and are unable to effectively address the increasingly complex challenges of carbon emission accounting. With the development of multi-energy system (MES) technology, carbon emission accounting is gradually moving towards greater accuracy and real-time performance. MES integrates multiple energy loads, such as electricity, heat, natural gas, and refrigeration, to provide a more comprehensive carbon emission assessment. However, current research primarily focuses on the accounting of a single energy load and lacks a comprehensive assessment of multiple energy loads. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a blockchain-based multi-energy system carbon emission accounting method and system to solve the problem of insufficient carbon emission accounting accuracy.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a blockchain-based multi-energy system carbon emissions accounting method, comprising:

[0008] Acquiring multi-energy load data, and designing a multi-energy system framework based on the multi-energy load data;

[0009] Based on the multi-energy system framework, design emission models and physical models for carbon emissions from different energy sources on the user side, and obtain carbon emission data from different energy sources on the user side;

[0010] Blockchain technology is introduced to verify, reach consensus and store the carbon emission data.

[0011] As a preferred solution of the blockchain-based multi-energy system carbon emission accounting method described in the present invention, wherein: obtaining multi-energy load data, and designing a multi-energy system framework based on the multi-energy load data, including:

[0012] Use collection equipment to obtain electricity and gas;

[0013] The electric energy and gas are converted through an electric refrigerator, an absorption refrigerator and a heat exchanger to obtain an electric load, a cooling load, a heating load and a gas load.

[0014] As a preferred solution of the blockchain-based multi-energy system carbon emission accounting method described in the present invention, based on the multi-energy system framework, an emission model of carbon emissions of different energy sources on the user side is designed. The emission model is expressed as:

[0015]

[0016] in, are the carbon emissions of electricity, heating, gas and cooling loads respectively; E is the energy consumption of different load types; E t,s represents the energy consumption of area s at time t; EF t,s represents the carbon emission factor of the spatial region s at time t; C represents the carbon emission amount; C time is the total carbon emissions of the region in different time periods; C load is the total carbon emissions of different load types; i represents the number of rows in the summation process.

[0017] As a preferred solution of the blockchain-based multi-energy system carbon emission accounting method described in the present invention, the following is a method for calculating carbon emissions of different energy sources on the user side based on the multi-energy system framework: the physical model of carbon emissions of different energy sources on the user side is designed, and the physical model includes a load-related model and an equipment model;

[0018] The load-related model is expressed as:

[0019] E e =P e t

[0020] E h =Q h ρ h c h Δt

[0021] Q h =P e ·t·η s

[0022] η s =f(α s , equipment efficiency)

[0023] E g =V g ρ g H g

[0024] E c =Qc ρ c c c Δt

[0025] η s =f(regional grid strength, local renewable energy share)

[0026] Among them, E e 、E h 、E g 、E c is the electricity, heating, gas and cooling load, P e is the electric power; t is the time; Q h For heat; is the density of the heat medium; c h is the heat capacity; ΔT is the temperature difference; α s is the regional climate parameter; V g is the volume of natural gas; is the density of natural gas; H g is the calorific value of natural gas; Q c is the cooling amount; ρ c is the density of the cooling medium; c c is the heat capacity of the cooling medium; η s is the region(s) specific energy efficiency or carbon emission adjustment factor.

[0027] As a preferred solution of the blockchain-based multi-energy system carbon emission accounting method described in the present invention, the blockchain technology is introduced, including:

[0028] Design a blockchain system including a user layer and a blockchain layer, and use the blockchain system to verify, reach consensus, and store the carbon emission data;

[0029] The user layer includes various user entities;

[0030] A smart contract comprising multiple peer nodes is deployed in the blockchain layer.

[0031] As a preferred solution of the blockchain-based multi-energy system carbon emission accounting method of the present invention, it also includes:

[0032] Each user entity is connected to the blockchain network through an independent peer node in the blockchain layer. The smart contract in the blockchain layer further verifies the user's geographic location data and links with the regional carbon emission policy library to ensure that the data complies with the spatial dimension.

[0033] As a preferred solution of the blockchain-based multi-energy system carbon emission accounting method of the present invention, wherein: the blockchain system is used to verify, reach consensus and store the carbon emission data, including:

[0034] Measure electricity load, cooling load, heating load, and gas load data, and use the emission model and physical model of different energy carbon emissions on the user side to obtain carbon emission data;

[0035] The carbon emission data is transmitted to the blockchain network, multi-party verification and consensus is carried out through smart contracts, and recorded in a tamper-proof manner on the blockchain's distributed ledger;

[0036] Add spatiotemporal tags to carbon emission data, and conduct spatiotemporal comparative analysis of historical data through the traceability of blockchain.

