Method and system for accurately calculating carbon emission of urban and rural resident living industry

Abstract

The embodiment of the invention provides a method and system for accurately calculating carbon emission of urban and rural resident living industry, and belongs to the technical field of power grid big data processing. The method comprises the following steps: acquiring power consumption in the living process of urban and rural residents; preprocessing the electricity consumption in the living process of the urban and rural residents to obtain the electricity consumption meeting the requirement; according to the power consumption meeting the requirement, constructing a model which calculates energy by using power and is based on an autoregressive distributed lag model; constructing a model for calculating a carbon factor by using electricity according to the electricity consumption meeting the requirement; determining hysteresis orders in the model of calculating energy by electricity and the model of calculating carbon factors by electricity through an AIC criterion so as to optimize the model of calculating energy by electricity and the model of calculating carbon factors by electricity; and obtaining the carbon emission of the urban and rural resident life industry according to the result obtained by the model of computerized energy and the result obtained by the model of computerized carbon factors. According to the method, the carbon emission of urban and rural resident living industries can be accurately calculated.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid big data processing, and in particular to a method and system for accurately calculating carbon emissions from urban and rural residents' daily lives. Background Art

[0002] The lifecycle carbon emissions of the residential sector consist of direct and indirect carbon emissions. Direct carbon emissions refer to the carbon emissions from direct energy consumption in residents' daily lives, including fuel consumption, electricity, and heat. Indirect carbon emissions refer to the carbon emissions implicit in the goods and services consumed by residents. Accurately calculating the carbon emissions of the residential sector is crucial for achieving these goals. Currently, the calculation of carbon emissions from the residential sector is primarily based on the IPCC carbon emissions accounting methodology, which states that carbon emissions equal the sum of the products of energy activities and corresponding carbon emission factors. Existing models for calculating carbon emissions from consumption in urban and rural residential sectors are incomplete and fail to accurately reflect carbon emissions from the residential sector. Therefore, a method and system for accurately calculating carbon emissions from the urban and rural residential sectors is needed. Summary of the Invention

[0003] The purpose of the embodiments of the present invention is to provide a method and system for accurately calculating carbon emissions from urban and rural residents' daily life. The method can accurately calculate carbon emissions from urban and rural residents' daily life.

[0004] To achieve the above objectives, an embodiment of the present invention provides a method for accurately calculating carbon emissions from urban and rural residents' daily lives, the method comprising:

[0005] Obtain electricity consumption in urban and rural residents' daily lives;

[0006] Pre-processing the electricity consumption of urban and rural residents in their daily lives to obtain electricity consumption that meets the requirements;

[0007] Constructing a model based on electric energy calculation using an autoregressive distributed lag model according to the electric consumption amount that meets the requirements;

[0008] Constructing a model for electrically calculating the carbon factor based on the electricity consumption that meets the requirements;

[0009] The lag order in the model based on the calculated energy and the model based on the calculated carbon factor is determined by the AIC criterion, thereby optimizing the model based on the calculated energy and the model based on the calculated carbon factor;

[0010] Based on the results obtained by the model using electrical energy calculation and the results obtained by the model using electrical carbon factor calculation, the carbon emissions of urban and rural residents' living industries are obtained.

[0011] Optionally, pre-processing the electricity consumption of the urban and rural residents in their daily lives to obtain the electricity consumption that meets the requirements includes:

[0012] Performing data cleaning on the electricity consumption to obtain available electricity consumption;

[0013] Detect abnormal data on available electricity consumption and make corrections based on actual conditions;

[0014] Perform a time series analysis on the corrected electricity consumption, and fill in the missing data to meet the electricity consumption requirement of formula (1):

[0015]

[0016] Among them, t is the time point, X t represents the data at time t in the modified electricity consumption time series data, X t-1 Represents the data of time t-1 in the modified electricity consumption time series, I t Represents the data at time t in the original electricity consumption time series data, I t-1 Represents the data at time t-1 in the original electricity consumption time series data.

