Engineering project carbon emission reduction management method

Abstract

The invention discloses an engineering project carbon emission reduction management method, and belongs to the technical field of carbon emission management, and the method comprises the following steps: S1, obtaining a carbon emission source of a to-be-managed engineering project in a use stage; s2, generating a source matrix and a transformation matrix according to the carbon emission of the carbon emission source in the use stage, and calculating a carbon emission influence factor; s3, obtaining the ontology condition of the to-be-managed engineering project, and determining the self influence factor of the to-be-managed engineering project; and S4, determining the predicted carbon emission of the to-be-managed engineering project according to the influence factor of the to-be-managed engineering project and the carbon emission influence factors of all the carbon emission sources in the use stage. The prediction of the carbon emission can provide an important reference for long-term energy conservation and emission reduction planning of the building, is helpful for formulating an emission reduction target meeting the sustainable development requirement, avoids excessive or insufficient emission reduction, and achieves the optimal balance of energy conservation and emission reduction.

Description

Technical Field

[0001] The present invention belongs to the technical field of carbon emission management, and specifically relates to a carbon emission reduction management method for an engineering project. Background Art

[0002] As global climate change becomes increasingly severe, reducing greenhouse gas emissions, especially carbon dioxide emissions, has become a major issue of concern to the international community. As one of the main sources of energy consumption and carbon emissions, the importance of carbon reduction in the construction sector is self-evident. During the use phase of buildings, a large amount of carbon emissions will be caused due to factors such as energy consumption (such as heating, cooling and lighting), aging and replacement of building materials, and waste disposal generated during operation and maintenance.

[0003] Traditionally, building carbon emission reduction management often relies on measures such as energy-saving renovation or the use of low-carbon building materials. Although these methods are effective, they lack the flexibility of early planning and dynamic management. In order to more effectively control and manage the carbon emissions of buildings during the use phase, it is necessary to predict the carbon emissions of construction projects.

[0004] In the existing technology, the prediction and evaluation of building carbon emissions mostly rely on static real-time data collection. Even if neural networks are used for prediction, the prediction accuracy is low, and the dynamic changes in the use of buildings are not taken into account. In addition, there is a lack of in-depth research on the relationship between the building's own characteristics (such as structure, materials and thermal insulation performance) and carbon emissions.

[0005] Therefore, it is particularly important to develop a method that can comprehensively consider various carbon emission sources during the building use phase, building characteristics and their dynamic changes, so as to accurately predict and effectively manage building carbon emissions. Summary of the invention

[0006] In order to solve the above problems, the present invention proposes a carbon emission reduction management method for engineering projects.

[0007] The technical solution of the present invention is: a method for managing carbon emission reduction in engineering projects comprises the following steps: S1. Obtain the carbon emission sources of the engineering project to be managed during the use phase; S2. Generate source matrix and transformation matrix according to the carbon emission of carbon emission sources in the use phase, and calculate carbon emission impact factors; S3. Obtain the entity situation of the engineering project to be managed and determine the self-influencing factors of the engineering project to be managed; S4. Determine the predicted carbon emissions of the engineering project to be managed based on its own influencing factors and the carbon emission influencing factors of all carbon emission sources during the use phase.

[0008] Furthermore, S2 includes the following sub-steps: S21. Determine the operating equipment corresponding to the carbon emission sources of the project to be managed during the use phase; S22. generating a source matrix for the carbon emission source according to the carbon emission of each operating equipment in the carbon emission source during the use phase; S23, generating a transformation matrix according to the maximum carbon emission and the minimum carbon emission of each operating equipment in the carbon emission source during the use phase; S24. Calculate the carbon emission impact factor based on the source matrix and transformation matrix of the carbon emission source.

[0009] Possible sources of carbon emissions from the project to be managed include fuel combustion, electricity consumption and vehicle transportation.

[0010] Electricity consumption: As the main source of carbon emissions during the building operation stage, the corresponding operating equipment includes lighting, air conditioning, elevators and heating, etc. These equipment all consume electricity, and the production of electricity (especially thermal power) will produce a large amount of carbon dioxide emissions.

[0011] Fuel combustion: Some buildings may use fossil energy such as natural gas for heating and cooking. The combustion process of these energy sources will also directly produce carbon dioxide emissions. For buildings that use regional centralized cooling and heating systems, their energy comes from external thermal power plants or energy stations. The carbon emissions corresponding to the fuel consumption in the steam production process need to be allocated to each building.

