Multi-carbon source fusion metering method and system

Abstract

The invention discloses a multi-carbon source fusion metering method and system, and the method comprises the steps: carrying out the data collection based on collection terminal equipment, and obtaining the energy consumption and level carbon emission measurement data of a user or an enterprise; according to the type of the energy consumption equipment, performing normalization processing on energy consumption and post-level carbon emission measurement data based on an energy hub model; constructing a multi-energy coupling model based on an energy hub according to the space coupling relationship and the time coupling relationship of the different energy consumption devices, and calculating the energy consumption efficiency of the different energy sources according to the multi-energy coupling model; according to a multi-energy system carbon flow theory, constructing an energy flow-carbon emission flow coupling transfer model based on the energy system carbon flow theory, and calculating carbon flow rates of different energy flows according to the energy flow-carbon emission flow coupling transfer model; and calculating energy consumption indirect carbon emission of different carbon sources of the user or the enterprise according to the carbon flow rate and the energy consumption efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission detection, and more specifically, to a multi-carbon source fusion metering method and system. Background Art

[0002] The research on multi-energy carbon emission flow method has become a hot field. Different from measuring carbon emissions by carbon factor conversion, multi-energy carbon emission flow method refers to the total amount of carbon emissions generated by energy consumption in the energy use activities of enterprises. It does not require various assumptions, thus avoiding the increase of uncertainty.

[0003] Existing standards and methods have many limitations. First, most current corporate carbon emission estimation methods are not universal and cannot be directly applied to other different companies or industries. Second, there are few studies on equipment-level carbon emissions. Third, existing methods conduct pre-assessment or post-assessment rather than real-time assessment, while real-time carbon monitoring can help cope with the changing environment by providing information and giving suggestions for controlling emissions.

[0004] Therefore, a multi-carbon source fusion measurement method is needed. Summary of the invention

[0005] The present invention proposes a multi-carbon source fusion metering method and system to solve the problem of how to efficiently determine carbon emissions.

[0006] In order to solve the above problems, according to one aspect of the present invention, a multi-carbon source fusion metering method is provided, the method comprising:

[0007] Collect data based on terminal equipment to obtain energy consumption and carbon emission measurement data of users or enterprises;

[0008] According to the type of energy-consuming equipment, the energy consumption and job-level carbon emission measurement data are normalized based on the energy hub model;

[0009] According to the spatial coupling relationship and temporal coupling relationship of different energy-consuming equipment, a multi-energy coupling model based on the energy hub is constructed, and the energy efficiency of different energy sources is calculated according to the multi-energy coupling model;

[0010] According to the carbon flow theory of multi-energy system, an energy flow-carbon emission flow coupling transfer model based on the energy system carbon flow theory is constructed, and the carbon flow rate of different energy flows is calculated according to the energy flow-carbon emission flow coupling transfer model;

[0011] Calculate the indirect carbon emissions from different carbon sources of users or enterprises based on carbon flow rate and energy efficiency.

[0012] Preferably, the data collection terminal equipment includes: an electric meter installed in the electricity consumption part and a carbon emission collection device and an energy consumption collection device installed in the electricity and heat consumption parts; the collected data include: carbon dioxide volume fraction, flue gas flow, flue gas temperature, flue gas pressure, flue gas moisture content, electricity consumption, natural gas consumption and heating consumption.

[0013] Preferably, during the normalization process,

[0014] For a single-input-single-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is:

[0015]

[0016] in, and are the carbon flow density at the input port and the carbon flow density at the output port of the energy conversion device respectively; V i I and are the input energy flow and the output energy flow respectively; η I is the relationship between the output energy flow and the input energy flow of the device;

[0017] For a single-input-multiple-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is:

[0018]

[0019] in, and represent the carbon flow density at the electrical output port and the carbon flow density at the thermal output port respectively; is the carbon flow density at the input port; η W is the power conversion efficiency; η Q is the thermal energy conversion efficiency; ∈ is the thermal energy coefficient.

[0020] Preferably, the multi-energy coupling model based on the energy hub is constructed according to the spatial coupling relationship and the temporal coupling relationship of different energy-consuming devices, including:

[0021] L=CP, that is

[0022] Among them, P is the energy hub input column vector; L is the energy hub output column vector; C is the coupling matrix, which represents the distribution and conversion relationship between the energy hub input and output, P i , L j , C ij are the elements of the corresponding vector or matrix; i and j are the number of rows and columns respectively.

