CN115310877A

CN115310877A - Power generation side carbon emission metering method based on data blood relationship analysis

Info

Publication number: CN115310877A
Application number: CN202211237762.4A
Authority: CN
Inventors: 黄彦璐; 马溪原; 林振福; 周悦; 陈炎森; 周长城; 张子昊
Original assignee: Southern Power Grid Digital Grid Research Institute Co Ltd
Current assignee: Southern Power Grid Digital Grid Research Institute Co Ltd
Priority date: 2022-10-11
Filing date: 2022-10-11
Publication date: 2022-11-08
Anticipated expiration: 2042-10-11
Also published as: CN115310877B

Abstract

The application relates to a power generation side carbon emission metering method based on data blood margin analysis. The method comprises the following steps: constructing a carbon emission determination model according to a carbon emission accounting theory and power grid data; calculating multi-source data according to an accounting data relation network, at least one data blood relationship and carbon emission in the carbon emission determination model to obtain a multi-source data traceability model; constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; establishing an area and power generation carbon emission relation identity, and obtaining a carbon emission factor correction model according to a unit power consumption carbon emission determination model and a power generation carbon emission relation identity; and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model. By adopting the method, the calculation accuracy and efficiency of the total carbon emission can be improved.

Description

Power generation side carbon emission metering method based on data blood relationship analysis

Technical Field

The application relates to the technical field of computers, in particular to a power generation side carbon emission metering method based on data blood relationship analysis.

Background

The treatment methods in the conventional art have significant drawbacks, respectively: (1) calculating standard extensive scale: the accounting basis relates to the parallel use of a plurality of sets of accounting rules. (2) discharge amount is difficult to calculate: the information of the power consumers is opaque, the carbon emission data of the power consumer layer is poor in acquireability, the fossil fuels consumed by the power generation of the target power generation object consume raw material quantity, the data collection difficulty is high, the data cannot be quantitatively calculated, and the carbon emission of the power consumers cannot be accurately mastered. (3) regional differentiation of carbon emission factor deficiency: carbon emission correction values are mostly adopted for carbon emission accounting of target power generation objects, the carbon emission correction values are lack of continuity, and the difference caused by the change of the carbon emission correction values and the accounting deviation caused by regional difference are ignored.

Disclosure of Invention

In view of the above, it is necessary to provide a method, an apparatus, a computer device, a computer readable storage medium, and a computer program product for measuring carbon emissions on a power generation side based on data blood-related analysis.

In a first aspect, the present application provides a method for power generation side carbon emission metering based on data blood margin analysis. The method comprises the following steps: according to a carbon emission accounting theory corresponding to a target power generation object and power grid data, constructing a carbon emission determination model aiming at the target power generation object; according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship and carbon emission accounting multi-source data corresponding to the target power generation object, obtaining a multi-source data tracing model corresponding to the target power generation object, wherein at least two carbon emission accounting multi-source data correspond to any one data blood relationship; constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; establishing a power generation carbon emission relation identity between an area and the target power generation object, and obtaining a carbon emission factor correction model according to a unit power consumption carbon emission determination model and the power generation carbon emission relation identity; and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model, wherein the target carbon emission metering model is used for determining the carbon emission of the target power generation object.

In a second aspect, the application further provides a power generation side carbon emission metering device based on data blood margin analysis. The device comprises: the carbon emission determination model building module is used for building a carbon emission determination model aiming at a target power generation object according to a carbon emission accounting theory corresponding to the target power generation object and power grid data; a multi-source data tracing model obtaining module, configured to obtain a multi-source data tracing model corresponding to the target power generation object according to an accounting data relationship network in the carbon emission determination model, at least one data blood relationship and carbon emission accounting multi-source data corresponding to the target power generation object, where at least two carbon emission accounting multi-source data correspond to any one data blood relationship; the unit power consumption carbon emission determination model obtaining module is used for constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; the carbon emission factor correction model obtaining module is used for constructing a power generation carbon emission relation identity equation of an area and the target power generation object, and obtaining a carbon emission factor correction model according to the unit power consumption carbon emission determination model and the power generation carbon emission relation identity equation; and the target carbon emission measurement model obtaining module is used for correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission measurement model, and the target carbon emission measurement model is used for determining the carbon emission of the target power generation object.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program: according to a carbon emission accounting theory corresponding to a target power generation object and power grid data, constructing a carbon emission determination model aiming at the target power generation object; according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship and carbon emission accounting multi-source data corresponding to the target power generation object, obtaining a multi-source data tracing model corresponding to the target power generation object, wherein at least two carbon emission accounting multi-source data correspond to any one data blood relationship; constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; establishing a power generation carbon emission relation identity between an area and the target power generation object, and obtaining a carbon emission factor correction model according to the unit power consumption carbon emission determination model and the power generation carbon emission relation identity; and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model, wherein the target carbon emission metering model is used for determining the carbon emission of the target power generation object.

In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of: according to a carbon emission accounting theory corresponding to a target power generation object and power grid data, constructing a carbon emission determination model aiming at the target power generation object; according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship and carbon emission accounting multi-source data corresponding to the target power generation object, obtaining a multi-source data tracing model corresponding to the target power generation object, wherein at least two carbon emission accounting multi-source data correspond to any one data blood relationship; constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; establishing a power generation carbon emission relation identity between an area and the target power generation object, and obtaining a carbon emission factor correction model according to a unit power consumption carbon emission determination model and the power generation carbon emission relation identity; and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model, wherein the target carbon emission metering model is used for determining the carbon emission of the target power generation object.

In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of: according to a carbon emission accounting theory corresponding to a target power generation object and power grid data, constructing a carbon emission determination model aiming at the target power generation object; according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship and carbon emission accounting multi-source data corresponding to the target power generation object, obtaining a multi-source data tracing model corresponding to the target power generation object, wherein at least two carbon emission accounting multi-source data correspond to any one data blood relationship; constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; establishing a power generation carbon emission relation identity between an area and the target power generation object, and obtaining a carbon emission factor correction model according to the unit power consumption carbon emission determination model and the power generation carbon emission relation identity; and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model, wherein the target carbon emission metering model is used for determining the carbon emission of the target power generation object.

According to the power generation side carbon emission metering method, the device, the computer equipment, the storage medium and the computer program product based on the data blood relationship analysis, a carbon emission determination model for a target power generation object is constructed according to a carbon emission accounting theory corresponding to the target power generation object and power grid data; according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship corresponding to the target power generation object and carbon emission accounting multi-source data, a multi-source data tracing model corresponding to the target power generation object is obtained, wherein at least one carbon emission accounting multi-source data corresponds to any one data blood relationship; constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; establishing a power generation carbon emission relation identity between an area and a target power generation object, and obtaining a carbon emission factor correction model according to a unit power consumption carbon emission determination model and the power generation carbon emission relation identity; and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model, wherein the target carbon emission metering model is used for determining the carbon emission of the target power generation object.

The data relationship between a target power generation object side and a user side is cleared up through the data blood relationship, external and internal emission coefficients and other data are fused, a data blood relationship network for carbon emission accounting of the target power generation object is constructed, information hidden in multi-source data is prevented from being ignored, a novel power generation enterprise accounting guide is combined, a replacement accounting method based on power grid data is combed, local and continuous calculation is carried out on carbon emission factors of fossil fuel and power utilization carbon emission factors of power generation, a target carbon emission metering model based on the carbon emission factors and used for metering carbon emission of the target power generation object is constructed, and the accuracy and efficiency of calculation of the total carbon emission of the target power generation object are improved.

