CN115936526A - Carbon emission data measuring and calculating method based on electric power big data - Google Patents
Carbon emission data measuring and calculating method based on electric power big data Download PDFInfo
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Abstract
The invention provides a carbon emission data measuring and calculating method based on electric power big data, which is applied to a carbon emission data measuring and calculating system based on the electric power big data, wherein the system comprises a data acquisition module, a data classification module, a data statistics module, a data measuring and calculating module and a scene simulation module.
Description
Technical Field
The invention relates to the technical field of carbon emission data measurement and calculation, in particular to a carbon emission data measurement and calculation method based on electric power big data.
Background
Carbon emission measurement is a precondition and a basis for implementing carbon peak reaching and carbon neutralization targets, carbon emission is mainly measured and calculated according to carbon emission data in the past year at present, and the carbon emission situation is difficult to dynamically perceive in time in the measuring and calculating process, so that the monitoring cost is difficult to greatly reduce, and further, the tile is difficult to be added for the research of carbon emission measurement and calculation.
Disclosure of Invention
Therefore, the present invention is directed to a method for measuring and calculating carbon emission data based on big power data, so as to solve at least the above problems.
The technical scheme adopted by the first aspect of the invention is as follows:
a carbon emission data measurement and calculation method based on electric power big data is applied to a carbon emission data measurement and calculation system based on electric power big data, the system comprises a data acquisition module, a data classification module, a data statistics module, a data measurement and calculation module and a scene simulation module, and the method comprises the following steps:
s1, collecting carbon emission data through a data collection module;
s2, classifying the carbon emission data acquired by the data acquisition module by the data classification module;
s3, constructing a carbon emission statistical analysis model through a data statistical module, and analyzing the classified carbon emission data by the carbon emission statistical analysis model;
s4, the data measuring and calculating module measures and calculates the carbon emission data according to the analysis result of the carbon emission statistical analysis model;
and S5, the scene simulation module carries out carbon emission scene simulation according to the carbon emission data measurement and calculation result.
Further, in step S1, the collecting of the carbon emission data by the data collecting module specifically includes:
the data acquisition module acquires carbon emission data according to the resident carbon consumption emission parameters, the resident electricity consumption carbon emission parameters, the resident electricity consumption, the enterprise electricity consumption, the industry electricity consumption and the city electricity consumption data.
Further, in step S2, the data classification module classifies the carbon emission data collected by the data collection module into:
the data classification module divides the carbon emission data that the data acquisition module was gathered into resident household basic data, key enterprise basic data, key trade basic data and the type of land market basic data, resident household basic data type divides according to resident consumption carbon emission parameter, resident power consumption carbon emission parameter and resident power consumption data, key enterprise basic data type divides according to enterprise power consumption data, key industry basic data type divides according to trade power consumption data, the type of land market basic data divides according to the type of land market power consumption data.
Further, in step S3, a carbon emission statistical analysis model is constructed by the data statistical module, and the analysis of the classified carbon emission data by the carbon emission statistical analysis model specifically includes:
the carbon emission statistical analysis model is trained according to the data of the residential carbon emission parameters, the residential electricity consumption, the enterprise electricity consumption, the industry electricity consumption and the city electricity consumption as parameters to obtain the residential attribute characteristics and the residential electricity consumption characteristics of the residential basic data types, the electricity consumption and output relationships and the product carbon emission coefficients of the key enterprise basic data types, the product carbon emission coefficients of the key industry basic data types and the industry electricity consumption and output relationships.
Further, in step S4, the data measurement and calculation module performs the carbon emission data measurement and calculation according to the analysis result of the carbon emission statistical analysis model specifically as follows:
the data measurement and calculation module calculates the basic data type of the residents through a list analysis method and an accumulative square root method to obtain the resident carbon emission measurement and calculation;
the data measurement and calculation module calculates basic data of key enterprises and basic data types of key industries through an ADL (adaptive data logging) model, an ECM (model control model) and a long-term balance model to respectively obtain key enterprise carbon emission measurement and calculation and key industry emission measurement and calculation;
and the data measurement and calculation module obtains the carbon emission measurement and calculation of the city through the use amount of various energy sources and carbon emission parameters of various energy sources in various industries for the type of the city basic data.
