Enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling

Abstract

The application discloses an enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling, and the method comprises the following steps: collecting production activity data, energy consumption data, material flow data, energy flow data and carbon emission factor data of each enterprise in an enterprise cluster to be evaluated within an evaluation period, and pre-processing the collected data; constructing a cluster material flow-energy flow coupling model; establishing an enterprise cluster carbon emission evaluation index system; based on the cluster material flow-energy flow coupling model and the enterprise cluster carbon emission evaluation index system, calculating the overall collaborative carbon reduction amount of the cluster, and using a cooperative game Shapley value method to allocate the collaborative carbon reduction amount to each member enterprise, and outputting the collaborative carbon reduction contribution degree ranking of each enterprise. The application realizes scientific quantification of the collaborative carbon reduction effect of the enterprise cluster and fair evaluation of the contribution degrees of the enterprises.

Description

Technical Field

[0001] This invention relates to the field of cluster-based collaborative carbon reduction, and more specifically, to an evaluation method for enterprise cluster-based collaborative carbon reduction based on material flow-energy flow coupling. Background Technology

[0002] Currently, carbon emission accounting and assessment mostly focus on individual enterprises, paying attention to their own energy consumption boundaries and direct emissions. However, modern industrial production often exhibits clustering characteristics, that is, enterprises in the upstream and downstream of the industrial chain (raw material suppliers, core manufacturers, distributors and recyclers) form closely cooperating enterprise clusters within a specific region or industrial ecosystem.

[0003] In this cluster model, carbon emissions are highly interconnected and transferable. A single company's emission reduction measures may be constrained by the carbon footprint of its upstream suppliers, or they may create carbon reduction opportunities for downstream companies. Existing technologies, such as carbon accounting methods based on single companies, cannot effectively measure the overall carbon reduction effect generated by the synergy of material and energy flows among companies (waste heat recovery, waste resource utilization, and intensive logistics), i.e., the synergistic carbon reduction effect of "1+1>2". Furthermore, the lack of quantitative evaluation methods for the synergistic contributions of individual companies within the cluster makes it difficult to incentivize the cluster as a whole to optimize for low carbon emissions.

[0004] Chinese invention application No. 202310579032.0 discloses "A Collaborative Carbon Reduction Method Applicable to Municipal Power Grid Companies". The method includes the following steps: Step 1: By statistically analyzing relevant power grid data within the jurisdiction of the target power grid company, a power grid data model is built based on the network topology diagram, and a carbon reduction target is introduced. Carbon reduction is achieved by optimizing the transmission and distribution network; Step 2: A system revenue model corresponding to the target power grid company is constructed in different power transactions; Step 3: A dual-objective optimization model of system revenue and low-carbon target is constructed and solved to obtain a scheduling scheme. Summary of the Invention

[0005] To address the technical problems of existing carbon accounting methods being unable to quantify the collaborative carbon reduction effect of enterprise clusters and making it difficult to fairly evaluate the contributions of each enterprise, this invention provides an evaluation method for collaborative carbon reduction of enterprise clusters based on material flow-energy flow coupling. The technical solution adopted by this invention is as follows: The first aspect of this invention provides a collaborative carbon reduction evaluation method for enterprise clusters based on material flow-energy flow coupling, the method comprising: Data on production activities, energy consumption, material flow, energy flow, and carbon emission factors of each enterprise in the enterprise cluster to be evaluated during the evaluation period are collected, and the collected data are preprocessed. Construct a clustered material flow-energy flow coupling model; Establish a carbon emission assessment index system for enterprise clusters; Based on the cluster material flow-energy flow coupling model and the enterprise cluster carbon emission evaluation index system, the overall collaborative carbon reduction of the cluster is calculated, and the collaborative carbon reduction is allocated to each member enterprise using the cooperative game Shapley value method, and the ranking of each enterprise's collaborative carbon reduction contribution is output.

[0006] As a preferred embodiment, the production activity data includes the output of each product. The energy consumption data includes the consumption of various types of energy. ,in Number the company The energy type is specified; the material flow data includes raw material consumption. Waste generation and the amount of material exchange between enterprises The energy flow data includes the amount of energy exchanged between enterprises. Carbon emission factor data includes carbon emission factors from various energy sources. And the implicit carbon emission factors of various raw materials .

[0007] As a preferred embodiment, the preprocessing includes cleaning, missing value imputation, and unit unification and normalization.