[0017] Optionally, a model based on electrical energy calculation based on an autoregressive distributed lag model is constructed according to the electricity consumption that meets the requirements, including:

[0018] Obtain the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements:

[0019] The model for calculating fossil energy consumption is constructed using formula (2):

[0020]

[0021] Among them, y t,r represents the fossil energy consumption of residents’ daily life at time t, p r ,q r 、s r represents the lag order of the model for calculating fossil energy consumption, represents the regression coefficient of the dependent variable of the model based on the calculation of fossil energy consumption at the i-th order, y t-i,r represents the fossil energy consumption of residents’ daily life at time t and lag i, β i,r represents the regression coefficient of electricity consumption in the model of calculating fossil energy consumption at the i-th order, x t-i represents the electricity consumption at time t lag i, γ i,r represents the regression coefficient of urban and rural residents’ disposable income when fossil energy consumption is calculated at the i-th order, zt-i represents the disposable income of urban and rural residents at time t and lag i, a r represents the intercept of the model for calculating fossil energy consumption, u t,r Represents the random error term of the model that calculates fossil energy consumption by electricity.

[0022] Optionally, a model based on electrical energy calculation based on an autoregressive distributed lag model is constructed according to the electricity consumption that meets the requirements, including:

[0023] Obtain the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements;

[0024] The model for calculating heat consumption by electricity is constructed using formula (3):

[0025]

[0026] Among them, y t,h represents the heat consumption of residents’ daily life at time t, p h ,q h 、s h represents the lag order of the model for calculating heat consumption, The regression coefficient of the dependent variable of the model with calculated heat consumption at the i-th order, y t-i,h represents the heat consumption of residents’ daily life industry at time t lag i, β i,h The regression coefficient of electricity consumption in the model of calculating heat consumption by electricity at the i-th order, x t-i represents the electricity consumption at time t lag i, γ i,h represents the regression coefficient of disposable income of urban and rural residents when heat consumption is calculated by electricity at the i-th order, z t-i represents the disposable income of urban and rural residents at time t and lag i, a h The intercept of the model that calculates heat consumption by electricity, u t,h Represents the random error term of the model that calculates heat consumption using electricity.

[0027] Optionally, a model for calculating the carbon factor electrically is constructed based on the electricity consumption that meets the requirements, including:

[0028] Obtain the physical quantity of fossil energy consumption, the carbon emission factor of fossil energy, and the standard coal conversion factor of fossil energy;

[0029] The carbon factor of fossil energy in the residential sector is calculated using formula (4):

[0030]

[0031] Among them, y t,fThe carbon factor of fossil energy in the residents' daily life at time t, AC t,j represents the physical amount of the j-th fossil energy consumption at time t, EF j represents the carbon emission factor of the jth fossil energy, T j It represents the standard coal conversion factor of the j-th fossil energy.

[0032] Optionally, a model for calculating the carbon factor electrically is constructed based on the electricity consumption that meets the requirements, including:

[0033] Obtain the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements;

[0034] The model of the fossil energy carbon factor of the residential sector is constructed using formula (5):

[0035]

[0036] Among them, y t,f represents the fossil energy carbon factor of the residents' living industry at time t, p f ,q f 、s f The lag order of the model representing the fossil energy carbon factor, represents the regression coefficient of the dependent variable of the model of fossil energy carbon factor at the i-th order, y t-i,f represents the fossil energy carbon factor of the residents' living industry at time t and lag i, β i,f The regression coefficient of electricity consumption in the model with fossil energy carbon factor at the i-th order, x t-i represents the electricity consumption at time t lag i, γ i,f represents the regression coefficient of urban and rural residents’ disposable income when calculating the fossil energy carbon factor at the i-th order, z t-i represents the disposable income of urban and rural residents at time t and lag i, a f The model intercept of the model representing the fossil energy carbon factor, u t,f Random error term in the model representing the fossil energy carbon factor.

[0037] Optionally, based on the results obtained from the model using electrical energy calculations and the model using electrical carbon factor calculations, the carbon emissions of urban and rural residents' daily lives can be obtained, including:

[0038] Determine whether the life processes of the urban and rural residents require a large amount of winter heating;

[0039] When urban and rural residents do not need a lot of winter heating in their daily lives, the fossil energy consumption is obtained according to formula (2), the fossil energy carbon factor is obtained according to formula (4) or formula (5), and the carbon emissions of urban and rural residents' daily life are calculated using the IPCC carbon emission accounting method;

[0040] When urban and rural residents need a lot of winter heating in their daily lives, the fossil energy consumption is obtained according to formula (2), the heat consumption is obtained according to formula (3), the fossil energy carbon factor is obtained according to formula (4) or formula (5), and the carbon emissions of urban and rural residents' daily lives are obtained through the IPCC carbon emission accounting calculation method.

