Carbon emission comprehensive efficiency evaluation method, system and device and storage medium

Abstract

The invention relates to a carbon emission comprehensive efficiency evaluation method, system and device and a storage medium. According to the method, after carbon emission data is obtained, based on the carbon emission data and a pre-constructed carbon emission comprehensive efficiency evaluation index model, at least one first-level evaluation index value and the index weight of each first-level evaluation index are obtained through a principal component analysis method and an analytic hierarchy process; the carbon emission comprehensive efficiency evaluation index model comprises a plurality of first-level evaluation indexes, and finally, based on first-level evaluation index values and corresponding index weights, obtaining a carbon emission comprehensive efficiency evaluation result. Compared with the prior art, the method has the advantages that the accuracy and objectivity of the evaluation result of the comprehensive efficiency of the carbon emission can be ensured under the condition that the original data is sufficient or insufficient, and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon monitoring, and in particular, to a method, system, device and storage medium for evaluating the comprehensive carbon emission efficiency. Background Art

[0002] Under the "dual carbon" goal, effective carbon emission monitoring and carbon efficiency assessment of industrial enterprises are of great significance for improving the carbon efficiency level and achieving the "dual carbon" goal.

[0003] Regarding carbon emission monitoring and analysis, certain explorations have been made in the prior art. For example, Chinese Patent CN118152835A discloses a method, device, terminal device and storage medium for analyzing carbon emission influencing factors. After obtaining the original carbon emission data, the method analyzes the original carbon emission data through the principal component analysis PCA dimensionality reduction algorithm to obtain the dimensionality-reduced data; performs clustering processing on the dimensionality-reduced data through the K-means clustering algorithm to obtain the clustering result; performs feature analysis on the clustering result through the linear discriminant analysis method to obtain the feature representation value; obtains the influence degree of the influencing factor on the target variable through the index decomposition analysis method; analyzes the carbon emission influencing factors according to the influence degree of the influencing factor on the target variable to obtain the carbon emission influencing factor analysis result; and establishes a quantitative evaluation standard system according to the carbon emission influencing factor analysis result to extract the key information of the carbon emission influencing factors.

[0004] However, the prior art mainly relies on data-driven analysis methods, ignoring the influence of factors such as expert experience. In the case of insufficient original data, the accuracy of the comprehensive carbon emission efficiency evaluation result will be limited, and ultimately there is still a lack of a clear evaluation index system, resulting in low efficiency and applicability in obtaining the comprehensive carbon emission efficiency evaluation result. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art that the accuracy of the comprehensive carbon emission efficiency evaluation result is limited in the case of insufficient original data, and the obtaining efficiency and applicability are low, and to provide a method, system, device and storage medium for evaluating the comprehensive carbon emission efficiency.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] According to the first aspect provided by the present invention, there is provided a method for evaluating the comprehensive efficiency of carbon emissions, including the following steps: S1, obtaining carbon emission data; S2, based on the carbon emission data and a pre-constructed comprehensive efficiency evaluation index model of carbon emissions, using the principal component analysis method and the analytic hierarchy process to obtain at least one primary evaluation index value and the index weight of each primary evaluation index, where the comprehensive efficiency evaluation index model of carbon emissions includes multiple primary evaluation indexes; S3, based on the primary evaluation index value and the corresponding index weight, obtaining the evaluation result of the comprehensive efficiency of carbon emissions.

[0008] As a preferred technical solution, each of the primary evaluation indexes includes multiple secondary evaluation indexes, and S2 specifically includes: S21, determining at least one secondary evaluation index value of the object to be evaluated; S22, using the principal component analysis method to perform dimensionality reduction processing on the secondary evaluation indexes to obtain the primary evaluation index value; S23, based on the primary evaluation index value, using the analytic hierarchy process to determine the corresponding index weight.

[0009] As a preferred technical solution, the primary evaluation index includes at least one of the following: carbon emission volume, carbon emission intensity, carbon emission growth rate, and carbon emission stability.

[0010] As a preferred technical solution, the secondary evaluation indexes of the carbon emission volume include at least one of the following: total annual carbon dioxide emissions, maximum monthly carbon dioxide emissions, minimum monthly carbon dioxide emissions, and average household annual carbon dioxide emissions; the secondary evaluation indexes of the carbon emission intensity include at least one of the following: carbon dioxide emissions per unit industrial added value and carbon dioxide emissions per unit area; the secondary evaluation indexes of the carbon emission growth rate include at least one of the following: carbon dioxide emission growth rate, annual growth rate of carbon dioxide emissions per unit industrial added value, and annual growth rate of carbon dioxide emissions per unit area; the secondary evaluation indexes of the carbon emission stability include at least one of the following: degree of year-on-year fluctuation of carbon dioxide emissions and degree of year-on-year fluctuation of carbon emission intensity.