[0008] As a preferred embodiment, the method for constructing a clustered material flow-energy flow coupled model includes: Assume the cluster contains Individual enterprises, a collection of enterprises ; Constructing the material flow matrix :

[0009] in Indicates from the enterprise Flow to enterprises The amount of material, The data comes directly from inter-company material exchange records; Constructing the energy flow matrix :

[0010] in Indicates from the enterprise Flow to enterprises energy amount The data comes directly from energy exchange records between enterprises; Construct the carbon emission function under the scenario of independent enterprise operation:

[0011] in, Indicates enterprise Carbon emissions under stand-alone operating scenario; Indicates enterprise The first consumed The amount of this type of energy; Indicates the first Carbon emission factors of various energy sources; Indicates enterprise The first consumed The quantity of each type of raw material; Indicates the first The implicit carbon emission factors of these raw materials; Indicates the total number of energy types; Indicates the total number of raw material types; The cluster's baseline total carbon emissions are:

[0012] The actual total carbon emissions of the cluster are:

[0013] in and Representing enterprises In the scenario of collaborative operation, the first The actual consumption of this type of energy and the first The actual consumption of the raw materials; The overall carbon reduction of the cluster is:

[0014] For any sub-alliance Its carbon emissions are defined as:

[0015] in, Represents a cluster of enterprises any subset of; Sub-alliance Carbon emissions; Sub-alliance The sum of carbon emissions of each enterprise operating independently; Sub-alliance Carbon reduction resulting from internal collaboration; The calculation formula is:

[0016] in, Indicates from the enterprise Flow to enterprises The amount of material, This indicates the carbon emission reduction benefit resulting from a unit of material exchange. Indicates from the enterprise Flow to enterprises energy amount This indicates the carbon emission reduction benefit resulting from a unit of energy exchange.

[0017] As a preferred embodiment, the enterprise cluster carbon emission evaluation index system includes a target layer, a criterion layer, and an index layer; The target layer includes the comprehensive index of collaborative carbon reduction among enterprise clusters. The criteria layer includes resource sharing synergy, energy cascade utilization, carbon flow optimization, and organizational management synergy; the indicator layer includes waste recycling rate corresponding to resource sharing synergy. and infrastructure sharing rate Waste heat recovery rate corresponding to energy cascade utilization rate Proportion of co-consumption with clean energy The implicit carbon reduction rate of the supply chain corresponding to the degree of carbon flow optimization. Synergy between carbon capture, utilization and storage This corresponds to the level of mutual trust and communication of carbon data and the number of collaborative carbon reduction projects.

[0018] As a preferred option, the enterprise cluster collaborative carbon reduction comprehensive index The calculation formula is: , in, Indicates the first The weights of each criterion layer; Indicates the first The first criterion level The weight of each indicator; Indicates the first The first criterion level Normalized values ​​of each indicator; The waste recycling rate The calculation formula is:

[0019] in, Indicates from the enterprise Flow to enterprises The amount of waste; Indicates enterprise The total amount of waste generated; The infrastructure sharing rate The calculation formula is:

[0020] in, This indicates the number of companies participating in shared infrastructure. Indicates the total number of enterprises in the cluster; The waste heat recovery rate The calculation formula is:

[0021] in, Indicates from the enterprise Flow to enterprises The residual heat; Indicates enterprise The total amount of recyclable waste heat resources generated; The proportion of clean energy co-consumption The calculation formula is:

[0022] in, This indicates the amount of clean energy that the cluster consumes through internal collaboration. This represents the total energy consumption of the cluster; The implicit carbon reduction rate of the supply chain The calculation formula is:

[0023] in, This indicates the implicit carbon emissions per unit of product within the evaluation period; This indicates the implicit carbon emissions per unit of product in the base period; Synergy between carbon capture, utilization and storage The calculation formula is:

[0024] in, Indicates enterprise The amount of CO2 captured; Indicates from the enterprise Delivered to enterprises The amount of CO2 used for utilization; This represents the total CO2 emissions of the cluster.

[0025] As a preferred approach, based on the aforementioned cluster material flow-energy flow coupling model and enterprise cluster carbon emission evaluation index system, the overall collaborative carbon reduction of the cluster is calculated, and the collaborative carbon reduction is allocated to each member enterprise using the cooperative game Shapley value method. The method for outputting the ranking of each enterprise's collaborative carbon reduction contribution includes: enterprise The synergistic carbon reduction contribution is calculated using the Shapley value:

[0026] in, Indicates enterprise The Shapley value, i.e., the enterprise's Contribution to cluster-based collaborative carbon reduction; Indicates no enterprises Any of the sub-alliances; Indicates alliance The number of companies in the country; Indicates the total number of enterprises in the cluster; Indicates alliance Carbon emissions; Indicates alliance Join the company Carbon emissions after; difference Indicates enterprise Join the alliance The resulting reduction in carbon emissions is the marginal contribution.

