Campus multi-energy network real-time carbon metering method and system

Abstract

The present application relates to the technical field of carbon emission, in particular to a park multi-energy network real-time carbon metering method and system, mainly comprising a unified factor calculation model of a construction node, a network transmission model and an energy storage system model; carbon emission responsibility balance relationship, effective energy power, equivalent carbon emission factor of energy supply node and equivalent carbon emission factor of energy storage node are obtained respectively, a carbon emission metering model is constructed, and carbon emission results are output based on terminal energy power data and equivalent carbon emission factor of each node. Through the above method, under the premise of known multi-energy physical energy flow, the carbon emission responsibilities in different energy forms such as electricity, gas, heat and cold are uniformly characterized as node carbon emission factor and branch carbon emission flow, the transfer and allocation of carbon emission responsibility in the multi-energy network are realized, thereby realizing the unified monitoring and metering of carbon emission in the form of park multi-energy, and providing a unified metering basis for overall carbon emission evaluation and management of zero-carbon park.

Description

Technical Field

[0001] This invention relates to the field of carbon emission technology, and more specifically, to a real-time carbon metering method and system for multi-energy networks in industrial parks. Background Technology

[0002] As spatial units with a high concentration of industrial production, public services, and infrastructure, industrial parks have large total energy consumption and complex energy structures, making them a significant source of regional carbon emissions. Therefore, industrial parks are a key area for carbon reduction and emission alleviation efforts, and systematic and precise carbon emission measurement is the foundation and key to supporting the low-carbon transformation of these parks.

[0003] Industrial park energy systems typically involve multiple energy forms, including electricity, gas, heat, and cooling, and are coupled through integrated energy hubs. Their complex energy flow structure poses significant challenges to the unified measurement and tracking of carbon emissions. Current carbon measurement methods in industrial parks are primarily based on ex-post statistical accounting, usually relying on energy consumption statistics combined with fixed emission factors for annual or monthly aggregation calculations. These methods struggle to reflect real-time carbon emission changes across different time periods and operating conditions, failing to align with actual energy flow and operational status, and limiting the timeliness and precision of measurement. Furthermore, these methods heavily rely on manual data processing and rule setting, exhibiting low levels of automation and real-time performance, making it difficult to support dynamic carbon management and operational optimization at the industrial park level. In addition, existing technologies mostly conduct carbon measurement independently for electricity, gas, or heat systems, lacking a unified carbon measurement model and technical system. This makes it difficult to generate unified carbon emission results at the industrial park scale. Moreover, carbon emission data collection, calculation, and transmission generally suffer from insufficient automation, weak data consistency, and poor traceability, failing to meet the reliability requirements of industrial park carbon verification and management. Summary of the Invention

[0004] The purpose of this invention is to provide a real-time carbon metering method and system for multi-energy networks in industrial parks to solve the existing problems.

[0005] This invention is achieved through the following technical solution:

[0006] In a first aspect, the present invention provides a method for real-time carbon metering of a multi-energy network in a park, comprising:

[0007] Obtain the injected carbon emissions from multiple energy supply points, and construct a node unified factor calculation model, a network transmission model, and an energy storage system model respectively;

[0008] Based on the injected carbon emissions, the carbon emission responsibility balance relationship, effective energy power, equivalent carbon emission factor of energy supply node and equivalent carbon emission factor of energy storage node are obtained through the node unified factor calculation model, network transmission model and energy storage system model, respectively.

[0009] Acquire end-user energy consumption data, construct a carbon emission measurement model, and output carbon emission results based on end-user energy consumption data and equivalent carbon emission factors at each node.

[0010] Preferably, the node unified factor calculation model includes:

[0011]

[0012] In the formula, and These represent the inflow and outflow nodes in the system topology, respectively. The set of branch paths; Indicates a branch During the period Actual arrival node Energy power; Indicates a branch The carbon emission factor carried by the energy flow reaching the destination, i.e., the carbon emission responsibility intensity corresponding to a unit of energy reaching the destination; Represents a node During the period The node carbon emission factor; Represents a node During the period to adjacent nodes Output energy power; Represents a node During the period Internal responsibility for carbon emissions injected into the system through energy supply.