Further, in step S5, the scene simulation module specifically performs the carbon emission scene simulation according to the carbon emission data measurement and calculation result by:
the scene simulation module obtains a carbon emission simulation scene through measuring and calculating resident carbon emission, measuring and calculating key enterprise carbon emission, measuring and calculating key industry emission and measuring and calculating city carbon emission.
The second aspect of the invention adopts the following technical scheme:
a power big data based carbon emission data measurement and calculation system for performing the method as set forth in the first aspect, the system comprising a data collection module, a data classification module, a data statistics module, a data measurement and calculation module, and a scene simulation module.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the data for measuring and calculating the carbon emission is explored based on the electricity consumption data of residents and enterprises from a microscopic view, so that the monitoring cost is greatly reduced, and the accuracy of measuring and calculating the carbon emission is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is apparent that the drawings in the following description are only preferred embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without inventive efforts.
Fig. 1 is a schematic overall flow chart of a method for measuring and calculating carbon emission data based on big power data according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of an overall structure of a carbon emission data measurement and calculation method based on big power data according to an embodiment of the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, the illustrated embodiments are provided to illustrate the invention and not to limit the scope of the invention.
Referring to fig. 1 and 2, in a first aspect of the present invention, a method for calculating carbon emission data based on big power data is provided, the method is applied to a system for calculating carbon emission data based on big power data, the system includes a data acquisition module, a data classification module, a data statistics module, a data calculation module, and a scene simulation module, and the method includes the following steps:
s1, collecting carbon emission data through a data collection module;
s2, classifying the carbon emission data acquired by the data acquisition module by the data classification module;
s3, constructing a carbon emission statistical analysis model through a data statistical module, and analyzing the classified carbon emission data by the carbon emission statistical analysis model;
s4, the data measuring and calculating module measures and calculates the carbon emission data according to the analysis result of the carbon emission statistical analysis model;
and S5, the scene simulation module carries out carbon emission scene simulation according to the carbon emission data measurement and calculation result.
In step S1, the collecting of the carbon emission data by the data collecting module specifically includes:
the data acquisition module acquires carbon emission data according to the resident carbon consumption emission parameters, the resident electricity consumption carbon emission parameters, the resident electricity consumption, the enterprise electricity consumption, the industry electricity consumption and the city electricity consumption data.
In step S2, the data classification module classifies the carbon emission data collected by the data collection module as follows:
the data classification module divides the carbon emission data that the data acquisition module was gathered into resident household basic data, key enterprise basic data, key trade basic data and the type of land market basic data, resident household basic data type divides according to resident consumption carbon emission parameter, resident power consumption carbon emission parameter and resident power consumption data, key enterprise basic data type divides according to enterprise power consumption data, key industry basic data type divides according to trade power consumption data, the type of land market basic data divides according to the type of land market power consumption data.
In step S3, a statistical analysis model of carbon emissions is constructed by the data statistics module, and the analysis of the classified carbon emissions by the statistical analysis model of carbon emissions is specifically as follows:
the carbon emission statistical analysis model is trained according to the resident consumption carbon emission parameter, the resident electricity consumption, the enterprise electricity consumption, the industry electricity consumption and the city electricity consumption data serving as parameters to obtain resident attribute characteristics and resident electricity consumption characteristics of a resident basic data type, electricity consumption and output relations and product carbon emission coefficients of key enterprise basic data types, product carbon emission coefficients of key industry basic data types and industry electricity consumption and output relations of key industry basic data types.
In step S4, the data measurement and calculation module performs the carbon emission data measurement and calculation according to the analysis result of the carbon emission statistical analysis model, specifically:
the data measurement and calculation module calculates the basic data type of the residents through a list analysis method and an accumulative square root method to obtain the resident carbon emission measurement and calculation;
the data measurement and calculation module calculates basic data of key enterprises and basic data types of key industries through an ADL (adaptive data logging) model, an ECM (model control model) and a long-term balance model to respectively obtain key enterprise carbon emission measurement and calculation and key industry emission measurement and calculation;
and the data measurement and calculation module obtains the carbon emission measurement and calculation of the city through the use amount of various energy sources and carbon emission parameters of various energy sources in various industries for the type of the city basic data.