[0012] Vehicle transportation: Fuel or electricity consumed to transport goods within a construction project (such as building material distribution and waste removal) is also considered indirect emissions caused by construction operations.

[0013] The beneficial effect of the above further scheme is that in the present invention, the source matrix presents all carbon emissions in the form of specific numerical values, and the carbon emission differences between different equipment can be analyzed. The transformation matrix provides the maximum and minimum values ​​of carbon emissions of each equipment operation, analyzes the fluctuation range of carbon emissions, including carbon emissions in certain extreme cases (such as full or empty equipment), and provides a basis for predicted risks. The carbon emission impact factor comprehensively considers the information of the source matrix and the transformation matrix, and provides a comprehensive assessment of the overall carbon emissions of the project.

[0014] Further, S22 includes the following sub-steps: S221, obtaining the average carbon emissions of each operating equipment corresponding to the carbon emission source during the use phase, and generating a carbon emission data set of the carbon emission source; S222, clustering the carbon emission data set of the carbon emission source, and determining the average value of each operating device in the corresponding cluster; S223, sorting the average values ​​of each running device in the corresponding cluster from small to large, and generating a source matrix.

[0015] The beneficial effect of the above further scheme is that in the present invention, by calculating the mean of the carbon emissions of the operating equipment, a representative value can be obtained, which represents the carbon emission level of the operating equipment during long-term use. Cluster analysis determines the characteristic value of each operating equipment, reflecting the carbon emission level of the equipment in each cluster, as comprehensive information of the carbon emission source.

[0016] Further, in S223, the source matrix The expression is: ; In the formula, It represents the average value of the first running device in the corresponding cluster after sorting from small to large. It represents the average carbon emission of the first operating equipment in the use phase after sorting from small to large. It represents the average value of the second running device in the corresponding cluster after sorting from small to large. It represents the average carbon emission of the second operating equipment in the use phase after sorting from small to large. Indicates the first The average value of the running devices in the corresponding cluster, Indicates the first The average carbon emissions of each operating equipment during the use phase, It means constructing a diagonal matrix, Represents the identity matrix.

[0017] Further, S23 includes the following sub-steps: S231, extracting the maximum carbon emissions of each operating device corresponding to the carbon emission source during the use phase, and generating a first characteristic column vector; S232, extracting the minimum carbon emissions of each operating device corresponding to the carbon emission source during the use phase, and generating a second characteristic column vector; S233. Use the covariance matrix between the first eigenvalue column vector and the second eigenvalue column vector as a transformation matrix.

[0018] The beneficial effect of the above further scheme is: in the present invention, the peak emission of each operating equipment can be reflected by extracting the maximum carbon emission, the minimum carbon emission represents the emission level of the equipment under the optimal operating conditions, the covariance matrix can reflect the extreme value of the carbon emission of all operating equipment, and the dimension reduction of data can be realized. The sum of the maximum singular value of the source matrix and the maximum singular value of the transformation matrix is ​​used as the carbon emission influencing factor, which can comprehensively reflect the changes in the emission characteristics of the carbon emission source.

[0019] Furthermore, in S24, the sum of the maximum singular value of the source matrix and the maximum singular value of the transformation matrix is ​​used as the carbon emission impact factor of the carbon emission source.

[0020] Furthermore, in S3, the self-impact factor The calculation formula is: ; In the formula, Indicates the first The heat transfer coefficient of the outer surface of the wall grid is: Indicates the first The heat transfer coefficient of the inner surface of the wall grid is Indicates the number of wall grids of the project to be managed.

[0021] The beneficial effect of the above further scheme is: in the present invention, the thermal insulation performance of the wall has an important influence on the energy consumption and carbon emissions of the building. There are many wall bodies in the building, so grid division is required. The outer surface heat transfer coefficient and the inner surface heat transfer coefficient respectively reflect the heat exchange capacity between the wall and the external environment and the indoor environment. The size of these two coefficients directly affects the absorption, storage and release of heat by the wall, and thus affects the energy consumption and carbon emissions of the building. δ is an indicator that combines the inner and outer surface heat transfer coefficients and the number of wall grids. It is used to quantify the heat transfer characteristics of the wall and evaluate the contribution of the wall to the overall energy consumption and carbon emissions of the building.

[0022] Further, S4 includes the following sub-steps: S41. Construct a carbon emission trend function based on the self-influencing factors of the engineering project to be managed and the carbon emission influencing factors of all carbon emission sources during the use phase; S42. Determine the predicted carbon emissions of the engineering project to be managed using the carbon emission trend function.