[0027] As a preferred option, the Shapley values ​​of each enterprise are... Sort the enterprises from largest to smallest and output the ranking of their collaborative carbon reduction contributions.

[0028] A second aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the aforementioned enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling.

[0029] A third aspect of the present invention provides a computer device, including a storage medium, a processor, and a computer program stored in the storage medium and executable by the processor, wherein the computer program, when executed by the processor, implements the steps of the aforementioned enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling.

[0030] Compared with the prior art, the beneficial effects of this invention are: This invention constructs a coupled material-energy flow model to systematically characterize the synergistic relationship between material and energy within an enterprise cluster, overcoming the limitations of individual enterprise evaluation and quantifying the overall synergistic carbon reduction of the cluster. By allocating synergistic carbon reduction based on the Shapley value method of cooperative game theory, it fairly quantifies the marginal contribution of each enterprise to the cluster's carbon reduction, effectively avoiding the "free-rider" phenomenon and outputting an incentive-based contribution ranking. By establishing a hierarchical indicator system encompassing four dimensions—resource sharing, energy cascade utilization, carbon flow optimization, and organizational management—it provides multi-dimensional and comprehensive data support for cluster low-carbon management. Through comparative calculations using both independent and collaborative operation scenarios, it clearly separates the net carbon reduction brought about by synergistic effects, improving the interpretability and credibility of the evaluation results. By utilizing the carbon emission function of the sub-alliance to decompose the carbon reduction benefits of material / energy exchange, it provides a unified basic data interface for Shapley value calculation, ensuring the scientific nature and repeatability of the allocation results. Attached Figure Description

[0031] Figure 1 The flowchart of the enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling provided in this embodiment is shown. Detailed Implementation

[0032] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the invention. It should be understood that the described embodiments are merely some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of the embodiments of this application.

[0033] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0034] In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims. In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0035] Furthermore, in the description of this application, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. The invention will be further described below with reference to the accompanying drawings and embodiments.

[0036] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0037] Example 1 Please refer to Figure 1 This embodiment provides a collaborative carbon reduction evaluation method for enterprise clusters based on material flow-energy flow coupling, the method including: S1: Collect production activity data, energy consumption data, material flow data, energy flow data, and carbon emission factor data of each enterprise in the enterprise cluster to be evaluated during the evaluation period, and preprocess the collected data. In one specific embodiment, the production activity data includes the output of each product. The energy consumption data includes the consumption of various types of energy. ,in Number the company The energy type is specified; the material flow data includes raw material consumption. Waste generation and the amount of material exchange between enterprises The energy flow data includes the amount of energy exchanged between enterprises. Carbon emission factor data includes carbon emission factors from various energy sources. And the implicit carbon emission factors of various raw materials .

[0038] In one specific embodiment, the preprocessing includes cleaning, missing value imputation, and unit unification and normalization.

[0039] Specifically, the following data is collected from each enterprise within the cluster to be evaluated during the evaluation period (usually one calendar year): Production activity data: Output of major products .

[0040] Energy consumption data: Consumption of various energy sources (electricity, coal, natural gas, heat, etc.) ,in Number the company It refers to the type of energy.

[0041] Material flow data: Raw material consumption Waste generation and the amount of material exchange between enterprises (From the enterprise) Flow to enterprises (Material quantity).

[0042] Energy flow data: Energy exchange between enterprises (From the enterprise) Flow to enterprises Energy resources, such as steam, waste heat, etc.

[0043] Carbon emission factor data: Carbon emission factors for various energy sources Implicit carbon emission factors of various raw materials .

[0044] Collaborative management of data: infrastructure sharing status, number of collaborative carbon reduction projects, carbon data sharing level, etc.

[0045] The collected data undergoes preprocessing, including cleaning (outlier identification and correction, logical consistency verification), missing value imputation (mean / median imputation, interpolation), unit unification and normalization (range standardization), etc., to form a standardized dataset.