[0013] Preferably, constructing the network transmission model includes:

[0014]

[0015]

[0016] In the formula, This indicates the energy transfer time delay of the branch; This represents the equivalent energy transfer efficiency of the pipeline at the corresponding time scale. Indicating a historical moment From node Energy power injected into the pipeline; Indicates the current moment Actual arrival node Effective energy power; When injecting energy into the node Carbon emission factors; To reach the node The energy carried by the energy supply equivalent carbon emission factor.

[0017] Preferably, constructing the energy storage system model includes:

[0018]

[0019] In the formula, for The equivalent carbon emission factor of energy storage nodes at any given time. for The equivalent carbon emission factor of energy storage nodes at any given time. Indicates a historical period; and Representing energy storage nodes Charging power and discharging power; and These represent the charging and discharging efficiencies of the energy storage device, respectively. The node carbon emission factor for energy storage at the charging time.

[0020] Preferably, it also includes obtaining a time-based recursive dynamic update model of carbon emission flows to obtain the node carbon emission factors in time periods. The update relationships include:

[0021]

[0022] In the formula, Indicates time period Carbon emission factor vectors for each node; The node energy balance operator matrix; Indicates the number of historical events Time period injection system, and in the current time period The energy carbon flow operator matrix that arrives at each node after being transmitted through the pipeline network; Indicates the time period The carbon emission responsibility vector directly injected into the system from primary energy sources, external energy supply units, or energy storage devices. For time period Carbon emission factor vectors at each node, This represents the total number of discrete time intervals.

[0023] Preferably, the construction of a carbon emission measurement model includes:

[0024]

[0025] In the formula, Indicates energy consumption unit Cumulative carbon emissions during the statistical period; Represents the set of discrete time periods within a statistical period; Indicates energy consumption unit The set of energy types consumed; Indicates energy consumption unit During the period Energy type The actual power consumption; Indication and energy consumption unit Connected to and supplying energy types Network nodes during time period The node carbon emission factor; Energy consumption unit With energy type The corresponding power supply node mapping function; This indicates the length of time corresponding to a single time period.

[0026] Secondly, the present invention also provides a real-time carbon metering system for multi-energy networks in industrial parks, comprising:

[0027] Multi-energy carbon meter module is used to collect and record basic information on carbon emissions from the park's multi-energy systems in real time;

[0028] The edge carbon computing and coordination unit and the park carbon metering cloud platform are used to obtain basic information on carbon emissions from multi-energy systems collected by multi-energy carbon meter modules, and to execute the above-mentioned real-time carbon metering method for multi-energy networks in parks.

[0029] Preferably, the multi-energy carbon meter module includes a source-side carbon meter, a grid-side carbon meter, and a load-side carbon meter:

[0030] Source-side carbon meters are used to collect information on energy input, operating status, and fuel consumption, and send the data to edge carbon computing and coordination units or cloud platforms.

[0031] The network-side carbon table is the basis for obtaining carbon information from neighboring nodes.

[0032] A load-side carbon meter is used to collect data on the electricity, gas, heat, and cooling energy consumption of enterprises, workshops, buildings, or equipment.

[0033] Preferably, it also includes a distributed ledger module, which is used to generate encrypted signature information from the corresponding carbon metering key data, calculation result summary and associated topology identifier. The encrypted signature information is written into the nodes of the distributed ledger module by the edge carbon computing and coordination unit or the cloud multi-energy carbon metering platform for storage, forming a carbon metering data link record that corresponds one-to-one with specific time, spatial location and calculation status.

[0034] Preferably, the park carbon metering cloud platform also includes, based on the source-side direct carbon emission metering results and multi-energy carbon flow data uploaded by the edge computing unit, a unified multi-energy carbon metering model to globally track and comprehensively calculate the carbon emissions of each energy system within the park.

