Collaborative optimization method of new energy facilities in highway carbon sink system

Abstract

The invention discloses a collaborative optimization method of new energy facilities in an expressway carbon sink system. The method comprises the following steps: monitoring carbon emission data of a full life cycle of an expressway and carrying out data fusion; carrying out accounting and intelligent analysis processing on the carbon emission data of the whole life cycle of the expressway; according to the invention, based on a'vehicle-road-ring 'carbon emission multi-dimensional integrated monitoring system, intelligent fusion and parameterization analysis of highway and traffic flow carbon emission multi-source data are carried out; a highway full life cycle carbon emission accounting model is established, an associated activity level metering system is constructed, a highway full life cycle carbon emission digital twinborn management system based on big data is constructed, and a highway carbon emission evaluation system is constructed to comprehensively analyze low-carbon high-speed full life cycle carbon emission characteristics. The coupling digital twinning technology realizes comprehensive visualization of carbon emission data, and provides important support for green and low-carbon development of road traffic.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission accounting, and in particular to a collaborative optimization method for new energy facilities in a highway carbon sink system. Background Art

[0002] At present, the construction of the highway carbon emission evaluation system has not yet been fully systematized and standardized, and there are still research gaps and deficiencies both at home and abroad. The research and practice related to carbon emission accounting of transportation infrastructure at home and abroad mainly focus on the whole life cycle theory, accounting methods and models. The research on carbon emission measurement methods in the construction and industrial fields has gradually matured, but the carbon emission accounting of transportation infrastructure is still in its infancy. Compared with the fixed source emissions from industry and construction, the complexity of the transportation system and the characteristics of its mobile carbon sources increase the difficulty of measuring carbon emissions. The international methods for estimating carbon emissions are mainly based on direct measurement, conservation of matter and emission coefficients, while the carbon emission measurement methods that are in line with the current characteristics of transportation infrastructure construction, operation and maintenance activities and engineering practices are still relatively weak, and a complete carbon emission accounting method system has not yet been formed. Summary of the Invention

[0003] The present invention provides a collaborative optimization method for new energy facilities in a highway carbon sink system, which can effectively solve the problem raised in the above background technology that the current research and practice on carbon emission accounting of transportation infrastructure at home and abroad are mainly concentrated in the whole life cycle theory, accounting methods and models. The research on carbon emission calculation methods in the construction and industrial fields has gradually matured, but the carbon emission accounting of transportation infrastructure is still in its infancy. The carbon emission calculation methods that conform to the characteristics of my country's transportation infrastructure construction, operation and maintenance activities and the actual engineering are still relatively weak, and a complete carbon emission accounting method system has not yet been formed.

[0004] To achieve the above objectives, the present invention provides the following technical solutions: a collaborative optimization method for new energy facilities in a highway carbon sink system,

[0005] The steps include:

[0006] Step 1: Monitor carbon emission data throughout the entire life cycle of the highway and perform data fusion;

[0007] Step 2: Calculate and intelligently analyze the carbon emission data of the entire life cycle of the highway;

[0008] Step 3: Conduct twin management and optimization of highway carbon emission data throughout its life cycle;

[0009] Step 1, multi-dimensional integrated monitoring of highway traffic carbon emissions, involves comprehensive, multi-faceted monitoring of highway traffic carbon emissions using a variety of monitoring methods, including intelligent monitoring of carbon emissions throughout their life cycle and fusion analysis of carbon emissions data.

[0010] The full life cycle carbon emission intelligent monitoring includes monitoring carbon emission data during the construction period and building an inventory, and monitoring and collecting carbon emission data during the operation and maintenance period;

[0011] Monitoring carbon emissions data during the construction period and building an inventory specifically includes setting monitoring targets, formulating a carbon emissions monitoring plan, applying advanced monitoring technologies, and collating and analyzing carbon emissions data. Monitoring and collecting carbon emissions data during the operation and maintenance period specifically includes using sensors and monitoring equipment, comprehensive monitoring, and applying artificial intelligence technology.

[0012] The carbon emission data fusion analysis includes parameter analysis, data visualization and data intelligent fusion.

[0013] According to the above technical solution, setting monitoring targets means clarifying the objectives of carbon emission monitoring, determining the main sources of carbon emissions during the construction process, quantifying carbon emissions, and identifying emission reduction opportunities;

[0014] The formulation of a carbon emission monitoring plan means that the plan includes all possible sources of carbon emissions and formulates monitoring means and methods for each link;

[0015] The application of advanced monitoring technology is to use professional carbon emission measurement equipment and remote sensing monitoring technology to conduct real-time and accurate monitoring of carbon emissions during the construction period;

[0016] The carbon emission data is collated and analyzed to collect carbon emission data from each link in real time, and the data is collated and analyzed to grasp the carbon emission situation and trend during the construction period.

