Carbon emission dynamic metering and tracking method, device and equipment for multi-energy complementary system

Abstract

The invention relates to the technical field of carbon emission tracking, and discloses a multi-energy complementary system carbon emission dynamic metering and tracking method, device and equipment, and the method comprises the steps: obtaining real-time operation data of electric power, thermal power, gas and energy storage in a multi-energy complementary system and carbon emission related data; calculating a power side real-time carbon emission factor, a thermal side real-time carbon emission factor and a gas side real-time carbon emission factor of each node in the multi-energy complementary system and a carbon emission factor of the energy storage system in an energy charging and discharging state based on the real-time operation data and the carbon emission related data; based on the real-time carbon emission factor of the power side, the real-time carbon emission factor of the thermal side, the real-time carbon emission factor of the gas side and the carbon emission factor of the energy storage system in the charging and discharging state, calculating the electric carbon emission, the gas carbon emission and the thermal carbon emission of the user; according to the invention, carbon emission factors and carbon emission of electricity, heat and gas of the multi-energy coupling system can be dynamically metered, and more accurate carbon accounting is realized.

Description

Technical Field

[0001] This invention relates to the field of carbon emission tracking technology, specifically to a method, apparatus, and equipment for dynamic measurement and tracking of carbon emissions from a multi-energy complementary system. Background Technology

[0002] Multi-energy complementary energy systems utilize multiple forms of energy for production, transmission, and consumption, enabling interaction among various energy sources and serving as a powerful tool for achieving low-carbon development. Currently, carbon measurement and monitoring in multi-energy complementary energy systems primarily rely on macro-statistical methods. These methods are often used at the national level to calculate the overall carbon emissions of power systems, providing a direct and practical estimate of total carbon emissions over a relatively long period. However, this approach fails to consider the specific carbon emission processes within the system, making it difficult to achieve refined analysis of power system carbon emissions. Furthermore, it is susceptible to errors in total emission statistics and carbon emission factor calculations, thus failing to support the low-carbon, intelligent management of multi-energy complementary energy systems.

[0003] Related technologies use carbon flow analysis to calculate carbon flow in regional integrated energy systems. Based on the lossless regional integrated energy system after network loss allocation, a unified matrix calculation formula for multi-energy carbon flow is obtained according to the proportional allocation principle. Carbon emission reduction and energy saving emission reduction are obtained based on the carbon flow calculation results. However, it does not consider complex multi-energy coupling patterns such as electricity, gas, and heat, and cannot track and measure the carbon emission factors of each energy consumption under multi-energy coupling patterns.

[0004] In view of the above-mentioned technologies, seeking a method and system for dynamic measurement and tracking of carbon emissions from multi-energy complementary systems is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides a method, apparatus and equipment for dynamic measurement and tracking of carbon emissions in a multi-energy complementary system, in order to solve the technical problem that the prior art cannot achieve the tracking and measurement of carbon emission factors of each energy consumption under the multi-energy coupling mode.

[0006] In a first aspect, the present invention provides a method for dynamic measurement and tracking of carbon emissions from a multi-energy complementary system, comprising:

[0007] To acquire real-time operational data and carbon emission-related data of electricity, heat, gas and energy storage in a multi-energy complementary system;

[0008] Based on real-time operational data and carbon emission-related data, the real-time carbon emission factors on the power side, heat side, and gas side of each node in the multi-energy complementary system are calculated, as well as the carbon emission factors of the energy storage system in the charging and discharging state.

[0009] The user's carbon emissions (electricity, gas, and heat) are calculated based on the real-time carbon emission factors on the power side, the heat side, the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state.

[0010] Optionally, the real-time carbon emission factor on the power side includes the real-time carbon emission factor of electricity and the carbon emission factor of combined heat and power.

[0011] The formula for calculating the real-time electricity carbon emission factor is as follows:

[0012]

[0013] In the formula, EF sys,t P is the real-time carbon emission factor for electricity. coal For coal-fired power generation, P gas For gas-fired power generation, P grid Power purchased from the power grid, P PV For photovoltaic power generation, P wind For wind power generation capacity, EF coal EF is the carbon emission factor for coal-fired power generation. gas For the carbon emission factor of gas-fired power generation, EF PV EF is the carbon emission factor of photovoltaic power generation. wind EF is the carbon emission factor of wind power generation. grid Real-time grid factor;

[0014] The formula for calculating the carbon emission factor of combined heat and power is:

[0015]

[0016] In the formula, EF CHP,elec and EF CHP,heat These are the carbon emission factors for electricity and heat generated by combined heat and power (CHP), respectively. CHP Q represents the output power of a combined heat and power (CHP) plant. CHP E represents the output heat of a combined heat and power (CHP) plant. CHP This represents the total carbon emissions from combined heat and power (CHP).

[0017] Optionally, the real-time carbon emission factor on the heat side includes the carbon emission factor corresponding to the heat output of the electric boiler, the carbon emission factor corresponding to the heat output of the waste heat boiler, and the carbon emission factor corresponding to the heat output of the heat pump.

[0018] The formula for calculating the carbon emission factor corresponding to the heat output of an electric boiler is as follows:

[0019]

[0020] In the formula, EF Qeh η is the carbon emission factor corresponding to the heat output of an electric boiler.eh For the conversion efficiency of electric heating boilers;

[0021] If the heat output of the waste heat boiler is industrial waste heat, then the carbon emission factor corresponding to the heat output of the waste heat boiler is zero. If the heat output of the waste heat boiler is fuel supplement heat, then the carbon emission factor corresponding to the heat output of the waste heat boiler is the carbon emission factor of the fuel.

[0022] The formula for calculating the carbon emission factor corresponding to the heat output of a heat pump is:

[0023]

[0024] In the formula, EF hp The carbon emission factor is the carbon emission factor corresponding to the heat output of the heat pump, and COP is the coefficient of performance of the heat pump.

[0025] Optionally, the real-time carbon emission factor on the gas side includes the carbon emission factor of gas generated by electricity, the carbon emission factor of natural gas, and the carbon emission factor of mixed gas;

[0026] The formula for calculating the carbon emission factor of gas generated by electricity is as follows:

[0027]

[0028] Among them, EF P2G Q is the carbon emission factor for gaseous emissions from electricity generation. gas η represents the calorific value of the electrically generated gas. P2G For electro-gas conversion efficiency;

[0029] The carbon emission factor for natural gas is calculated using the standard factor, while the carbon emission factor for mixed gases is calculated as a weighted average of the individual carbon emission factors for all gases.