In step S5, the scene simulation module performs the carbon emission scene simulation according to the carbon emission data measurement and calculation result, specifically:
the scene simulation module obtains a carbon emission simulation scene through measuring and calculating resident carbon emission, measuring and calculating key enterprise carbon emission, measuring and calculating key industry emission and measuring and calculating city carbon emission.
Exemplary, residential carbon emissions measurements: the method comprises the steps of firstly, dividing residents into three dimensions of rural areas, cities, per-capita income and per-capita consumption of eight types of consumption according to each city, carrying out cross attribute feature classification and list-linked list analysis, and simultaneously carrying out cluster analysis to obtain resident attribute features.
And secondly, according to the carbon consumption emission coefficient table, combining the attribute characteristics of residents, thereby obtaining the carbon consumption emission coefficients of various residents and determining the conversion coefficients r of various attribute characteristics.
Thirdly, according to the total amount of the electricity consumption of each household and the structure composition of the electricity consumption (considering the contribution of green electricity), grouping the household by adopting a Sturges method, and then layering grouping results by utilizing an accumulative square root method, thereby obtaining a classification result of the characteristics of the electricity consumption of the household;
and fourthly, determining the carbon emission conversion coefficient h of various types of resident electricity consumption by combining the carbon emission parameters according to energy consumption and the characteristic classification result of the resident electricity consumption.
Fifthly, determining a conversion coefficient r for each household resident according to the area coordinates ij (ii) a Meanwhile, according to the classification characteristics of the electricity consumption, a conversion coefficient hmj is determined for each household resident; and finally, calculating the carbon emission of each household resident according to the consumption data.
C emission measurement of key enterprises: firstly, determining a list of key enterprises, main product types corresponding to the key enterprises, various types of yields, enterprise business scale and number of people.
Secondly, an ARDL model, a short-term error correction model (ECM model) and a long-term balance model are adopted to search the quantitative relation between the power consumption of the enterprise and different types of output, business income and scale.
Thirdly, by taking the carbon emission coefficients of various products of IPCC as a reference, the derivation process of the coefficients of various products is analyzed, and the precondition setting conditions of the coefficients of various products are obtained, namely: the energy consumption configuration of the product and the possible types of electrical energy used constitute the configuration.
And fourthly, analyzing and obtaining the adjusted product carbon emission parameters by combining the power consumption data of various enterprises, the enterprise power consumption structure data, the IPCC product carbon emission coefficient and the energy consumption structure premise setting conditions measured and calculated by the IPCC product carbon emission coefficient.
And (4) calculating the carbon emission of each key enterprise by combining the power consumption data of the enterprises, the quantitative relation between the power consumption and the output and the adjusted carbon emission coefficient.
Measuring and calculating the carbon emission of key industries: firstly, determining a key industry list, main product types corresponding to each key industry,
Various types of total output and the total industrial output scale.
Secondly, an ARDL model, a short-term error correction model (ECM model) and a long-term balance model are adopted to search the quantitative relation between the power consumption of the key industry and the output quantity and the output scale of different types.
Thirdly, by referring to the carbon emission coefficients of various products of IPCC, the derivation process of the coefficients of various products is analyzed, and the precondition setting conditions of the coefficients of various products are obtained, namely: the energy consumption configuration of the product and the possible types of electrical energy used constitute the configuration.
And fourthly, analyzing and obtaining the adjusted product carbon emission parameters by combining the power consumption data of the key industry, the power consumption structure data of the industry, the carbon emission coefficient of the IPCC product and the energy consumption structure precondition setting conditions measured and calculated by the carbon emission coefficient of the IPCC product.
And fifthly, calculating the carbon emission of the key industry according to the power consumption data of the key industry, the corresponding relationship between the output and the power consumption and the adjusted carbon emission coefficient of the corresponding product.
And sixthly, acquiring various energy consumption data of the statistical bureau about seven major industries and various subclasses of industries, measuring and calculating the carbon emission of key industries according to the carbon emission coefficients of various energy of national and international standards, and carrying out comparison analysis and inspection on the results of power consumption measurement and calculation.