[0035] The technical solution of the present invention has at least the following advantages and beneficial effects:

[0036] The method provided by this invention mainly includes constructing a unified node factor calculation model, a network transmission model, and an energy storage system model; obtaining the carbon emission responsibility balance relationship, effective energy power, equivalent carbon emission factors of energy supply nodes, and equivalent carbon emission factors of energy storage nodes, respectively; constructing a carbon emission measurement model; and outputting carbon emission results based on terminal energy consumption power data and equivalent carbon emission factors of each node. Through this method, under the premise of known multi-energy physical energy flows, the carbon emission responsibility under different energy forms such as electricity, gas, heat, and cooling is uniformly represented as node carbon emission factors and branch carbon emission flows, realizing the transmission and allocation of carbon emission responsibility in multi-energy networks. This achieves unified monitoring and measurement of carbon emissions under multiple energy forms in the park, providing a unified measurement basis for the overall carbon emission assessment and management of zero-carbon parks. Attached Figure Description

[0037] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This invention relates to the architecture of a multi-energy carbon metering system for industrial parks.

[0039] Figure 2 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0040] 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, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0041] The independently described modules or sub-modules may or may not be physically separated; they may be implemented in software or hardware, and some modules or sub-modules may be implemented in software, with the processor calling the software to implement the function of these modules or sub-modules, while other modules or sub-modules may be implemented in hardware, such as through hardware circuits. Furthermore, some or all of the modules can be selected to achieve the purpose of this application's solution according to actual needs.

[0042] Please refer to Figures 1-2This invention provides a real-time carbon metering method for multi-energy networks in industrial parks. In these multi-energy systems, electricity, natural gas, heat, and cooling are coupled through transmission and distribution networks and integrated energy hubs, with carbon emissions being transferred and distributed along energy flow paths within the system. To achieve unified metering and tracking of carbon emissions from multiple energy sources within the industrial park, a carbon emission flow metering model suitable for multi-energy systems in industrial parks is constructed. This model, based on the fundamental principle of "energy conservation - carbon conservation," realizes the continuous transfer and distribution of carbon emissions within the multi-energy network under the premise of known physical flows of multiple energy sources, including:

[0043] S101: Obtain the injected carbon emissions from multiple energy supply points and construct a node unified factor calculation model, a network transmission model, and an energy storage system model respectively;

[0044] The park's multi-energy system is abstracted as a generalized directed graph. , where the set of nodes Includes power nodes, natural gas nodes, heating nodes, cooling nodes, and energy storage nodes; edge set. This model represents the transmission and conversion relationships of various energy sources within the power grid, gas grid, heating grid, cooling grid, and conversion equipment. It assumes that the physical operating state of the system is known at the studied timescale (e.g., 15 minutes or 1 hour), including the energy flow distribution of various energy sources, equipment output, and load levels. This data can be obtained through the existing energy acquisition and metering system of the integrated energy system. It assumes that the electricity and gas systems meet instantaneous equilibrium at this timescale, while the heating and cooling systems, due to the characteristics of medium flow and thermal inertia, do not need to meet instantaneous energy equilibrium. Carbon emission responsibility (carbon emission flow) itself does not have an independent physical form but rather exists as a "virtual attached quantity" transmitted, converted, and stored within the system along with the energy flow.

[0045] S102: Based on the injected carbon emissions, the carbon emission responsibility balance relationship, effective energy power, equivalent carbon emission factor of energy supply node and equivalent carbon emission factor of energy storage node are obtained through the node unified factor calculation model, network transmission model and energy storage system model, respectively.

[0046] S103: Obtain end-user energy consumption data, construct a carbon emission measurement model, and output carbon emission results based on end-user energy consumption data and equivalent carbon emission factors at each node.

[0047] In one exemplary embodiment of the present invention, to uniformly describe carbon emission responsibility under different energy forms, a nodal carbon emission factor variable is introduced to characterize the carbon emission intensity corresponding to a unit of equivalent energy. Defined in discrete time periods... Next, node The carbon emission factor is Its unit is For any branch road ,definition For the time period Internal nodes To the node The equivalent energy power transmitted, where non-electric energy sources such as natural gas, heat, and cold energy are converted to a unified energy benchmark using their lower heating value or enthalpy. Based on this, the branch carbon emission flow rate is defined as... Used to characterize energy from nodes Passed to node Carbon emission responsibility.