[0046] S2: Construct a cluster material flow-energy flow coupling model; In one specific embodiment, the method for constructing a clustered material flow-energy flow coupled model includes: Assume the cluster contains Individual enterprises, a collection of enterprises ; Constructing the material flow matrix :

[0047] in Indicates from the enterprise Flow to enterprises Material quantity (tons / year). The data comes directly from inter-company material exchange records; Constructing the energy flow matrix :

[0048] in Indicates from the enterprise Flow to enterprises Energy quantity (GJ / year) The data comes directly from energy exchange records between enterprises; Construct the carbon emission function under the scenario of independent enterprise operation:

[0049] in, Indicates enterprise Carbon emissions under stand-alone operating scenario; Indicates enterprise The first consumed The amount of this type of energy; Indicates the first Carbon emission factors of various energy sources; Indicates enterprise The first consumed The quantity of each type of raw material; Indicates the first The implicit carbon emission factors of these raw materials; Indicates the total number of energy types; Indicates the total number of raw material types; It should be noted that, under the scenario of independent operation of enterprises (i.e., assuming no exchange of matter or energy between enterprises), the enterprise... carbon emissions It is determined by its own activity level and emission factors.

[0050] The cluster's baseline total carbon emissions are:

[0051] It should be noted that the total baseline carbon emissions for the cluster are... This represents the sum of carbon emissions of each company operating independently.

[0052] It should be noted that in a cluster collaborative operation scenario, the exchange of materials and energy between enterprises will affect each other's carbon emissions. The actual total carbon emissions of the cluster... Defined as the sum of carbon emissions of all enterprises, calculated based on actual observed energy and material consumption data under a collaborative operation scenario:

[0053] in and Representing enterprises In the scenario of collaborative operation, the first The actual consumption of this type of energy (which already implies synergistic effects) and the first The actual consumption of the raw materials; The overall carbon reduction of the cluster is:

[0054] For any sub-alliance Its carbon emissions are defined as:

[0055] in, Represents a cluster of enterprises any subset of; Sub-alliance Carbon emissions; Sub-alliance The sum of carbon emissions of each enterprise operating independently; Sub-alliance Carbon reduction resulting from internal collaboration; The calculation formula is:

[0056] in, Indicates from the enterprise Flow to enterprises The amount of material, This represents the carbon emission reduction benefit (tCO2 / ton) resulting from a unit material exchange, calculated by comparing the implicit carbon of the raw materials before and after the substitution (e.g., if a company...). Used by enterprises Waste replaces virgin raw materials ,but ); Indicates from the enterprise Flow to enterprises energy amount This means that the carbon emission reduction benefit from a unit of energy exchange is equal to the emission factor of the energy source being replaced (for example, if a company...). Used by enterprises Waste heat can replace purchased heat. This formula decomposes the synergistic carbon reduction into the sum of the contributions of each material / energy exchange, providing a basis for Shapley value calculation.

[0057] S3: Establish a carbon emission evaluation index system for enterprise clusters; In one specific embodiment, the enterprise cluster carbon emission evaluation index system includes a target layer, a criterion layer, and an index layer; The target layer includes the comprehensive index of collaborative carbon reduction among enterprise clusters. The criteria layer includes resource sharing synergy, energy cascade utilization, carbon flow optimization, and organizational management synergy; the indicator layer includes waste recycling rate corresponding to resource sharing synergy. and infrastructure sharing rate Waste heat recovery rate corresponding to energy cascade utilization rate Proportion of co-consumption with clean energy The implicit carbon reduction rate of the supply chain corresponding to the degree of carbon flow optimization. Synergy between carbon capture, utilization and storage This corresponds to the level of mutual trust and communication of carbon data and the number of collaborative carbon reduction projects.

[0058] In one specific embodiment, the enterprise cluster collaborative carbon reduction comprehensive index The calculation formula is: , in, Indicates the first The weights of each criterion layer; Indicates the first The first criterion level The weight of each indicator; Indicates the first The first criterion level Normalized values ​​of each indicator; The waste recycling rate The calculation formula is:

[0059] in, Indicates from the enterprise Flow to enterprises The amount of waste; Indicates enterprise The total amount of waste generated; The infrastructure sharing rate The calculation formula is:

[0060] in, This indicates the number of companies participating in shared infrastructure. Indicates the total number of enterprises in the cluster; The waste heat recovery rate The calculation formula is:

[0061] in, Indicates from the enterprise Flow to enterprises The residual heat; Indicates enterprise The total amount of recyclable waste heat resources generated; The proportion of clean energy co-consumption The calculation formula is:

[0062] in, This indicates the amount of clean energy that the cluster consumes through internal collaboration. This represents the total energy consumption of the cluster; The implicit carbon reduction rate of the supply chain The calculation formula is:

[0063] in, This indicates the implicit carbon emissions per unit of product within the evaluation period; This indicates the implicit carbon emissions per unit of product in the base period; Synergy between carbon capture, utilization and storage The calculation formula is:

[0064] in, Indicates enterprise The amount of CO2 captured; Indicates from the enterprise Delivered to enterprises The amount of CO2 used for utilization; This represents the total CO2 emissions of the cluster.