[0023] The beneficial effect of the above further scheme is: in the present invention, when constructing the carbon emission trend function, the inherent influencing factors of the engineering project to be managed and the carbon emission influencing factors of all carbon emission sources during the use phase are taken into account, which covers both the architectural characteristics of the construction project itself and the carbon emissions from various sources during the operation process.

[0024] Furthermore, in S41, the carbon emission trend function The expression is: ; In the formula, Indicates the first The carbon emission source corresponds to Total carbon emissions of operating equipment, Indicates the first The number of operating equipment corresponding to each carbon emission source, Indicates the number of carbon emission sources in the use phase of the project to be managed. represents the self-influencing factor of the engineering project to be managed, Indicates the first The carbon emission influencing factors of each carbon emission source.

[0025] The beneficial effects of the present invention are: (1) By identifying the carbon emission sources of buildings during their use phase, the present invention can clearly determine the main contributing equipment to carbon emissions. The source matrix and transformation matrix can quantify the emission characteristics and relationships of each carbon emission source, providing a basis for carbon emission prediction. (2) The present invention calculates the carbon emission impact factor, comprehensively considers the carbon emission of the project to be managed during the entire use phase, and considers that the building's own impact factor reflects the thermal performance and energy consumption characteristics of the building itself, which is an important factor that cannot be ignored when formulating emission reduction measures, and can more accurately predict carbon emissions; (3) The carbon emissions predicted by the present invention can provide an important reference for the long-term energy conservation and emission reduction planning of buildings, help to formulate emission reduction targets that meet the requirements of sustainable development, avoid excessive or insufficient emission reduction, and achieve the best balance between energy conservation and emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of the carbon emission reduction management method for engineering projects. DETAILED DESCRIPTION

[0027] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0028] like Figure 1 As shown, the present invention provides a method for managing carbon emission reduction in an engineering project, comprising the following steps: S1. Obtain the carbon emission sources of the engineering project to be managed during the use phase; S2. Generate source matrix and transformation matrix according to the carbon emission of carbon emission sources in the use phase, and calculate carbon emission impact factors; S3. Obtain the entity situation of the engineering project to be managed and determine the self-influencing factors of the engineering project to be managed; S4. Determine the predicted carbon emissions of the engineering project to be managed based on its own influencing factors and the carbon emission influencing factors of all carbon emission sources during the use phase.

[0029] In this embodiment of the present invention, S2 includes the following sub-steps: S21. Determine the operating equipment corresponding to the carbon emission sources of the project to be managed during the use phase; S22. generating a source matrix for the carbon emission source according to the carbon emission of each operating equipment in the carbon emission source during the use phase; S23, generating a transformation matrix according to the maximum carbon emission and the minimum carbon emission of each operating equipment in the carbon emission source during the use phase; S24. Calculate the carbon emission impact factor based on the source matrix and transformation matrix of the carbon emission source.

[0030] Possible sources of carbon emissions from the project to be managed include fuel combustion, electricity consumption and vehicle transportation.

[0031] Electricity consumption: As the main source of carbon emissions during the building operation stage, the corresponding operating equipment includes lighting, air conditioning, elevators and heating, etc. These equipment all consume electricity, and the production of electricity (especially thermal power) will produce a large amount of carbon dioxide emissions.

[0032] Fuel combustion: Some buildings may use fossil energy such as natural gas for heating and cooking. The combustion process of these energy sources will also directly produce carbon dioxide emissions. For buildings that use regional centralized cooling and heating systems, their energy comes from external thermal power plants or energy stations. The carbon emissions corresponding to the fuel consumption in the steam production process need to be allocated to each building.

[0033] Vehicle transportation: Fuel or electricity consumed to transport goods within a construction project (such as building material distribution and waste removal) is also considered indirect emissions caused by construction operations.

[0034] In the present invention, the source matrix presents all carbon emissions in the form of specific numerical values, and can analyze the differences in carbon emissions between different equipment. The transformation matrix provides the maximum and minimum values ​​of carbon emissions from the operation of each device, analyzes the fluctuation range of carbon emissions, and includes carbon emissions in certain extreme cases (such as full or empty equipment), providing a basis for predicted risks. The carbon emission impact factor comprehensively considers the information of the source matrix and the transformation matrix, and provides a comprehensive assessment of the overall carbon emissions of the project.