Drawings

FIG. 1 is a diagram of an embodiment of an application environment of a method for measuring carbon emissions on a power generation side based on data blood-related analysis;

FIG. 2 is a schematic flow chart illustrating a method for measuring carbon emissions on the power generation side based on data blood-based analysis according to an embodiment;

FIG. 3 is a schematic flow chart diagram illustrating a method for obtaining a multi-source data traceability model in one embodiment;

FIG. 4 is a flowchart illustrating a method for obtaining correspondences between data blooding relationships, under an embodiment;

FIG. 5 is a schematic flow chart diagram illustrating a method for obtaining a carbon emissions determination model for a unit electricity usage in one embodiment;

FIG. 6 is a schematic flow chart diagram illustrating a method for obtaining a carbon emission factor correction model in one embodiment;

FIG. 7 is a schematic flow chart diagram of a method for obtaining a carbon emissions determination model in one embodiment;

FIG. 8 is a logic diagram of a method for implementing a power generation side carbon emissions metering based on data blood margin analysis in one embodiment;

FIG. 9 is a block diagram of a power generation side carbon emission metering device based on data blood margin analysis in one embodiment;

FIG. 10 is a diagram showing an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The method for measuring carbon emission on the power generation side based on data blood margin analysis can be applied to the application environment shown in fig. 1. The terminal 102 acquires data, the server 104 receives the data of the terminal 102 in response to an instruction of the terminal 102 and performs calculation on the acquired data, and the server 104 transmits the calculation result of the data back to the terminal 102 and is displayed by the terminal 102. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104, or may be located on the cloud or other network server. The server 104 constructs a carbon emission determination model for the target power generation object according to the carbon emission accounting theory corresponding to the target power generation object and the power grid data; according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship corresponding to a target power generation object and carbon emission accounting multi-source data, obtaining a multi-source data traceability model corresponding to the target power generation object, wherein at least one carbon emission accounting multi-source data corresponds to any one data blood relationship; constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; establishing a power generation carbon emission relation identity between an area and a target power generation object, and obtaining a carbon emission factor correction model according to a unit power consumption carbon emission determination model and the power generation carbon emission relation identity; and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model, wherein the target carbon emission metering model is used for determining the carbon emission of the target power generation object. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart car-mounted devices, and the like. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, and the like. The server 104 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.

In one embodiment, as shown in fig. 2, a method for measuring carbon emissions on the power generation side based on data blood-related analysis is provided, which is described by taking the method as an example applied to the server in fig. 1, and includes the following steps:

step 202, constructing a carbon emission determination model aiming at the target power generation object according to the carbon emission accounting theory corresponding to the target power generation object and the power grid data.

The target power generation object may be a power station, a power supply unit, or a department that allocates power resources, and the allocation may be performed based on input or output of power resources in any fixed area.

The carbon emission accounting theory can be a carbon emission accounting method of a target power generation object aiming at greenhouse gases, and main parameters in the method are carbon emission of the target power generation object, carbon dioxide emission of fossil fuel combustion and emission of net input used power.

The grid data may be grid data required by a carbon emission accounting theory, and mainly includes carbon emission of a target power generation object, carbon dioxide emission of fossil fuel combustion, and emission generated by net input of used power, and may also include data such as a standard coal conversion coefficient of fossil fuel, a power supply unit map, and standard coal consumption according to business requirements.

The carbon emission determination model can be obtained by improving a carbon emission accounting method of a target power generation object aiming at greenhouse gases according to actual requirements according to power grid data, and parameters of the model can be modified in real time according to the actual requirements so as to improve the accuracy of calculation.

Specifically, a carbon emission determination model for a target power generation object is constructed based on a power generation enterprise greenhouse gas carbon emission accounting method and power grid data, wherein the construction process is divided into the following three steps.

The first step is as follows: regarding the fossil fuel consumption, the calculation is replaced by the standard coal consumption of the unit power generation amount of regional carbon emission corresponding to the target power generation object, and the various fossil fuel consumption is converted by conversion coefficients of the standard coal and the fossil fuel low calorific value. And (3) obtaining a fossil fuel carbon emission accounting formula by adopting conversion of an international steam meter card:

the FDL is the total power generation amount of the target power generation object, and the SCC is the standard coal consumption amount converted from the power generation of the target power generation object in the provincial unit. 29307.6 is the standard coal Low (level) calorific value, CCSC _i Conversion coefficient of low calorific value standard coal of unit power generation type fossil fuel, gamma _i And the standard coal conversion coefficient is used as a correction factor. EF _i Are the i fuel calorific value emission factors.

And secondly, constructing a fossil fuel carbon emission substitution formula by using the meter electricity consumption and the regional unit electricity carbon emission corresponding to the target power generation object based on the net input power emission accounting formula corresponding to the target power generation object:

wherein JFDL is the electricity consumption, EC, of the meter corresponding to the target power generation object _i The carbon emission of local power generation is in balance relation with the carbon emission of power generation input from the outside of the area minus the carbon emission of power generation outside the output area and the carbon emission of power consumption of local community, wherein the relation is as follows:

wherein, EC _i Carbon emissions per unit of electricity consumption for area i, C _{Direct connection} For direct power generation of side carbon row, C _{Input device} Carbon emission as an input external charge, C _{Output of} Carbon emission as an output area external electric quantity, E _i Is the total social power usage for area i.

Thirdly, establishing an expression corresponding to the carbon emission accounting method of the target power generation object for the greenhouse gas according to the carbon emission accounting theory:

wherein C is the carbon emission of the target power generation target, E _{Burning of} Carbon dioxide emissions for fossil fuel combustion, E _{Electric power} The electrical power generated emissions are used for the net input.

Wherein, the carbon dioxide emission accounting formula of the fossil fuel combustion of the target power generation object is as follows:

wherein E is _{Burning of} Fossil fuel fired carbon emissions, AD, targeted power generation targets _i Activity level calorific value of various fuels for target power generation object, i is type of fossil fuel, EF _i Is the emission factor of the ith fossil fuel. Wherein, AD _i Comprises the following steps:

wherein, AD _i Activity level for ith fossil fuel, FC _i Consumption of the ith fossil Fuel, NCV _i Is the average lower calorific value of the ith fossil fuel.

According to the carbon emission accounting theory, the net input uses the emission accounting formula of electricity generation as:

wherein, AD _{Electric power} For net input of electricity, EF, to the power generation enterprise _{Electric power} And the carbon emission is regional power grid carbon emission.

And after correcting the carbon emission accounting theory, substituting the carbon emission accounting formula determined in the first step and the carbon emission substitution formula determined in the second step by using corresponding power grid data to obtain a carbon emission determination model for the target power generation object.

And 204, calculating the multi-source data tracing model corresponding to the target power generation object according to the accounting data relation network in the carbon emission determination model, at least one data blood relationship corresponding to the target power generation object and the carbon emission accounting multi-source data.

The accounting data relation network can be a network formed by relations among all power grid data in the target power generation object.

The data blood relationship can be a relationship similar to human social blood relationship formed among data in the process of generating, processing, transferring to extinction and the like of the power grid data of the target power generation object.