[0011] As a preferred technical solution, S22 specifically includes: performing standardization processing on the secondary evaluation index values; forming a data matrix with the standardized secondary evaluation index values; calculating the covariance matrix of the data matrix; performing eigenvalue and eigenvector decomposition on the covariance matrix to obtain the explained variance of each principal component; according to the size of the eigenvalues, selecting the principal components whose cumulative explained variance reaches a preset threshold or more; after linearly combining the scores of the selected principal components, obtaining the corresponding primary evaluation index value.

[0012] As a preferred technical solution, the S23 specifically includes: based on the first-level evaluation index values, introducing expert experience to obtain a judgment matrix; after normalizing the judgment matrix, calculating the maximum eigenvalue and the corresponding eigenvector of the judgment matrix to obtain the corresponding weight vector.

[0013] As a preferred technical solution, in the S3, the evaluation result of the carbon emission comprehensive efficiency is determined by the comprehensive efficiency score, and the calculation formula of the comprehensive efficiency score is:

[0014]

[0015] In the formula, A represents the comprehensive efficiency score, W i represents the weight of the i-th first-level evaluation index, and s i represents the standardized score of the i-th first-level evaluation index.

[0016] According to the second aspect of the present invention, there is provided a carbon emission comprehensive efficiency evaluation system, including a data acquisition module, an evaluation index value and weight acquisition module, and a comprehensive efficiency evaluation module, wherein: the data acquisition module is used to acquire carbon emission data; the evaluation index value and weight acquisition module is used to obtain at least one first-level evaluation index value and the index weight of each first-level evaluation index based on the carbon emission data and a pre-constructed carbon emission comprehensive efficiency evaluation index model by using the principal component analysis method and the analytic hierarchy process method, and the carbon emission comprehensive efficiency evaluation index model includes a plurality of first-level evaluation indexes; the carbon emission comprehensive efficiency evaluation module is used to obtain the carbon emission comprehensive efficiency evaluation result based on the first-level evaluation index value and the corresponding index weight.

[0017] According to the third aspect of the present invention, there is provided a carbon emission comprehensive efficiency evaluation device, including a memory, a processor, and a program stored in the memory, and the processor implements the method when executing the program.

[0018] According to the fourth aspect of the present invention, there is provided a storage medium, on which a program is stored, and the method is implemented when the program is executed.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The present invention combines the principal component analysis method and the analytic hierarchy process method to obtain the first-level evaluation index value and the index weight of each first-level evaluation index, combines the data advantage of the principal component analysis method with the expert experience advantage of the analytic hierarchy process method, and can ensure the accuracy and objectivity of the carbon emission comprehensive efficiency evaluation result whether the original data is sufficient or not.

[0021] 2. The present invention pre - constructs a comprehensive carbon emission efficiency evaluation index model, which includes multiple first - level evaluation indicators, and each first - level evaluation indicator further includes multiple second - level evaluation indicators. The hierarchical and structured design of the evaluation indicators combined with the subjective - objective combined weight allocation method enables the comprehensive carbon emission efficiency evaluation to have a clear quantitative evaluation index system, which can improve the acquisition efficiency of the comprehensive carbon emission efficiency evaluation results, and helps to effectively evaluate the overall carbon emission efficiency and quickly identify weak links.

[0022] 3. The present invention can not only help enterprises and parks clarify their current carbon emission levels and improvement spaces, but also provide decision - making support for optimizing their carbon reduction paths, realizing the transformation from extensive management to refined management. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a schematic flow chart of the method provided by the present invention;

[0024] Figure 2 is a schematic flow chart of step S2 in Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] The present invention will be described in detail below with reference to the drawings and specific embodiments. This embodiment is implemented on the premise of the technical solution of the present invention, and gives detailed implementation methods and specific operation processes, but the protection scope of the present invention is not limited to the following embodiments.