[0030] Optionally, the carbon emission factors in the charging and discharging states include the equivalent carbon emission factor when the electric energy storage device is charging at time t, the equivalent carbon emission factor when the electric energy storage device is discharging at time t, the carbon emission factor when the thermal storage device is charging, the carbon emission factor when the thermal storage device is releasing heat, the carbon emission factor when the gas storage device is filling, and the carbon emission factor when the gas storage device is releasing.

[0031] The formulas for calculating the equivalent carbon emission factor of the energy storage device at time t during charging and the equivalent carbon emission factor of the energy storage device at time t during discharging are as follows:

[0032]

[0033] In the formula, EF ES，t，ch EF is the equivalent carbon emission factor of an energy storage device at time t when it is being charged. ES，t，dis E is the equivalent carbon emission factor of the energy storage device at time t during discharge. ES,t and E ES,t-1P represents the electrical energy stored in the device at time t and time t-1, respectively. dis η is the discharge power of the energy storage device. ES Δt represents the discharge efficiency of the energy storage device, and Δt represents the discharge time.

[0034] The carbon emission factor of thermal storage equipment for heat charging is determined based on the carbon emission factor of the heat source, while the carbon emission factor of thermal storage equipment for heat release is calculated based on the efficiency of the thermal storage equipment and the carbon emission factor of the thermal storage equipment for heat charging.

[0035] The carbon emission factors for both gas storage equipment filling and gas storage equipment venting are determined based on the carbon emission factors of the gas source.

[0036] Optionally, the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions are calculated based on the real-time carbon emission factors on the electricity side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state, including:

[0037] The user's carbon emissions are calculated based on the real-time carbon emission factor on the power side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0038] E1 = EF e P e =P coal EF coal +P gas EF gas +P grid EF grid +P PV EF PV +P wind EF wind

[0039] +EF CHP，elec P CHP +EF ES，t，dis P dis -EF ES，t，ch P ch -EF sys,t P eh

[0040] -EF sys,t P hp -EF sys,t P P2G

[0041] In the formula, E1 represents carbon emissions from electricity, and EF... e For electricity users' carbon emission factors, P e For user power consumption, P dis P represents the discharge power of the energy storage device. ch P is the charging power of the energy storage device. ehP is the electrical input power of the electric boiler. hp P is the electrical input power of the heat pump. P2G The electrical input power for electric gas generation;

[0042] The user's carbon emissions are calculated based on the real-time carbon emission factor on the gas side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0043] E2 = EF g V g =EF gas，n V i +EF P2G V P2G +EF gas，m V dis -EF gas，m V ch -EF gas V gas

[0044] In the formula, E2 represents carbon emissions, and EF... g For gas users' carbon emission factors, V g V represents the user's gas flow rate. i For the gas flow rate from the superior gas network, EF gas，n As the carbon emission factor of the upper-level gas network, EF gas V is the carbon emission factor for natural gas. P2G For the production of electricity-generated gas, V dis V is the venting flow rate of the gas storage equipment. ch EF is the gas flow rate for charging gas storage equipment. gas，m EF is the carbon emission factor of the gas source for gas storage equipment. gas V is the carbon emission factor for gas-fired power generation. gas For natural gas consumption;

[0045] The user's thermal carbon emissions are calculated based on the real-time carbon emission factor on the thermal side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0046]

[0047] In the formula, E3 represents thermal carbon emissions, and EF... h Q is the carbon emission factor for heat users. h For user heat power, Q eh EF is the heat output power of the electric boiler. w The carbon emission factor corresponding to the heat output of the waste heat boiler. Carbon emission factors from heat storage equipment The carbon emission factor for charging thermal storage equipment, Q hp Q represents the heat output power of the heat pump. wQ represents the heat output power of the waste heat boiler. dis Q represents the heat release power of the thermal storage device. ch The power required to charge the thermal storage equipment.

[0048] Optionally, the method for dynamic measurement and tracking of carbon emissions in multi-energy complementary systems also includes: verifying whether the sum of input carbon emissions and net absorbed carbon emissions from the energy storage system is equal to the sum of carbon emissions from electricity, heat, and gas consumption on the user side and carbon emissions released by the energy storage system; if they are not equal, outputting a system imbalance warning.

[0049] Optionally, after calculating the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions based on the real-time carbon emission factors on the electricity side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state, the method further includes:

[0050] A digital twin model of the user node is constructed based on the user's electrical carbon emissions, gaseous carbon emissions, and thermal carbon emissions to simulate the distribution of electrical, thermal, and gaseous carbon flows in real time.

[0051] Blockchain-based evidence storage technology is used to upload and trace carbon flow data in the digital twin model.

[0052] Secondly, the present invention provides a dynamic metering and tracking device for carbon emissions of a multi-energy complementary system, comprising:

[0053] The data acquisition module is used to acquire real-time operating data and carbon emission-related data of electricity, heat, gas and energy storage in the multi-energy complementary system;

[0054] The carbon emission factor calculation module is used to calculate the real-time carbon emission factor on the power side, the real-time carbon emission factor on the heat side, the real-time carbon emission factor on the gas side, and the carbon emission factor of the energy storage system in the charging and discharging state of each node in the multi-energy complementary system based on real-time operating data and carbon emission related data.

[0055] The carbon emission calculation module is used to calculate the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions based on the real-time carbon emission factors on the power side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state.

[0056] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the multi-energy complementary system carbon emission dynamic measurement and tracking method described in the first aspect or any corresponding embodiment.

[0057] The present invention has the following beneficial effects:

[0058] This invention acquires real-time operational data and carbon emission-related data of electricity, heat, gas, and energy storage in a multi-energy complementary system. Based on this data, it calculates the real-time carbon emission factors of the electricity side, heat side, and gas side of each node in the system, as well as the carbon emission factor of the energy storage system under charging and discharging conditions. This allows for the calculation of the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions. The invention can dynamically measure the carbon emission factors and carbon emissions of electricity, heat, and gas in a multi-energy coupled system, achieving more accurate carbon accounting.