[0035] In the embodiment of the present invention, S22 includes the following sub-steps: S221, obtaining the average carbon emissions of each operating equipment corresponding to the carbon emission source during the use phase, and generating a carbon emission data set of the carbon emission source; S222, clustering the carbon emission data set of the carbon emission source, and determining the average value of each operating device in the corresponding cluster; S223, sorting the average values ​​of each running device in the corresponding cluster from small to large, and generating a source matrix.

[0036] In the present invention, by calculating the mean of the carbon emissions of the operating equipment, a representative value can be obtained, which represents the carbon emission level of the operating equipment during long-term use. Cluster analysis determines the characteristic value of each operating equipment, reflecting the carbon emission level of the equipment in each cluster, as comprehensive information of the carbon emission source.

[0037] In the embodiment of the present invention, in S223, the source matrix The expression is: ; In the formula, It represents the average value of the first running device in the corresponding cluster after sorting from small to large. It represents the average carbon emission of the first operating equipment in the use phase after sorting from small to large. It represents the average value of the second running device in the corresponding cluster after sorting from small to large. It represents the average carbon emission of the second operating equipment in the use phase after sorting from small to large. Indicates the first The average value of the running devices in the corresponding cluster, Indicates the first The average carbon emissions of each operating equipment during the use phase, It means constructing a diagonal matrix, Represents the identity matrix.

[0038] In this embodiment of the present invention, S23 includes the following sub-steps: S231, extracting the maximum carbon emissions of each operating device corresponding to the carbon emission source during the use phase, and generating a first characteristic column vector; S232, extracting the minimum carbon emissions of each operating device corresponding to the carbon emission source during the use phase, and generating a second characteristic column vector; S233. Use the covariance matrix between the first eigenvalue column vector and the second eigenvalue column vector as a transformation matrix.

[0039] In the present invention, the peak emission of each operating device can be reflected by extracting the maximum carbon emission, the minimum carbon emission represents the emission level of the device under the optimal operating conditions, the covariance matrix can reflect the extreme value of the carbon emissions of all operating devices, and the dimensionality reduction of the data can be realized. The sum of the maximum singular value of the source matrix and the maximum singular value of the transformation matrix is ​​used as the carbon emission influencing factor, which can comprehensively reflect the changes in the emission characteristics of the carbon emission source. The first eigenvalue column vector and the second eigenvalue column vector both contain several numerical values, and the covariance matrix can be in 2×2 form. The elements in the first row and the first column are the variances of all elements of the first eigenvalue column vector, the elements in the second row and the second column are the variances of all elements of the second eigenvalue column vector, the elements in the first row and the second column are the covariances between the elements of the two column vectors, and the elements in the first row and the first column can be the same as the elements in the first row and the second column.

[0040] In the embodiment of the present invention, in S24, the sum of the maximum singular value of the source matrix and the maximum singular value of the transformation matrix is ​​used as the carbon emission impact factor of the carbon emission source.

[0041] In the embodiment of the present invention, in S3, the self-influence factor The calculation formula is: ; In the formula, Indicates the first The heat transfer coefficient of the outer surface of the wall grid is: Indicates the first The heat transfer coefficient of the inner surface of the wall grid is Indicates the number of wall grids of the project to be managed.

[0042] In the present invention, the thermal insulation performance of the wall has an important impact on the energy consumption and carbon emissions of the building. There are many wall bodies in the building, so grid division is required. The outer surface heat transfer coefficient and the inner surface heat transfer coefficient reflect the heat exchange capacity between the wall and the external environment and the indoor environment respectively. The size of these two coefficients directly affects the absorption, storage and release of heat by the wall, and thus affects the energy consumption and carbon emissions of the building. δ is an indicator that combines the inner and outer surface heat transfer coefficients and the number of wall grids. It is used to quantify the heat transfer characteristics of the wall and evaluate the contribution of the wall to the overall energy consumption and carbon emissions of the building.

[0043] In this embodiment of the present invention, S4 includes the following sub-steps: S41. Construct a carbon emission trend function based on the self-influencing factors of the engineering project to be managed and the carbon emission influencing factors of all carbon emission sources during the use phase; S42. Determine the predicted carbon emissions of the engineering project to be managed using the carbon emission trend function.

[0044] In the present invention, when constructing the carbon emission trend function, the inherent influencing factors of the engineering project to be managed and the carbon emission influencing factors of all carbon emission sources during the use phase are taken into account, which covers both the architectural characteristics of the construction project itself and the carbon emissions from various sources during the operation process.