[0041] Optionally, the method includes:

[0042] Obtaining the fossil energy consumption and heat consumption of urban and rural residents' daily life;

[0043] The monthly values of fossil energy consumption and heat consumption are constructed using formula (6):

[0044]

[0045] Among them, y m,γ represents the monthly fossil energy consumption / heat consumption in month m, γ represents fossil energy / heat, x m represents the known electricity consumption of urban and rural residents, A represents the variance weight matrix between the electricity consumption of urban and rural residents and the monthly fossil energy consumption / heat consumption, c represents the set of months grouped by year and season, y c,γ Indicates the total consumption constraint of fossil energy consumption / heat consumption in the corresponding season.

[0046] On the other hand, the present invention also provides a system for accurately calculating carbon emissions from urban and rural residents' daily lives, the system comprising:

[0047] A data preprocessing module is used to obtain the electricity consumption of urban and rural residents in their daily lives and preprocess the electricity consumption;

[0048] The electricity calculation module is used to calculate fossil energy consumption based on electricity consumption and per capita disposable income of urban and rural residents;

[0049] The electricity-heat calculation module is used to calculate heat consumption based on electricity consumption and per capita disposable income of urban and rural residents;

[0050] The electric carbon factor module is used to calculate the carbon factor of fossil energy based on electricity consumption and per capita disposable income of urban and rural residents;

[0051] The result output module is used to calculate the carbon emissions of urban and rural residents' living industries based on the obtained fossil energy consumption, heat consumption and fossil energy carbon factor.

[0052] Optionally, the system includes:

[0053] Monthly split module, used to split the annual carbon emission results monthly according to the monthly electricity consumption;

[0054] The urban-rural difference calculation module calculates the carbon emissions of urban and rural residents based on the differences in electricity consumption and per capita disposable income between urban and rural areas.

[0055] Through the above technical solution, the present invention provides a method and system for accurately calculating carbon emissions from urban and rural residents' daily lives. By obtaining the electricity consumption of urban and rural residents during their daily lives, the electricity consumption during urban and rural residents' daily lives can be preprocessed to obtain an electricity consumption that meets the requirements. After obtaining the electricity consumption that meets the requirements, a model based on the autoregressive distributed lag model based on electricity-based energy can be constructed based on the electricity consumption that meets the requirements. A model based on the autoregressive distributed lag model based on electricity-based carbon factors can be constructed based on the electricity consumption that meets the requirements. The lag order in the model based on electricity-based energy and the model based on electricity-based carbon factors can be determined using the AIC criterion, thereby optimizing the model based on electricity-based energy and the model based on electricity-based carbon factors. After obtaining the results of the model based on electricity-based energy and the model based on electricity-based carbon factors, the carbon emissions of urban and rural residents' daily lives can be calculated according to the IPCC carbon emission accounting. This method can accurately calculate the carbon emissions of urban and rural residents' daily lives.

[0056] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0058] Figure 1 This is a flow chart of a method for accurately calculating carbon emissions from urban and rural residents' daily life according to one embodiment of the present invention;

[0059] Figure 2 This is a flowchart of a pre-processing method for accurately calculating carbon emissions from urban and rural residents' daily life according to one embodiment of the present invention;

[0060] Figure 3 It is a flowchart of obtaining carbon emissions from urban and rural residents' living industries according to a method for accurately calculating carbon emissions from urban and rural residents' living industries in accordance with one embodiment of the present invention. DETAILED DESCRIPTION

[0061] The following describes the specific implementation of the embodiment of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiment of the present invention and is not used to limit the embodiment of the present invention.

[0062] In the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0063] Figure 1 This is a flow chart of a method for accurately calculating carbon emissions from urban and rural residents' daily lives according to one embodiment of the present invention. In the present invention, the process of calculating carbon emissions may include:

[0064] In step S1, the electricity consumption of urban and rural residents in their daily lives is obtained.

[0065] In step S2, the electricity consumption of urban and rural residents in their daily lives is preprocessed to obtain electricity consumption that meets the requirements.

[0066] In step S3, a model for calculating energy based on electricity is constructed based on an autoregressive distributed lag model according to the electricity consumption that meets the requirements.

[0067] In step S4, a model for calculating the carbon factor by electricity is constructed according to the electricity consumption that meets the requirements.

[0068] In step S5 , the hysteresis order in the model based on the calculated energy and the model based on the calculated carbon factor is determined by the AIC criterion, thereby optimizing the model based on the calculated energy and the model based on the calculated carbon factor.

[0069] In step S6, the carbon emissions of urban and rural residents' living industries are obtained based on the results obtained by the model of electronically calculated energy and the results obtained by the model of electronically calculated carbon factors.