The carbon emission accounting multi-source data may be data sets of different sources corresponding to quantities related to carbon emission calculated when the target power generation object generates power.

The multivariate data traceability model can be a model for tracing the carbon emission accounting basic calculation indexes of the target power generation object based on the data blood relationship.

Specifically, the first step: and (3) determining a model according to the carbon emission of the target power generation object, and combing an accounting data index basis, wherein the accounting data index basis comprises a fossil fuel carbon emission factor, power generation amount of each power type, external input electric quantity of the target power generation object and unit power consumption carbon emission. And tracing the carbon emission accounting basic calculation indexes of the target power generation object based on the data blood relationship, and constructing an accounting data relationship network in the carbon emission determination model. Wherein, the data blood relationship corresponding to the checking data relationship network is respectively as follows: the carbon emission factor data consanguinity relationship of fossil fuel, the generated energy data consanguinity relationship of each power supply type, the data consanguinity relationship of external input electric quantity of a power plant and the data consanguinity relationship of carbon emission factor data of unit electricity consumption.

The carbon emission accounting multi-source data corresponding to the data blood relationship mainly comprises the following steps: (1) source: power plant information: acquiring the name of a power plant, the serial number of the power plant, the serial number of a power consumption client, the type of a power supply and the region of the power plant; (2) source: power type code mapping: acquiring a corresponding power type name through a power type code; (3) source: standard coal conversion coefficient of fossil fuel: the low-level heating default value of the fossil fuel and the low-level value of the fossil fuel are converted into a standard coal coefficient; (4) source: power supply unit mapping: acquiring names of areas such as power plant information, electricity purchasing information, electricity utilization information and electricity generation information through the power supply unit codes; (5) source: and electricity purchasing information: the method comprises the following steps that power generation of a power plant (according to the overall balance characteristic of power supply and demand of a power grid, the power generation of the power plant is equal to the total power input by a power grid company from the power plant), electric power outside an input area (the area of the power plant for which the input power of the power grid company is obtained through the power plant number, and the area of the power grid company is not equal to the area of the power plant for which the input power belongs is the electric power outside the input area), and electric power outside an output area (the area of the power plant for which the input power of the power grid company is obtained through the power plant number, and the area of the power plant does not accord with the area of the power grid company for which the input power is the electric power outside the output area); (6) source: standard coal consumption: the consumption of standard coal for power generation of each province; (7) source: generating capacity: the total generated energy, the generated energy of each power type and the firepower generated energy account for the ratio; (8) source: the relation between the metering point number and the user number is as follows: acquiring the serial number of the power plant meter through the serial number of the power plant information user; (9) source: electric charge information: the power consumption (the sum of all the user charging electric quantity) of the whole society and the external input electric quantity of the power plant.

The second step is that: establishing a carbon emission factor data consanguinity relation of fossil fuels, and a source: power plant information → source: power type code map → source: standard coal conversion coefficient for fossil fuel → consumption of carbon emission factor for fossil fuel.

The third step: establishing a blood relationship of generated energy data of each power supply type, wherein the source is as follows: power plant information → source: power type code map → source: purchase power information → power type i generated carbon displacement.

The fourth step: establishing a blood relationship of external input electric quantity data of the power plant, source: power plant information → source number of metering point and user relationship number → source: electric charge information → electric quantity purchased outside the power plant.

The fifth step: establishing a unit electricity and carbon emission factor data blood relationship, and obtaining: power supply unit map → source: power purchase information + source: standard coal consumption + source: generated energy + source: power plant information + source: metering point and user relationship number relationship + source: electricity consumption information → electric quantity purchased outside the area + electric quantity sold outside the area + electric quantity generated by each province + standard coal consumption of each province → unit electric generation standard coal consumption of the area i + standard coal consumption of the power plant → direct carbon emission of the area + carbon emission of the purchased electric quantity + carbon emission of the sold outside the area + total social electricity consumption → carbon emission factor of the unit electricity consumption.

And finally, combining the carbon emission factor data consanguinity relationship of the fossil fuel, the generated energy data consanguinity relationship of each power type, the data consanguinity relationship of the external input electric quantity of the power plant and the carbon emission factor data consanguinity relationship of the unit power consumption by using an accounting data relationship network in the carbon emission determination model to obtain a multi-source data traceability model corresponding to the target power generation object.

And step 206, constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model.

The network-to-network carbon emission accounting model can be a carbon emission accounting model of input and output electric quantity of each province between the power grid and the power grid.

The point-to-grid carbon emission accounting model can be a carbon emission accounting model of input and output electric quantity of the power grid to the power station.

The unit power consumption carbon emission determination model can be a model obtained by optimizing a unit power consumption carbon emission calculation method.

Specifically, based on the data blood relationship, local power generation at the power generation side is traced, the data index sources of power consumption data outside the output area, power outside the input area and power consumption data of the whole society are fused, carbon emission accounting multi-source data are fused, and a carbon emission accounting model (grid-to-grid carbon emission accounting model) of each province input and output electric quantity between the power grid and a carbon emission accounting model (point-to-grid carbon emission accounting model) of input and output electric quantity of the power grid to the power station exist in the power plant information of the power purchasing source purchasing the power outside the output area, and the unit power consumption carbon emission computing method is optimized.

The first step is as follows: constructing a formula corresponding to the unit power consumption carbon emission calculation method:

wherein, E _i The power consumption of the whole society of the area i; EC (EC) _i Direct emission of carbon dioxide generated for power generation in the geographical range covered by the area i; e _j,i Carbon emission generated by power generation which is net sent to the regional power grid i for the region j (carbon dioxide emission generated by power generation outside the input region); e _i,k Carbon emission generated by power generation which is sent to the region j for the region k (corresponding carbon dioxide emission generated by power generation outside the output region); c _i Carbon emissions due to power generation that are net sent from the region k to the region j (carbon dioxide emissions due to power generation outside the output region).

The second step is that: establishing a network-to-network carbon emission accounting model, and inputting the carbon emission outside the area, wherein the method comprises the following steps: net-to-net input and point-to-net input carbon emission, wherein the expression of the net-to-net carbon emission accounting model is as follows:

wherein E is _j1,i The electric quantity outside the network-to-network input area corresponds to the carbon dioxide emission; EP _j1,i Standard coal is consumed for power generation of a local grid j carbon emission power supply unit; RT (reverse transcription) _j The proportion of the thermal power generation capacity of the carbon emission power supply in the region j is determined; gamma is a standard carbon block coefficient, is obtained through actual measurement or empirical values, and adopts a national standard default value.

The third step: establishing a point-to-grid carbon emission accounting model, wherein the expression is as follows:

wherein E is _j2,i For corresponding CO to external electric quantity of point-to-network input area ₂ Discharge capacity; EP _j2,i And standard coal consumption is consumed for power generation of the power type unit of the delivery point.

For the calculation model of the carbon emission outside the output area, the expression is as follows:

wherein E is _k,i The electric quantity outside the output area corresponds to the carbon dioxide emission; EP _i The average value of the standard coal consumption for power generation of the regional i carbon emission power supply unit; RT (reverse transcription) _k The proportion of the thermal power generation capacity of the i-carbon emission power supply in the region is shown.