[0017] According to the above technical solution, the sensors and monitoring equipment used are connected to the operation and maintenance platform for data connection. Based on the sensors and monitoring equipment on the highway, the speed, model, weight and age of the vehicles on the road, as well as the passenger flow in the service area, are monitored in real time. In combination with the geographic information system, the monitoring data is linked with the geographic information of the highway to realize the monitoring and analysis of carbon emissions of traffic flows in different geographical areas.

[0018] The comprehensive monitoring is connected with the data of the target highway toll station to fully understand the traffic flow characteristics of the highway section, including the number of vehicles, vehicle types, and mileage, and realize the comprehensive monitoring of the carbon emission data of the traffic flow;

[0019] The use of artificial intelligence technology is to model and simulate highway traffic flow, and estimate and predict the carbon emissions of traffic flow by predicting different traffic flows and vehicle speeds.

[0020] According to the above technical solution, the parametric analysis is performed on highway carbon emission data to extract key parameter information. The parametric analysis can use statistical analysis and machine learning techniques to mine and analyze carbon emission data, extract key features, and establish a corresponding carbon emission model.

[0021] The data visualization is to display the carbon emission data obtained through analysis through visualization technology so that managers can understand the carbon emission situation more intuitively. Data visualization can use charts and maps to display and present the analyzed data;

[0022] The intelligent data fusion is to intelligently integrate the carbon emission data collected from different sources and types to form complete highway carbon emission data. Data fusion can use data mining and machine learning technologies to associate and match carbon emission data from different sources to form a complete data set and perform logical reasoning analysis.

[0023] According to the above technical solution, in step 2, the construction of the carbon emission calculation model for the entire life cycle of highways first requires clarifying the specific carbon accounting objects, demarcating the accounting scope of highways, and performing carbon dioxide equivalent accounting for the carbon emissions generated by the six major greenhouse gases CO2, CH4, N2O, HFCs, PFCs, and SF6 throughout the entire life cycle;

[0024] Specific accounting of CO2 emissions from highways during the production and transportation of building materials and equipment, roadbed and pavement construction, highway operation and maintenance, and demolition and disposal;

[0025] It includes building a carbon emission calculation model for the construction period and building a carbon emission calculation model for the operation and maintenance period.

[0026] According to the above technical solution, the construction period carbon emission calculation model is constructed as follows:

[0027] A. Carbon emissions during the highway construction phase should include the carbon emissions generated by the completion of the construction of each sub-project and the carbon emissions generated during the implementation of various measures and projects. Carbon emissions generated by highway construction should be calculated as follows:

[0028]

[0029] Where: C gjz is the carbon emission during the highway construction phase, kgCO2e, E gjz,iis the energy consumption of highway construction category i, EF i is the carbon emission factor of the i-th energy type, kgCO2 / kWh, which is taken from the standard appendix;

[0030] B. Carbon emissions during the demolition phase of a highway should include carbon emissions from various energy sources used manually or mechanically during demolition activities. Carbon emissions from highway construction should be calculated as follows:

[0031]

[0032] Where: C gjz is the carbon emission during the highway construction phase, kgCO2e, E gjz,i is the energy consumption of highway construction category i, EF i is the carbon emission factor of the i-th energy type, kgCO2 / kWh, which is taken from the standard appendix;

[0033] C. Carbon emissions generated during the production of highway construction materials should be calculated as follows:

[0034]

[0035] Where: C gsc is the carbon emission during the highway construction material production stage, kgCO2e, M i is the consumption of the i-th building material, F i is the carbon emission factor of the i-th building material, kgCO2e;

[0036] D. Carbon emissions from the transportation of construction materials for highways should be calculated as follows:

[0037]

[0038] Where: C gys is the carbon emission during the transportation of building materials on highways, kgCO2e, M i is the consumption of the i-th building material, kg, D i is the average transportation distance of the i-th type of building material, km, T i is the carbon emission factor per unit weight and transportation distance under the transportation mode of the i-th building material, t·km.

[0039] According to the above technical solution, the construction of the carbon emission calculation model during the operation and maintenance period means that the carbon emission calculation scope of the expressway operation and maintenance stage should include the carbon emissions of expressway traffic and maintenance, operation and maintenance of expressway ancillary equipment, green projects, and sustainable energy during operation. The carbon emission calculation model generated during the expressway maintenance stage is:

[0040] C gyw =C gwh +Cgfyw +C gtx -C p -C k ;

[0041] Where C gyw is the carbon emissions generated during the operation and maintenance phase of the expressway, kgCO2e, C gwh is the carbon emission generated during the highway maintenance phase, kgCO2e, C gfyw is the carbon emission during the operation and maintenance phase of highway ancillary equipment, kgCO2e, C gtx is the carbon emissions generated by highway vehicles, kgCO2e, C p is the carbon reduction of highway vegetation, kgCO2e, C k is the carbon reduction from sustainable energy on highways, kgCO2e.