[0070] In the present invention, when calculating carbon emissions from the lives of urban and rural residents, the amount of electricity consumed by urban and rural residents during their lives can be first obtained. After obtaining the electricity consumption, the electricity consumption consumed by urban and rural residents during their lives can be preprocessed to obtain an electricity consumption that meets the requirements. After obtaining the electricity consumption that meets the requirements, a model based on an autoregressive distributed lag model that calculates energy based on electricity can be constructed based on the electricity consumption that meets the requirements. A model based on an autoregressive distributed lag model that calculates carbon factors based on electricity can be constructed based on the electricity consumption that meets the requirements. The lag order in the model based on energy based on electricity and the model based on carbon factors can be determined using the AIC criterion, thereby optimizing the model based on energy based on electricity and the model based on carbon factors. After obtaining the results of the model based on energy based on electricity and the model based on carbon factors based on electricity, the carbon emissions of urban and rural residents' living industries can be calculated based on the IPCC carbon emission accounting. This method can accurately calculate the carbon emissions of urban and rural residents' living industries.

[0071] In one embodiment of the present invention, Figure 2 As shown, the pre-processing process may include:

[0072] In step S7, data cleaning is performed on the electricity consumption to obtain available electricity consumption.

[0073] In step S8, the available power consumption is detected for abnormal data and corrected according to the actual situation.

[0074] In step S9, the corrected power consumption is analyzed in time series, and the missing data is supplemented to meet the power consumption requirement of formula (1):

[0075]

[0076] Among them, t is the time point, X t represents the data at time t in the modified electricity consumption time series data, X t-1 Represents the data of time t-1 in the modified electricity consumption time series, I t Represents the data at time t in the original electricity consumption time series data, I t-1 Represents the data at time t-1 in the original electricity consumption time series data.

[0077] In the present invention, when pre-processing the acquired electricity consumption, the electricity consumption can be cleaned first, so that the available electricity consumption can be obtained. After obtaining the available electricity consumption, the available electricity consumption can be detected for abnormal data, and can be corrected according to actual conditions to further ensure the data availability of the electricity consumption. After the correction is completed, the corrected electricity consumption can be subjected to time series analysis. When missing data is found through the time series analysis, the missing data can be supplemented to meet the electricity consumption requirements of formula (1), thereby ensuring that the supplemented data is consistent with the original sequence of electricity consumption.

[0078] In one embodiment of the present invention, the process of constructing a model based on electrical computing energy may include:

[0079] In step S10, the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements are obtained.

[0080] In step S11, a model for calculating fossil energy consumption is constructed using formula (2):

[0081]

[0082] Among them, y t,r represents the fossil energy consumption of residents’ daily life at time t, p r ,qr 、s r represents the lag order of the model for calculating fossil energy consumption, represents the regression coefficient of the dependent variable of the model based on the calculation of fossil energy consumption at the i-th order, y t-i,r represents the fossil energy consumption of residents’ daily life at time t and lag i, β i,r represents the regression coefficient of electricity consumption in the model of calculating fossil energy consumption at the i-th order, x t-i represents the electricity consumption at time t lag i, γ i,r represents the regression coefficient of urban and rural residents’ disposable income when fossil energy consumption is calculated at the i-th order, z t-i represents the disposable income of urban and rural residents at time t and lag i, a r represents the intercept of the model for calculating fossil energy consumption, u t,r Represents the random error term of the model that calculates fossil energy consumption by electricity.

[0083] In this invention, the fossil energy consumption activity of the residential sector is affected not only by electricity data but also by changes in the economic level of residents and the urban-rural income gap. Therefore, factors such as the per capita disposable income of urban and rural residents can be incorporated into supplementary variables to construct a model for calculating fossil energy consumption. A model for calculating fossil energy consumption can be constructed using formula (2), and the fossil energy consumption of the residential sector at time t can be calculated using formula (2).

[0084] In one embodiment of the present invention, the process of constructing a model based on electrical computing energy may further include:

[0085] In step S12, the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements are obtained.