[0037] In a second aspect, the present invention provides a blockchain-based multi-energy system carbon emission accounting system, comprising:

[0038] An energy system design module, configured to obtain multi-energy load data and design a multi-energy system framework based on the multi-energy load data;

[0039] The data acquisition module is used to design the emission model and physical model of carbon emissions from different energy sources on the user side based on the multi-energy system framework, and obtain the carbon emission data of different energy sources on the user side;

[0040] The data storage module is used to introduce blockchain technology to verify, reach consensus and store the carbon emission data.

[0041] In a third aspect, the present invention provides a computing device, comprising:

[0042] memory and processor;

[0043] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the blockchain-based multi-energy system carbon emission accounting method are implemented.

[0044] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the blockchain-based multi-energy system carbon emission accounting method.

[0045] Compared with existing technologies, this invention offers the following benefits: it improves the accuracy, real-time nature, and transparency of carbon emissions accounting; by introducing spatiotemporal distribution parameters, it enables refined modeling of user-side carbon emissions, identifying high-carbon emission regions and time periods, and providing a technical basis for developing differentiated carbon reduction policies; and by leveraging blockchain technology, it enhances data credibility. This makes a significant contribution to advancing global carbon reduction and sustainable development goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 This is a logical diagram of the overall process of the blockchain-based multi-energy system carbon emission accounting method according to one embodiment of the present invention;

[0048] Figure 2 A schematic diagram of a multi-energy system framework of a blockchain-based multi-energy system carbon emissions accounting method according to an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of the blockchain system structure of a blockchain-based multi-energy system carbon emission accounting method according to one embodiment of the present invention;

[0050] Figure 4 This is a schematic diagram of the user-side carbon emission accounting process of the blockchain-based multi-energy system carbon emission accounting method according to one embodiment of the present invention;

[0051] Figure 5 This is a schematic diagram of the actual application results of the blockchain-based multi-energy system carbon emission accounting method according to one embodiment of the present invention. DETAILED DESCRIPTION

[0052] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0053] Example 1

[0054] Reference Figure 1-Figure 5 , as one embodiment of the present invention, provides a blockchain-based multi-energy system carbon emission accounting method, comprising:

[0055] S100: Acquire multi-energy load data and design a multi-energy system framework based on the multi-energy load data;

[0056] Preferably, electricity and gas are obtained by using collection equipment; electricity and gas are converted through electric refrigerators, absorption refrigerators and heat exchangers to obtain electricity load, cooling load, heating load and gas load.

[0057] In the embodiment of the present application, the collection equipment includes a transformer and a gas turbine; specifically, the multi-energy system framework is as follows Figure 2 As shown;

[0058] User-side carbon emissions primarily refer to greenhouse gas emissions generated by energy consumption in daily life. These emissions primarily include electricity, heating, cooling, and natural gas combustion. Electricity consumption is a significant source of user-side carbon emissions, and therefore, electricity load plays a central role in carbon emission calculations. Heating and cooling loads are ubiquitous in commercial buildings and daily life, with heating loads being particularly pronounced in summer and cooling loads in winter. Both have a significant impact on energy consumption and carbon emissions. Natural gas is commonly used for heating and power generation, making it an essential component of carbon emission accounting. The multi-energy system framework design integrates four energy loads: electricity, heating, natural gas, and cooling, to comprehensively assess user-side carbon emissions.

[0059] In an optional embodiment, the data collection equipment may also be a smart electricity meter, a gas flow meter, a temperature sensor, a pressure sensor, etc. Smart electricity meters can accurately collect relevant data on electricity, such as voltage, current, and power, providing a basis for the acquisition and analysis of electricity; gas flow meters can accurately measure the flow of gas, ensuring the accurate acquisition of gas data; temperature sensors can be used to monitor temperature changes in various links of the system, providing a basis for the analysis of cooling and heating loads and the monitoring of equipment operating status; and pressure sensors can detect the pressure in the gas pipeline in real time to ensure the stability and safety of the gas supply. These data collection devices work together to provide comprehensive and accurate support for the acquisition of multi-energy load data, thereby laying a solid data foundation for the design of the multi-energy system framework.