And finally, obtaining an optimized unit power consumption carbon emission determination model according to the network-to-network carbon emission accounting model established in the second step and the point-to-network carbon emission accounting model established in the third step and by combining a multi-source data traceability model.

And 208, constructing a power generation carbon emission relation identity between the region and the target power generation object, and obtaining a carbon emission factor correction model according to the unit power consumption carbon emission determination model and the power generation carbon emission relation identity.

The power generation carbon emission relationship identity may be an equation of a relationship between the carbon emission amount of the target power generation object and the power generation amount of each power supply type, among others.

Wherein the carbon emission factor correction model may be with a modified positive factor γ _i For correcting the model of the carbon emission determination model.

Specifically, a power generation carbon emission relation identity between the area and the target power generation object is constructed, and a carbon emission factor correction model for correcting the carbon emission determination model is obtained according to the unit power consumption carbon emission determination model and the power generation carbon emission relation identity. The method comprises the following specific steps:

the first step is as follows: and obtaining the generated carbon emission of the accounting area i based on the generated standard coal consumption, wherein the expression is as follows:

wherein E is _i The power generation carbon emission amount of the region i; c _i Standard coal consumption for zone i; gamma is a standard coal carbon emission coefficient, is obtained through actual measurement or empirical value, and adopts a national standard default value.

The second step is that: according to a fossil fuel consumption carbon emission metering model of a power generation enterprise:

constructing an identity relation between the carbon discharge capacity of the power generation side and the power generation capacity of each power type:

wherein FDL _ijk Power generation amount of power plant generation type j for i area k, EFR _ij The carbon emission per power generation type j for the region i.

The third step: based on monthly carbon emission of business demands, an OLS least square method is used for obtaining a fitting curve to carry out parameter estimation to obtain EFR of unit power generation carbon emission of which the power generation type of the region i is j _ij While the modification positive factor gamma can be obtained _i And obtaining the carbon emission factor correction model with the modified positive factor.

And step 210, correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model.

The target carbon emission measurement model may be a carbon emission determination model obtained by correcting the target carbon emission measurement model, and is used to determine the carbon emission amount of the target power generation target.

Specifically, the first step: determining a fossil fuel consumption carbon emission accounting formula corresponding to a target power generation object:

wherein, E _{Burning of} Fossil fuel elimination for generating target power generation objectCarbon consumption discharge, FDL _i The power generation amount of the power source type i, EFR, corresponding to the target power generation object _i The belonging area type corresponding to the target power generation object is i unit power generation carbon emission.

The second step is that: determining an externally purchased electric power carbon emission accounting formula of a target power generation object:

the third step: and (4) according to the carbon emission determination model, combining a fossil fuel consumption carbon emission accounting formula and an externally purchased electric power carbon emission accounting formula to obtain a target carbon emission metering model.

Wherein C' is the target carbon emission. The overall implementation logic is shown in fig. 8.

In the power generation side carbon emission metering method based on data blood relationship analysis, a carbon emission determination model for a target power generation object is constructed according to a carbon emission accounting theory corresponding to the target power generation object and power grid data; according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship corresponding to the target power generation object and carbon emission accounting multi-source data, a multi-source data tracing model corresponding to the target power generation object is obtained, wherein at least one carbon emission accounting multi-source data corresponds to any one data blood relationship; constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model; establishing a power generation carbon emission relation identity between an area and a target power generation object, and obtaining a carbon emission factor correction model according to a unit power consumption carbon emission determination model and the power generation carbon emission relation identity; and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model, wherein the target carbon emission metering model is used for determining the carbon emission of the target power generation object.

In one embodiment, as shown in fig. 3, obtaining a multi-source data tracing model corresponding to a target power generation object according to an accounting data relationship network in a carbon emission determination model, at least one data blood relationship corresponding to the target power generation object, and carbon emission accounting multi-source data, includes:

step 302, according to an accounting data relation network in the carbon emission determination model, determining a corresponding relation between at least one data blood relationship corresponding to the target power generation object and at least two carbon emission accounting multi-source data, and obtaining a multi-source data fusion corresponding relation corresponding to at least one target power generation object.

The multi-source data fusion corresponding relation can be a corresponding relation formed by any one data blood relationship and at least two carbon emission accounting multi-source data.

Specifically, the first step: and (3) determining a model according to the carbon emission of the target power generation object, and combing an accounting data index basis, wherein the accounting data index basis comprises fossil fuel carbon emission factors, power generation amount of each power type, external input electric quantity of the target power generation object and unit power consumption carbon emission. And tracing the carbon emission accounting basic calculation indexes of the target power generation object based on the data blood relationship, and constructing an accounting data relationship network in the carbon emission determination model. Wherein, the data blood relationship corresponding to the checking data relationship network is respectively as follows: the carbon emission factor data blood relationship of fossil fuel, the generated energy data blood relationship of each power supply type, the external input electric quantity data blood relationship of the power plant and the carbon emission factor data blood relationship of unit electricity consumption.

The carbon emission accounting multi-source data corresponding to the data blood relationship mainly comprises the following steps: (1) source: power plant information: acquiring the name of a power plant, the serial number of the power plant, the serial number of a power consumption client, the type of a power supply and the region of the power plant; (2) source: power type code mapping: acquiring a corresponding power type name through a power type code; (3) source: standard coal conversion coefficient of fossil fuel: the fossil fuel low-level heating default value and the fossil fuel low-level value are converted into the standard coal coefficient; (4) source: power supply unit mapping: acquiring the names of areas to which power plant information, electricity purchasing information, electricity utilization information, electricity generation information and the like belong through a power supply unit code; (5) source: and electricity purchasing information: the method comprises the following steps that power generation of a power plant (according to the overall balance characteristic of power supply and demand of a power grid, the power generation of the power plant is equal to the total power input by a power grid company from the power plant), electric power outside an input area (the area of the power plant for which the input power of the power grid company is obtained through the power plant number, and the area of the power grid company is not equal to the area of the power plant for which the input power belongs is the electric power outside the input area), and electric power outside an output area (the area of the power plant for which the input power of the power grid company is obtained through the power plant number, and the area of the power plant does not accord with the area of the power grid company for which the input power is the electric power outside the output area); (6) source: standard coal consumption: the consumption of standard coal for power generation of each province; (7) source: generating capacity: the total generated energy, the generated energy of each power type and the firepower generated energy account for the ratio; (8) source: the relation between the metering point number and the user number is as follows: acquiring the serial number of the power plant meter through the serial number of the power plant information user; (9) source: electricity charge information: the power consumption (the sum of all the user charging electric quantity) of the whole society and the external input electric quantity of the power plant.

The second step is that: establishing a fossil fuel carbon emission factor data consanguinity relationship (first corresponding relationship), source: power plant information → source: power type code map → source: standard coal conversion coefficient for fossil fuel → consumption of carbon emission factor for fossil fuel.

The third step: establishing a blood relationship (second corresponding relationship) of the generated energy data of each power supply type, wherein the source: power plant information → source: power type code map → source: purchase power information → power type i generated carbon emission.

The fourth step: establishing a blood relationship (third corresponding relationship) of the external input electric quantity data of the power plant, wherein the source is as follows: power plant information → source number of metering point and user relationship number → source: electric charge information → electric quantity purchased outside the power plant.