[0086] In step S13, a model for calculating heat consumption by electricity is constructed using formula (3):

[0087]

[0088] Among them, y t,h represents the heat consumption of residents’ daily life at time t, p h ,q h 、s h represents the lag order of the model for calculating heat consumption, The regression coefficient of the dependent variable of the model with calculated heat consumption at the i-th order, y t-i,h represents the heat consumption of residents’ daily life industry at time t lag i, β i,h The regression coefficient of electricity consumption in the model of calculating heat consumption by electricity at the i-th order, x t-irepresents the electricity consumption at time t lag i, γ i,h represents the regression coefficient of disposable income of urban and rural residents when heat consumption is calculated by electricity at the i-th order, z t-i represents the disposable income of urban and rural residents at time t and lag i, a h The intercept of the model that calculates heat consumption by electricity, u f,h Represents the random error term of the model that calculates heat consumption using electricity.

[0089] Energy consumption for winter heating is one of the important sources of carbon emissions from the residential sector, especially in the northern cold regions. With the growth of residents' income, economic development, and environmental protection requirements, winter heating has gradually shifted from private coal burning to centralized heating (especially in the northern regions). At the same time, data correlation analysis shows that heat consumption, electricity consumption, and residents' income show a certain correlation. Therefore, in the present invention, when considering the carbon emissions of urban and rural residents' living industries, heat consumption in the northern cold regions can also be considered. Because heat consumption and electricity consumption show a correlation with residents, the per capita disposable income of urban and rural residents can be selected as a supplementary variable to construct a model for calculating heat consumption based on electricity. A model for calculating heat consumption based on electricity can be constructed using formula (3), and the required heat consumption of residents' living industries can be obtained using formula (3).

[0090] In one embodiment of the present invention, the process of obtaining the fossil energy carbon factor of the residential sector may include:

[0091] In step S14, the physical amount of fossil energy consumption, the carbon emission factor of fossil energy, and the standard coal conversion factor of fossil energy are obtained.

[0092] In step S15, the fossil energy carbon factor of the residential sector is calculated using formula (4):

[0093]

[0094] Among them, y t,f The carbon factor of fossil energy in the residents' daily life at time t, AC t,j represents the physical amount of the j-th fossil energy consumption at time t, EF j represents the carbon emission factor of the jth fossil energy, T j It represents the standard coal conversion factor of the j-th fossil energy.

[0095] In the present invention, when constructing a model based on the electronically calculated carbon factor, that is, when constructing the electronically calculated fossil energy carbon factor, the physical amount of fossil energy consumption, the carbon emission factor of fossil energy and the standard coal conversion factor of fossil energy can be obtained first, and then the fossil energy carbon factor of the residential life industry can be calculated by formula (4). Therefore, a model based on the electronically calculated carbon factor can be constructed according to formula (4).

[0096] In one embodiment of the present invention, the process of obtaining the fossil energy carbon factor of the residential industry may further include:

[0097] In step S16, the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements are obtained.

[0098] In step S17, a model of the fossil energy carbon factor of the residential sector is constructed using formula (5):

[0099]

[0100] Among them, y t,f represents the fossil energy carbon factor of the residents' living industry at time t, p f ,q f 、s f The lag order of the model representing the fossil energy carbon factor, represents the regression coefficient of the dependent variable of the model of fossil energy carbon factor at the i-th order, y t-i,f represents the fossil energy carbon factor of the residents' living industry at time t and lag i, β i,f The regression coefficient of electricity consumption in the model with fossil energy carbon factor at the i-th order, x t-i represents the electricity consumption at time t lag i, γ i,f represents the regression coefficient of urban and rural residents’ disposable income when calculating the fossil energy carbon factor at the i-th order, z t-i represents the disposable income of urban and rural residents at time t and lag i, a f The model intercept of the model representing the fossil energy carbon factor, u t,f Random error term in the model representing the fossil energy carbon factor.

[0101] Analysis of carbon emission data from Anhui's residential industries reveals that fossil energy consumption accounts for approximately 50% of carbon emissions. The structure of fossil energy consumption changes year by year, and using electricity data to fit the physical consumption of each type of fossil energy has a high error. However, through correlation analysis, it is found that the fossil energy carbon factor is significantly affected by changes in electricity consumption, residents' economic level, and urban-rural income differences, and the correlation is significant. Therefore, after obtaining the required electricity consumption and per capita disposable income of urban and rural residents, a model for the fossil energy carbon factor based on the autoregressive distributed lag model can be constructed according to formula (5). The fossil energy carbon factor can be calculated using formula (5).

[0102] In one embodiment of the present invention, Figure 3 As shown in the figure, the process of obtaining carbon emissions from urban and rural residents' daily life can include:

[0103] In step S18, it is determined whether the life process of urban and rural residents requires a lot of winter heating.