[0059] This invention considers the temporary carbon footprint characteristics of electric shock, thermal storage, and gas storage. Specifically, electric energy storage is dynamically locked according to the system emission factor during charging and discharging, thermal storage is associated with the carbon emission factor of the heat source, and gas storage is bound to the gas source to determine the carbon emission factor, thereby achieving accurate carbon emission calculation with high spatiotemporal resolution.

[0060] This invention visualizes the carbon flow of a multi-energy complementary energy system by simulating the distribution of carbon flows in electricity, heat, and gas using digital twins, and achieves reliable traceability of carbon emission data across the entire chain of the multi-energy complementary energy system by constructing a carbon ledger for multiple types of energy storage through blockchain evidence storage. Attached Figure Description

[0061] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0062] Figure 1 This is a flowchart illustrating the dynamic measurement and tracking method for carbon emissions from a multi-energy complementary system in an embodiment of the present invention.

[0063] Figure 2 This is a structural block diagram of the carbon emission dynamic metering and tracking device for a multi-energy complementary system according to an embodiment of the present invention;

[0064] Figure 3 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] Currently, the main method for carbon measurement and monitoring of multi-energy complementary energy systems is the macro-statistical method. This method can obtain the total carbon emissions of the system over a long period, but it does not consider the specific carbon emission process of the system. It cannot grasp the specific distribution and refined analysis of carbon emissions within the multi-energy complementary energy system. First, it cannot carry out low-carbon, refined and intelligent management based on the spatiotemporal distribution of carbon emissions, which is not conducive to low-carbon transformation. Second, it cannot provide real-time and accurate single emission factors per unit product of electricity, gas and heat, which is not conducive to carbon emission accounting and low-carbon production for downstream users.

[0067] Some carbon flow analysis methods also have the following problems: 1. Limitations of single energy metering: Traditional methods only calculate carbon emissions for electricity or heat alone, without considering the interactive effects of multi-energy coupling (such as carbon transfer in the power-to-gas process), leading to distorted allocation; 2. Static factor error: Using fixed emission factors (such as the grid annual average factor) cannot reflect the dynamic carbon emission factors of wind and solar power output fluctuations and energy storage charging and discharging; 3. Limited energy storage types: Existing schemes mostly design carbon metering for electric energy storage, without covering carbon temporary storage and transfer mechanisms in forms such as thermal storage and gas storage.

[0068] To address at least one of the aforementioned problems, embodiments of the present invention propose a method for dynamic measurement and tracking of carbon emissions from a multi-energy complementary system. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0069] This embodiment provides a method for dynamic measurement and tracking of carbon emissions from a multi-energy complementary system, such as... Figure 1 As shown, the process includes the following steps:

[0070] Step S101: Obtain real-time operating data and carbon emission-related data of electricity, heat, gas and energy storage in the multi-energy complementary system;

[0071] Step S102: Based on real-time operating data and carbon emission-related data, calculate the real-time carbon emission factor on the power side, the real-time carbon emission factor on the heat side, the real-time carbon emission factor on the gas side, and the carbon emission factor of the energy storage system in the charging and discharging state for each node in the multi-energy complementary system.

[0072] Step S103: Calculate the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions based on the real-time carbon emission factors on the power side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state.

[0073] Specifically, by constructing an intelligent sensor network, including high-precision smart meters, ultrasonic heat meters, gas flow meters, gas chromatographs, CO2 concentration sensors, temperature and humidity sensors, flue gas flow sensors, atmospheric pressure sensors, and other instruments, real-time operating data and carbon emission-related data of electricity, heat, gas, and energy storage in the multi-energy complementary system are collected.

[0074] The real-time power operation data includes: wind power generation P wind Photovoltaic power generation P PV The output power P of combined heat and power CHP Coal-fired power generation P coal Gas-fired power generation P gas and the power purchased by the power grid P grid The electrical input power P of the electric boiler eh The electrical input power P of the heat pump hp Electric input power P P2G .

[0075] Real-time thermal operation data includes: heat output Q from the combined heat and power (CHP) plant. CHP The heat output power Q of the electric boiler eh Waste heat boiler heat output power Q w Heat pump heat output power Q hp .

[0076] Real-time gas operation data includes: natural gas consumption v has Electric gas production V P2G .

[0077] Real-time operational data for energy storage includes:

[0078] Energy storage: The charging power P of energy storage devices ch The discharge power P of the energy storage device dis .

[0079] Thermal storage: Thermal storage equipment charging power Q ch The heat release power Q of the thermal storage equipment dis .

[0080] Gas storage: Gas storage equipment filling flow rate V ch Gas storage equipment venting flow rate V dis .

[0081] Carbon emission related data: Carbon emissions from coal-fired power generation (E) coal Total carbon emissions from combined heat and power (CHP) E CHP Carbon emission factor EF of coal-fired power generation coal Carbon emission factor EF of gas-fired power generation gas Photovoltaic power generation carbon emission factor EF PVCarbon emission factor EF of wind power generation wind Specifically, the grid marginal factor subscription module can be used to obtain real-time carbon emission factors through a RESTful API, and the carbon emission factors of wind power generation can be corrected by combining the efficiency of photovoltaic inverters and the power curves of wind turbines through the wind and solar power generation carbon factor correction module. The cross-carbon impact of CHP, P2G and other equipment can be corrected through a multi-energy coupling compensator.

[0082] In some embodiments, the real-time carbon emission factor on the power side includes the real-time carbon emission factor of electricity and the carbon emission factor of combined heat and power.

[0083] The formula for calculating the real-time electricity carbon emission factor is as follows:

[0084]

[0085] In the formula, EF sys,t P is the real-time carbon emission factor for electricity. coal For coal-fired power generation, P gas For gas-fired power generation, P grid Power purchased from the power grid, P PV For photovoltaic power generation, P wind For wind power generation capacity, EF coal EF is the carbon emission factor for coal-fired power generation. gas For the carbon emission factor of gas-fired power generation, EF PV EF is the carbon emission factor of photovoltaic power generation. wind EF is the carbon emission factor of wind power generation. grid Real-time grid factor;

[0086] The formula for calculating the carbon emission factor of combined heat and power is:

[0087]

[0088]

[0089] In the formula, EF CHP,elec and EF CHP,heat These are the carbon emission factors for electricity and heat generated by combined heat and power (CHP), respectively. CHP Q represents the output power of a combined heat and power (CHP) plant. CHP E represents the output heat of a combined heat and power (CHP) plant. CHP This represents the total carbon emissions from combined heat and power (CHP).