[0026] Embodiment 1:

[0027] As Figure 1 shown, this embodiment provides a comprehensive carbon emission efficiency evaluation method, which specifically includes: Step S1, obtaining carbon emission data; Step S2, based on the carbon emission data and the pre - constructed comprehensive carbon emission efficiency evaluation index model, using the principal component analysis method and the analytic hierarchy process to obtain at least one first - level evaluation index value and the index weight of each first - level evaluation indicator. The comprehensive carbon emission efficiency evaluation index model includes multiple first - level evaluation indicators; Step S3, based on the first - level evaluation index value and the corresponding index weight, obtaining the comprehensive carbon emission efficiency evaluation result.

[0028] Among them, the Principal Components Analysis (PCA) aims to utilize the idea of dimensionality reduction to extract and transform multiple indicators into a few comprehensive indicators. In a data-driven manner, PCA summarizes the main features implicit in the comprehensive efficiency evaluation indicators of carbon emissions, which helps reduce the redundancy of multi-dimensional indicators, highlight important information, and improve the accuracy and objectivity of the evaluation results of comprehensive carbon emission efficiency. The Analytic Hierarchy Process (AHP) decomposes complex problems into several levels and factors, establishes a judgment matrix, and calculates the maximum eigenvalue and corresponding eigenvector of the matrix to obtain the weights of the importance degrees of different solutions, providing a basis for the selection of the optimal solution. Due to the advantage of expert experience, AHP can ensure the rationality and credibility of weight setting even when there is less original data. Therefore, the method provided in this embodiment combines the data advantage of the principal components analysis method with the expert experience advantage of the analytic hierarchy process method, ensuring the accuracy and objectivity of the evaluation results of comprehensive carbon emission efficiency whether the original data is sufficient or not.

[0029] In the foregoing method, the comprehensive efficiency evaluation index model of carbon emissions is pre-constructed, including multiple first-level evaluation indicators, and each first-level evaluation indicator includes multiple second-level evaluation indicators. Each second-level evaluation indicator has a corresponding pre-designed calculation formula. Based on this, as Figure 2 shown, step S2 specifically includes: step S21, determining at least one second-level evaluation index value of the object to be evaluated. Optionally, the evaluation objects include industrial parks and enterprises; step S22, using the principal components analysis method to perform dimensionality reduction processing on the second-level evaluation indicators to obtain the first-level evaluation index values; step S23, based on the first-level evaluation index values, using the analytic hierarchy process method to determine the corresponding index weights.

[0030] Optionally, the first-level evaluation indicators include at least one of the following: carbon emission volume, carbon emission intensity, carbon emission growth rate, and carbon emission stability. Specifically:

[0031] (1) The second-level evaluation indicators of carbon emission volume include at least one of the following: annual total carbon dioxide emissions, maximum monthly carbon dioxide emissions, minimum monthly carbon dioxide emissions, and average annual carbon dioxide emissions per household. Exemplarily:

[0032] Annual total carbon dioxide emissions (tons) = ∑(Monthly carbon dioxide emissions within a natural year);

[0033] Maximum monthly carbon dioxide emissions (tons) = max(Monthly carbon dioxide emissions within a natural year);

[0034] Minimum monthly carbon dioxide emissions = min(Monthly carbon dioxide emissions within a natural year);

[0035] Total annual carbon dioxide emissions per household (tons) = Total annual carbon dioxide emissions (tons) / Total number of households.

[0036] (2) The secondary evaluation indicators of carbon emission intensity include at least one of the following: Carbon dioxide emissions per unit of industrial added value and carbon dioxide emissions per unit area. Exemplarily:

[0037]

[0038] (3) The secondary evaluation indicators of carbon emission growth rate include at least one of the following: Carbon dioxide emission growth rate, annual growth rate of carbon dioxide emissions per unit of industrial added value, and annual growth rate of carbon dioxide emissions per unit area. Exemplarily:

[0039]

[0040] And the calculation formula for carbon emissions per unit of industrial added value is:

[0041]

[0042] And the calculation formula for carbon emissions per unit area is:

[0043]

[0044] (4) The secondary evaluation indicators of carbon emission stability include at least one of the following: Degree of year-on-year fluctuation of carbon dioxide emissions and degree of year-on-year fluctuation of carbon emission intensity. Exemplarily:

[0045]

[0046] In the formula, N represents the total number of months in a natural year, and the calculation formula for the year-on-year growth rate of carbon emissions is:

[0047]

[0048] And the calculation formulas for the year-on-year growth rate of carbon emission intensity and carbon dioxide emission intensity are respectively:

[0049]

[0050] Optionally, step S22 specifically includes: performing standardization processing on the secondary evaluation indicator values; forming a data matrix with the standardized secondary evaluation indicator values; calculating the covariance matrix of the data matrix; performing eigenvalue and eigenvector decomposition on the covariance matrix to obtain the explained variance of each principal component; selecting the principal components with the cumulative explained variance reaching above the preset threshold according to the eigenvalue size; and linearly combining the scores of the selected principal components to obtain the corresponding primary evaluation indicator values.