[0104] In step S19, when urban and rural residents do not need a large amount of winter heating during their lives, the fossil energy consumption is obtained according to formula (2), the fossil energy carbon factor is obtained according to formula (4) or formula (5), and the carbon emissions of urban and rural residents' living industries are calculated through IPCC carbon emission accounting.

[0105] In step S20, when urban and rural residents need a lot of winter heating in their daily lives, the fossil energy consumption is obtained according to formula (2), the heat consumption is obtained according to formula (3), the fossil energy carbon factor is obtained according to formula (4) or formula (5), and the carbon emissions of urban and rural residents' daily lives are calculated through the IPCC carbon emission accounting.

[0106] In the present invention, when obtaining the carbon emissions of urban and rural residents' daily life, it is possible to first determine whether the urban and rural residents in the area need a large amount of winter heating during their daily lives. In the case of whether a large amount of winter heating is needed, the fossil energy consumption can be calculated according to formula (2), and then the fossil energy carbon factor can be obtained according to formula (4) or formula (5). After obtaining the fossil energy consumption and the fossil energy carbon factor, the carbon emissions of urban and rural residents' daily life can be calculated using the IPCC carbon emission accounting method. In the case of a large amount of winter heating required by urban and rural residents during their daily lives, the heat consumption of the residents can be considered. Therefore, the fossil energy consumption can be obtained according to formula (2), and then the heat consumption can be obtained according to formula (3), and then the fossil energy carbon factor can be obtained according to formula (4) or formula (5). After obtaining each calculation factor, the carbon emissions of urban and rural residents' daily life can be obtained using the IPCC carbon emission accounting method.

[0107] In one embodiment of the present invention, the process of obtaining the monthly values of fossil energy consumption and heat consumption in urban and rural residents' daily life industries may include:

[0108] In step S21, the fossil energy consumption and heat consumption of urban and rural residents' daily life are obtained.

[0109] In step S22, the monthly values of fossil energy consumption and heat consumption are constructed using formula (6):

[0110]

[0111] Among them, y m,γ represents the monthly fossil energy consumption / heat consumption in month m, γ represents fossil energy / heat, x m represents the known electricity consumption of urban and rural residents, A represents the variance weight matrix between the electricity consumption of urban and rural residents and the monthly fossil energy consumption / heat consumption, c represents the set of months grouped by year and season, y c,γ Indicates the total consumption constraint of fossil energy consumption / heat consumption in the corresponding season.

[0112] In the present invention, when constructing the monthly values of fossil energy consumption and heat consumption in urban and rural residents' daily life, the values can be obtained through the modeling of formula (6). Formula (6) can be calculated according to the corresponding seasons. For example, c represents the set of months grouped by the annual season. Winter months can be November, December, January, February, and March, and summer months can be July, August, and September.

[0113] In another aspect, the present invention also provides a system for accurately calculating carbon emissions from urban and rural residents' daily lives. The system may include a data preprocessing module, an energy calculation module, an energy calculation carbon factor module, and a result output module. The data preprocessing module is used to obtain electricity consumption data from urban and rural residents' daily lives and perform preprocessing on the electricity consumption data, such as cleaning, anomaly detection, missing value interpolation, and feature engineering. The energy calculation module calculates fossil energy consumption using electricity consumption data and household disposable income data based on the autoregressive distributed lag (ARDL) model. This module receives the preprocessed data and outputs an estimate of fossil energy consumption. The heat calculation module estimates heat consumption based on electricity consumption data and calculates heat consumption carbon emissions by combining the heat carbon emission factor. This module operates similarly to the energy calculation model, but focuses on heat consumption estimation. The carbon factor module combines historical fossil energy consumption data and carbon emission data to calculate the fossil energy carbon emission factor. This module operates in parallel with the energy calculation model, providing the necessary parameters for carbon emission calculation. The result data module can output the overall carbon emission results of urban and rural residents in their daily lives.

[0114] In the present invention, the system can also include a monthly splitting module and an urban-rural difference calculation module. The monthly splitting module can use monthly electricity consumption data to split the annual carbon emissions results by month. This module operates after the total carbon emissions calculation is completed and provides refined results in the time dimension. The urban-rural difference calculation module can calculate the carbon emissions of urban and rural residents separately, achieving differentiated carbon emissions calculation.