The fifth step: establishing a blood relationship (fourth corresponding relationship) of carbon emission factor data of unit electricity consumption, wherein the source comprises: power supply unit map → source: power purchase information + source: standard coal consumption + source: generated energy + source: power plant information + source: metering point and user relationship number relationship + source: electricity consumption information → electric quantity purchased outside the area + electric quantity sold outside the area + electric quantity generated by each province + standard coal consumption of each province → unit electric generation standard coal consumption of the area i + standard coal consumption of the power plant → direct carbon emission of the area + carbon emission of the purchased electric quantity + carbon emission of the sold outside the area + total social electricity consumption → carbon emission factor of the unit electricity consumption.

And 304, according to the multi-source data fusion corresponding relation corresponding to the target power generation object, obtaining a multi-source data traceability model corresponding to the target power generation object by using an accounting data relation network in the carbon emission determination model.

Specifically, a multi-source data traceability model corresponding to a target power generation object is obtained by combining a fossil fuel carbon emission factor data consanguinity relationship, a power generation amount data consanguinity relationship of each power type, a power plant external input electric quantity data consanguinity relationship and a unit power consumption carbon emission factor data consanguinity relationship by using an accounting data relationship network in a carbon emission determination model.

In this embodiment, the corresponding relationship between the data bloody margin relationship and the carbon emission accounting multisource data is further determined through the accounting data relationship network in the carbon emission determination model, and the multisource data traceability model is obtained by using the corresponding relationship and the relationship network, so that a reasonable corresponding relationship can be established according to the actual situation of the target power generation object, and an accurate calculation model is obtained.

In one embodiment, as shown in fig. 4, determining a corresponding relationship between at least one data blood relationship corresponding to a target power generation object and at least two carbon emission accounting multi-source data according to an accounting data relationship network in a carbon emission determination model to obtain a multi-source data fusion corresponding relationship corresponding to at least one target power generation object includes:

step 402, determining a first data blood relationship, a second data blood relationship, a third data blood relationship and a fourth data blood relationship according to an accounting data relationship network in the carbon emission determination model.

The first data blood relationship is a fossil fuel carbon emission factor data blood relationship, the second data blood relationship is a power generation amount data blood relationship of each power type, the third data blood relationship is a power plant external input electric quantity data blood relationship, and the fourth data blood relationship is a unit power carbon emission factor data blood relationship.

Specifically, according to a carbon emission determination model of a target power generation object, a data index basis is combed and calculated, wherein the data index basis comprises a fossil fuel carbon emission factor, power generation amount of each power supply type, external input electric quantity of the target power generation object and unit power consumption carbon emission. And tracing the carbon emission accounting basic calculation indexes of the target power generation object based on the data blood relationship, and constructing an accounting data relationship network in the carbon emission determination model. Wherein, the data blood relationship corresponding to the checking data relationship network is respectively as follows: the carbon emission factor data blood relationship of fossil fuel, the generated energy data blood relationship of each power supply type, the external input electric quantity data blood relationship of the power plant and the carbon emission factor data blood relationship of unit electricity consumption.

The carbon emission accounting multi-source data corresponding to the data blood relationship mainly comprises the following steps: (1) source: power plant information: acquiring the name of a power plant, the serial number of the power plant, the serial number of a power consumption client, the type of a power supply and the region of the power plant; (2) source: power type code mapping: acquiring a corresponding power type name through a power type code; (3) source: standard coal conversion coefficient of fossil fuel: the low-level heating default value of the fossil fuel and the low-level value of the fossil fuel are converted into a standard coal coefficient; (4) source: power supply unit mapping: acquiring names of areas such as power plant information, electricity purchasing information, electricity utilization information and electricity generation information through the power supply unit codes; (5) source: electricity purchasing information: the method comprises the following steps that power generation of a power plant (according to the overall balance characteristic of power supply and demand of a power grid, the power generation of the power plant is equal to the total power input by a power grid company from the power plant), electric power outside an input area (the area of the power plant for which the input power of the power grid company is obtained through the power plant number, and the area of the power grid company is not equal to the area of the power plant for which the input power belongs is the electric power outside the input area), and electric power outside an output area (the area of the power plant for which the input power of the power grid company is obtained through the power plant number, and the area of the power plant does not accord with the area of the power grid company for which the input power is the electric power outside the output area); (6) source: standard coal consumption: the consumption of standard coal for power generation of each province; (7) source: generating capacity: the total generated energy, the generated energy of each power type and the firepower generated energy account for the ratio; (8) source: the relation between the number of the metering point and the number of the user is as follows: acquiring the serial number of the power plant meter through the serial number of the power plant information user; (9) source: electric charge information: the power consumption (the sum of all the user charging electric quantity) of the whole society and the external input electric quantity of the power plant.

Step 404, according to the first data blood relationship, the second data blood relationship, the third data blood relationship and the fourth data blood relationship and the corresponding relationship between the at least two carbon emission check multi-source data, a first corresponding relationship corresponding to the first data blood relationship, a second corresponding relationship corresponding to the second data blood relationship, a third corresponding relationship corresponding to the third data blood relationship and a fourth corresponding relationship corresponding to the fourth data blood relationship are obtained.

Specifically, a fossil fuel carbon emission factor data blood-related relationship (first corresponding relationship) is established, and the source: power plant information → source: power type code map → source: standard coal conversion coefficient for fossil fuel → carbon emission factor consumed by fossil fuel.

Establishing a blood relationship (second corresponding relationship) of the generated energy data of each power supply type, wherein the source: power plant information → source: power type code map → source: purchase power information → power type i generated carbon emission.

Establishing a blood relationship (third corresponding relationship) of the external input electric quantity data of the power plant, wherein the source is as follows: power plant information → source, number of metering point and user relationship number → source: electric charge information → electric quantity purchased outside the power plant.

Establishing a blood relationship (fourth corresponding relationship) of carbon emission factor data of unit electricity consumption, wherein the source comprises: power supply unit map → source: power purchase information + source: standard coal consumption + source: generated energy + source: power plant information + source: metering point and user relationship numbering + source: electricity consumption information → electric quantity purchased outside the area + electric quantity sold outside the area + electric quantity generated by each province + standard coal consumption of each province → unit electric generation standard coal consumption of the area i + standard coal consumption of the power plant → direct carbon emission of the area + carbon emission of the purchased electric quantity + carbon emission of the sold outside the area + total social electricity consumption → carbon emission factor of the unit electricity consumption.

In the embodiment, the blood relationship of the plurality of data is determined through the accounting data relationship network in the carbon emission determination model, and the corresponding relationship between each blood relationship of the data and at least two carbon emission accounting multi-source data is established, so that the network and the relationship between each data in the target power generation object can be accurately positioned, the data relation degree is improved, and the accuracy is improved.

In one embodiment, as shown in fig. 5, constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model, and the point-to-network carbon emission accounting model, includes:

and 502, constructing a network-to-network carbon emission accounting model according to the network-to-network carbon dioxide emission, the network-to-network consumption standard coal quantity, the network-to-network thermal power generation capacity occupation ratio and the standard coal carbon emission coefficient.

The emission of the carbon dioxide from the grid to the grid can be the emission of the carbon dioxide between the grid and the power grid.

The grid-to-grid consumption standard coal quantity can be the consumption standard coal for the power generation of a carbon emission power supply unit between a power grid and the power grid.