[0051] Optionally, step S23 specifically includes: based on the first-level evaluation index values, introducing expert experience to obtain a judgment matrix; after normalizing the judgment matrix, calculating the maximum eigenvalue and the corresponding eigenvector of the judgment matrix to obtain the corresponding weight vector.

[0052] Optionally, step S3 specifically includes: the comprehensive carbon emission efficiency evaluation result is determined by the comprehensive efficiency score, and the calculation formula for the comprehensive efficiency score is:

[0053]

[0054] In the formula, A represents the comprehensive efficiency score, W i represents the weight of the i-th first-level evaluation index, and s i represents the standardized score of the i-th first-level evaluation index.

[0055] Furthermore, according to the calculation result of the comprehensive efficiency score and in combination with the pre-set rating criteria, the final comprehensive carbon emission efficiency evaluation result can be determined. For example, the following rating criteria are adopted: when the comprehensive efficiency score is in the interval [85, 100], the comprehensive carbon emission efficiency evaluation result is considered excellent; when the comprehensive efficiency score is in the interval [70, 85), the comprehensive carbon emission efficiency evaluation result is considered good; when the comprehensive efficiency score is in the interval [60, 70), the comprehensive carbon emission efficiency evaluation result is considered average; when the comprehensive efficiency score is in the interval [0, 60), the comprehensive carbon emission efficiency evaluation result is considered poor.

[0056] Embodiment 2:

[0057] This embodiment provides a comprehensive carbon emission efficiency evaluation system, which includes a data acquisition module, an evaluation index value and weight acquisition module, and a comprehensive efficiency evaluation module. Specifically: the data acquisition module is used to acquire carbon emission data; the evaluation index value and weight acquisition module is used to obtain at least one first-level evaluation index value and the index weight of each first-level evaluation index based on the carbon emission data and the pre-constructed comprehensive carbon emission efficiency evaluation index model. The comprehensive carbon emission efficiency evaluation index model includes multiple first-level evaluation indexes; the comprehensive carbon emission efficiency evaluation module is used to obtain the comprehensive carbon emission efficiency evaluation result based on the first-level evaluation index value and the corresponding index weight. The specific execution processes of each module in the system are basically the same as the implementation processes of the steps in the method of Embodiment 1, and will not be elaborated here.

[0058] Furthermore, this embodiment also provides a comprehensive carbon emission efficiency evaluation device, which includes a memory, a processor, and a program stored in the memory. When the processor executes the program, it implements one or more steps of the method in Embodiment 1. The device processor includes a central processing unit (CPU), which can execute various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or computer program instructions loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for device operation can also be stored. The CPU, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus. Multiple components in the device are connected to the I / O interface, including: an input unit, such as a keyboard, a mouse, etc.; an output unit, such as various types of displays, speakers, etc.; a storage unit, such as a disk, an optical disc, etc.; and a communication unit, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit allows the device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks. The processing unit executes each of the methods and processes described above, such as one or more steps of the method in Embodiment 1. For example, in some embodiments, each step of the method in Embodiment 1 can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device via the ROM and / or the communication unit. When the computer program is loaded into the RAM and executed by the CPU, one or more steps in Embodiment 1 can be executed. Alternatively, in other embodiments, the CPU can be configured to execute one or more steps of the method in Embodiment 1 by any other appropriate means (e.g., by means of firmware). The functions described above can be at least partially executed by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), system on a chip (SOC), complex programmable logic devices (CPLD), and so on.

[0059] Further, this embodiment also provides a storage medium, on which a program is stored, and when the program is executed, one or more steps of the method in Embodiment 1 are implemented. The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, so that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or server. In the context of the present invention, a computer-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0060] The preferred specific embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art can make many modifications and variations based on the concept of the present invention without creative efforts. Therefore, all technical solutions that can be obtained by those skilled in the art in the technical field of the present invention through logical analysis, reasoning, or limited experiments based on the concept of the present invention on the basis of the prior art should fall within the protection scope determined by the claims.