[0090] Specifically, the dynamic carbon emission factor calculation engine integrates grid API, meteorological data, and equipment efficiency models in real time to obtain the carbon emission factors of photovoltaic power generation and wind power generation, which are the sources of electricity. Machine learning is then used to predict changes in wind and solar power output and grid factors to optimize carbon emission prediction.

[0091] By calculating the real-time electricity carbon emission factor in real time using data such as real-time grid factors, wind and solar carbon emission factors, and photovoltaic power generation and wind power generation, more accurate carbon accounting can be achieved.

[0092] Furthermore, the real-time carbon emission factor on the heat side includes the carbon emission factor corresponding to the heat output of the electric boiler, the carbon emission factor corresponding to the heat output of the waste heat boiler, and the carbon emission factor corresponding to the heat output of the heat pump.

[0093] The formula for calculating the carbon emission factor corresponding to the heat output of an electric boiler is as follows:

[0094]

[0095] In the formula, EF Qeh η is the carbon emission factor corresponding to the heat output of an electric boiler. eh This refers to the conversion efficiency of the electric boiler.

[0096] If the heat output of the waste heat boiler is industrial waste heat, then the carbon emission factor corresponding to the heat output of the waste heat boiler is zero. If the heat output of the waste heat boiler is fuel supplement heat, then the carbon emission factor corresponding to the heat output of the waste heat boiler is the carbon emission factor of the fuel.

[0097] The formula for calculating the carbon emission factor corresponding to the heat output of a heat pump is:

[0098]

[0099] In the formula, EF hp The carbon emission factor is the carbon emission factor corresponding to the heat output of the heat pump, and COP is the coefficient of performance of the heat pump.

[0100] Optionally, the real-time carbon emission factor on the gas side includes the carbon emission factor of gas generated by electricity, the carbon emission factor of natural gas, and the carbon emission factor of mixed gas;

[0101] The formula for calculating the carbon emission factor of gas generated by electricity is as follows:

[0102]

[0103] Among them, EF P2G Q is the carbon emission factor for gaseous emissions from electricity generation. gas η represents the calorific value of the electrically generated gas. P2G This refers to the efficiency of the electro-gas conversion.

[0104] The carbon emission factor for natural gas is calculated using the standard factor, while the carbon emission factor for mixed gases is calculated as a weighted average of the individual carbon emission factors for all gases.

[0105] Furthermore, the carbon emission factors under the charging and discharging states include the equivalent carbon emission factor when the electric energy storage device is charging at time t, the equivalent carbon emission factor when the electric energy storage device is discharging at time t, the carbon emission factor when the thermal storage device is charging, the carbon emission factor when the thermal storage device is releasing heat, the carbon emission factor when the gas storage device is filling, and the carbon emission factor when the gas storage device is releasing gas.

[0106] The formulas for calculating the equivalent carbon emission factor of the energy storage device at time t during charging and the equivalent carbon emission factor of the energy storage device at time t during discharging are as follows:

[0107]

[0108] In the formula, EF ES，t，ch EF is the equivalent carbon emission factor of an energy storage device at time t when it is being charged. ES，t，dis E is the equivalent carbon emission factor of the energy storage device at time t during discharge. ES,t and E ES,t-1 P represents the electrical energy stored in the device at time t and time t-1, respectively. dis η is the discharge power of the energy storage device. ES Δt represents the discharge efficiency of the energy storage device, and Δt represents the discharge time.

[0109] The carbon emission factor for thermal storage equipment charging is determined based on the carbon emission factor of the heat source, while the carbon emission factor for thermal storage equipment releasing heat is calculated based on the efficiency of the thermal storage equipment and its charging carbon emission factor.

[0110]

[0111] In the formula, Carbon emission factors from heat storage equipment The carbon emission factor for charging thermal storage equipment, Q dis Q represents the heat release power of the thermal storage device. ch The power required to charge the thermal storage equipment.

[0112] The carbon emission factors for both gas storage equipment filling and venting are determined based on the carbon emission factor of the gas source. For example, the EF (emission factor) of P2G. P2G Based on the carbon emission factor of the electric gas generator, the carbon emission factor of the gas source is recorded in the electricity carbon label.

[0113] Specifically, a carbon storage and release mechanism is established for various types of energy storage systems, including electric energy storage, thermal energy storage, and gas storage. The carbon footprint is recorded and released according to the carbon emission factors at the charging and discharging times. For electric energy storage, the system emission factors are dynamically locked during charging and discharging. For thermal energy storage, the carbon emission factors are associated with the heat source (such as waste heat or CHP). For gas storage, the carbon emission factors are bound to the gas source (such as P2G electricity carbon tags or natural gas factors). The carbon emission factors under the charging and discharging states of electric, thermal, and gas energy storage are calculated separately to establish a carbon storage and release mechanism for various types of energy storage, thereby achieving real-time and accurate monitoring of carbon flow.

[0114] Optionally, the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions are calculated based on the real-time carbon emission factors on the electricity side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state, including:

[0115] The user's carbon emissions are calculated based on the real-time carbon emission factor on the power side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0116] E1 = EF e P e =P coal EF coal +P gas EF gas +P grid EF grid +P PV EF PV +P wind EF wind

[0117] +EF CHP，elec P CHP +EF ES，t，dis P dis -EF ES，t，ch P ch -EF sys,t P eh

[0118] -EF sys,t P hp -EF sys,t P P2G

[0119] In the formula, E1 represents carbon emissions from electricity, and EF... e For electricity users' carbon emission factors, P e For user power consumption, P dis P represents the discharge power of the energy storage device. ch P is the charging power of the energy storage device. eh P is the electrical input power of the electric boiler. hp P is the electrical input power of the heat pump.P2G The electrical input power for electric gas generation;

[0120] The user's carbon emissions are calculated based on the real-time carbon emission factor on the gas side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0121] E2 = EF g V g =EF gas，n V i +EF P2G V P2G +EF gas，m V dis -EF gas，m V ch -EF gas V gas

[0122] In the formula, E2 represents carbon emissions, and EF... g For gas users' carbon emission factors, V g V represents the user's gas flow rate. i For the gas flow rate from the superior gas network, EF gas，n As the carbon emission factor of the upper-level gas network, EF gas V is the carbon emission factor for natural gas. P2G For the production of electricity-generated gas, V dis V is the venting flow rate of the gas storage equipment. ch EF is the gas flow rate for charging gas storage equipment. gas，m EF is the carbon emission factor of the gas source for gas storage equipment. gas V is the carbon emission factor for gas-fired power generation. gas For natural gas consumption;

[0123] The user's thermal carbon emissions are calculated based on the real-time carbon emission factor on the thermal side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0124]

[0125] In the formula, E3 represents thermal carbon emissions, and EF... h Q is the carbon emission factor for heat users. h For user heat power, Q eh EF is the heat output power of the electric boiler. w The carbon emission factor corresponding to the heat output of the waste heat boiler. Carbon emission factors from heat storage equipment The carbon emission factor for charging thermal storage equipment, Q hp Q represents the heat output power of the heat pump. w Q represents the heat output power of the waste heat boiler. dis Q represents the heat release power of the thermal storage device. chThe power required to charge the thermal storage equipment.