[0115] Through the above technical solution, the present invention provides a method and system for accurately calculating carbon emissions from urban and rural residents' daily lives. By obtaining the electricity consumption of urban and rural residents during their daily lives, the electricity consumption during urban and rural residents' daily lives can be preprocessed to obtain an electricity consumption that meets the requirements. After obtaining the electricity consumption that meets the requirements, a model based on the autoregressive distributed lag model based on electricity-based energy can be constructed based on the electricity consumption that meets the requirements. A model based on the autoregressive distributed lag model based on electricity-based carbon factors can be constructed based on the electricity consumption that meets the requirements. The lag order in the model based on electricity-based energy and the model based on electricity-based carbon factors can be determined using the AIC criterion, thereby optimizing the model based on electricity-based energy and the model based on electricity-based carbon factors. After obtaining the results of the model based on electricity-based energy and the model based on electricity-based carbon factors, the carbon emissions of urban and rural residents' daily lives can be calculated according to the IPCC carbon emission accounting. This method can accurately calculate the carbon emissions of urban and rural residents' daily lives.

[0116] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0117] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0120] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0121] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0122] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0123] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0124] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for accurately calculating carbon emissions from urban and rural residents' daily lives, characterized by: The method comprises: Obtain electricity consumption in urban and rural residents' daily lives; Pre-processing the electricity consumption of urban and rural residents in their daily lives to obtain electricity consumption that meets the requirements; Constructing a model based on electric energy calculation using an autoregressive distributed lag model according to the electric consumption amount that meets the requirements; Constructing a model for electrically calculating the carbon factor based on the electricity consumption that meets the requirements; The lag order in the model based on the calculated energy and the model based on the calculated carbon factor is determined by the AIC criterion, thereby optimizing the model based on the calculated energy and the model based on the calculated carbon factor; Based on the results obtained by the model using electrical energy calculation and the model using electrical carbon factor calculation, the carbon emissions of urban and rural residents' living industries are obtained.

2. The method according to claim 1, characterized in that Preprocessing the electricity consumption of urban and rural residents in their daily lives to obtain electricity consumption that meets the requirements includes: Performing data cleaning on the electricity consumption to obtain available electricity consumption; Detect abnormal data on available electricity consumption and make corrections based on actual conditions; Perform a time series analysis on the corrected electricity consumption, and fill in the missing data to meet the electricity consumption requirement of formula (1): Among them, t is the time point, X t represents the data at time t in the modified electricity consumption time series data, X t-1 Represents the data of time t-1 in the modified electricity consumption time series, I t Represents the data at time t in the original electricity consumption time series data, I t-1 Represents the data at time t-1 in the original electricity consumption time series data.

3. The method according to claim 1, characterized in that According to the electricity consumption that meets the requirements, a model based on electric energy calculation based on an autoregressive distributed lag model is constructed, including: Obtain the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements: The model for calculating fossil energy consumption is constructed using formula (2): Among them, y t,r represents the fossil energy consumption of residents’ daily life at time t, p r ,q r 、s r represents the lag order of the model for calculating fossil energy consumption, represents the regression coefficient of the dependent variable of the model based on the calculation of fossil energy consumption at the i-th order, y t-i,r represents the fossil energy consumption of residents’ daily life at time t and lag i, β i,r represents the regression coefficient of electricity consumption in the model of calculating fossil energy consumption at the i-th order, x t-j represents the electricity consumption at time t lag i, γ i,r represents the regression coefficient of urban and rural residents’ disposable income when fossil energy consumption is calculated at the i-th order, z t-i represents the disposable income of urban and rural residents at time t and lag i, a r represents the intercept of the model for calculating fossil energy consumption, u t,r Represents the random error term of the model that calculates fossil energy consumption by electricity.

4. The method according to claim 3, characterized in that According to the electricity consumption that meets the requirements, a model based on electric energy calculation based on an autoregressive distributed lag model is constructed, including: Obtain the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements; The model for calculating heat consumption by electricity is constructed using formula (3): Among them, y t,h represents the heat consumption of residents’ daily life at time t, p h ,q h 、s h represents the lag order of the model for calculating heat consumption, represents the regression coefficient of the dependent variable of the model with electric heat consumption at the i-th order, y t-i,h represents the heat consumption of residents’ daily life industry at time t lag i, β i,h represents the regression coefficient of electricity consumption in the model of calculating heat consumption by electricity at the i-th order, x t-i represents the electricity consumption at time t lag i, γ i,h represents the regression coefficient of urban and rural residents' disposable income when heat consumption is calculated by electricity at the i-th order, z t-i represents the disposable income of urban and rural residents at time t and lag i, a h The intercept of the model that calculates heat consumption by electricity, u t,h Represents the random error term of the model that calculates heat consumption based on electricity.