[0048] For any node During the period The carbon emission responsibility satisfies the following unified balance relationship, namely the node unified factor calculation model:

[0049]

[0050] In the formula, and These represent the inflow and outflow nodes in the system topology, respectively. The set of branch paths; Indicates a branch During the period Actual arrival node The energy output needs to take into account factors such as transmission delay and loss along the way; Indicates a branch The carbon emission factor carried by the energy flow to the destination, i.e., the carbon emission liability intensity corresponding to a unit of energy delivered. Represents a node During the period The node carbon emission factor is used to characterize the carbon emission responsibility allocated to a unit of energy transported outward from that node. Represents a node During the period to adjacent nodes Output energy power. Represents a node During the period The carbon emission responsibility injected into the system through energy supply originates from internal / external energy supply points and is collected by deployed carbon meters on the power generation side. This balance indicates that the node carbon emission factor is determined solely by the carbon emission responsibility of the energy actually arriving at the node in the current time period and the direct emissions generated by the node itself, and is unrelated to energy flows that are still in the transmission process and have not yet arrived at the node.

[0051] In one exemplary embodiment of the present invention, in a park's electricity and gas system, due to the high energy transmission speed and weak network inertia, the impact of transmission delay on metering results can be ignored. The network transmission equation for the carbon emission flow is as follows:

[0052] and ;

[0053] in, Represents a node During the period To the node Output instantaneous energy power, For nodes During the period The node carbon emission factor.

[0054] For the park's heating and cooling systems, due to significant time delays and losses along the pipeline during the transmission of heat or cold media, the instantaneous balance between energy and carbon emission responsibilities is not met. (Branch lines are then constructed.) The physical pipe length is Time period The average transport velocity of the fluid in the lower pipe is Then its transmission delay is defined as , This indicates the energy transfer time delay of this branch;

[0055] At the same time, pipeline energy transmission efficiency is introduced. Characterizing transmission loss. Ignoring medium leakage, carbon emission responsibility is conserved within the pipeline, while effective energy decays. The carbon emission flow network transmission model is as follows:

[0056]

[0057]

[0058] In the formula, This indicates the energy transfer time delay of the branch; This represents the equivalent energy transfer efficiency of the pipeline at the corresponding time scale. Indicating a historical moment From node Energy power injected into the pipeline; Indicates the current moment Actual arrival node Effective energy power; When injecting energy into the node Carbon emission factors; To reach the node The energy carried by the energy supply equivalent carbon emission factor.

[0059] In one exemplary embodiment of the present invention, the energy storage devices (including electrical, thermal, and cooling) within the park do not generate direct carbon emissions themselves. Their carbon emission responsibility stems from the carbon emission factor corresponding to the energy absorbed during the charging (or thermal / cold storage) phase, and is subsequently released back into the system across time scales during the discharging (or heat release / cooling) phase. In the unified carbon emission flow network, the energy storage devices are abstracted as independent nodes. It connects to the energy node via a branch and injects energy into the network as an equivalent energy source during the energy release phase. The energy storage node itself does not generate new carbon emissions; its role is only to temporarily store and re-release historical carbon emission responsibilities over time. At any given time period... Equivalent carbon emission factor of energy storage nodes This is equal to the ratio of the currently unreleased carbon emission responsibility within the energy storage system to the corresponding available energy. The model for the energy storage system includes:

[0060]

[0061] In the formula, for The equivalent carbon emission factor of energy storage nodes at any given time. for The equivalent carbon emission factor of energy storage nodes at any given time. Indicates a historical period; and Representing energy storage nodes Charging power and discharging power; and These represent the charging and discharging efficiencies of the energy storage device, respectively. The node carbon emission factor for energy storage at the charging time.

[0062] At the system level, to uniformly handle multiple hot and cold branches with different time delays, a time-recursive dynamic update model for carbon emission flows is introduced. Let the maximum transmission delay of the system correspond to... For each discrete time period, the node carbon emission factor in that time period The update relationship can be represented as:

[0063]

[0064] In the formula, Indicates time period The carbon emission factor vector of each node, whose elements characterize the carbon emission responsibility borne by a unit of energy at the corresponding node; The node energy balance operator matrix is ​​used to characterize the energy balance in the time period. Energy collection, distribution, and balance constraints at the node level; Indicates the number of historical events Time period injection system, and in the current time period The energy carbon flow operator matrix that arrives at each node after transmission through the pipeline network has its matrix elements determined by the corresponding branch. The magnitude of energy flow at any given time, the transmission delay mapping relationship, and the energy loss parameters along the path are jointly determined to characterize the cross-time transfer process of carbon emission responsibility with time delay and loss characteristics; Indicates the time period The carbon emission responsibility vector for energy sources directly injected into the system from primary energy sources, external energy supply units, or energy storage devices is determined by the corresponding energy supply capacity and emission factor. For time period Carbon emission factor vectors at each node, This represents the total number of discrete time intervals.