[0023] Preferably, the carbon flow rates of different energy flows are calculated according to the energy flow-carbon emission flow coupled transfer model, including:

[0024] R = ρP, that is

[0025] Among them, R is the carbon flow rate; ρ is the carbon flow density matrix of energy carbon flow, which represents the carbon flow density of different energy consumption nodes; P is the column vector of the usage of a given energy.

[0026] Preferably, the calculation of the indirect carbon emissions of different carbon sources of a user or enterprise based on the carbon flow rate and energy efficiency includes:

[0027]

[0028] Among them, F is the indirect carbon emissions from energy use; R is the carbon flow rate of energy carbon flow, dt is the time vector, and the formula shows that carbon emissions are the integral of the carbon flow rate within a given time.

[0029] According to another aspect of the present invention, a multi-carbon source fusion metering system is provided, the system comprising:

[0030] A data collection unit is used to collect data based on a collection terminal device to obtain energy consumption and carbon emission measurement data of users or enterprises;

[0031] A data processing unit, used for normalizing the energy consumption and carbon emission measurement data according to the type of energy-consuming equipment based on the energy hub model;

[0032] An energy efficiency determination unit, used to construct a multi-energy coupling model based on an energy hub according to the spatial coupling relationship and temporal coupling relationship of different energy-consuming devices, and calculate the energy efficiency of different energy sources according to the multi-energy coupling model;

[0033] A carbon flow rate determination unit is used to construct an energy flow-carbon emission flow coupling transfer model based on the energy system carbon flow theory according to the multi-energy system carbon flow theory, and calculate the carbon flow rates of different energy flows according to the energy flow-carbon emission flow coupling transfer model;

[0034] The indirect carbon emissions from energy use determination unit is used to calculate the indirect carbon emissions from energy use of different carbon sources of users or enterprises based on carbon flow rate and energy efficiency.

[0035] Preferably, the data collection terminal equipment includes: an electric meter installed in the electricity consumption part and a carbon emission collection device and an energy consumption collection device installed in the electricity and heat consumption parts; the collected data include: carbon dioxide volume fraction, flue gas flow, flue gas temperature, flue gas pressure, flue gas moisture content, electricity consumption, natural gas consumption and heating consumption.

[0036] Preferably, the data processing unit, during the normalization process,

[0037] For a single-input-single-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is:

[0038]

[0039] in, and are the carbon flow density at the input port and the carbon flow density at the output port of the energy conversion device respectively; V i I and are the input energy flow and the output energy flow respectively; η I is the relationship between the output energy flow and the input energy flow of the device;

[0040] For a single-input-multiple-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is:

[0041]

[0042] in, and represent the carbon flow density at the electrical output port and the carbon flow density at the thermal output port respectively; is the carbon flow density at the input port; η W is the power conversion efficiency; η Q is the thermal energy conversion efficiency; ∈ is the thermal energy coefficient.

[0043] Preferably, the energy efficiency determination unit constructs a multi-energy coupling model based on the energy hub according to the spatial coupling relationship and the temporal coupling relationship of different energy-consuming devices, including:

[0044] L=CP, that is

[0045] Among them, P is the energy hub input column vector; L is the energy hub output column vector; C is the coupling matrix, which represents the distribution and conversion relationship between the energy hub input and output, P i , L j , C ij are the elements of the corresponding vector or matrix; i and j are the number of rows and columns respectively.

[0046] Preferably, the carbon flow rate determination unit calculates the carbon flow rates of different energy flows according to the energy flow-carbon emission flow coupled transfer model, including:

[0047] R=ρP, that is

[0048] Among them, R is the carbon flow rate; ρ is the carbon flow density matrix of energy carbon flow, which represents the carbon flow density of different energy consumption nodes; P is the column vector of the usage of a given energy.

[0049] Preferably, the energy indirect carbon emissions determination unit calculates the energy indirect carbon emissions of different carbon sources of the user or enterprise according to the carbon flow rate and energy efficiency, including:

[0050]

[0051] Among them, F is the indirect carbon emissions from energy use; R is the carbon flow rate of energy carbon flow, dt is the time vector, and the formula shows that carbon emissions are the integral of the carbon flow rate within a given time.