[0065] S4: Based on the cluster material flow-energy flow coupling model and the enterprise cluster carbon emission evaluation index system, calculate the overall collaborative carbon reduction of the cluster, and use the cooperative game Shapley value method to distribute the collaborative carbon reduction to each member enterprise, and output the ranking of each enterprise's collaborative carbon reduction contribution. In a specific embodiment, based on the cluster material flow-energy flow coupling model and the enterprise cluster carbon emission evaluation index system, the overall collaborative carbon reduction of the cluster is calculated, and the collaborative carbon reduction is allocated to each member enterprise using the cooperative game Shapley value method. The method for outputting the ranking of each enterprise's collaborative carbon reduction contribution includes: enterprise The synergistic carbon reduction contribution is calculated using the Shapley value:

[0066] in, Indicates enterprise The Shapley value, i.e., the enterprise's Contribution to cluster-based collaborative carbon reduction; Indicates no enterprises Any of the sub-alliances; Indicates alliance The number of companies in the country; Indicates the total number of enterprises in the cluster; Indicates alliance Carbon emissions; Indicates alliance Join the company Carbon emissions after; difference Indicates enterprise Join the alliance The resulting reduction in carbon emissions is the marginal contribution.

[0067] In one specific embodiment, the Shapley values ​​of each enterprise are... Sort the enterprises from largest to smallest and output the ranking of their collaborative carbon reduction contributions.

[0068] Example 2 This embodiment provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling described in Embodiment 1.

[0069] Example 3 This embodiment provides a computer device, including a storage medium, a processor, and a computer program stored in the storage medium and executable by the processor. When the computer program is executed by the processor, it implements the steps of the enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling described in Embodiment 1.

[0070] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A collaborative carbon reduction evaluation method for enterprise clusters based on material flow-energy flow coupling, characterized in that, The method includes: Data on production activities, energy consumption, material flow, energy flow, and carbon emission factors of each enterprise in the enterprise cluster to be evaluated during the evaluation period are collected, and the collected data are preprocessed. Construct a clustered material flow-energy flow coupling model; Establish a carbon emission assessment index system for enterprise clusters; Based on the cluster material flow-energy flow coupling model and the enterprise cluster carbon emission evaluation index system, the overall collaborative carbon reduction of the cluster is calculated, and the collaborative carbon reduction is allocated to each member enterprise using the cooperative game Shapley value method, and the ranking of each enterprise's collaborative carbon reduction contribution is output.

2. The enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling according to claim 1, characterized in that, The production activity data includes the output of each product. The energy consumption data includes the consumption of various types of energy. ,in Number the company The energy type is specified; the material flow data includes raw material consumption. Waste generation and the amount of material exchange between enterprises The energy flow data includes the amount of energy exchanged between enterprises. Carbon emission factor data includes carbon emission factors from various energy sources. And the implicit carbon emission factors of various raw materials .

3. The enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling according to claim 2, characterized in that, The preprocessing includes cleaning, missing value imputation, and unit unification and normalization.

4. The enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling according to claim 3, characterized in that, The method for constructing a clustered material flow-energy flow coupled model includes: Assume the cluster contains Individual enterprises, a collection of enterprises ; Constructing the material flow matrix : in Indicates from the enterprise Flow to enterprises The amount of material, The data comes directly from inter-company material exchange records; Constructing the energy flow matrix : in Indicates from the enterprise Flow to enterprises energy amount The data comes directly from energy exchange records between enterprises; Construct the carbon emission function under the scenario of independent enterprise operation: in, Indicates enterprise Carbon emissions under stand-alone operating scenario; Indicates enterprise The first consumed The amount of this type of energy; Indicates the first Carbon emission factors of various energy sources; Indicates enterprise The first consumed The quantity of each type of raw material; Indicates the first The implicit carbon emission factors of these raw materials; Indicates the total number of energy types; Indicates the total number of raw material types; The cluster's baseline total carbon emissions are: The actual total carbon emissions of the cluster are: in and Representing enterprises In the scenario of collaborative operation, the first The actual consumption of this type of energy and the first The actual consumption of the raw materials; The overall carbon reduction of the cluster is: For any sub-alliance Its carbon emissions are defined as: in, Represents a cluster of enterprises any subset of; Sub-alliance Carbon emissions; Sub-alliance The sum of carbon emissions of each enterprise operating independently; Sub-alliance Carbon reduction resulting from internal collaboration; The calculation formula is: in, Indicates from the enterprise Flow to enterprises The amount of material, This indicates the carbon emission reduction benefit resulting from a unit of material exchange. Indicates from the enterprise Flow to enterprises energy amount This indicates the carbon emission reduction benefit resulting from a unit of energy exchange.