[0065] Based on the above model, the carbon emission flow distribution and carbon emission factors of multiple energy systems (electricity, gas, heat, and cooling) within the park can be obtained throughout the entire operating cycle. A cumulative carbon emission measurement model for any energy-consuming unit within the statistical period can be constructed, including:

[0066]

[0067] In the formula, Indicates energy consumption unit Cumulative carbon emissions during the statistical period; Represents the set of discrete time periods within a statistical period; Indicates energy consumption unit The range of energy types consumed includes electricity, natural gas, heat, and cold energy; Indicates energy consumption unit During the period Energy type The actual power consumption; Indication and energy consumption unit Connected to and supplying energy types Network nodes during time period The node carbon emission factor; Energy consumption unit With energy type The corresponding power supply node mapping function; This indicates the length of time corresponding to a single time period.

[0068] This invention also provides a real-time carbon metering system for a multi-energy network in a park, used in the aforementioned real-time carbon metering method for a multi-energy network in a park, comprising:

[0069] Multi-energy carbon meter module is used to collect and record basic information on carbon emissions from the park's multi-energy systems in real time;

[0070] The edge carbon computing and coordination unit, located locally within the park, serves as an intermediate collaborative layer between the edge carbon meters and the cloud platform. It aggregates data uploaded from multiple energy carbon meters across the park, cleans, verifies, and fuses heterogeneous data from various sources, and, combined with the park's multi-energy system topology and operational status information, performs real-time calculations of multi-energy carbon emission flows within the region. The edge carbon computing and coordination unit can independently complete the main carbon metering calculation tasks within the park without relying on the cloud, thereby reducing communication latency and improving system real-time performance and operational reliability. Simultaneously, it can synchronize calculation results and raw data to the cloud-based multi-energy carbon metering platform as needed for global analysis and management.

[0071] The park's carbon metering cloud platform serves as the system's global computing and management center, used for unified modeling, centralized management, and long-term storage of carbon emissions from multiple energy sources within the park. Based on direct carbon emission metering results from the source side and multi-energy carbon flow data uploaded by edge computing units, the cloud platform uses a unified multi-energy carbon metering model to globally track and comprehensively calculate carbon emissions from various energy systems within the park. It also supports flexible configuration and switching of different carbon accounting standards and boundaries, thereby meeting diverse application needs such as policy regulation, carbon asset management, and low-carbon operation assessment.

[0072] Based on the multi-energy coupled operation characteristics and unified carbon emission metering requirements of the park, this paper proposes a cloud-edge-device collaborative multi-energy carbon meter system architecture for the park. This architecture enables dynamic tracking, real-time metering, and unified accounting of carbon emissions from various energy flows such as electricity, gas, heat, and cooling within the park. The multi-energy carbon meter system mainly consists of three parts: multi-energy carbon meter modules distributed across various energy nodes and energy-consuming units within the park; edge carbon computing and coordination units located locally within the park; and a cloud-based multi-energy carbon metering and management platform. These parts are interconnected via wired or wireless communication networks, forming a hierarchical and collaborative carbon metering system architecture. A schematic diagram of the system structure is shown below. Figure 1 As shown, solid lines represent energy transmission or energy conversion relationships, while dashed lines represent data communication and collaborative computing relationships.

[0073] In one exemplary embodiment of the present invention, the multi-energy carbon meter module includes:

[0074] Source-side carbon meters are installed inside the park or on various energy supply sides connected to the park, including but not limited to distributed generation devices, gas boilers, combined heat and power systems, district heating and cooling interfaces, and external power or gas access points. They are used to collect information on energy input, operating status, and fuel consumption. Through flue gas sensors or real-time conversion based on fuel consumption and emission factors, they obtain the direct carbon emissions or equivalent carbon emission intensity per unit time and send the relevant data to the edge carbon computing and coordination unit or the park's carbon metering cloud platform.