[0052] The present invention provides a multi-carbon source fusion metering method and system, including: data collection based on a collection terminal device to obtain energy consumption and job grade carbon emission measurement data of users or enterprises; normalization of energy consumption and job grade carbon emission measurement data based on an energy hub model according to the type of energy-consuming equipment; building a multi-energy coupling model based on an energy hub according to the spatial coupling relationship and temporal coupling relationship of different energy-consuming equipment, and calculating the energy efficiency of different energy sources according to the multi-energy coupling model; building an energy flow-carbon emission flow coupling transfer model based on the energy system carbon flow theory according to the multi-energy system carbon flow theory, and calculating the carbon flow rate of different energy flows according to the energy flow-carbon emission flow coupling transfer model; calculating the indirect carbon emissions of different carbon sources of users or enterprises according to the carbon flow rate and energy efficiency. The present invention can accurately measure the direct or indirect carbon emissions of multiple energy sources in the energy consumption scenario of industrial parks, and provide data support for the low-carbon transformation of park energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0054] Figure 1 is a flow chart of a multi-carbon source fusion metering method 100 according to an embodiment of the present invention;

[0055] Figure 2 A schematic diagram of the coupling relationship between energy flow and carbon emission flow in a heat network according to an embodiment of the present invention;

[0056] Figure 3 Schematic diagram of the structure of a multi-carbon source fusion metering system 300 according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0058] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0059] Figure 1 1 is a flow chart of a multi-carbon source fusion metering method 100 according to an embodiment of the present invention. Figure 1 As shown, the multi-carbon source fusion metering method provided by the embodiment of the present invention can accurately measure the direct or indirect carbon emissions of various energy sources in the energy consumption scenarios of industrial parks, and provide data support for the low-carbon transformation of energy consumption in the park.

[0060] The multi-carbon source fusion metering method 100 provided in the embodiment of the present invention starts from step 101. In step 101, data collection is performed based on a collection terminal device to obtain energy consumption and job-level carbon emission measurement data of users or enterprises.

[0061] Preferably, the data collection terminal equipment includes: an electric meter installed in the electricity consumption part and a carbon emission collection device and an energy consumption collection device installed in the electricity and heat consumption parts; the collected data include: carbon dioxide volume fraction, flue gas flow, flue gas temperature, flue gas pressure, flue gas moisture content, electricity consumption, natural gas consumption and heating consumption.

[0062] In the present invention, the energy users are equipped with terminal equipment for data collection, including: installing an electric meter in the electricity consumption part, and installing a carbon emission collection device and an energy consumption collection device in the gas and heat consumption parts. The collected parameters include: carbon dioxide volume fraction, flue gas flow, flue gas temperature, flue gas pressure, flue gas moisture content, electricity consumption, natural gas consumption, heating consumption, etc.

[0063] Data acquisition is performed through a data acquisition system. The data acquisition system includes: a voltage sampling module, which is connected to the acquisition terminal device and is used to acquire the voltage signal acquired by the terminal device; a current sampling module, which is connected to the acquisition terminal device and is used to acquire the current signal acquired by the terminal device; an amplification unit, which is respectively connected to the voltage sampling module and the current sampling module and is used to amplify the voltage and current signals acquired by the voltage sampling module and the current sampling module; an A / D conversion unit, which is connected to the amplification unit and is used to perform analog-to-digital conversion on the amplified signal; a processing unit, which is connected to the A / D conversion unit and is used to process the analog-to-digital converted signal. The external interface includes a 485 interface, an RJ45 interface, and a CAN bus interface, which is convenient for centralized collection of data from user energy consumption and direct carbon emission collection equipment.

[0064] In the present invention, the collected data is processed into a digital model, a data model is constructed, and the data is pushed to a data center service for data storage through the MQTT communication service in the device.

[0065] In step 102, the energy consumption and carbon emission measurement data are normalized based on the energy hub model according to the type of energy-consuming equipment.