A second aspect of the present invention provides a system for measuring and calculating carbon emission data based on big electric power data, the system being used for executing the method as set forth in the first aspect, the system comprising a data acquisition module, a data classification module, a data statistics module, a data measuring and calculating module and a scene simulation module.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (7)
1. The method for measuring and calculating the carbon emission data based on the big power data is applied to a system for measuring and calculating the carbon emission data based on the big power data, the system comprises a data acquisition module, a data classification module, a data statistics module, a data measuring and calculating module and a scene simulation module, and the method comprises the following steps:
s1, collecting carbon emission data through a data collection module;
s2, classifying the carbon emission data acquired by the data acquisition module by the data classification module;
s3, constructing a carbon emission statistical analysis model through a data statistical module, and analyzing the classified carbon emission data by the carbon emission statistical analysis model;
s4, the data measuring and calculating module measures and calculates the carbon emission data according to the analysis result of the carbon emission statistical analysis model;
and S5, the scene simulation module carries out carbon emission scene simulation according to the carbon emission data measurement and calculation result.
2. The method for calculating the carbon emission data based on the big power data as claimed in claim 1, wherein in step S1, the collecting the carbon emission data by the data collecting module specifically comprises:
the data acquisition module acquires carbon emission data according to the resident carbon consumption emission parameters, the resident electricity consumption carbon emission parameters, the resident electricity consumption, the enterprise electricity consumption, the industry electricity consumption and the city electricity consumption data.
3. The method for calculating the carbon emission data based on the big power data as claimed in claim 2, wherein in step S2, the data classification module classifies the carbon emission data collected by the data collection module into:
the data classification module divides the carbon emission data that the data acquisition module was gathered into resident household basic data, key enterprise basic data, key trade basic data and the type of land market basic data, resident household basic data type divides according to resident consumption carbon emission parameter, resident power consumption carbon emission parameter and resident power consumption data, key enterprise basic data type divides according to enterprise power consumption data, key industry basic data type divides according to trade power consumption data, the type of land market basic data divides according to the type of land market power consumption data.
4. The method for calculating the carbon emission data based on the big power data according to claim 1, wherein in step S3, a statistical analysis model of carbon emission is constructed through a data statistics module, and the statistical analysis model of carbon emission analyzes the classified carbon emission data specifically as follows:
the carbon emission statistical analysis model is trained according to the resident consumption carbon emission parameter, the resident electricity consumption, the enterprise electricity consumption, the industry electricity consumption and the city electricity consumption data serving as parameters to obtain resident attribute characteristics and resident electricity consumption characteristics of a resident basic data type, electricity consumption and output relations and product carbon emission coefficients of key enterprise basic data types, product carbon emission coefficients of key industry basic data types and industry electricity consumption and output relations of key industry basic data types.
5. The method for calculating carbon emission data based on big power data as claimed in claim 1, wherein in step S4, the data calculating module calculates the carbon emission data according to the analysis result of the statistical analysis model of carbon emission specifically:
the data measurement and calculation module calculates the basic data type of the residents through a list analysis method and an accumulative square root method to obtain the resident carbon emission measurement and calculation;
the data measurement and calculation module calculates basic data of key enterprises and basic data types of key industries through an ADL (adaptive data logging) model, an ECM (model control model) and a long-term balance model to respectively obtain key enterprise carbon emission measurement and calculation and key industry emission measurement and calculation;
and the data measurement and calculation module obtains the carbon emission measurement and calculation of the city through the use amount of various energy sources and carbon emission parameters of various energy sources in various industries for the city basic data types.
6. The method for calculating the carbon emission data based on the big power data as claimed in claim 5, wherein in step S5, the scene simulation module performs the carbon emission scene simulation according to the calculation result of the carbon emission data specifically:
and the scene simulation module is used for obtaining a carbon emission simulation scene through measuring and calculating the carbon emission of residents, measuring and calculating the carbon emission of key enterprises, measuring and calculating the emission of key industries and measuring and calculating the carbon emission of cities.
7. A power big data based carbon emission data measurement and calculation system, characterized in that the system is used for executing the method of claims 1-6, and the system comprises a data acquisition module, a data classification module, a data statistics module, a data measurement and calculation module and a scene simulation module.
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| CN117709550A (en) * | 2024-01-24 | 2024-03-15 | 西安电力高等专科学校 | ARDL and convolutional neural network model-based energy consumption prediction method |
| CN117709550B (en) * | 2024-01-24 | 2024-06-25 | 西安电力高等专科学校 | Energy consumption prediction method based on ARDL and convolutional neural network model |
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