5. The enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling according to claim 1, characterized in that, The enterprise cluster carbon emission evaluation index system includes a target layer, a criterion layer, and an index layer. The target layer includes the comprehensive index of collaborative carbon reduction among enterprise clusters. The criteria layer includes resource sharing synergy, energy cascade utilization, carbon flow optimization, and organizational management synergy; the indicator layer includes waste recycling rate corresponding to resource sharing synergy. and infrastructure sharing rate ; Waste heat recovery rate corresponding to energy cascade utilization Proportion of co-consumption with clean energy The implicit carbon reduction rate of the supply chain corresponding to the degree of carbon flow optimization. Synergy between carbon capture, utilization and storage ; The level of mutual trust and communication of carbon data and the number of collaborative carbon reduction projects correspond to the degree of coordination in organizational management.

6. The enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling according to claim 5, characterized in that, The comprehensive index of collaborative carbon reduction in enterprise clusters The calculation formula is: ， in, Indicates the first The weights of each criterion layer; Indicates the first The first criterion level The weight of each indicator; Indicates the first The first criterion level Normalized values ​​of each indicator; The waste recycling rate The calculation formula is: in, Indicates from the enterprise Flow to enterprises The amount of waste; Indicates enterprise The total amount of waste generated; The infrastructure sharing rate The calculation formula is: in, This indicates the number of companies participating in shared infrastructure. Indicates the total number of enterprises in the cluster; The waste heat recovery rate The calculation formula is: in, Indicates from the enterprise Flow to enterprises The residual heat; Indicates enterprise The total amount of recyclable waste heat resources generated; The proportion of clean energy co-consumption The calculation formula is: in, This indicates the amount of clean energy that the cluster consumes through internal collaboration. This represents the total energy consumption of the cluster; The implicit carbon reduction rate of the supply chain The calculation formula is: in, This indicates the implicit carbon emissions per unit of product within the evaluation period; This indicates the implicit carbon emissions per unit of product in the base period; Synergy between carbon capture, utilization and storage The calculation formula is: in, Indicates enterprise The amount of CO2 captured; Indicates from the enterprise Delivered to enterprises The amount of CO2 used for utilization; This represents the total CO2 emissions of the cluster.

7. The enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling according to claim 4, characterized in that, Based on the aforementioned cluster material flow-energy flow coupling model and enterprise cluster carbon emission evaluation index system, the overall collaborative carbon reduction of the cluster is calculated, and the collaborative carbon reduction is allocated to each member enterprise using the cooperative game Shapley value method. The method for outputting the ranking of each enterprise's collaborative carbon reduction contribution includes: enterprise The synergistic carbon reduction contribution is calculated using the Shapley value: in, Indicates enterprise The Shapley value, i.e., the enterprise's Contribution to cluster-based collaborative carbon reduction; Indicates no enterprises Any of the sub-alliances; Indicates alliance The number of companies in the country; Indicates the total number of enterprises in the cluster; Indicates alliance Carbon emissions; Indicates alliance Join the company Carbon emissions after; difference Indicates enterprise Join the alliance The resulting reduction in carbon emissions is the marginal contribution.

8. The enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling according to claim 7, characterized in that, Shapley values ​​of each company Sort the enterprises from largest to smallest and output the ranking of their collaborative carbon reduction contributions.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling as described in any one of claims 1 to 8.

10. A computer device, characterized in that: The system includes a storage medium, a processor, and a computer program stored in the storage medium and executable by the processor, wherein the computer program, when executed by the processor, implements the steps of the enterprise cluster collaborative carbon reduction evaluation method based on material flow-energy flow coupling as described in any one of claims 1 to 8.

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