[0042] According to the above technical solution, in step three, the big data-based low-carbon highway carbon emission digital twin integrated platform realizes real-time monitoring and management of carbon emissions throughout the entire life cycle of highways through digital twin models, carbon emission prediction and assessment, visualization and decision support, intelligent monitoring and early warning, and data security assurance.

[0043] It includes data integration and processing, digital twin modeling, carbon emission data analysis, intelligent decision support, real-time monitoring and early warning, visual analysis and display, and data security assurance.

[0044] According to the above technical solution, the data integration and processing uses big data analysis to conduct secondary integration and processing of the calculated highway carbon emission data. By integrating multiple data sources, comprehensive and accurate carbon emission data is obtained to support carbon emission reduction decisions. During the construction period, topographic, soil and meteorological data are integrated to assess the impact of these factors on future carbon emissions. At the same time, carbon emissions are assessed for the building materials and equipment expected to be used, and these data are integrated to predict the total carbon emissions during the construction phase.

[0045] During the operation and maintenance period, traffic flow data and maintenance data during operation are integrated and compared with data from the construction period to fully understand the carbon emissions of the expressway throughout its life cycle;

[0046] The digital twin modeling constructs a digital twin model based on the collected data to predict and evaluate highway carbon emissions. The digital twin model needs to include a physical twin and a data twin. The physical twin is to model the actual physical system as a digital system, while the data twin is to model the collected data as a digital system. The digital twin model can be used to simulate and predict the actual system and optimize and manage it.

[0047] During the construction phase, a digital twin model of the highway will be created based on design parameters, building materials, and construction methods. The model will reflect the expected carbon emissions and assess the impact of design decisions on carbon emissions.

[0048] During the operation and maintenance period, the digital twin model will be updated based on actual operation data and historical emission data to more accurately reflect the actual carbon emissions of the highway;

[0049] The carbon emission data analysis is based on the digital twin model to predict and evaluate the carbon emissions of highways, using machine learning algorithms and time series analysis methods to predict and evaluate. The prediction results are used to formulate carbon emission reduction plans and programs;

[0050] During the construction phase, digital twin models are analyzed to predict carbon emission peaks and their occurrence times during the construction process, identify the materials, construction equipment, and construction processes with the highest carbon sources, and identify potential carbon emission reduction strategies.

[0051] During the operation and maintenance period, analyze the carbon emission data during the operation and maintenance period, identify the links in the operation and maintenance process that can effectively reduce carbon emissions, and propose optimization strategies.

[0052] According to the above technical solution, the intelligent decision support system uses artificial intelligence technology to analyze and predict carbon emission data to provide support for decision-making. By modeling and analyzing historical data, it can obtain trends and changes in carbon emissions, providing a basis for formulating emission reduction targets and measures.

[0053] During the construction period, AI technology is used to optimize construction strategies and perform calculations and forecasts for each sub-project;

[0054] During the operation and maintenance period, AI and machine learning technologies are used to predict when maintenance should be performed based on monitoring data and historical information to reduce traffic congestion and carbon emissions, providing decision support for operation and maintenance strategies.

[0055] The real-time monitoring and early warning system uses digital twin technology and big data technology to achieve real-time monitoring and early warning of carbon emissions, issue early warnings and reminders when carbon emissions exceed the standard, and take timely measures to prevent excessive increases in carbon emissions.

[0056] During the construction phase, carbon emissions are monitored in real time to ensure they align with the digital twin model's predictions. If emissions exceed a predetermined threshold, an alert is triggered, prompting managers to take corrective measures.

[0057] During the operation and maintenance period, carbon emissions from highway operation and maintenance equipment and traffic flows are monitored in real time, and early warnings are issued for abnormal emissions to ensure low carbon emissions during normal highway operation.

[0058] The visual analysis and display uses data visualization technology to visualize the carbon emission data of the entire life cycle of the highway, providing users with intuitive and easy-to-understand data analysis results, and providing visual charts for the construction and operation and maintenance periods of the highway, facilitating users' data analysis and decision-making;

[0059] The data security assurance strengthens data protection and security management, ensures data integrity and confidentiality, adopts data encryption, access control, and data backup to protect data security, and ensures the reliability and stability of the platform.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] 1. Based on the multi-dimensional integrated monitoring system of "vehicle-road-environment" carbon emissions, the present invention conducts intelligent fusion and parametric analysis of multi-source data on carbon emissions of highways and traffic flows, establishes a carbon emission accounting model for the entire life cycle of highways and constructs a related activity level measurement system, builds a digital twin management system for carbon emissions of highways throughout their life cycle based on big data, constructs a highway carbon emission evaluation system to comprehensively analyze the carbon emission characteristics of low-carbon highways throughout their life cycle, couples digital twin technology to achieve comprehensive visualization of carbon emission data, and provides carbon emission reduction decision-making plans for different operating scenarios, providing important support for the green and low-carbon development of road transportation.