[0060] S102: Based on the multi-energy system framework, design an emission model and physical model for carbon emissions from different energy sources on the user side, and obtain carbon emission data from different energy sources on the user side;

[0061] Preferably, the total carbon emissions F is equal to the carbon emissions of electricity in each time period Thermal carbon emissions Natural gas carbon emissions and cooling load discharge The emission model is expressed as:

[0062]

[0063] The energy consumption of different load types, the energy consumption at time t, the carbon emission factor of the load, and the carbon emission factor at time t are expressed in matrix form. The mathematical model is as follows:

[0064]

[0065] Total energy consumption E total It is the sum of the energy of regions from 1 to m from t = 1 to t = n. The mathematical model is as follows:

[0066]

[0067] Carbon emissions C is equal to the product of the energy consumption E of different load types and the emission factors EF of these loads. The mathematical model is as follows:

[0068] C=E⊙EF

[0069] Total carbon emissions in different time periods C time Equal to the energy consumption E at time t t,s The transposition of and its carbon emission factor EF t,s The mathematical model for product summation is as follows:

[0070]

[0071] Total carbon emissions C for different load types load It is equal to the sum of carbon emissions from 1 to n, and its mathematical model is as follows:

[0072]

[0073] in, are the carbon emissions of electricity, heating, gas and cooling loads respectively; E is the energy consumption of different load types; EF is the carbon emission factor of these loads; E t,s represents the energy consumption of area s at time t; EF t,s represents the carbon emission factor of region s at time t; E total is the total energy consumption; e is an n-dimensional column vector with 1 as its element; C represents carbon emissions; ⊙ is the Hadamard product; C time is the total carbon emissions in different time periods; C load is the total carbon emissions of different load types.

[0074] In the embodiment of the present application, the dimension of the matrix is ​​n×4, representing n time periods and 4 load types.

[0075] Preferably, the physical model includes a load-related model and an equipment model;

[0076] Load-dependent models:

[0077] E e =P e t

[0078] E h =Q h ρ h c h Δt

[0079] Q h =P e ·t·η s

[0080] η s =f(α s , equipment efficiency)

[0081] E g =V g ρ g H g

[0082] E c =Q c ρ c c c Δt

[0083] η s =f(regional grid strength, local renewable energy share)

[0084] Among them, P e is the electric power; t is the time; Q h is the calorific value; ρ h ——heat medium density; c h is the heat capacity; ΔT is the temperature difference; α s is the regional climate parameter; V g is the volume of natural gas; ——density of natural gas; H g is the calorific value of natural gas; Q c is the cooling amount; ——density of cooling medium; c c is the heat capacity of the cooling medium; η s is the region(s) specific energy efficiency or carbon emission adjustment factor.

[0085] The heat output is equal to the product of the gas turbine's power consumption, heat generation efficiency, and heat exchange efficiency. The cooling capacity is equal to the product of the energy converter's power consumption and energy conversion coefficient plus the product of the refrigeration equipment's power consumption and heat-to-cooling conversion efficiency coefficient. The mathematical expression of the equipment model is as follows:

[0086] Q h =P GT μ GT ·η HE

[0087] Q c =P EC CO EC +P AC μ AC

[0088] Among them, P GT 、P EC and P AC are the power consumption of gas turbine, energy converter and refrigerator respectively; μ GT is the heat production efficiency of the gas turbine; η HE is the heat exchange efficiency of HE; CO EC is the energy conversion coefficient of the energy converter; μ AC is the heat-cooling conversion efficiency coefficient of AC power; equipment efficiency parameter μ GT Dynamic corrections are required based on regional energy policies and equipment installation locations (such as industrial areas / residential areas).

[0089] It should be noted that by designing emission and physical models for different energy sources on the user side, accurate carbon emission data for different energy sources can be obtained. This helps users clearly understand the carbon emissions generated by their own energy use, providing data support and decision-making basis for energy conservation and emission reduction. The emission model provides a clear formula for carbon emissions from different energy types such as electricity, heating, gas, and cooling loads, and takes into account different time periods and load types. This makes the calculation of carbon emission data more comprehensive, accurate, and detailed, which is conducive to identifying key links and time periods for carbon emissions, thereby enabling targeted emission reduction measures.