[0126] Specifically, the power grid includes several nodes, each of which can be a power plant or a user. By calculating carbon emission data such as the carbon emissions of electricity, heat, and gas at each node in the power grid, and further calculating the carbon emission factors of electricity users, gas users, and heat users based on the user's power consumption, gas flow rate, and heat consumption, accurate carbon emission tracking can be achieved.

[0127] Furthermore, methods for dynamic measurement and tracking of carbon emissions from multi-energy complementary systems also include:

[0128] Verify whether the sum of input carbon emissions and net carbon emissions absorbed by the energy storage system is equal to the sum of carbon emissions from electricity, heat, and gas consumption on the user side and carbon emissions released by the energy storage system. If they are not equal, output a system imbalance prompt.

[0129] Specifically, the verification formula is: ∑E in +∑E storage =∑E out +∑E loss In the formula, E in E represents carbon emissions from coal, gas, and power grid inputs. storage For energy storage systems to net absorb carbon emissions, E out For the carbon emissions from electricity, heat, and gas consumption on the user side, E loss This study aims to release carbon emissions from energy storage systems. By considering input, output, and energy storage status, the carbon emission factors of different nodes in a multi-energy complementary system are verified through carbon balance analysis.

[0130] In some embodiments, after calculating the user's electrical carbon emissions, gas carbon emissions, and thermal carbon emissions based on the real-time carbon emission factor on the electricity side, the real-time carbon emission factor on the heat side, the real-time carbon emission factor on the gas side, and the carbon emission factor of the energy storage system in the charging and discharging state, the method further includes:

[0131] A digital twin model of the user node is constructed based on the user's electrical carbon emissions, gaseous carbon emissions, and thermal carbon emissions to simulate the distribution of electrical, thermal, and gaseous carbon flows in real time.

[0132] Blockchain-based evidence storage technology is used to upload and trace carbon flow data in the digital twin model.

[0133] Specifically, digital twin simulation is used to visualize carbon flow, constructing a digital twin model to simulate the distribution of electrical, thermal, and gaseous carbon flows in real time, predicting future carbon emission trends, and using a carbon flow matrix to record the carbon emission intensity at each node, enabling cross-media carbon footprint tracing. In this digital twin simulation, Internet of Things (IoT) sensor data is incorporated to dynamically adjust the simulation accuracy of the digital twin model, and machine learning is used to predict changes in wind and solar power output and grid factors, optimizing carbon emission prediction.

[0134] By employing blockchain notarization technology, green electricity trading certificates (such as I-REC and GEC) are recorded on the blockchain to ensure that the source of power generation is linked to carbon emissions, and carbon emission data (such as EF) is stored on the blockchain. sys,t Carbon data from energy storage systems (such as carbon ledgers and P2G carbon tags) is stored on the blockchain to ensure traceability and immutability. Simultaneously, cross-chain protocols (such as Polkadot) enable the interoperability of carbon data from different energy systems, supporting multi-regional carbon trading.

[0135] The dynamic measurement and tracking method for carbon emissions from multi-energy complementary systems can be implemented through a five-layer architecture. This system includes a data acquisition layer, an edge computing layer, a digital twin layer, a blockchain evidence storage layer, and an application service layer.

[0136] The data acquisition layer is equipped with Class 0.5 smart meters, ±1% ultrasonic heat meters, CH / H chromatographs-flow meters, and a group of CO concentration-flue gas-environmental monitoring sensors to achieve second-level synchronous sensing of electricity, heat, gas, and carbon, providing a data foundation with sub-1% error for subsequent accounting.

[0137] The edge computing layer deploys local carbon accounting nodes: the dynamic carbon emission factor engine subscribes to grid marginal factors in real time via a RESTful API, and integrates wind and solar power forecasts, inverter efficiency, wind turbine power curves, and the CHP / P2G cross-compensation model to update the carbon intensity of the electricity-heat-gas three-medium system every minute; the multi-energy coupling distributor adopts the end-product energy method or... The analytical method accurately decomposes the carbon footprint of CHP (carbon footprint of electricity and heat); the energy storage carbon ledger management unit records the carbon footprint of electricity, heat and gas energy storage differently according to the principle of "locking during charging and releasing during discharging", ensuring that the carbon footprint is not lost or repeated during the spatiotemporal transfer process.

[0138] The digital twin layer drives virtual carbon flow simulation with a finite state machine: it automatically switches between state 1 "high-penetration low-carbon mode of wind and solar power", state 2 "purchased high-carbon power mode" and state 3 "energy storage peak-shaving carbon temporary storage mode" according to real-time boundary conditions; the physical-data hybrid model couples the electric-thermal-airflow equations online and performs rolling calibration of parameters such as efficiency, COP, and pipeline heat loss through IoT measured data; the built-in LSTM module can predict the system carbon intensity 24 hours in advance, providing a look-ahead signal with an accuracy of 0.1kgCO / kWh for scheduling.

[0139] The blockchain evidence storage layer is built on Hyperledger Fabric to construct a decentralized carbon ledger. Dynamic factors, energy storage carbon ledgers, and P2G carbon tags are uploaded to the chain as soon as they are generated. Smart contracts automatically verify emission reductions and trigger carbon trading. Zero-knowledge proof interfaces ensure that sensitive corporate data is not leaked. Through the Polkadot cross-chain protocol, carbon data mutual recognition between multiple parks and regions is realized, supporting the transfer of green electricity traceability certificates and one-click verification of EU CBAM carbon tariffs.