[0066] Preferably, during the normalization process,

[0067] For a single-input-single-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is:

[0068]

[0069] in, and are the carbon flow density at the input port and the carbon flow density at the output port of the energy conversion device respectively; V i I and are the input energy flow and the output energy flow respectively; η I is the relationship between the output energy flow and the input energy flow of the device;

[0070] For a single-input-multiple-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is:

[0071]

[0072] in, and represent the carbon flow density at the electrical output port and the carbon flow density at the thermal output port respectively; is the carbon flow density at the input port; η Wis the power conversion efficiency; η Q is the thermal energy conversion efficiency; ∈ is the thermal energy coefficient.

[0073] In the present invention, a carbon emission source model of a typical industrial park is constructed based on the carbon emission modeling of multiple types of energy conversion equipment. According to the number of input ports and output ports, the energy conversion equipment in the industrial park can be divided into two categories: single-input-single-output equipment and single-input-multiple-output equipment. The carbon emissions of the two types of equipment are modeled.

[0074] (1) Single-input-single-output conversion equipment

[0075] For energy conversion equipment, there is no carbon emission injection other than input or carbon emission outflow other than output during operation. Therefore, according to the conservation of carbon emissions, the carbon emission corresponding to the input energy is equal to the carbon emission corresponding to the output energy, so:

[0076]

[0077] In the formula, and are the carbon flow density at the input port and the carbon flow density at the output port of energy conversion device I (I = EB, AB, CERG, WARG, etc.), V i I and are the input energy flow and the output energy flow respectively.

[0078] The relationship between the output energy flow and the input energy flow of a device can be expressed by the efficiency η I Indicates that:

[0079]

[0080] According to the above formula, the relationship between the carbon flow density at the input port and the carbon flow density at the output port of the single-input-single-output energy conversion device can be obtained as shown in the following formula:

[0081]

[0082] (2) Single-input-multiple-output conversion equipment

[0083] The power conversion efficiency η can be defined separately W and thermal energy conversion efficiency η Q , so that the output and output are:

[0084]

[0085] Where V i CHP Indicates the energy value of the input natural gas, and They are electrical output and thermal output respectively.

[0086] For this type of equipment, the carbon emission conservation law shows that the carbon emission at the input port is equal to the sum of the carbon emission at the output port, so:

[0087]

[0088] In the formula, and They represent the carbon flow density at the input port, the carbon flow density at the electrical output port, and the carbon flow density at the thermal output port, respectively.

[0089] The total input carbon emissions need to be allocated among multiple output ports. Since the carbon emission flow is virtual, this allocation method is not unique. The analysis method shows that the carbon emissions of different output ports should be consistent with the output ports. is proportional, then:

[0090]

[0091] Where ∈ is the thermal energy coefficient.

[0092] Combining the above formula, the relationship between the carbon flow density of the input port and the output port can be obtained (divided into electrical and thermal parts):

[0093]

[0094] In step 103, a multi-energy coupling model based on an energy hub is constructed according to the spatial coupling relationship and the temporal coupling relationship of different energy-consuming devices, and the energy efficiency of different energy sources is calculated according to the multi-energy coupling model.

[0095] Preferably, the multi-energy coupling model based on the energy hub is constructed according to the spatial coupling relationship and the temporal coupling relationship of different energy-consuming devices, including:

[0096] L=CP, that is

[0097] Among them, P is the energy hub input column vector; L is the energy hub output column vector; C is the coupling matrix, which represents the distribution and conversion relationship between the energy hub input and output, P i , L j , C ij are the elements of the corresponding vector or matrix; i and j are the number of rows and columns respectively.

[0098] In the present invention, the energy hub can be regarded as a two-port network. The energy input into the energy hub in various forms such as electricity and natural gas is converted and stored in the system to obtain the output (such as electricity, heat, and cold). The functional relationship between the input and output can be expressed as:

[0099] L=CP

[0100] Right now:

[0101]

[0102] Where P is the energy hub input column vector; L is the energy hub output column vector; C is the coupling matrix, which represents the distribution and conversion relationship between the energy hub input and output. i , L j , C ij are the elements of the corresponding vector or matrix; i and j are the number of rows and columns respectively.