[0075] Grid-side carbon meters are installed at key nodes in the park's internal power grid, heating network, cooling network, and integrated energy system, including substations, heat exchange stations, energy collection points, and multi-energy conversion nodes. Based on carbon information from neighboring nodes and combined with energy flow data from the current node, they calculate the carbon flow rate, carbon flow density, and indirect carbon emissions corresponding to network losses for various energy sources within the park's network. This characterizes the carbon emission transfer relationships during the transmission, distribution, and conversion of multiple energy sources within the park. Grid-side carbon meters participate in centralized carbon emission flow calculations under the coordination of edge carbon calculation and coordination units.

[0076] Load-side carbon meters are installed at various energy-consuming entities or units within the park. They can be directly integrated into smart meters, integrated energy consumption acquisition terminals, or energy management systems. They are used to collect electricity, gas, heat, and cooling energy consumption data at the enterprise, workshop, building, or equipment level. Based on the carbon emission factor information fed back by grid-side carbon meters or edge carbon calculation and coordination units, they can calculate the corresponding indirect carbon emissions and cumulative carbon emissions in real time, thereby achieving refined carbon metering and responsibility quantification at the energy-consuming unit level within the park.

[0077] One exemplary embodiment of the present invention ensures the authenticity, integrity, and immutability of multi-energy carbon metering data in the park during the collection, calculation, and transmission processes. The multi-energy carbon meter system introduces distributed ledger technology as a trusted evidence storage mechanism for carbon metering data within a cloud-edge-device collaborative architecture. After the various source-side carbon meters, grid-side carbon meters, and load-side carbon meters complete the collection of energy flow and basic carbon emission data, the edge carbon computing and coordination unit performs consistency verification and time synchronization of the multi-source carbon data. After completing the phased carbon emission flow calculation, it generates encrypted signature information from the corresponding key carbon metering data, calculation result summary, and associated topology identifier. This encrypted signature information is written into the distributed ledger node for evidence storage by the edge carbon computing and coordination unit or the cloud-based multi-energy carbon metering platform, forming a carbon metering data link record that corresponds one-to-one with specific time, spatial location, and calculation status. During system operation, the distributed ledger only stores data from key carbon measurement nodes confirmed at the edge or in the cloud, without participating in real-time carbon emission flow calculations. This allows for traceable management of carbon emission data throughout the entire process, from edge-side collection and calculation to cloud-side aggregation, without affecting system real-time performance. When conducting subsequent carbon verification, carbon audits, or carbon trading settlements, the stored information in the distributed ledger can be used to verify and restore the carbon measurement results for any time period, energy node, or energy-consuming unit, avoiding disputes over carbon emission liability caused by data tampering, changes in calculation methods, or missing information.

[0078] By deeply integrating distributed ledger technology with the cloud-edge-device collaborative multi-energy carbon meter system in the industrial park, the system not only achieves real-time perception, dynamic calculation, and unified accounting of carbon emissions from multiple energy sources, but also further constructs a data credibility mechanism that matches the carbon metering process. This effectively overcomes the problems of difficult verification of carbon data and difficulty in tracing results in existing multi-energy carbon metering systems, and provides reliable data infrastructure support for the refined management of carbon emissions, optimization of low-carbon operation, and carbon asset management in industrial parks.

[0079] The aforementioned carbon emission flow measurement model is implemented in the park's cloud-edge-device collaborative multi-energy carbon meter system through a "device-side data collection, edge-side calculation, and cloud-side aggregation" approach, thereby ensuring the consistency and interpretability of carbon measurement results across the physical layer, model layer, and system implementation layer. Specifically, the source-side carbon meter corresponds to the carbon emission injection item in the model. The data collected by the grid-side carbon meter, including fuel consumption, equipment output, and emission factors, is used to determine the carbon emission responsibility vector of each source-side node in each time period, i.e., the carbon emission injection amount in the model. This type of carbon meter provides carbon emission sources for a unified carbon emission flow model. The grid-side carbon meter embeds a unified calculation model for node carbon emission factors, an energy network carbon emission factor transfer model, and an energy storage system carbon emission factor calculation model. The multi-energy flow data, node power, and operating status information collected by the meter are used to construct the energy flow connection relationships, branch power, and node energy balance equations in the model. Under the unified scheduling of the edge carbon calculation and coordination unit, it participates in the hourly update calculation of node carbon emission factors. Through the collaborative calculation of the grid-side carbon meter, the node carbon emission factors of each energy network node in different time periods, as well as the carbon emission flow rate of each branch transmitted with the energy flow, can be obtained, thus characterizing the dynamic transfer process of carbon emission responsibility in the multi-energy network of the park. The load-side carbon meter corresponds to the carbon emission measurement equation. The power data of terminal energy consumption such as electricity, gas, heat and cooling collected by it are used as the energy consumption item of the energy-consuming unit in the model. Combined with the carbon emission factor of the corresponding energy supply node fed back by the grid-side carbon meter or edge computing unit, the indirect carbon emission is calculated hourly according to the carbon measurement equation of the energy-consuming unit, and accumulated within the statistical period to form the cumulative carbon emission result at the energy-consuming unit level.