[0140] The application services cater to three types of users: government, enterprises, and trading markets. The visualization dashboard presents the distribution of carbon flow from electricity to heat to gas in real time using graphics. The carbon asset trading interface seamlessly connects with carbon management platforms such as regional carbon markets. The policy compliance report generator can automatically generate verification documents according to the ISO 14064 template, achieving a "one-click closed loop" from data to assets to compliance.

[0141] This invention also provides a device for dynamic measurement and tracking of carbon emissions from a multi-energy complementary system, such as... Figure 2 As shown, it includes:

[0142] The data acquisition module 201 is used to acquire real-time operating data and carbon emission-related data of electricity, heat, gas and energy storage in the multi-energy complementary system;

[0143] The carbon emission factor calculation module 202 is used to calculate the real-time carbon emission factor on the power side, the real-time carbon emission factor on the heat side, the real-time carbon emission factor on the gas side, and the carbon emission factor of the energy storage system in the charging and discharging state of each node in the multi-energy complementary system based on real-time operating data and carbon emission related data.

[0144] The carbon emission calculation module 203 is used to calculate the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions based on the real-time carbon emission factors on the power side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state.

[0145] The carbon emission dynamic metering and tracking device for multi-energy complementary systems in this invention acquires real-time operating data and carbon emission-related data of electricity, heat, gas, and energy storage in the multi-energy complementary system. Based on the real-time operating data and carbon emission-related data, it calculates the real-time carbon emission factors on the electricity side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state of each node in the multi-energy complementary system. Then, it calculates the user's electricity carbon emission, gas carbon emission, and heat carbon emission. It can dynamically measure the carbon emission factors and carbon emissions of electricity, heat, and gas in the multi-energy coupled system, and can achieve more accurate carbon accounting.

[0146] Furthermore, the real-time carbon emission factor on the power side includes the real-time carbon emission factor of electricity and the carbon emission factor of combined heat and power.

[0147] The formula for calculating the real-time electricity carbon emission factor is as follows:

[0148]

[0149] In the formula, EF sys,t P is the real-time carbon emission factor for electricity. coal For coal-fired power generation, P gas For gas-fired power generation, P grid Power purchased from the power grid, P PV For photovoltaic power generation, P wind For wind power generation capacity, EF coal EF is the carbon emission factor for coal-fired power generation. gas For the carbon emission factor of gas-fired power generation, EF PV EF is the carbon emission factor of photovoltaic power generation. wind EF is the carbon emission factor of wind power generation. grid Real-time grid factor;

[0150] The formula for calculating the carbon emission factor of combined heat and power is:

[0151]

[0152] In the formula, EF CHP,elec and EF CHP,heat These are the carbon emission factors for electricity and heat generated by combined heat and power (CHP), respectively. CHP Q represents the output power of a combined heat and power (CHP) plant. CHP E represents the output heat of a combined heat and power (CHP) plant. CHP This represents the total carbon emissions from combined heat and power (CHP).

[0153] Furthermore, the real-time carbon emission factor on the heat side includes the carbon emission factor corresponding to the heat output of the electric boiler, the carbon emission factor corresponding to the heat output of the waste heat boiler, and the carbon emission factor corresponding to the heat output of the heat pump.

[0154] The formula for calculating the carbon emission factor corresponding to the heat output of an electric boiler is as follows:

[0155]

[0156] In the formula, EF Qeh η is the carbon emission factor corresponding to the heat output of an electric boiler. eh For the conversion efficiency of electric heating boilers;

[0157] If the heat output of the waste heat boiler is industrial waste heat, then the carbon emission factor corresponding to the heat output of the waste heat boiler is zero. If the heat output of the waste heat boiler is fuel supplement heat, then the carbon emission factor corresponding to the heat output of the waste heat boiler is the carbon emission factor of the fuel.

[0158] The formula for calculating the carbon emission factor corresponding to the heat output of a heat pump is:

[0159]

[0160] In the formula, EF hp The carbon emission factor is the carbon emission factor corresponding to the heat output of the heat pump, and COP is the coefficient of performance of the heat pump.

[0161] Furthermore, the real-time carbon emission factors on the gas side include carbon emission factors for gas generated by electricity, carbon emission factors for natural gas, and carbon emission factors for mixed gases;

[0162] The formula for calculating the carbon emission factor of gas generated by electricity is as follows:

[0163]

[0164] Among them, EF P2G Q is the carbon emission factor for gaseous emissions from electricity generation. gas η represents the calorific value of the electrically generated gas. P2G For electro-gas conversion efficiency;

[0165] The carbon emission factor for natural gas is calculated using the standard factor, while the carbon emission factor for mixed gases is calculated as a weighted average of the individual carbon emission factors for all gases.

[0166] Furthermore, the carbon emission factors under the charging and discharging states include the equivalent carbon emission factor when the electric energy storage device is charging at time t, the equivalent carbon emission factor when the electric energy storage device is discharging at time t, the carbon emission factor when the thermal storage device is charging, the carbon emission factor when the thermal storage device is releasing heat, the carbon emission factor when the gas storage device is filling, and the carbon emission factor when the gas storage device is releasing gas.

[0167] The formulas for calculating the equivalent carbon emission factor of the energy storage device at time t during charging and the equivalent carbon emission factor of the energy storage device at time t during discharging are as follows:

[0168]

[0169] In the formula, EF ES，t，ch EF is the equivalent carbon emission factor of an energy storage device at time t when it is being charged. ES，t，dis E is the equivalent carbon emission factor of the energy storage device at time t during discharge. ES,t and E ES,t-1 P represents the electrical energy stored in the device at time t and time t-1, respectively. dis η is the discharge power of the energy storage device. ES Δt represents the discharge efficiency of the energy storage device, and Δt represents the discharge time.

[0170] The carbon emission factor of thermal storage equipment for heat charging is determined based on the carbon emission factor of the heat source, while the carbon emission factor of thermal storage equipment for heat release is calculated based on the efficiency of the thermal storage equipment and the carbon emission factor of the thermal storage equipment for heat charging.

[0171] The carbon emission factors for both gas storage equipment filling and gas storage equipment venting are determined based on the carbon emission factors of the gas source.