[0103] Energy storage units realize energy transfer across time periods and coordinate the imbalance between "source and load" in the grid. They have the functions of shaving peaks and filling valleys and suppressing fluctuations in renewable energy, thus promoting the economical and efficient operation of the energy supply system. Various forms of energy storage can ensure the progress of the energy conversion process. In addition to energy storage in the form of water pumps, batteries, flywheels, etc., thermal energy storage is also an important form of energy storage. Intrinsic storage methods to improve load controllability have now emerged, such as household appliance control strategies with thermal inertia. Taking a typical industrial park with two energy forms of electricity and gas as an example, the output is electricity demand and heat demand, which can be expressed in matrix form as follows:

[0104]

[0105] Where: η T is the transformer efficiency; is the CHP power generation efficiency; is the CHP heating efficiency; η GB is the heating efficiency of the gas boiler; υ is the natural gas distribution coefficient; η ES is the energy storage efficiency; η TS is the thermal energy storage efficiency; E e and E h They are electric and thermal energy storage, respectively, where distributed renewable energy generation is included in the energy hub input power P e middle.

[0106] In step 104, according to the carbon flow theory of multi-energy systems, an energy flow-carbon emission flow coupling transfer model based on the energy system carbon flow theory is constructed, and the carbon flow rates of different energy flows are calculated according to the energy flow-carbon emission flow coupling transfer model.

[0107] Preferably, the carbon flow rates of different energy flows are calculated according to the energy flow-carbon emission flow coupled transfer model, including:

[0108] R=ρP, that is

[0109] Among them, R is the carbon flow rate; ρ is the carbon flow density matrix of energy carbon flow, which represents the carbon flow density of different energy consumption nodes; P is the column vector of the usage of a given energy.

[0110] In step 105, the indirect carbon emissions of different carbon sources of the user or enterprise are calculated according to the carbon flow rate and energy efficiency.

[0111] Preferably, the calculation of the indirect carbon emissions of different carbon sources of a user or enterprise based on the carbon flow rate and energy efficiency includes:

[0112]

[0113] Among them, F is the indirect carbon emissions from energy use; R is the carbon flow rate of energy carbon flow, dt is the time vector, and the formula shows that carbon emissions are the integral of the carbon flow rate within a given time.

[0114] Figure 3 Schematic diagram of the structure of a multi-carbon source fusion metering system 300 according to an embodiment of the present invention. Figure 3 As shown, the multi-carbon source fusion metering system 300 provided in the embodiment of the present invention includes: a data acquisition unit 301, a data processing unit 302, an energy efficiency determination unit 303, a carbon flow rate determination unit 304 and an energy indirect carbon emission determination unit 305.

[0115] Preferably, the data collection unit 301 is used to collect data based on a collection terminal device to obtain energy consumption and job-level carbon emission measurement data of users or enterprises.

[0116] Preferably, the data collection terminal equipment includes: an electric meter installed in the electricity consumption part and a carbon emission collection device and an energy consumption collection device installed in the electricity and heat consumption parts; the collected data include: carbon dioxide volume fraction, flue gas flow, flue gas temperature, flue gas pressure, flue gas moisture content, electricity consumption, natural gas consumption and heating consumption.

[0117] Preferably, the data processing unit 302 is used to normalize the energy consumption and job-level carbon emission measurement data based on the energy hub model according to the type of energy-consuming equipment.

[0118] Preferably, the data processing unit 302, during the normalization process,

[0119] For a single-input-single-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is:

[0120]

[0121] in, and are the carbon flow density at the input port and the carbon flow density at the output port of the energy conversion device respectively; V i I and are the input energy flow and the output energy flow respectively; η I is the relationship between the output energy flow and the input energy flow of the device;

[0122] For a single-input-multiple-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is:

[0123]

[0124] in, and represent the carbon flow density at the electrical output port and the carbon flow density at the thermal output port respectively; is the carbon flow density at the input port; η W is the power conversion efficiency; η Q is the thermal energy conversion efficiency; ∈ is the thermal energy coefficient.

[0125] Preferably, the energy efficiency determination unit 303 is used to construct a multi-energy coupling model based on the energy hub according to the spatial coupling relationship and temporal coupling relationship of different energy-consuming devices, and calculate the energy efficiency of different energy sources according to the multi-energy coupling model.

[0126] Preferably, the energy efficiency determination unit 303 constructs a multi-energy coupling model based on the energy hub according to the spatial coupling relationship and the temporal coupling relationship of different energy-consuming devices, including:

[0127] L=CP, that is

[0128] Among them, P is the energy hub input column vector; L is the energy hub output column vector; C is the coupling matrix, which represents the distribution and conversion relationship between the energy hub input and output, P i , L j , C ij are the elements of the corresponding vector or matrix; i and j are the number of rows and columns respectively.