5. The method according to claim 4, characterized in that A model for calculating the carbon factor based on the electricity consumption that meets the requirements is constructed, including: Obtain the physical quantity of fossil energy consumption, the carbon emission factor of fossil energy, and the standard coal conversion factor of fossil energy; The carbon factor of fossil energy in the residential sector is calculated using formula (4): Among them, y t,f The carbon factor of fossil energy in the residents' daily life at time t, AC t,j represents the physical amount of the j-th fossil energy consumption at time t, EF j represents the carbon emission factor of the jth fossil energy, T j It represents the standard coal conversion factor of the jth fossil energy.

6. The method according to claim 4, characterized in that A model for calculating the carbon factor based on the electricity consumption that meets the requirements is constructed, including: Obtain the electricity consumption and per capita disposable income of urban and rural residents that meet the requirements; The model of fossil energy carbon factor of residents’ living industry is constructed by formula (5): Among them, y t,f represents the carbon factor of fossil energy in the residential sector at time t, p f ,q f 、s f The lag order of the model representing the fossil energy carbon factor, represents the regression coefficient of the dependent variable of the model of fossil energy carbon factor at the i-th order, y t-i,f represents the fossil energy carbon factor of the residents' living industry at time t and lag i, β i,f represents the regression coefficient of electricity consumption in the model with fossil energy carbon factor at the i-th order, x t-i represents the electricity consumption at time t lag i, γ i,f represents the regression coefficient of urban and rural residents’ disposable income when calculating the fossil energy carbon factor at the i-th order, z t-i represents the disposable income of urban and rural residents at time t and lag i, a f The model intercept of the model representing the fossil energy carbon factor, u t,f Random error term in the model representing the fossil energy carbon factor.

7. The method according to any one of claims 5 to 6, characterized in that: Based on the results obtained from the model using electrical energy calculations and the model using electrical carbon factor calculations, the carbon emissions from urban and rural residents' daily lives are obtained, including: Determine whether the life processes of the urban and rural residents require a large amount of winter heating; When urban and rural residents do not need a lot of winter heating in their daily lives, the fossil energy consumption is obtained according to formula (2), the fossil energy carbon factor is obtained according to formula (4) or formula (5), and the carbon emissions of urban and rural residents' daily life are calculated using the IPCC carbon emission accounting method; When urban and rural residents need a lot of winter heating in their daily lives, the fossil energy consumption is obtained according to formula (2), the heat consumption is obtained according to formula (3), the fossil energy carbon factor is obtained according to formula (4) or formula (5), and the carbon emissions of urban and rural residents' daily lives are obtained through the IPCC carbon emission accounting calculation method.

8. The method according to claim 4, characterized in that The method comprises: Obtaining the fossil energy consumption and heat consumption of urban and rural residents' daily life; The monthly values of fossil energy consumption and heat consumption are constructed using formula (6): Among them, y m,γ represents the monthly fossil energy consumption / heat consumption in month m, γ represents fossil energy / heat, x m represents the known electricity consumption of urban and rural residents, A represents the variance weight matrix between the electricity consumption of urban and rural residents and the monthly fossil energy consumption / heat consumption, c represents the set of months grouped by year and season, y c,γ Indicates the total consumption constraint of fossil energy consumption / heat consumption in the corresponding season.

9. A system for accurately calculating carbon emissions from urban and rural residents' daily lives, characterized by: The system comprises: A data preprocessing module is used to obtain the electricity consumption of urban and rural residents in their daily lives and preprocess the electricity consumption; The electricity calculation module is used to calculate fossil energy consumption based on electricity consumption and per capita disposable income of urban and rural residents; The electricity-heat calculation module is used to calculate heat consumption based on electricity consumption and per capita disposable income of urban and rural residents; The electric carbon factor module is used to calculate the carbon factor of fossil energy based on electricity consumption and per capita disposable income of urban and rural residents; The result output module is used to calculate the carbon emissions of urban and rural residents' living industries based on the obtained fossil energy consumption, heat consumption and fossil energy carbon factor.

10. The system according to claim 9, characterized in that The system comprises: Monthly split module, used to split the annual carbon emission results monthly according to the monthly electricity consumption; The urban-rural difference calculation module calculates the carbon emissions of urban and rural residents based on the differences in electricity consumption and per capita disposable income between urban and rural areas.

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