The ratio of the thermal power generation of the grid to the grid can be the ratio of the thermal power generation of the carbon emission power supply between the grid and the grid.

The standard coal carbon emission coefficient can be obtained by actual measurement or experience value, and adopts a standard carbon emission coefficient of a national standard default value.

Specifically, a net-to-net carbon emission accounting model is established, and the carbon emission outside the input area comprises the following steps: net-to-net input and point-to-net input carbon emission, wherein the expression of the net-to-net carbon emission accounting model is as follows:

wherein E is _j1,i The electric quantity outside the network-to-network input area corresponds to the carbon dioxide emission; EP _j1,i Generating power consumption standard coal for a local grid j carbon emission power supply unit; RT (reverse transcription) _j The proportion of the thermal power generation capacity of the carbon emission power supply in the region j is determined; gamma is a standard carbon emission coefficient, is obtained through actual measurement or empirical value, and adopts a national standard default value.

And step 504, constructing a point-to-grid carbon emission accounting model according to the point-to-grid carbon dioxide emission, the point-to-grid consumption standard coal amount and the standard coal carbon emission coefficient.

The point-to-grid carbon dioxide emission can be carbon dioxide emission between a power grid and a power station.

The point-to-grid consumption standard coal quantity can be the consumption standard coal of the carbon emission power supply unit between the power grid and the power station for power generation.

Specifically, a point-to-network carbon emission accounting model is established, and the expression is as follows:

wherein E is _j2,i For corresponding CO to external electric quantity of point-to-network input area ₂ Discharge capacity; EP _j2,i And standard coal consumption is generated for the power supply type unit of the delivery point.

And step 506, constructing a calculation model of carbon emission outside the output area according to the output carbon dioxide emission, the average value of the consumed standard coal and the carbon emission coefficient of the standard coal.

Wherein the output carbon dioxide emission may be an output area carbon dioxide emission.

Wherein, the average value of the consumption standard coal can be the average value of the consumption standard coal of the regional carbon emission power unit for power generation.

The calculation model of the carbon emission outside the output area may be a calculation model for calculating the carbon emission corresponding to the electric energy output outside the specified area.

Specifically, for the calculation model of the carbon emission amount outside the output area, the expression is as follows:

wherein E is _k,i The electric quantity outside the output area corresponds to the carbon dioxide emission; EP _i The average value of the standard coal consumption for power generation of the regional i carbon emission power supply unit is obtained; RT (reverse transcription) _k The proportion of the thermal power generation capacity of the i-carbon emission power supply in the region is shown.

And step 508, obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model, the point-to-network carbon emission accounting model and the output area external carbon emission calculation model.

Specifically, a formula corresponding to the unit electricity consumption carbon emission calculation method is constructed:

wherein E is _i The power consumption of the whole society of the area i; EC (EC) _i Direct emission of carbon dioxide generated for power generation in the geographical range covered by the area i; e _j,i Carbon emission generated by power generation and net sent to the regional power grid i for the region j (corresponding carbon dioxide emission generated by power generation outside the input region); e _i,k Carbon emissions due to power generation that are net sent to the region j for the region k (corresponding carbon dioxide emissions due to power generation outside the output region); c _i Carbon emissions due to power generation that are net sent from the region k to the region j (carbon dioxide emissions due to power generation outside the output region).

And according to the established network-to-network carbon emission accounting model, the established network-to-network carbon emission accounting model and the multi-source data traceability model, obtaining an optimized unit power consumption carbon emission determination model.

In the embodiment, the unit power consumption carbon emission determination model is obtained by establishing the accounting model between different scenes and combining the multi-source data traceability model, so that the unit power consumption carbon emission determination model can pay attention to different factors in actual production, and the accuracy and efficiency of the model are improved.

In one embodiment, as shown in fig. 6, constructing a power generation carbon emission relationship identity between an area and a target power generation object, and obtaining a carbon emission factor correction model according to a unit power consumption carbon emission determination model and the power generation carbon emission relationship identity, includes:

step 602, according to a fossil fuel consumption carbon emission accounting formula in the carbon emission determination model, a power generation carbon emission relation identity between the region and the target power generation object is constructed.

The fossil fuel carbon emission accounting formula can be an accounting formula obtained by combining a fossil fuel carbon dioxide emission accounting formula and an international steam meter card conversion algorithm.

The power generation carbon emission relationship identity equation may be a relationship equation between the carbon emission amount of the target power generation object and the power generation amount of each power supply type.

Specifically, the power generation carbon emission amount of the accounting area i is obtained based on the power generation standard coal consumption amount, and the expression is as follows:

wherein FDL _ijk Generating capacity, EFR, of type j for i-zone k power plant _ij The carbon emission per power generation type j for the region i.

And step 604, obtaining a fitting curve corresponding to the generating carbon emission relation identity and the unit power consumption carbon emission determination model by using a least square method according to the generating carbon emission relation identity and the unit power consumption carbon emission determination model, and obtaining a carbon emission factor correction model.

Specifically, based on monthly carbon emission of business requirements, an OLS least square method is used for obtaining a fitting curve to carry out parameter estimation to obtain a unit power generation carbon emission EFR with the power generation type of the area i as j _ij While the modification positive factor gamma can be obtained _i And obtaining the carbon emission factor correction model with the modified positive factor.

In the embodiment, the carbon emission factor correction model with the correction positive factor is obtained by constructing the power generation carbon emission relationship identity between the area and the target power generation object, giving the identity and the unit power consumption carbon emission determination model, and fitting by using a least square model, and the carbon emission factor correction model can be modified aiming at the carbon emission determination model based on the actual situation, so that the modified model can calculate the carbon emission amount more accurately and more efficiently under the actual situation.

In one embodiment, as shown in fig. 7, constructing a carbon emission determination model for a target power generation object according to a carbon emission accounting theory corresponding to the target power generation object and power grid data includes:

and step 702, obtaining a fossil fuel carbon emission accounting formula according to a fossil fuel carbon dioxide emission accounting formula corresponding to the target power generation object and an international steam meter card conversion algorithm.

The fossil fuel carbon dioxide emission accounting formula can be an accounting formula obtained by substituting and calculating the consumption of regional carbon emission unit generated energy standard coal corresponding to a target power generation object, and performing conversion coefficient conversion on the consumption of various fossil fuels by using the standard coal and the lower heating value of the fossil fuel to obtain conversion coefficients.

The international steam meter card conversion algorithm can be a conversion table which is internationally used for calculating the relation between the steam and the resource consumption.

The fossil fuel carbon emission accounting formula can be an accounting formula obtained by combining a fossil fuel carbon dioxide emission accounting formula and an international steam meter conversion algorithm.

Specifically, for the fossil fuel consumption, the calculation is replaced by the standard coal consumption per unit of generated power output using regional carbon emissions corresponding to the target power generation object, and the various fossil fuel consumptions are converted by conversion coefficients using the standard coal and the lower calorific value of the fossil fuel (fossil fuel carbon dioxide emission accounting formula). And (3) obtaining a fossil fuel carbon emission accounting formula by adopting conversion of an international steam meter card:

the FDL is the total power generation amount of the target power generation object, and the SCC is the standard coal consumption amount converted from power generation of the target power generation object in a provincial unit. 29307.6 is the standard coal Low (level) calorific value, CCSC _i Conversion coefficient of low calorific value standard coal of unit power generation type fossil fuel, gamma _i And the standard coal conversion coefficient is used as a correction factor. EF _i I fuel calorific value emission factors.