[0129] Preferably, the carbon flow rate determination unit 304 is used to construct an energy flow-carbon emission flow coupling transfer model based on the energy system carbon flow theory according to the multi-energy system carbon flow theory, and calculate the carbon flow rates of different energy flows according to the energy flow-carbon emission flow coupling transfer model.

[0130] Preferably, the carbon flow rate determination unit 304 calculates the carbon flow rates of different energy flows according to the energy flow-carbon emission flow coupled transfer model, including:

[0131] R=ρP, that is

[0132] Among them, R is the carbon flow rate; ρ is the carbon flow density matrix of energy carbon flow, which represents the carbon flow density of different energy consumption nodes; P is the column vector of the usage of a given energy.

[0133] Preferably, the energy indirect carbon emission determination unit 305 is used to calculate the energy indirect carbon emission of different carbon sources of the user or enterprise according to the carbon flow rate and energy efficiency.

[0134] Preferably, the energy indirect carbon emissions determination unit 305 calculates the energy indirect carbon emissions of different carbon sources of the user or enterprise according to the carbon flow rate and energy efficiency, including:

[0135]

[0136] Among them, F is the indirect carbon emissions from energy use; R is the carbon flow rate of energy carbon flow, dt is the time vector, and the formula shows that carbon emissions are the integral of the carbon flow rate within a given time.

[0137] The multi-carbon source fusion metering system 300 of the embodiment of the present invention corresponds to the multi-carbon source fusion metering method 100 of another embodiment of the present invention, and will not be described in detail herein.

[0138] The invention has been described above with reference to a few embodiments. However, it is readily apparent to a person skilled in the art that other embodiments than the ones disclosed above are equally within the scope of the invention, as defined by the appended patent claims.

[0139] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise therein. All references to "a / said / the [means, components, etc.]" are to be openly interpreted as at least one instance of said means, components, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not necessarily have to be performed in the exact order disclosed, unless explicitly stated otherwise.

[0140] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0141] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0142] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0143] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A multi-carbon source fusion metering method, characterized in that: The method comprises: Data collection is performed based on the terminal equipment to obtain the energy consumption and carbon emission measurement data of users or enterprises; According to the type of energy-consuming equipment, the energy consumption and job-level carbon emission measurement data are normalized based on the energy hub model; According to the spatial coupling relationship and temporal coupling relationship of different energy-consuming equipment, a multi-energy coupling model based on the energy hub is constructed, and the energy efficiency of different energy sources is calculated according to the multi-energy coupling model; According to the carbon flow theory of multi-energy system, an energy flow-carbon emission flow coupling transfer model based on the energy system carbon flow theory is constructed, and the carbon flow rate of different energy flows is calculated according to the energy flow-carbon emission flow coupling transfer model; Calculate the indirect carbon emissions from different carbon sources of users or enterprises based on carbon flow rate and energy efficiency.

2. The method according to claim 1, characterized in that The data collection terminal equipment includes: an electric meter installed in the electricity consumption part and a carbon emission collection device and an energy consumption collection device installed in the electricity and heat consumption parts; the collected data include: carbon dioxide volume fraction, flue gas flow, flue gas temperature, flue gas pressure, flue gas moisture content, electricity consumption, natural gas consumption and heating consumption.

3. The method according to claim 1, characterized in that During the normalization process, For a single-input-single-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is: in, and are the carbon flow density at the input port and the carbon flow density at the output port of the energy conversion device respectively; and are the input energy flow and the output energy flow respectively; η I is the relationship between the output energy flow and the input energy flow of the device; For a single-input-multiple-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is: in, and represent the carbon flow density at the electrical output port and the carbon flow density at the thermal output port respectively; is the carbon flow density at the input port; η W is the power conversion efficiency; η Q is the thermal energy conversion efficiency; ∈ is the thermal energy coefficient.

4. The method according to claim 1, characterized in that: According to the spatial coupling relationship and temporal coupling relationship of different energy-consuming devices, a multi-energy coupling model based on an energy hub is constructed, including: L=CP, that is Among them, P is the energy hub input column vector; L is the energy hub output column vector; C is the coupling matrix, which represents the distribution and conversion relationship between the energy hub input and output, P i , L j , C ij are the elements of the corresponding vector or matrix; i and j are the number of rows and columns respectively.