[0080] This invention constructs a multi-energy carbon emission flow measurement model. Under the premise of known physical energy flows of multiple energy sources, it uniformly represents the carbon emission responsibility under different energy forms such as electricity, gas, heat, and cooling as node carbon emission factors and branch carbon emission flows, realizing the transmission and allocation of carbon emission responsibility in the multi-energy network. This enables unified monitoring and measurement of carbon emissions under multiple energy forms in the park, providing a unified measurement basis for the overall carbon emission assessment and management of zero-carbon parks.

[0081] To address the shortcomings of existing carbon metering systems, which rely on centralized computing and lack real-time performance, this invention constructs a cloud-edge-device collaborative multi-energy carbon meter system architecture. This architecture deploys basic data collection, regional carbon emission flow calculation, and global management functions in a layered manner. By setting up edge carbon computing and coordination units locally within the park, multi-energy carbon emission flow calculation and node carbon emission factor updates can be completed locally in real time, reducing reliance on cloud communication and computing. This effectively improves the real-time performance and operational reliability of the park's carbon metering system under complex operating conditions.

[0082] In existing technologies, the correspondence between carbon meter data and carbon accounting models is unclear, and carbon emission results lack a clear source of responsibility. This invention clarifies the functional division of source-side carbon meters, grid-side carbon meters, and load-side carbon meters in a unified carbon emission flow model. Source-side carbon meters correspond to direct carbon emission injection, grid-side carbon meters correspond to the transmission and allocation of carbon emission responsibility within the network, and load-side carbon meters correspond to the measurement of carbon emissions from end-use energy. This enables the step-by-step transmission and quantification of carbon emission responsibility along the energy flow path, improving the interpretability and verifiability of carbon metering results in industrial parks.

[0083] To address the transmission delay and flow loss characteristics prevalent in thermal and cooling systems, this invention introduces a time-recursive dynamic update model for carbon emission flows. This model links carbon emission responsibility to historical energy injection processes, avoiding measurement biases introduced by the instantaneous balance assumption. This method can more accurately reflect the carbon emission responsibility transfer characteristics of thermal and cooling systems during actual operation, improving the accuracy of non-electric energy carbon measurement results in park-scale applications.

[0084] To enhance the credibility of carbon measurement data, this invention introduces a distributed ledger as a notarization mechanism for key carbon measurement data in a cloud-edge-device collaborative carbon meter system, ensuring the immutable recording of carbon measurement results and related information. This mechanism achieves full traceability of carbon emission data without participating in real-time calculations, effectively supporting subsequent applications such as carbon verification, carbon auditing, and carbon asset management.