[0062] 2. Focusing on the characteristics of expressways throughout their entire life cycle and targeting the construction, construction, operation and maintenance management characteristics of my country's expressways, a carbon emission accounting system for the entire life cycle of expressways will be established. Based on a bottom-up carbon emission accounting method, carbon emission characteristics will be accurately analyzed, and a multi-dimensional integrated monitoring system for traffic flow carbon emissions will be developed. Intelligent fusion and parametric analysis of multi-source data on carbon emissions of expressways and traffic flows will be carried out, and a carbon emission analysis platform for the entire life cycle of expressways based on big data will be built. The carbon emission characteristics of low-carbon expressways throughout their entire life cycle and traffic flows will be comprehensively analyzed, and relevant carbon neutrality countermeasures and carbon management plans will be proposed.

[0063] 3. Establish a complete tracking and deep integration system for complex and multi-dimensional data to solve the problem of difficulty in comprehensive, accurate and efficient tracking of dynamic and static data during highway construction and operation and maintenance. Establish a carbon emission accounting and artificial intelligence analysis model for highways throughout their life cycle to overcome the difficult problem of modern highway carbon emission calculation and analysis being highly dependent on manual labor. Establish a real-time feedback and management system for highway carbon emission status driven by digital twin technology to break through the bottleneck of poor precision and low accuracy in carbon reduction strategy formulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0065] In the drawings:

[0066] Figure 1 is a step flow chart of the collaborative optimization method of the present application. DETAILED DESCRIPTION

[0067] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application.

[0068] Embodiment: As shown in the present application provides a technical solution, a collaborative optimization method of new energy facilities in highway carbon sink system, comprising the following steps: Figure 1

[0069] Step one, monitoring the carbon emission data of the whole life cycle of the highway and carrying out data fusion;

[0070] Step two, accounting and intelligent analysis and processing of the carbon emission data of the whole life cycle of the highway;

[0071] Step three, twin management and optimization processing of the whole life cycle carbon emission data of the highway;

[0072] Step one, highway traffic flow carbon emission multi-dimensional integrated monitoring refers to comprehensively using various monitoring means to monitor the carbon emission of highway traffic flow from all directions and multiple angles, including whole life cycle carbon emission intelligent monitoring and carbon emission data fusion analysis;

[0073] Whole life cycle carbon emission intelligent monitoring includes monitoring construction period carbon emission data and constructing list and monitoring and collecting operation period carbon emission data;

[0074] Monitoring construction period carbon emission data and constructing list specifically includes setting monitoring target, formulating carbon emission monitoring plan, applying advanced monitoring technology and analyzing carbon emission data, monitoring and collecting operation period carbon emission data specifically includes using sensors and monitoring equipment, all-around monitoring and using artificial intelligence technology;

[0075] Carbon emission data fusion analysis includes parameterization analysis, data visualization and data intelligent fusion.

[0076] Based on the above technical solution, setting monitoring target means specifying the target of carbon emission monitoring, determining the main carbon emission source in the construction process, quantifying carbon emission, and identifying emission reduction opportunities;

[0077] Formulating carbon emission monitoring plan means that the plan includes all possible carbon emission sources, including fuel combustion, equipment operation, construction process materials and energy consumption, and formulating monitoring means and methods for each link;

[0078] ​The application of advanced monitoring technology is to use professional carbon emission measurement equipment and remote sensing monitoring technology to conduct real-time and accurate monitoring of carbon emissions during the construction period;

[0079] Organize and analyze carbon emission data to collect carbon emission data from each link in real time, including cost lists, organize and analyze them, and grasp the carbon emission situation and trends during the construction period.

[0080] Based on the above technical solution, sensors and monitoring equipment are used to connect data with the operation and maintenance platform. Based on the sensors and monitoring equipment on the highway, the speed, model, weight and age of vehicles on the road, as well as the passenger flow in the service area, are monitored in real time. In combination with the geographic information system, the monitoring data is linked with the geographic information of the highway to realize the monitoring and analysis of carbon emissions of traffic flows in different geographical areas.

[0081] Comprehensive monitoring connects with data from target highway toll stations to fully understand traffic flow characteristics along the highway, including vehicle numbers, vehicle types, and mileage, enabling comprehensive monitoring of traffic flow carbon emission data.

[0082] Artificial intelligence technology is used to model and simulate highway traffic flows, and to estimate and predict the carbon emissions of traffic flows by predicting different traffic flows and vehicle speeds.