[0090] It should also be noted that physical models include load-related models and equipment models. The load-related models correlate load-related physical quantities such as electrical power, calorific value, and natural gas volume. The equipment models define the power consumption and related efficiency coefficients of different equipment. These models can deeply analyze the physical relationship between energy consumption, load, and equipment, providing a theoretical basis and analytical tools for optimizing energy utilization and improving energy efficiency. For example, these models can analyze the operating efficiency of equipment, identify inefficient equipment, and improve or replace it, thereby reducing energy consumption and carbon emissions.

[0091] Furthermore, this model design, based on a multi-energy system framework, comprehensively considers the synergies and interactions among multiple energy sources, contributing to the optimized operation of the entire multi-energy system and the overall management of carbon emissions. This has significant practical significance and application value for promoting sustainable energy development and addressing climate change. It not only helps users reduce operating costs but also enhances the social image and environmental responsibility of businesses or institutions, generating positive economic and social benefits.

[0092] S104: Introduce blockchain technology to verify, reach consensus and store carbon emission data.

[0093] Preferably, a blockchain system including a user layer and a blockchain layer is designed, and the blockchain system is used to verify, reach consensus and store carbon emission data.

[0094] Preferably, the user layer includes various user entities; and a smart contract including multiple peer nodes is deployed in the blockchain layer.

[0095] Preferably, spatiotemporal tags are added to carbon emission data, and cluster analysis is performed on the carbon emission data through spatiotemporal tags to generate regional carbon emission reports, supporting regulatory agencies to formulate dynamic carbon quotas according to spatial dimensions; and spatiotemporal comparative analysis of historical data is performed through the traceability of blockchain.

[0096] Specifically, blockchain systems such as Figure 3 As shown, it includes a user layer and a blockchain layer, establishes a communication link between the user and the peer node n, and transmits the carbon flow of the user node to the blockchain layer.

[0097] In the embodiment of the present application, the user layer is the core component of the system framework, including various user entities such as commercial buildings and public facilities.

[0098] It should be noted that the blockchain layer is a decentralized network built on blockchain technology, responsible for ensuring the credibility of user-side carbon emissions accounting. It consists of multiple peer-to-peer nodes that deploy smart contracts. These smart contracts are a crucial component in verifying user carbon emissions data and recording it on the blockchain. Due to the decentralized nature of the blockchain network, all users share the same trusted data source, eliminating the possibility of data forgery and tampering.

[0099] Preferably, each user entity is connected to the blockchain network via an independent peer node in the blockchain layer.

[0100] Preferably, a blockchain system is used to verify, reach consensus, and store carbon emission data, including:

[0101] Carbon emissions data is derived by measuring electricity, cooling, heating, and gas load data and conducting in-depth analysis of the collected data using user-side carbon emission models and physical models for different energy sources. The emission model integrates the energy consumption of different energy types—electricity, heating, gas, and cooling—and their corresponding carbon emission factors, taking into account differences across time periods and load types. Using complex calculation logic, it accurately calculates the carbon emissions of each energy source in each time period and for each load type, and then summarizes the total carbon emissions for each time period and load type.

[0102] The physical model is based on physical parameters such as electric power, time, calorific value, heat medium density, heat capacity, temperature difference, natural gas volume, natural gas density, natural gas calorific value, cooling capacity, cooling medium density, and cooling medium heat capacity in the load-related model, as well as key indicators such as the power consumption of GT, EC, and AC, the heat production efficiency of GT, the heat exchange efficiency of HE, the energy conversion coefficient of EC, and the heat-to-cooling conversion efficiency coefficient of AC in the equipment model. It deeply analyzes the physical relationship between energy consumption, load, and equipment, provides a solid physical basis for the accuracy of carbon emission data, and ensures that the calculation results truly reflect the carbon emissions of energy use on the user side.

[0103] The calculated carbon emissions data is transmitted to the blockchain network. During the transmission process, multi-layer encryption technologies, such as the AES encryption algorithm, are used to encrypt the data. At the same time, secure transmission protocols such as SSL / TLS are combined to ensure the integrity and confidentiality of the data during transmission, effectively preventing data theft, tampering, or loss.

[0104] Once carbon emissions data enters the blockchain network, it undergoes multi-party verification and consensus through pre-deployed smart contracts. Smart contracts are self-executing codes that detail the rules and processes for verifying and reaching consensus on carbon emissions data. Participating parties in this verification and consensus process include energy suppliers, users, regulators, and other stakeholders.