[0172] Furthermore, the carbon emission calculation module is also used for:

[0173] The user's carbon emissions are calculated based on the real-time carbon emission factor on the power side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0174] E1 = EF e P e =P coal EF coal +P gas EF gas +P grid EF grid +P PV EF PV +P wind EF wind

[0175] +EF CHP，elec P CHP +EF ES，t，dis P dis -EF ES，t，ch P ch -EF sys,t P eh

[0176] -EF sys,t P hp -EF sys,t P P2G

[0177] In the formula, E1 represents carbon emissions from electricity, and EF... e For electricity users' carbon emission factors, P e For user power consumption, P dis P represents the discharge power of the energy storage device. ch P is the charging power of the energy storage device. eh P is the electrical input power of the electric boiler. hp P is the electrical input power of the heat pump. P2G The electrical input power for electric gas generation;

[0178] The user's carbon emissions are calculated based on the real-time carbon emission factor on the gas side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0179] E2 = EFg V g =EF gas，n V i +EF P2G V P2G +EF gas，m V dis -EF gas，m V ch -EF gas V gas

[0180] In the formula, E2 represents carbon emissions, and EF... g For gas users' carbon emission factors, V g V represents the user's gas flow rate. i For the gas flow rate from the superior gas network, EF gas，n As the carbon emission factor of the upper-level gas network, EF gas V is the carbon emission factor for natural gas. P2G For the production of electricity-generated gas, V dis V is the venting flow rate of the gas storage equipment. ch EF is the gas flow rate for charging gas storage equipment. gas，m EF is the carbon emission factor of the gas source for gas storage equipment. gas V is the carbon emission factor for gas-fired power generation. gas For natural gas consumption;

[0181] The user's thermal carbon emissions are calculated based on the real-time carbon emission factor on the thermal side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows:

[0182]

[0183] In the formula, E3 represents thermal carbon emissions, and EF... h Q is the carbon emission factor for heat users. h For user heat power, Q eh EF is the heat output power of the electric boiler. w The carbon emission factor corresponding to the heat output of the waste heat boiler. Carbon emission factors from heat storage equipment The carbon emission factor for charging thermal storage equipment, Q hp Q represents the heat output power of the heat pump. w Q represents the heat output power of the waste heat boiler. dis Q represents the heat release power of the thermal storage device. ch The power required to charge the thermal storage equipment.

[0184] Furthermore, the multi-energy complementary system carbon emission dynamic measurement and tracking system also includes:

[0185] The carbon balance verification module is used to verify whether the sum of input carbon emissions and net carbon emissions absorbed by the energy storage system is equal to the sum of carbon emissions from electricity, heat, and gas consumption on the user side and carbon emissions released by the energy storage system. If they are not equal, a system imbalance prompt will be output.

[0186] Furthermore, the multi-energy complementary system carbon emission dynamic measurement and tracking system also includes:

[0187] The digital twin module is used to build a digital twin model of a user node based on the user's electrical carbon emissions, gaseous carbon emissions, and thermal carbon emissions, and to simulate the distribution of electrical, thermal, and gaseous carbon flows in real time.

[0188] The blockchain module is used to record and trace carbon flow data in the digital twin model using blockchain evidence storage technology.

[0189] This invention also provides a schematic diagram of the structure of a computer device, such as... Figure 3 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 3 Take a processor 10 as an example.

[0190] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0191] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0192] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0193] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0194] The computer device also includes an input device 30 and an output device 40. The processor 10, memory 20, input device 30, and output device 40 can be connected via a bus or other means. Figure 3 Taking the example of a connection between China and Israel via a bus.

[0195] Input device 30 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the computer device, such as a touchscreen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 40 may include display devices, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors). The aforementioned display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some alternative embodiments, the display device may be a touchscreen.

[0196] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0197] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0198] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and all such modifications and variations fall within the scope of protection.

Claims

1. A method for dynamic measurement and tracking of carbon emissions from a multi-energy complementary system, characterized in that, include: To acquire real-time operational data and carbon emission-related data of electricity, heat, gas and energy storage in a multi-energy complementary system; Based on real-time operational data and carbon emission-related data, the real-time carbon emission factors on the power side, heat side, and gas side of each node in the multi-energy complementary system are calculated, as well as the carbon emission factors of the energy storage system in the charging and discharging state. The user's carbon emissions (electricity, gas, and heat) are calculated based on the real-time carbon emission factors on the power side, the heat side, the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state.

2. The method according to claim 1, characterized in that, Real-time carbon emission factors on the power side include real-time carbon emission factors for electricity and carbon emission factors for combined heat and power (CHP). The formula for calculating the real-time electricity carbon emission factor is as follows: In the formula, EF sys,t P is the real-time carbon emission factor for electricity. coal For coal-fired power generation, P gas For gas-fired power generation, P grid Power purchased from the power grid, P PV For photovoltaic power generation, P wind For wind power generation capacity, EF coal EF is the carbon emission factor for coal-fired power generation. gas For the carbon emission factor of gas-fired power generation, EF PV EF is the carbon emission factor of photovoltaic power generation. wind EF is the carbon emission factor of wind power generation. grid Real-time grid factor; The formula for calculating the carbon emission factor of combined heat and power is: In the formula, EF CHP,elec and EF CHP,heat These are the carbon emission factors for electricity and heat generated by combined heat and power (CHP), respectively. tHP Q represents the output power of a combined heat and power (CHP) plant. CHP E represents the output heat of a combined heat and power (CHP) plant. CHP This represents the total carbon emissions from combined heat and power (CHP).

3. The method according to claim 2, characterized in that, The real-time carbon emission factor on the thermal side includes the carbon emission factor corresponding to the heat output of the electric boiler, the carbon emission factor corresponding to the heat output of the waste heat boiler, and the carbon emission factor corresponding to the heat output of the heat pump. The formula for calculating the carbon emission factor corresponding to the heat output of an electric boiler is as follows: In the formula, EF Qeh η is the carbon emission factor corresponding to the heat output of an electric boiler. eh For the conversion efficiency of electric heating boilers; If the heat output of the waste heat boiler is industrial waste heat, then the carbon emission factor corresponding to the heat output of the waste heat boiler is zero. If the heat output of the waste heat boiler is fuel supplement heat, then the carbon emission factor corresponding to the heat output of the waste heat boiler is the carbon emission factor of the fuel. The formula for calculating the carbon emission factor corresponding to the heat output of a heat pump is: In the formula, EF hp The carbon emission factor is the carbon emission factor corresponding to the heat output of the heat pump, and COP is the coefficient of performance of the heat pump.