[0085] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0086] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. This computer software product, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0087] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for real-time carbon metering of a multi-energy network in a park, characterized in that, include: Obtain the injected carbon emissions from multiple energy supply points, and construct a node unified factor calculation model, a network transmission model, and an energy storage system model respectively; Based on the injected carbon emissions, the carbon emission responsibility balance relationship, effective energy power, equivalent carbon emission factor of energy supply node and equivalent carbon emission factor of energy storage node are obtained through the node unified factor calculation model, network transmission model and energy storage system model, respectively. Acquire end-user energy consumption data, construct a carbon emission measurement model, and output carbon emission results based on end-user energy consumption data and equivalent carbon emission factors at each node. The node unified factor calculation model includes: In the formula, and These represent the inflow and outflow nodes in the system topology, respectively. The set of branch paths; Indicates a branch During the period Actual arrival node Energy power; Indicates a branch The carbon emission factor carried by the energy flow reaching the destination, i.e., the carbon emission responsibility intensity corresponding to a unit of energy reaching the destination; Represents a node During the period The node carbon emission factor; Represents a node During the period to adjacent nodes Output energy power; Represents a node During the period The responsibility for carbon emissions injected into the system through energy supply; Constructing the network transmission model includes: In the formula, This indicates a delay in energy transfer time; This represents the equivalent energy transfer efficiency of the pipeline at the corresponding time scale. Indicating a historical moment From node Energy power injected into the pipeline; Indicates the current moment Actual arrival node Effective energy power; When injecting energy into the node Carbon emission factors; To reach the node The energy carried by the energy supply equivalent carbon emission factor; Constructing the energy storage system model includes: In the formula, for The equivalent carbon emission factor of energy storage nodes at any given time. for The equivalent carbon emission factor of energy storage nodes at any given time. Indicates a historical period; and Representing energy storage nodes Charging power and discharging power; and These represent the charging and discharging efficiencies of the energy storage device, respectively. The node carbon emission factor for energy storage at the charging time.

2. The real-time carbon metering method for a multi-energy network in a park according to claim 1, characterized in that, This also includes obtaining a time-based recursive dynamic update model of carbon emission flows to obtain the node carbon emission factors in time periods. The update relationships include: In the formula, Indicates time period Carbon emission factor vectors for each node; The node energy balance operator matrix; Indicates the number of historical events Time period injection system, and in the current time period The energy carbon flow operator matrix that arrives at each node after being transmitted through the pipeline network; Indicates the time period The carbon emission responsibility vector directly injected into the system from primary energy sources, external energy supply units, or energy storage devices. For time period Carbon emission factor vectors at each node, This represents the total number of discrete time intervals.

3. The real-time carbon metering method for a multi-energy network in a park according to claim 2, characterized in that, Constructing a carbon emission measurement model includes: In the formula, Indicates energy consumption unit Cumulative carbon emissions during the statistical period; Represents the set of discrete time periods within a statistical period; Indicates energy consumption unit The set of energy types consumed; Indicates energy consumption unit During the period Energy type The actual power consumption; Indication and energy consumption unit Connected to and supplying energy types Network nodes during time period The node carbon emission factor; Energy consumption unit With energy type The corresponding power supply node mapping function; This indicates the length of time corresponding to a single time period.

4. A real-time carbon metering system for a multi-energy network in a park, characterized in that, include: Multi-energy carbon meter module is used to collect and record basic information on carbon emissions from the park's multi-energy systems in real time; The edge carbon computing and coordination unit and the park carbon metering cloud platform are used to obtain basic information on carbon emissions from multi-energy systems collected by the multi-energy carbon meter module, and to execute the real-time carbon metering method for multi-energy networks in parks as described in any one of claims 1-3.

5. A real-time carbon metering system for a multi-energy network in a park according to claim 4, characterized in that, The multi-energy carbon meter module includes a source-side carbon meter, a grid-side carbon meter, and a load-side carbon meter: Source-side carbon meters are used to collect information on energy input, operating status, and fuel consumption, and send the data to edge carbon computing and coordination units or cloud platforms. The network-side carbon table is the basis for obtaining carbon information from neighboring nodes. A load-side carbon meter is used to collect data on the electricity, gas, heat, and cooling energy consumption of enterprises, workshops, buildings, or equipment.

6. The real-time carbon metering system for a multi-energy network in a park according to claim 5, characterized in that, It also includes a distributed ledger module, which generates encrypted signature information from the corresponding key carbon measurement data, calculation result summary and associated topology identifier. The encrypted signature information is written into the nodes of the distributed ledger module by the edge carbon computing and coordination unit or the cloud multi-energy carbon measurement platform for storage, forming a carbon measurement data link record that corresponds one-to-one with the specific time, spatial location and calculation status.

7. A real-time carbon metering system for a multi-energy network in a park according to claim 6, characterized in that, The park's carbon metering cloud platform also includes global tracking and comprehensive accounting of carbon emissions from various energy systems within the park, based on the source-side direct carbon emission metering results and multi-energy carbon flow data uploaded by edge computing units and a unified multi-energy carbon metering model.

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