[0105] Energy suppliers will compare their own recorded energy supply data with the energy data involved in carbon emission calculations to verify the consistency of electricity supply data and electricity-related data in carbon emission calculations; users will verify the matching degree between their own load data and the calculation results based on their actual energy usage; and regulatory agencies will review whether the data is compliant.

[0106] Only when all parties reach a consensus on the authenticity, accuracy, and completeness of carbon emissions data, based on the rules of the smart contract, and confirm that the data is accurate and meets relevant requirements, can the data enter the next step of the storage process. This multi-party verification and consensus mechanism effectively avoids the potential for data manipulation or misjudgment by a single entity, ensuring the fairness and credibility of carbon emissions data.

[0107] Carbon emissions data, verified and agreed upon by multiple parties, is recorded in a tamper-proof manner on the blockchain's distributed ledger. Blockchain's distributed ledger technology is characterized by decentralization, immutability, and traceability. Each blockchain node maintains a complete copy of the ledger, and when new data is recorded, it requires confirmation and synchronization by a majority of nodes in the network.

[0108] Specifically, such as Figure 4As shown, on the user side, including commercial buildings and public facilities, sensors and smart meters collect real-time energy consumption data and calculate carbon emissions. This data covers various energy loads, including electricity, heat, natural gas, and cooling. This carbon emissions data is then securely transmitted to the blockchain network at the blockchain layer.

[0109] It should be noted that because smart contracts are self-executing programs, user-side carbon emissions data undergoes multi-party verification and consensus through smart contracts, ensuring its credibility and consistency. This data is then recorded in a tamper-proof manner on the blockchain's distributed ledger.

[0110] Specifically, the carbon emissions of a commercial building in summer and winter are used as an example to illustrate. By using the method of the present invention, the results obtained are as follows: Figure 5 As shown, in Figure 5 In the table, Electricity refers to electricity, Heat refers to heating, Gas refers to gas, Cooling refers to cooling, and CO2 emission refers to carbon dioxide emissions; Figure 5 The left picture is summer. Figure 5 The right-hand graph shows winter, where electricity consumption is the primary source of carbon emissions from commercial buildings. Peak carbon emissions occur between 9:00 AM and 9:00 PM, showing a distinct peak-valley pattern.

[0111] Furthermore, it's worth noting that cooling loads contribute more to carbon emissions in the summer, while heating loads have a greater impact in the winter. Reducing user-side carbon emissions requires improving the energy efficiency of heating and cooling loads and increasing the proportion of clean energy. Overall, the introduction of blockchain technology and carbon emission accounting methods can record user-side carbon emission data and contribute to the implementation of carbon reduction policies.

[0112] The above is a schematic scheme of a blockchain-based multi-energy system carbon emission accounting method according to this embodiment. It should be noted that the technical scheme of the blockchain-based multi-energy system carbon emission accounting system and the technical scheme of the blockchain-based multi-energy system carbon emission accounting method described above are based on the same concept. For details not described in detail in the technical scheme of the blockchain-based multi-energy system carbon emission accounting system in this embodiment, please refer to the description of the technical scheme of the blockchain-based multi-energy system carbon emission accounting method described above.

[0113] The blockchain-based multi-energy system carbon emission accounting system in this embodiment includes:

[0114] Energy system design module, used to obtain multi-energy load data and design a multi-energy system framework based on the multi-energy load data;

[0115] The data acquisition module is used to design the emission model and physical model of carbon emissions from different energy sources on the user side based on the multi-energy system framework, and obtain the carbon emission data of different energy sources on the user side;

[0116] The data storage module is used to introduce blockchain technology to verify, reach consensus and store carbon emission data.

[0117] This embodiment also provides a computing device suitable for blockchain-based carbon emission accounting for multi-energy systems, including:

[0118] Memory and processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the blockchain-based multi-energy system carbon emission accounting method proposed in the above embodiment.

[0119] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements the blockchain-based carbon emission accounting method for a multi-energy system as proposed in the above embodiment.

[0120] The storage medium proposed in this embodiment and the method for implementing carbon emission accounting of a multi-energy system based on blockchain proposed in the above embodiment belong to the same inventive concept. For technical details not fully described in this embodiment, please refer to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0121] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented with the help of software and necessary general hardware, and of course can also be implemented by hardware. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0122] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A blockchain-based carbon emission accounting method for a multi-energy system, characterized in that: include: Acquiring multi-energy load data, and designing a multi-energy system framework based on the multi-energy load data; Based on the multi-energy system framework, design emission models and physical models for carbon emissions from different energy sources on the user side, and obtain carbon emission data from different energy sources on the user side; Blockchain technology is introduced to verify, reach consensus and store the carbon emission data.