[0045] In the embodiment of the present invention, in S41, the carbon emission trend function The expression is: ; In the formula, Indicates the first The carbon emission source corresponds to Total carbon emissions of operating equipment, Indicates the first The number of operating equipment corresponding to each carbon emission source, Indicates the number of carbon emission sources in the use phase of the project to be managed. represents the self-influencing factor of the engineering project to be managed, Indicates the first The carbon emission influencing factors of each carbon emission source.

[0046] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A method for managing carbon emission reduction in engineering projects, characterized in that: The following steps are involved: S1. Obtain the carbon emission sources of the engineering project to be managed during the use phase; S2. Generate source matrix and transformation matrix according to the carbon emission of carbon emission sources in the use phase, and calculate carbon emission impact factors; S3. Obtain the entity situation of the engineering project to be managed and determine the self-influencing factors of the engineering project to be managed; S4. Determine the predicted carbon emissions of the engineering project to be managed based on its own influencing factors and the carbon emission influencing factors of all carbon emission sources during the use phase.

2. The method for managing carbon emission reduction in engineering projects according to claim 1, characterized in that: The S2 comprises the following sub-steps: S21. Determine the operating equipment corresponding to the carbon emission sources of the project to be managed during the use phase; S22. generating a source matrix for the carbon emission source according to the carbon emission of each operating equipment in the carbon emission source during the use phase; S23, generating a transformation matrix according to the maximum carbon emission and the minimum carbon emission of each operating equipment in the carbon emission source during the use phase; S24. Calculate the carbon emission impact factor based on the source matrix and transformation matrix of the carbon emission source.

3. The method for managing carbon emission reduction in engineering projects according to claim 2, characterized in that: The S22 includes the following sub-steps: S221, obtaining the average carbon emissions of each operating equipment corresponding to the carbon emission source during the use phase, and generating a carbon emission data set of the carbon emission source; S222, clustering the carbon emission data set of the carbon emission source, and determining the average value of each operating device in the corresponding cluster; S223, sorting the average values ​​of each running device in the corresponding cluster from small to large, and generating a source matrix.

4. The method for managing carbon emission reduction in engineering projects according to claim 3, characterized in that: In S223, the source matrix The expression is: ； In the formula, It represents the average value of the first running device in the corresponding cluster after sorting from small to large. It represents the average carbon emission of the first operating equipment in the use phase after sorting from small to large. It represents the average value of the second running device in the corresponding cluster after sorting from small to large. It represents the average carbon emission of the second operating equipment in the use phase after sorting from small to large. Indicates the first The average value of the running devices in the corresponding cluster, Indicates the first The average carbon emissions of each operating equipment during the use phase, It means constructing a diagonal matrix, Represents the identity matrix.

5. The method for managing carbon emission reduction in engineering projects according to claim 2, characterized in that: The S23 comprises the following sub-steps: S231, extracting the maximum carbon emissions of each operating device corresponding to the carbon emission source during the use phase, and generating a first characteristic column vector; S232, extracting the minimum carbon emissions of each operating device corresponding to the carbon emission source during the use phase, and generating a second characteristic column vector; S233. Use the covariance matrix between the first eigenvalue column vector and the second eigenvalue column vector as a transformation matrix.

6. The method for managing carbon emission reduction in engineering projects according to claim 2, characterized in that: In S24, the sum of the maximum singular value of the source matrix and the maximum singular value of the transformation matrix is ​​used as the carbon emission impact factor of the carbon emission source.

7. The method for managing carbon emission reduction in engineering projects according to claim 1, characterized in that: In S3, the impact factor The calculation formula is: ； In the formula, Indicates the first The heat transfer coefficient of the outer surface of the wall grid is: Indicates the first The heat transfer coefficient of the inner surface of the wall grid is Indicates the number of wall grids of the project to be managed.

8. The method for managing carbon emission reduction in engineering projects according to claim 1, characterized in that: The S4 comprises the following sub-steps: S41. Construct a carbon emission trend function based on the self-influencing factors of the engineering project to be managed and the carbon emission influencing factors of all carbon emission sources during the use phase; S42. Determine the predicted carbon emissions of the engineering project to be managed using the carbon emission trend function.

9. The method for managing carbon emission reduction in engineering projects according to claim 8, characterized in that: In S41, the carbon emission trend function The expression is: ； In the formula, Indicates the first The carbon emission source corresponds to Total carbon emissions of operating equipment, Indicates the first The number of operating equipment corresponding to each carbon emission source, Indicates the number of carbon emission sources in the use phase of the project to be managed. represents the self-influencing factor of the engineering project to be managed, Indicates the first The carbon emission influencing factors of each carbon emission source.

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