5. The method according to claim 1, characterized in that The carbon flow rates of different energy flows are calculated according to the energy flow-carbon emission flow coupled transfer model, including: R=ρP, that is Among them, R is the carbon flow rate; ρ is the carbon flow density matrix of energy carbon flow, which represents the carbon flow density of different energy consumption nodes; P is the column vector of the usage of a given energy.

6. The method according to claim 1, characterized in that The calculation of the indirect carbon emissions of different carbon sources of users or enterprises based on the carbon flow rate and energy efficiency includes: Among them, F is the indirect carbon emissions from energy use; R is the carbon flow rate of energy carbon flow, dt is the time vector, and the formula shows that carbon emissions are the integral of the carbon flow rate within a given time.

7. A multi-carbon source fusion metering system, characterized in that: The system comprises: A data collection unit is used to collect data based on a collection terminal device to obtain energy consumption and carbon emission measurement data of users or enterprises; A data processing unit, used for normalizing the energy consumption and carbon emission measurement data according to the type of energy-consuming equipment based on the energy hub model; An energy efficiency determination unit, used to construct a multi-energy coupling model based on an energy hub according to the spatial coupling relationship and temporal coupling relationship of different energy-consuming devices, and calculate the energy efficiency of different energy sources according to the multi-energy coupling model; A carbon flow rate determination unit is used to construct an energy flow-carbon emission flow coupling transfer model based on the energy system carbon flow theory according to the multi-energy system carbon flow theory, and calculate the carbon flow rates of different energy flows according to the energy flow-carbon emission flow coupling transfer model; The indirect carbon emissions from energy use determination unit is used to calculate the indirect carbon emissions from energy use of different carbon sources of users or enterprises based on carbon flow rate and energy efficiency.

8. The system according to claim 7, characterized in that The data collection terminal equipment includes: an electric meter installed in the electricity consumption part and a carbon emission collection device and an energy consumption collection device installed in the electricity and heat consumption parts; the collected data include: carbon dioxide volume fraction, flue gas flow, flue gas temperature, flue gas pressure, flue gas moisture content, electricity consumption, natural gas consumption and heating consumption.

9. The system according to claim 7, characterized in that The data processing unit, during the normalization process, For a single-input-single-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is: in, and are the carbon flow density at the input port and the carbon flow density at the output port of the energy conversion device respectively; V i I and are the input energy flow and the output energy flow respectively; η I is the relationship between the output energy flow and the input energy flow of the device; For a single-input-multiple-output conversion device, the relationship between the carbon flow density at the input port and the carbon flow density at the output port is: in, and represent the carbon flow density at the electrical output port and the carbon flow density at the thermal output port respectively; is the carbon flow density at the input port; η W is the power conversion efficiency; η Q is the thermal energy conversion efficiency; ∈ is the thermal energy coefficient.

10. The system according to claim 7, characterized in that The energy efficiency determination unit constructs a multi-energy coupling model based on the energy hub according to the spatial coupling relationship and the temporal coupling relationship of different energy-consuming devices, including: L=CP, that is Among them, P is the energy hub input column vector; L is the energy hub output column vector; C is the coupling matrix, which represents the distribution and conversion relationship between the energy hub input and output, P i , L j , C ij are the elements of the corresponding vector or matrix; i and j are the number of rows and columns respectively.

11. The system according to claim 7, characterized in that The carbon flow rate determination unit calculates the carbon flow rates of different energy flows according to the energy flow-carbon emission flow coupled transfer model, including: R=ρP, that is Among them, R is the carbon flow rate; ρ is the carbon flow density matrix of energy carbon flow, which represents the carbon flow density of different energy consumption nodes; P is the column vector of the usage of a given energy.

12. The system according to claim 7, characterized in that The energy indirect carbon emissions determination unit calculates the energy indirect carbon emissions of different carbon sources of users or enterprises according to the carbon flow rate and energy efficiency, including: Among them, F is the indirect carbon emissions from energy use; R is the carbon flow rate of energy carbon flow, dt is the time vector, and the formula shows that carbon emissions are the integral of the carbon flow rate within a given time.

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