2. The blockchain-based multi-energy system carbon emission accounting method according to claim 1 is characterized in that: Acquiring multi-energy load data and designing a multi-energy system framework based on the multi-energy load data, including: Use collection equipment to obtain electricity and gas; The electric energy and gas are converted through an electric refrigerator, an absorption refrigerator and a heat exchanger to obtain an electric load, a cooling load, a heating load and a gas load.

3. The blockchain-based multi-energy system carbon emission accounting method according to claim 2 is characterized in that: Based on the multi-energy system framework, an emission model for carbon emissions from different energy sources on the user side is designed. The emission model is expressed as: in, are the carbon emissions of electricity, heating, gas and cooling loads respectively; E is the energy consumption of different load types; E t,s represents the energy consumption of the spatial coordinate s at time t; EF t,s represents the carbon emission factor at time t with spatial coordinate s; C represents carbon emission; C time is the total carbon emissions in different time periods; C load is the total carbon emissions of different load types; i represents the number of rows in the summation process.

4. The blockchain-based multi-energy system carbon emission accounting method according to claim 3 is characterized in that: Based on the multi-energy system framework, a physical model of carbon emissions from different energy sources on the user side is designed. The physical model includes a load-related model and an equipment model. The load-related model is expressed as: E e =P e t From h =Q h ρ h c h Δt Q h =P e ·t·η s η s =f(α s , equipment efficiency) E g =V g r g H g From c =Q c ρ c c c Δt η s =f(regional grid strength, local renewable energy share) Among them, E e 、E h 、E g 、E c is the electricity, heating, gas and cooling load, P e is the electric power; t is the time; Q h is the calorific value; ρ h is the density of the heat medium; c h is the heat capacity; ΔT is the temperature difference; α s is the regional climate parameter; V g is the volume of natural gas; is the density of natural gas; H g is the calorific value of natural gas; Q c is the cooling amount; is the density of the cooling medium; c c is the heat capacity of the cooling medium; η s is the region(s) specific energy efficiency or carbon emission adjustment factor.

5. The blockchain-based multi-energy system carbon emission accounting method according to claim 4 is characterized in that: Introducing blockchain technology, including: Design a blockchain system including a user layer and a blockchain layer, and use the blockchain system to verify, reach consensus, and store the carbon emission data; The user layer includes various user entities; A smart contract comprising multiple peer nodes is deployed in the blockchain layer.

6. The blockchain-based multi-energy system carbon emission accounting method according to claim 5 is characterized in that: Also includes, Each user entity is connected to the blockchain network through an independent peer node in the blockchain layer. The smart contract in the blockchain layer further verifies the user's geographic location data and links with the regional carbon emission policy library to ensure that the data complies with the spatial dimension.

7. The blockchain-based multi-energy system carbon emission accounting method according to claim 5 or 6, characterized in that: Utilizing the blockchain system to verify, reach consensus on, and store the carbon emission data includes: Measure electricity load, cooling load, heating load, and gas load data, and use the emission model and physical model of different energy carbon emissions on the user side to obtain carbon emission data; The carbon emission data is transmitted to the blockchain network, multi-party verification and consensus is carried out through smart contracts, and recorded in the distributed ledger of the blockchain in a tamper-proof manner; Add spatiotemporal tags to carbon emission data, and conduct spatiotemporal comparative analysis of historical data through the traceability of blockchain.

8. A system using the blockchain-based multi-energy system carbon emission accounting method according to any one of claims 1 to 7, characterized in that: include: An energy system design module, configured to obtain multi-energy load data and design a multi-energy system framework based on the multi-energy load data; The data acquisition module is used to design the emission model and physical model of carbon emissions from different energy sources on the user side based on the multi-energy system framework, and obtain the carbon emission data of different energy sources on the user side; The data storage module is used to introduce blockchain technology to verify, reach consensus and store the carbon emission data.

9. An electronic device comprising: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the blockchain-based multi-energy system carbon emission accounting method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the blockchain-based multi-energy system carbon emission accounting method described in any one of claims 1 to 7.

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