4. The method according to claim 3, characterized in that, Real-time carbon emission factors on the gas side include carbon emission factors for gas generated by electricity, carbon emission factors for natural gas, and carbon emission factors for mixed gases; The formula for calculating the carbon emission factor of gas generated by electricity is as follows: Among them, EF P2G Q is the carbon emission factor for gaseous emissions from electricity generation. gas η represents the calorific value of the electrically generated gas. P2G For electro-gas conversion efficiency; The carbon emission factor for natural gas is calculated using the standard factor, while the carbon emission factor for mixed gases is calculated as a weighted average of the individual carbon emission factors for all gases.

5. The method according to claim 4, characterized in that, Carbon emission factors under charging and discharging states include the equivalent carbon emission factor of the energy storage device when charging at time t, the equivalent carbon emission factor of the energy storage device when discharging at time t, the carbon emission factor of the thermal storage device when charging, the carbon emission factor of the thermal storage device when discharging, the carbon emission factor of the gas storage device when charging, and the carbon emission factor of the gas storage device when discharging. The formulas for calculating the equivalent carbon emission factor of the energy storage device at time t during charging and the equivalent carbon emission factor of the energy storage device at time t during discharging are as follows: In the formula, EF ES，t，ch EF is the equivalent carbon emission factor of an energy storage device at time t when it is being charged. ES，t，dis E is the equivalent carbon emission factor of the energy storage device at time t during discharge. ES,t and E ES,t-1 P represents the electrical energy stored in the device at time t and time t-1, respectively. dis η is the discharge power of the energy storage device. ES Δt represents the discharge efficiency of the energy storage device, and Δt represents the discharge time. The carbon emission factor of thermal storage equipment for heat charging is determined based on the carbon emission factor of the heat source, while the carbon emission factor of thermal storage equipment for heat release is calculated based on the efficiency of the thermal storage equipment and the carbon emission factor of the thermal storage equipment for heat charging. The carbon emission factors for both gas storage equipment filling and gas storage equipment venting are determined based on the carbon emission factors of the gas source.

6. The method according to claim 5, characterized in that, The user's carbon emissions (electricity, gas, and heat) are calculated based on real-time carbon emission factors from the electricity side, heat side, gas side, and the energy storage system under charging and discharging conditions. The user's carbon emissions are calculated based on the real-time carbon emission factor on the power side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows: E1=EF e P e =P coal EF coal +P gas EF gas +P grid EF grid +P PV EF PV +P wind EF wind +EF CHP，elec P CHP +EF ES，t，dis P dis -EF ES，t，ch P ch -EF sys,t P eh -EF sys,t P hp -EF sys,t P P2G In the formula, E1 represents carbon emissions from electricity, and EF... e For electricity users' carbon emission factors, P e For user power consumption, P dis P represents the discharge power of the energy storage device. ch P is the charging power of the energy storage device. eh P is the electrical input power of the electric boiler. hp P is the electrical input power of the heat pump. P2G The electrical input power for electric gas generation; The user's carbon emissions are calculated based on the real-time carbon emission factor on the gas side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows: E2=EF g V g EF gas，n V i +EF P2G V P2G +EF gas，m V dis -EF gas，m V ch -EF gas V gas In the formula, E2 represents carbon emissions, and EF... g For gas users' carbon emission factors, V g V represents the user's gas flow rate. i For the gas flow rate from the superior gas network, EF gas，n As the carbon emission factor of the upper-level gas network, EF gas V is the carbon emission factor for natural gas. P2G For the production of electricity-generated gas, V dis V is the venting flow rate of the gas storage equipment. ch EF is the gas flow rate for charging gas storage equipment. gas，m EF is the carbon emission factor of the gas source for gas storage equipment. gas V is the carbon emission factor for gas-fired power generation. gas For natural gas consumption; The user's thermal carbon emissions are calculated based on the real-time carbon emission factor on the thermal side and the carbon emission factor of the energy storage system under charging and discharging conditions. The calculation formula is as follows: In the formula, E3 represents thermal carbon emissions, and EF... h Q is the carbon emission factor for heat users. h For user heat power, Q eh EF is the heat output power of the electric boiler. w The carbon emission factor corresponding to the heat output of the waste heat boiler. Carbon emission factors from heat storage equipment The carbon emission factor for charging thermal storage equipment, Q hp Q represents the heat output power of the heat pump. w Q represents the heat output power of the waste heat boiler. dis Q represents the heat release capacity of the thermal storage device. ch The power required to charge the thermal storage equipment.

7. The method according to claim 6, characterized in that, Also includes: Verify whether the sum of input carbon emissions and net carbon emissions absorbed by the energy storage system is equal to the sum of carbon emissions from electricity, heat, and gas consumption on the user side and carbon emissions released by the energy storage system. If they are not equal, output a system imbalance prompt.

8. The method according to claim 1, characterized in that, After calculating the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions based on the real-time carbon emission factors on the electricity side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state, the process also includes: A digital twin model of the user node is constructed based on the user's electrical carbon emissions, gaseous carbon emissions, and thermal carbon emissions to simulate the distribution of electrical, thermal, and gaseous carbon flows in real time. Blockchain-based evidence storage technology is used to upload and trace carbon flow data in the digital twin model.

9. A dynamic carbon emission metering and tracking device for a multi-energy complementary system, characterized in that, include: The data acquisition module is used to acquire real-time operating data and carbon emission-related data of electricity, heat, gas and energy storage in the multi-energy complementary system; The carbon emission factor calculation module is used to calculate the real-time carbon emission factor on the power side, the real-time carbon emission factor on the heat side, the real-time carbon emission factor on the gas side, and the carbon emission factor of the energy storage system in the charging and discharging state of each node in the multi-energy complementary system based on real-time operating data and carbon emission related data. The carbon emission calculation module is used to calculate the user's electricity carbon emissions, gas carbon emissions, and heat carbon emissions based on the real-time carbon emission factors on the power side, the real-time carbon emission factors on the heat side, the real-time carbon emission factors on the gas side, and the carbon emission factors of the energy storage system in the charging and discharging state.

10. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the method for dynamic measurement and tracking of carbon emissions from a multi-energy complementary system as described in any one of claims 1 to 8.

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