[0083] Based on the above technical solution, parametric analysis is performed on highway carbon emission data to extract key parameter information. Parametric analysis can use statistical analysis and machine learning techniques to mine and analyze carbon emission data, extract key features, and establish a corresponding carbon emission model.

[0084] Data visualization is to display the carbon emission data obtained through analysis through visualization technology so that managers can understand the carbon emission situation more intuitively. Data visualization can use charts and maps to display and present the analyzed data;

[0085] Intelligent data fusion is the intelligent fusion of carbon emission data collected from different sources and types to form complete highway carbon emission data. Data fusion can use data mining and machine learning technologies to associate and match carbon emission data from different sources to form a complete data set and perform logical reasoning and analysis.

[0086] Based on the above technical solution, in step 2, the construction of the carbon emission calculation model for the entire life cycle of highways first requires clarifying the specific carbon accounting objects, delineating the accounting scope of highways, and calculating the carbon dioxide equivalent of the six major greenhouse gases CO2, CH4, N2O, HFCs, PFCs, and SF6 throughout the entire life cycle;

[0087] Specific accounting of CO2 emissions from highways during the production and transportation of building materials and equipment, roadbed and pavement construction, highway operation and maintenance, and demolition and disposal;

[0088] It includes building a carbon emission calculation model for the construction period and building a carbon emission calculation model for the operation and maintenance period.

[0089] Based on the above technical solution, the carbon emission calculation model for the construction period is constructed as follows:

[0090] A. Carbon emissions during the highway construction phase should include the carbon emissions generated by the completion of the construction of each sub-project and the carbon emissions generated during the implementation of various measures and projects. Carbon emissions generated by highway construction should be calculated as follows:

[0091]

[0092] Where: C gjz is the carbon emission during the highway construction phase, kgCO2e, E gjz,i is the energy consumption of highway construction category i, EF i is the carbon emission factor of the i-th energy type, kgCO2 / kWh, which is taken from the standard appendix;

[0093] B. Carbon emissions during the demolition phase of a highway should include carbon emissions from various energy sources used manually or mechanically during demolition activities. Carbon emissions from highway construction should be calculated as follows:

[0094]

[0095] Where: C gjz is the carbon emission during the highway construction phase, kgCO2e, E gjz,i is the energy consumption of highway construction category i, EF i is the carbon emission factor of the i-th energy type, kgCO2 / kWh, which is taken from the standard appendix;

[0096] C. Carbon emissions generated during the production of highway construction materials should be calculated as follows:

[0097]

[0098] Where: C gsc is the carbon emission during the highway construction material production stage, kgCO2e, M i is the consumption of the i-th building material, F i is the carbon emission factor of the i-th building material, kgCO2e;

[0099] D. Carbon emissions from the transportation of construction materials for highways should be calculated as follows:

[0100]

[0101] Where: C gys is the carbon emission during the transportation of building materials on highways, kgCO2e, M i is the consumption of the i-th building material, kg, D i is the average transportation distance of the i-th type of building material, km, T i is the carbon emission factor per unit weight and transportation distance under the transportation mode of the i-th building material, t·km.

[0102] Based on the above technical solution, the construction of the carbon emission calculation model during the operation and maintenance period means that the carbon emission calculation scope of the expressway operation and maintenance stage should include the carbon emissions during the operation of the expressway, the operation and maintenance of expressway ancillary equipment, green projects, and sustainable energy. The carbon emission calculation model generated during the expressway maintenance stage is:

[0103] C gyw =C gwh +C gfyw +C gtx -C p -C k ;

[0104] Where C gyw is the carbon emissions generated during the operation and maintenance phase of the expressway, kgCO2e, C gwh is the carbon emission generated during the highway maintenance phase, kgCO2e, C gfyw is the carbon emission during the operation and maintenance phase of highway ancillary equipment, kgCO2e, C gtx is the carbon emissions generated by highway vehicles, kgCO2e, C p is the carbon reduction of highway vegetation, kgCO2e, C k is the carbon reduction from sustainable energy on highways, kgCO2e.

[0105] Based on the above technical solution, in step three, a big data-based low-carbon highway carbon emission digital twin integrated platform will achieve real-time monitoring and management of carbon emissions throughout the entire life cycle of highways through digital twin models, carbon emission prediction and assessment, visualization and decision support, intelligent monitoring and early warning, and data security assurance.

[0106] It includes data integration and processing, digital twin modeling, carbon emission data analysis, intelligent decision support, real-time monitoring and early warning, visual analysis and display, and data security assurance.