And step 704, based on the net input power emission accounting formula corresponding to the target power generation object, correcting the table electricity consumption and the regional unit electricity consumption carbon emission amount corresponding to the target power generation object to obtain a fossil fuel carbon emission amount substitution formula.

The net input power emission accounting formula may be a carbon emission accounting formula corresponding to power input to the target power generation object in the carbon emission accounting theory.

The electricity consumption of the meter can be the measurement result of the meter or the meter on the electricity consumption, namely the meter reading corresponding to the electricity consumption.

The unit electricity carbon emission amount of the area may be a carbon emission amount corresponding to one unit of electricity usage amount in the specified area.

The fossil fuel carbon emission substitution formula may be a fossil fuel carbon emission calculation formula obtained by correcting the electricity consumption according to the meter corresponding to the target power generation object and the carbon emission of the electricity consumption in the regional unit.

Specifically, based on a net input power emission accounting formula corresponding to the target power generation object, a fossil fuel carbon emission substitution formula is constructed by using the meter electricity consumption and the regional unit electricity carbon emission corresponding to the target power generation object:

Step 706, correcting the carbon emission accounting theory by using a fossil fuel carbon emission accounting formula and a fossil fuel carbon emission substitution formula, and constructing a carbon emission determination model for the target power generation object based on the corrected carbon emission accounting theory and the power grid data.

Establishing an expression corresponding to a carbon emission accounting method of a target power generation object for greenhouse gases according to a carbon emission accounting theory:

In this embodiment, the carbon emission accounting theory is modified through the carbon dioxide accounting formula corresponding to the fossil fuel and the related power grid data, so that the calculation of the carbon emission caused by the carbon emission accounting theory on the fossil fuel better meets the actual requirement, the improved carbon emission determination model can meet the calculation of the carbon emission corresponding to the fossil fuel, and the subsequent model modification can enable the modified model to have higher accuracy.

It should be understood that, although the steps in the flowcharts related to the embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the application also provides a power generation side carbon emission metering device based on data blood margin analysis, which is used for realizing the power generation side carbon emission metering method based on data blood margin analysis. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so that specific limitations in one or more embodiments of the power generation-side carbon emission metering device based on data blood-level analysis provided below can be referred to the limitations in the power generation-side carbon emission metering method based on data blood-level analysis, and details are not repeated herein.

In one embodiment, as shown in fig. 9, there is provided a power generation side carbon emission metering device based on data blood margin analysis, including: the carbon emission determination model comprises a carbon emission determination model building module, a multi-source data traceability model obtaining module, a unit power consumption carbon emission determination model obtaining module, a carbon emission factor correction model obtaining module and a target carbon emission measurement model obtaining module, wherein:

the carbon emission determination model building module 902 is configured to build a carbon emission determination model for the target power generation object according to the carbon emission accounting theory corresponding to the target power generation object and the power grid data;

a multi-source data traceability model obtaining module 904, configured to obtain a multi-source data traceability model corresponding to the target power generation object according to the accounting data relationship network in the carbon emission determination model, the at least one data blood relationship corresponding to the target power generation object, and the carbon emission accounting multi-source data, where at least one carbon emission accounting multi-source data corresponds to any one data blood relationship;

a unit power consumption carbon emission determination model obtaining module 906, configured to construct a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtain a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model, and the point-to-network carbon emission accounting model;

a carbon emission factor correction model obtaining module 908, configured to construct a power generation carbon emission relationship identity between the region and the target power generation object, and obtain a carbon emission factor correction model according to a unit power consumption carbon emission determination model and the power generation carbon emission relationship identity;

and a target carbon emission measurement model obtaining module 910, configured to correct the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission measurement model, where the target carbon emission measurement model is used to determine the carbon emission of the target power generation object.

In one embodiment, the multi-source data traceability model obtaining module is configured to determine a corresponding relationship between at least one data blood relationship corresponding to the target power generation object and at least two carbon emission accounting multi-source data according to an accounting data relationship network in the carbon emission determination model, and obtain a multi-source data fusion corresponding relationship corresponding to the at least one target power generation object; and according to the multi-source data fusion corresponding relation corresponding to the target power generation object, obtaining a multi-source data traceability model corresponding to the target power generation object by using an accounting data relation network in the carbon emission determination model.

In one embodiment, the multi-source data traceability model obtaining module is used for determining a first data blood relationship, a second data blood relationship, a third data blood relationship and a fourth data blood relationship according to an accounting data relationship network in the carbon emission determination model; the first data blood relationship is a fossil fuel carbon emission factor data blood relationship, the second data blood relationship is a power generation amount data blood relationship of each power type, the third data blood relationship is a power plant external input electric quantity data blood relationship, and the fourth data blood relationship is a unit power carbon emission factor data blood relationship; obtaining a first corresponding relation corresponding to the first data blood relationship, a second corresponding relation corresponding to the second data blood relationship, a third corresponding relation corresponding to the third data blood relationship and a fourth corresponding relation corresponding to the fourth data blood relationship according to the corresponding relations between the first data blood relationship, the second data blood relationship, the third data blood relationship and the fourth data blood relationship and between the at least two carbon emission accounting multi-source data respectively; the first corresponding relation, the second corresponding relation, the third corresponding relation and the fourth corresponding relation are multi-source data fusion corresponding relations corresponding to the target power generation object.

In one embodiment, the unit power consumption carbon emission determination model obtaining module is used for constructing a grid-to-grid carbon emission accounting model according to the grid-to-grid carbon dioxide emission, the grid-to-grid consumption standard coal quantity, the grid-to-grid thermal power generation capacity occupation ratio and the standard coal carbon emission coefficient; constructing a point-to-grid carbon emission accounting model according to the point-to-grid carbon dioxide emission, the point-to-grid consumption standard coal quantity and the standard coal carbon emission coefficient; constructing a calculation model of carbon emission outside the output area according to the output carbon dioxide emission, the average value of the consumed standard coal and the carbon emission coefficient of the standard coal; and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model, the point-to-network carbon emission accounting model and the output area external carbon emission accounting model.

In one embodiment, the carbon emission factor correction model obtaining module is used for constructing a power generation carbon emission relation identity equation of the region and the target power generation object according to a fossil fuel consumption carbon emission accounting formula in the carbon emission determination model; according to the generating carbon emission relation identity and the unit power consumption carbon emission determination model, obtaining a fitting curve corresponding to the generating carbon emission relation identity and the unit power consumption carbon emission determination model by using a least square method to obtain a carbon emission factor correction model; and obtaining a carbon emission factor correction model with a modified positive factor based on the fitted curve.

In one embodiment, the carbon emission determination model construction module is used for obtaining a fossil fuel carbon emission accounting formula according to a fossil fuel carbon dioxide emission accounting formula and an international steam meter card conversion algorithm corresponding to a target power generation object; based on a net input power emission accounting formula corresponding to a target power generation object, correcting by using the meter electricity consumption and the regional unit electricity consumption carbon emission corresponding to the target power generation object to obtain a fossil fuel carbon emission substitution formula; and correcting the carbon emission accounting theory by using a fossil fuel carbon emission accounting formula and a fossil fuel carbon emission substitution formula, and constructing a carbon emission determination model aiming at a target power generation object based on the corrected carbon emission accounting theory and power grid data.