Claims

1. A method for evaluating the comprehensive efficiency of carbon emissions, characterized in that: The following steps are involved: S1, obtain carbon emission data; S2, based on the carbon emission data and a pre-constructed carbon emission comprehensive efficiency evaluation index model, using principal component analysis and analytic hierarchy process to obtain at least one first-level evaluation index value and an index weight of each first-level evaluation index, wherein the carbon emission comprehensive efficiency evaluation index model includes multiple first-level evaluation indicators; S3, obtaining a carbon emission comprehensive efficiency evaluation result based on the first-level evaluation index value and the corresponding index weight.

2. The carbon emission comprehensive efficiency evaluation method according to claim 1 is characterized in that: Each of the first-level evaluation indicators includes multiple second-level evaluation indicators, and S2 specifically includes: S21, determining at least one secondary evaluation index value of the object to be evaluated; S22, using principal component analysis to reduce the dimension of the secondary evaluation index to obtain a primary evaluation index value; S23, based on the first-level evaluation index value, determine the corresponding index weight using the hierarchical analysis method.

3. The carbon emission comprehensive efficiency evaluation method according to claim 2 is characterized in that: The first-level evaluation indicators include at least one of the following: carbon emission volume, carbon emission intensity, carbon emission growth rate and carbon emission stability.

4. The carbon emission comprehensive efficiency evaluation method according to claim 3 is characterized in that: The secondary evaluation index of carbon emission volume includes at least one of the following: annual total carbon dioxide emissions, maximum monthly carbon dioxide emissions, minimum monthly carbon dioxide emissions and annual average carbon dioxide emissions per household; The secondary evaluation index of carbon emission intensity includes at least one of the following: carbon dioxide emissions per unit of industrial added value and carbon dioxide emissions per unit area; The secondary evaluation index of the carbon emission growth rate includes at least one of the following: carbon dioxide emission growth rate, annual growth rate of carbon dioxide emissions per unit of industrial added value and annual growth rate of carbon dioxide emissions per unit area; The secondary evaluation index of carbon emission stability includes at least one of the following: the year-on-year fluctuation degree of carbon dioxide emissions and the year-on-year fluctuation degree of carbon dioxide emission intensity.

5. The carbon emission comprehensive efficiency evaluation method according to claim 2 is characterized in that: The S22 specifically includes: Standardizing the secondary evaluation index values; The standardized secondary evaluation index values ​​are combined into a data matrix; Calculating a covariance matrix of the data matrix; Decomposing the covariance matrix by eigenvalues ​​and eigenvectors to obtain the explained variance of each principal component; According to the size of the eigenvalue, the principal component whose cumulative explained variance reaches above the preset threshold is selected; After linearly combining the selected principal component scores, the corresponding first-level evaluation index value is obtained.

6. The carbon emission comprehensive efficiency evaluation method according to claim 5 is characterized in that: The S23 specifically includes: Based on the first-level evaluation index value, expert experience is introduced to obtain a judgment matrix; After the judgment matrix is ​​normalized, the corresponding weight vector is obtained by calculating the maximum eigenvalue and the corresponding eigenvector of the judgment matrix.

7. The carbon emission comprehensive efficiency evaluation method according to claim 1 is characterized in that: In S3, the carbon emission comprehensive efficiency evaluation result is determined by a comprehensive efficiency score, and the calculation formula of the comprehensive efficiency score is: In the formula, A represents the comprehensive efficiency score, W i represents the weight of the i-th primary evaluation index, s i Represents the standardized score of the i-th first-level evaluation indicator.

8. A carbon emission comprehensive efficiency evaluation system, characterized in that: It includes data collection module, evaluation index value and weight acquisition module and comprehensive efficiency evaluation module, among which: The data acquisition module is used to obtain carbon emission data; The evaluation index value and weight acquisition module is used to obtain at least one first-level evaluation index value and the index weight of each first-level evaluation index by using principal component analysis and hierarchical analysis based on the carbon emission data and a pre-constructed carbon emission comprehensive efficiency evaluation index model, wherein the carbon emission comprehensive efficiency evaluation index model includes multiple first-level evaluation indicators; The carbon emission comprehensive efficiency evaluation module is used to obtain the carbon emission comprehensive efficiency evaluation result based on the first-level evaluation index value and the corresponding index weight.

9. A carbon emission comprehensive efficiency evaluation device, comprising a memory, a processor, and a program stored in the memory, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A storage medium having a program stored thereon, characterized in that: When the program is executed, the method according to any one of claims 1 to 7 is implemented.

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