[0107] Based on the above technical solution, data integration and processing uses big data analysis to conduct secondary integration and processing of the calculated highway carbon emission data. By integrating multiple data sources, comprehensive and accurate carbon emission data is obtained to support carbon emission reduction decisions. During the construction period, topographic, soil and meteorological data are integrated to assess the impact of these factors on future carbon emissions. At the same time, carbon emissions of the building materials and equipment expected to be used are assessed, and these data are integrated to predict the total carbon emissions during the construction phase.

[0108] During the operation and maintenance period, traffic flow data and maintenance data during operation are integrated and compared with data from the construction period to fully understand the carbon emissions of the expressway throughout its life cycle;

[0109] Digital twin modeling builds a digital twin model based on collected data to predict and evaluate highway carbon emissions. The digital twin model needs to include both physical twins and data twins. The physical twin models the actual physical system as a digital system, while the data twin models the collected data as a digital system. The digital twin model can be used to simulate and predict the actual system and optimize and manage the actual system.

[0110] During the construction phase, a digital twin model of the highway will be created based on design parameters, building materials, and construction methods. The model will reflect the expected carbon emissions and assess the impact of design decisions on carbon emissions.

[0111] During the operation and maintenance period, the digital twin model will be updated based on actual operation data and historical emission data to more accurately reflect the actual carbon emissions of the highway;

[0112] Carbon emission data analysis uses digital twin models to predict and evaluate highway carbon emissions, using machine learning algorithms and time series analysis methods. The prediction results are used to formulate carbon emission reduction plans and programs;

[0113] During the construction phase, digital twin models are analyzed to predict carbon emission peaks and their occurrence times during the construction process, identify the materials, construction equipment, and construction processes with the highest carbon sources, and identify potential carbon emission reduction strategies.

[0114] During the operation and maintenance period, analyze the carbon emission data during the operation and maintenance period, identify the links in the operation and maintenance process that can effectively reduce carbon emissions, and propose optimization strategies.

[0115] Based on the above technical solutions, intelligent decision support uses artificial intelligence technology to analyze and predict carbon emission data to support decision-making. By modeling and analyzing historical data, it can obtain trends and changes in carbon emissions, providing a basis for formulating emission reduction targets and measures.

[0116] For the construction period, AI technology is used to optimize construction strategies, and each sub-project is accounted for and predicted, including optimizing construction scheduling and equipment usage plans;

[0117] For the operation and maintenance period, AI and machine learning technologies are used to predict when to perform maintenance to reduce traffic congestion and carbon emissions based on monitoring data and historical information, providing decision support for operation and maintenance strategies;

[0118] Real-time monitoring and early warning through digital twin technology and big data technology, real-time monitoring and early warning of carbon emissions, early warning and reminders of carbon emissions exceeding the standard, and timely measures to prevent excessive carbon emissions;

[0119] During the construction period, real-time monitoring of carbon emissions during the construction process is carried out to ensure that it is consistent with the prediction of the digital twin model. If carbon emissions exceed the predetermined threshold, an early warning is triggered to remind management personnel to take corrective action;

[0120] During the operation and maintenance period, real-time monitoring of highway operation and maintenance equipment and traffic flow carbon emissions is carried out to warn of abnormal emissions and ensure low carbon emissions during normal operation of the highway;

[0121] Visual analysis and display using data visualization technology to visualize highway life cycle carbon emissions data and provide users with intuitive and easy-to-understand data analysis results. Visual charts are displayed for highway construction and operation periods to facilitate user data analysis and decision-making;

[0122] Data security protection strengthens data protection and security management to ensure data integrity and confidentiality. Data encryption, access control, and data backup are used to protect data security and ensure platform reliability and stability.

[0123] Finally, it should be noted that the above description is only a preferred example of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some technical features. Any modification, equivalent substitution, improvement, etc. within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A collaborative optimization method for new energy facilities in a highway carbon sequestration system, characterized by: The steps include: Step 1: Monitor carbon emission data throughout the entire life cycle of the highway and perform data fusion; Step 2: Calculate and intelligently analyze the carbon emission data of the entire life cycle of the highway; Step 3: Conduct twin management and optimization of highway carbon emission data throughout its life cycle; Step 1, multi-dimensional integrated monitoring of highway traffic carbon emissions, involves comprehensive, multi-faceted monitoring of highway traffic carbon emissions using a variety of monitoring methods, including intelligent monitoring of carbon emissions throughout their life cycle and fusion analysis of carbon emissions data. The full life cycle carbon emission intelligent monitoring includes monitoring carbon emission data during the construction period and building an inventory, and monitoring and collecting carbon emission data during the operation and maintenance period; Monitoring carbon emissions data during the construction period and building an inventory specifically includes setting monitoring targets, formulating a carbon emissions monitoring plan, applying advanced monitoring technologies, and collating and analyzing carbon emissions data. Monitoring and collecting carbon emissions data during the operation and maintenance period specifically includes using sensors and monitoring equipment, comprehensive monitoring, and applying artificial intelligence technology. The carbon emission data fusion analysis includes parameter analysis, data visualization and data intelligent fusion.

2. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 1 is characterized by: Setting monitoring targets refers to clarifying the objectives of carbon emission monitoring, determining the main sources of carbon emissions during the construction process, quantifying carbon emissions, and identifying emission reduction opportunities; The formulation of a carbon emission monitoring plan means that the plan includes all possible sources of carbon emissions and formulates monitoring means and methods for each link; The application of advanced monitoring technology is to use professional carbon emission measurement equipment and remote sensing monitoring technology to conduct real-time and accurate monitoring of carbon emissions during the construction period; The carbon emission data is collated and analyzed to collect carbon emission data from each link in real time, and the data is collated and analyzed to grasp the carbon emission situation and trend during the construction period.

3. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 1 is characterized by: The sensors and monitoring equipment mentioned above are used to connect data with the operation and maintenance platform. Based on the sensors and monitoring equipment on the highway, the speed, model, weight and age of the vehicles on the road, as well as the passenger flow in the service area, are monitored in real time. In combination with the geographic information system, the monitoring data is associated with the geographic information of the highway to realize the monitoring and analysis of carbon emissions of traffic flows in different geographical areas. The comprehensive monitoring is connected with the data of the target highway toll station to fully understand the traffic flow characteristics of the highway section, including the number of vehicles, vehicle types, and mileage, and realize the comprehensive monitoring of the carbon emission data of the traffic flow; The use of artificial intelligence technology is to model and simulate highway traffic flow, and estimate and predict the carbon emissions of traffic flow by predicting different traffic flows and vehicle speeds.

4. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 1 is characterized by: The parametric analysis is to perform parametric analysis on highway carbon emission data to extract key parameter information. The parametric analysis can use statistical analysis and machine learning techniques to mine and analyze carbon emission data, extract key features, and establish a corresponding carbon emission model. The data visualization is to display the carbon emission data obtained through analysis through visualization technology so that managers can understand the carbon emission situation more intuitively. Data visualization can use charts and maps to display and present the analyzed data; The intelligent data fusion is to intelligently integrate the carbon emission data collected from different sources and types to form complete highway carbon emission data. Data fusion can use data mining and machine learning technologies to associate and match carbon emission data from different sources to form a complete data set and perform logical reasoning analysis.

5. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 1 is characterized by: In the second step, the construction of the carbon emission calculation model for the entire life cycle of highways first requires the identification of specific carbon accounting objects, the demarcation of the accounting scope of highways, and the calculation of carbon dioxide equivalents for the six major greenhouse gases CO2, CH4, N2O, HFCs, PFCs, and SF6 throughout the entire life cycle; Specific accounting of CO2 emissions from highways during the production and transportation of building materials and equipment, roadbed and pavement construction, highway operation and maintenance, and demolition and disposal; It includes building a carbon emission calculation model for the construction period and building a carbon emission calculation model for the operation and maintenance period.

6. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 5 is characterized by: The carbon emission calculation model for the construction period is specifically as follows: A. Carbon emissions during the highway construction phase should include the carbon emissions generated by the completion of the construction of each sub-project and the carbon emissions generated during the implementation of various measures and projects. Carbon emissions generated by highway construction should be calculated as follows: Where: C gjz is the carbon emission during the highway construction phase, kgCO2e, E gjz,i is the energy consumption of highway construction category i, EF i is the carbon emission factor of the i-th energy source, kgCO2 / kWh, taken from the standard appendix; B. Carbon emissions during the demolition phase of a highway should include carbon emissions from various energy sources used manually or mechanically during demolition activities. Carbon emissions from highway construction should be calculated as follows: Where: C gjz is the carbon emission during the highway construction phase, kgCO2e, E gjz,i is the energy consumption of highway construction category i, EF i is the carbon emission factor of the i-th energy source, kgCO2 / kWh, taken from the standard appendix; C. Carbon emissions generated during the production of highway construction materials should be calculated as follows: Where: C gsc is the carbon emission during the highway construction material production stage, kgCO2e, M i is the consumption of the i-th building material, F i is the carbon emission factor of the i-th building material, kgCO2e; D. Carbon emissions from the transportation of construction materials for highways should be calculated as follows: Where: C gys is the carbon emission during the transportation of building materials on highways, kgCO2e, M i is the consumption of the i-th building material, kg, D i is the average transportation distance of the i-th type of building material, km, T i is the carbon emission factor per unit weight and transportation distance under the transportation mode of the i-th building material, t·km.

7. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 5 is characterized by: The construction of the carbon emission calculation model during the operation and maintenance period means that the carbon emission calculation scope during the operation and maintenance period of the expressway should include the carbon emissions during the operation period of the expressway, the operation and maintenance of expressway ancillary equipment, green projects, and sustainable energy. The carbon emission calculation model generated during the expressway maintenance period is: C gyw =C gwh +C gfyw +C gtx -C p -C k ; Where C gyw is the carbon emission generated during the operation and maintenance phase of the expressway, kgCO2e, C gwh is the carbon emission generated during the highway maintenance phase, kgCO2e, C gfyw is the carbon emission during the operation and maintenance phase of highway ancillary equipment, kgCO2e, C gtx is the carbon emissions generated by highway vehicles, kgCO2e, C p is the carbon reduction of highway vegetation, kgCO2e, C k is the carbon reduction from sustainable energy on highways, kgCO2e.

8. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 1 is characterized by: In step three, the big data-based low-carbon highway carbon emission digital twin integrated platform achieves real-time monitoring and management of carbon emissions throughout the entire life cycle of highways through digital twin models, carbon emission prediction and assessment, visualization and decision support, intelligent monitoring and early warning, and data security assurance. It includes data integration and processing, digital twin modeling, carbon emission data analysis, intelligent decision support, real-time monitoring and early warning, visual analysis and display, and data security assurance.

9. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 8 is characterized by: The data integration and processing uses big data analysis to conduct secondary integration and processing of the calculated highway carbon emission data. By integrating multiple data sources, comprehensive and accurate carbon emission data is obtained to support carbon emission reduction decisions. During the construction period, topographic, soil and meteorological data are integrated to assess the impact of these factors on future carbon emissions. At the same time, carbon emissions of the building materials and equipment expected to be used are assessed, and these data are integrated to predict the total carbon emissions during the construction phase. During the operation and maintenance period, traffic flow data and maintenance data during operation are integrated and compared with data from the construction period to fully understand the carbon emissions of the expressway throughout its life cycle; The digital twin modeling constructs a digital twin model based on the collected data to predict and evaluate highway carbon emissions. The digital twin model needs to include a physical twin and a data twin. The physical twin is to model the actual physical system as a digital system, while the data twin is to model the collected data as a digital system. The digital twin model can be used to simulate and predict the actual system and optimize and manage it. During the construction phase, a digital twin model of the highway will be created based on design parameters, building materials, and construction methods. The model will reflect the expected carbon emissions and assess the impact of design decisions on carbon emissions. During the operation and maintenance period, the digital twin model will be updated based on actual operation data and historical emission data to more accurately reflect the actual carbon emissions of the highway; The carbon emission data analysis is based on the digital twin model to predict and evaluate the carbon emissions of highways, using machine learning algorithms and time series analysis methods to predict and evaluate. The prediction results are used to formulate carbon emission reduction plans and programs; During the construction phase, digital twin models are analyzed to predict carbon emission peaks and their occurrence times during the construction process, identify the materials, construction equipment, and construction processes with the highest carbon sources, and identify potential carbon emission reduction strategies. During the operation and maintenance period, analyze the carbon emission data during the operation and maintenance period, identify the links in the operation and maintenance process that can effectively reduce carbon emissions, and propose optimization strategies.

10. The collaborative optimization method of new energy facilities in a highway carbon sequestration system according to claim 8, characterized in that: The intelligent decision support system uses artificial intelligence technology to analyze and predict carbon emission data to support decision-making. By modeling and analyzing historical data, it can obtain trends and changes in carbon emissions, providing a basis for formulating emission reduction targets and measures. During the construction period, AI technology is used to optimize construction strategies and perform calculations and forecasts for each sub-project; During the operation and maintenance period, AI and machine learning technologies are used to predict when maintenance should be performed based on monitoring data and historical information to reduce traffic congestion and carbon emissions, providing decision support for operation and maintenance strategies. The real-time monitoring and early warning system uses digital twin technology and big data technology to achieve real-time monitoring and early warning of carbon emissions, issue early warnings and reminders when carbon emissions exceed the standard, and take timely measures to prevent excessive increases in carbon emissions. During the construction phase, carbon emissions are monitored in real time to ensure they align with the digital twin model's predictions. If emissions exceed a predetermined threshold, an alert is triggered, prompting managers to take corrective measures. During the operation and maintenance period, carbon emissions from highway operation and maintenance equipment and traffic flows are monitored in real time, and early warnings are issued for abnormal emissions to ensure low carbon emissions during normal highway operation. The visual analysis and display uses data visualization technology to visualize the carbon emission data of the entire life cycle of the highway, providing users with intuitive and easy-to-understand data analysis results, and providing visual charts for the construction and operation and maintenance periods of the highway, facilitating users' data analysis and decision-making; The data security assurance strengthens data protection and security management, ensures data integrity and confidentiality, adopts data encryption, access control, and data backup to protect data security, and ensures the reliability and stability of the platform.

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