The modules in the power generation side carbon emission metering device based on data blood source analysis can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 10. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing server data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method for power generation side carbon emission metering based on data blood margin analysis.

Those skilled in the art will appreciate that the architecture shown in fig. 10 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, in which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

In one embodiment, a computer program product or computer program is provided that includes computer instructions stored in a computer readable storage medium. The computer instructions are read by a processor of a computer device from a computer-readable storage medium, and the computer instructions are executed by the processor to cause the computer device to perform the steps in the above-mentioned method embodiments.

It should be noted that, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), magnetic Random Access Memory (MRAM), ferroelectric Random Access Memory (FRAM), phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the various embodiments provided herein may be, without limitation, general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, or the like.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for measuring carbon emission on a power generation side based on data blood margin analysis, the method comprising:

according to a carbon emission accounting theory corresponding to a target power generation object and power grid data, constructing a carbon emission determination model aiming at the target power generation object;

according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship and carbon emission accounting multi-source data corresponding to the target power generation object, obtaining a multi-source data tracing model corresponding to the target power generation object, wherein at least two carbon emission accounting multi-source data correspond to any one data blood relationship;

constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model;

establishing a power generation carbon emission relation identity between an area and the target power generation object, and obtaining a carbon emission factor correction model according to the unit power consumption carbon emission determination model and the power generation carbon emission relation identity;

and correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission metering model, wherein the target carbon emission metering model is used for determining the carbon emission of the target power generation object.

2. The method according to claim 1, wherein the obtaining the multi-source data tracing model corresponding to the target power generation object according to the accounting data relationship network in the carbon emission determination model, the at least one data blood relationship corresponding to the target power generation object and the carbon emission accounting multi-source data comprises:

determining a corresponding relation between at least one data consanguinity relation corresponding to the target power generation object and at least two carbon emission accounting multi-source data according to the accounting data relation network in the carbon emission determination model to obtain a multi-source data fusion corresponding relation corresponding to at least one target power generation object;

and according to the multi-source data fusion corresponding relation corresponding to the target power generation object, obtaining a multi-source data traceability model corresponding to the target power generation object by using the accounting data relation network in the carbon emission determination model.

3. The method according to claim 2, wherein the determining a correspondence between at least one data consanguinity relationship corresponding to the target power generation object and at least two carbon emission accounting multi-source data according to the accounting data relationship network in the carbon emission determination model to obtain a multi-source data fusion correspondence corresponding to at least one target power generation object comprises:

determining a first data blood relationship, a second data blood relationship, a third data blood relationship and a fourth data blood relationship according to the accounting data relationship network in the carbon emission determination model; the first data blood relationship is a fossil fuel carbon emission factor data blood relationship, the second data blood relationship is a power generation amount data blood relationship of each power type, the third data blood relationship is a power plant external input electric quantity data blood relationship, and the fourth data blood relationship is a unit power carbon emission factor data blood relationship;

obtaining a first corresponding relation corresponding to the first data blood relationship, a second corresponding relation corresponding to the second data blood relationship, a third corresponding relation corresponding to the third data blood relationship and a fourth corresponding relation corresponding to the fourth data blood relationship according to the corresponding relations between the first data blood relationship, the second data blood relationship, the third data blood relationship and the fourth data blood relationship and between at least two carbon emission accounting multi-source data; the first corresponding relationship, the second corresponding relationship, the third corresponding relationship, and the fourth corresponding relationship are the multi-source data fusion corresponding relationship corresponding to the target power generation object.

4. The method of claim 1, wherein the constructing a net-to-net carbon emission accounting model and a point-to-net carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the net-to-net carbon emission accounting model and the point-to-net carbon emission accounting model comprises:

constructing a network-to-network carbon emission accounting model according to network-to-network carbon dioxide emission, network-to-network consumption standard coal quantity, network-to-network thermal power generation capacity occupation ratio and standard coal carbon emission coefficient;

constructing a point-to-network carbon emission accounting model according to the point-to-network carbon dioxide emission, the point-to-network consumption standard coal amount and the standard coal carbon emission coefficient;

constructing a calculation model of carbon emission outside the output area according to the output carbon dioxide emission, the average value of the consumed standard coal and the carbon emission coefficient of the standard coal;

and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model, the point-to-network carbon emission accounting model and the output area external carbon emission calculation model.

5. The method of claim 1, wherein constructing a carbon emission relationship identity between the area and the target power generation object, and obtaining a carbon emission factor correction model according to the carbon emission determination model for the unit power consumption and the carbon emission relationship identity, comprises:

according to a fossil fuel consumption carbon emission accounting formula in a carbon emission determination model, constructing a power generation carbon emission relation identity equation of the region and the target power generation object;

obtaining a fitting curve corresponding to the generating carbon emission relation identity and the unit power consumption carbon emission determination model by using a least square method according to the generating carbon emission relation identity and the unit power consumption carbon emission determination model to obtain the carbon emission factor correction model;

and obtaining the carbon emission factor correction model with a modified positive factor based on the fitted curve.

6. The method according to claim 1, wherein the constructing a carbon emission determination model for a target power generation object according to a carbon emission accounting theory corresponding to the target power generation object and power grid data comprises:

obtaining a fossil fuel carbon emission accounting formula according to a fossil fuel carbon dioxide emission accounting formula and an international steam meter card conversion algorithm corresponding to the target power generation object;

based on a net input power emission accounting formula corresponding to the target power generation object, correcting by using the meter electricity consumption and the regional unit electricity consumption carbon emission corresponding to the target power generation object to obtain a fossil fuel carbon emission substitution formula;

and correcting the carbon emission accounting theory by using the fossil fuel carbon emission accounting formula and the fossil fuel carbon emission substitution formula, and constructing the carbon emission determination model for the target power generation object based on the corrected carbon emission accounting theory and the power grid data.

7. A power generation side carbon emission metering device based on data blood margin analysis, the device comprising:

the carbon emission determination model building module is used for building a carbon emission determination model aiming at a target power generation object according to a carbon emission accounting theory corresponding to the target power generation object and power grid data;

the multi-source data traceability model obtaining module is used for obtaining a multi-source data traceability model corresponding to the target power generation object according to an accounting data relation network in the carbon emission determination model, at least one data blood relationship corresponding to the target power generation object and carbon emission accounting multi-source data, wherein at least two carbon emission accounting multi-source data correspond to any one data blood relationship;

the unit power consumption carbon emission determination model obtaining module is used for constructing a network-to-network carbon emission accounting model and a point-to-network carbon emission accounting model, and obtaining a unit power consumption carbon emission determination model according to the multi-source data traceability model, the network-to-network carbon emission accounting model and the point-to-network carbon emission accounting model;

the carbon emission factor correction model obtaining module is used for constructing a power generation carbon emission relation identity between an area and the target power generation object, and obtaining a carbon emission factor correction model according to the unit power consumption carbon emission determination model and the power generation carbon emission relation identity;

and the target carbon emission measurement model obtaining module is used for correcting the carbon emission determination model based on the carbon emission factor correction model to obtain a target carbon emission measurement model, and the target carbon emission measurement model is used for determining the carbon emission of the target power generation object.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.

9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 6 when executed by a processor.