A substation full life cycle carbon footprint dynamic management and control method and system and medium

Abstract

The present application relates to the technical field of electric power engineering, and particularly relates to a substation full life cycle carbon footprint dynamic management and control method and system and a medium, comprising determining the carbon emission space-time boundary of different life cycle stages of a substation according to physical structure data of the substation body facilities and temporary buildings; based on the carbon emission space-time boundary and a pre-constructed substation basic digital twin, extracting the carbon emission space-time distribution characteristics of the substation body facilities and temporary buildings in each life cycle stage, obtaining the synergistic carbon reduction path of the substation body facilities and temporary buildings based on the carbon emission space-time distribution characteristics, and simulating the carbon emission reduction trajectory of each synergistic carbon reduction path in the full life cycle by using a digital enhanced twin, to obtain a target carbon reduction path. The present application accurately captures the carbon emission space-time distribution characteristics and coupling effects by fusing physical structure data and a digital enhanced twin, and realizes the synergistic optimization of the full life cycle carbon footprint of a substation.

Description

Technical Field

[0001] This invention relates to the field of power engineering technology, and in particular to a method, system and medium for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle. Background Technology

[0002] With the continuous development of the power industry, substations, as the core hubs for power transmission and distribution, involve multiple stages throughout their entire life cycle, including planning and design, equipment and material production, on-site construction, operation and maintenance, and dismantling and scrapping. This complex process is accompanied by a large amount of material consumption and energy use, and its carbon emission sources are characterized by complexity, dispersion, and cross-stage characteristics. Therefore, accurate quantification and effective management of carbon emissions throughout the entire life cycle of substations has become an important focus in the field of power engineering construction.

[0003] In current applications, substation carbon footprint accounting typically focuses on the main building and long-term operating electrical equipment, neglecting temporary facilities that exist extensively during construction and are dismantled immediately after completion. While these temporary facilities have short lifespans, the carbon emissions from their material production and disposal, as well as energy consumption during construction, are integral parts of the overall project carbon footprint. Ignoring them will result in accounting results that fail to accurately reflect the actual carbon emission levels of the substation project. Furthermore, existing methods lack the ability to dynamically correlate and accurately map carbon emission data between the main building and temporary facilities. The construction of prefabricated houses is closely related in terms of time and space distribution. The scale, layout and usage period of temporary facilities during the construction phase are dynamically adjusted according to the changes in the main project design and construction organization plan. However, existing methods are difficult to establish a data correlation mechanism between the two, making it impossible to achieve the linkage update of carbon emission information at each stage, and also impossible to effectively connect with real-time data in the actual project scenario. This results in fragmented and static carbon emission data, making it difficult to support an accurate grasp of the actual carbon emission status of the project. Therefore, the above problems jointly restrict the refinement and effectiveness of substation carbon emission management, making it difficult to meet the needs of modern power engineering for full-cycle, traceable carbon footprint management. Summary of the Invention

[0004] To address the above technical issues, this invention provides a method, system, and medium for dynamic management and control of the carbon footprint of a substation throughout its entire lifecycle.

[0005] In a first aspect, the present invention provides a method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle, the method comprising the following steps: The spatial and temporal boundaries of carbon emissions at different life stages of the substation are determined based on the physical structure data of the substation's main facilities and temporary buildings. Carbon emission sources are identified based on the spatiotemporal boundaries of carbon emissions to obtain a set of carbon emission source items. The carbon emission amount of each carbon emission source is calculated based on the set of carbon emission source items to form an initial carbon footprint dataset. The initial carbon footprint dataset is mapped to the pre-built digital twin of the substation infrastructure to construct a digital augmented twin. The digital augmented twin was used to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary buildings at each stage of their life cycle. Based on the spatiotemporal distribution characteristics of carbon emissions, the carbon emission coupling effect between the substation main facilities and temporary buildings is analyzed to obtain the collaborative carbon reduction path of the substation main facilities and temporary buildings. Resource competition risk is identified for the collaborative carbon reduction path to obtain a set of resource conflict nodes. Based on the set of resource conflict nodes, a digital augmented twin is used to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire life cycle, thereby obtaining the target carbon reduction path.

[0006] In a further implementation scheme, the step of determining the spatiotemporal boundaries of carbon emissions at different life stages of the substation based on the physical structure data of the substation's main facilities and temporary buildings includes: Based on the physical structure data of the substation main facilities and temporary buildings, the spatial existence status of the substation main facilities and temporary buildings at different life cycle stages is analyzed to obtain the spatial boundary data of the substation main facilities and temporary buildings in each life cycle stage. Extract the start and end times, duration, and connection relationships between each life cycle stage of the substation to generate basic time sequence data of the substation's main facilities. Extract the erection time, usage period, demolition time, and predicted turnover and relocation time of temporary buildings during construction to generate time-series dynamic data of temporary buildings; Based on the time-series basic data of the substation main facilities and the time-series dynamic data of the temporary buildings, the temporal coupling relationship between the intervention period of the temporary buildings and the procedures of the substation main facilities is analyzed to obtain the time boundary data of the substation main facilities and temporary buildings in each life cycle stage. Based on the spatial boundary data and the temporal boundary data, the geographic spatial boundaries and statistical time intervals corresponding to carbon emission accounting in each life cycle stage are analyzed to obtain the spatiotemporal boundaries of carbon emissions in different life cycle stages of the substation.

[0007] In a further implementation, the step of identifying carbon emission sources based on the spatiotemporal boundary of carbon emissions to obtain a set of carbon emission source items includes: Based on the aforementioned carbon emission spatiotemporal boundary, the effective time interval and effective spatial range for carbon emission accounting at each stage of the substation's life cycle are extracted to generate the effective spatiotemporal range for carbon emissions. Based on the physical structure data of the substation's main facilities and temporary buildings, and the planning of the mechanical operation area, the carbon emission sources within the effective time and space range of carbon emissions are located to obtain the carbon emission activity targets. The carbon emission behavior of the carbon emission activity targets within the effective time and space range of carbon emission is analyzed to obtain the carbon emission activity type; The carbon emission activity objects are structurally labeled based on the carbon emission activity type to generate a set of carbon emission source items.

[0008] In a further implementation, the step of mapping the initial carbon footprint dataset to a pre-built substation infrastructure digital twin to construct an enhanced digital twin includes: Extract all associated physical entity nodes and process nodes from the pre-built substation basic digital twin to form a twin node information database; The association mapping relationship between the initial carbon footprint dataset and the twin node information database is established by using a spatiotemporal dual matching mapping rule; The initial carbon footprint dataset is written into the corresponding physical entity nodes and process nodes in the substation basic digital twin using the aforementioned association mapping relationship, thereby obtaining a digitally enhanced twin.

[0009] In a further implementation, the step of using the digital augmented twin to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary structures at each stage of their life cycle includes: Based on the three-dimensional spatial coordinate system built into the digital augmented twin, the spatial occupancy range of the substation main facilities and temporary buildings at each stage of their life cycle is divided into spatial grids, and the continuous space in the digital augmented twin is discretized into several spatial units. The carbon emission intensity per unit area is calculated based on the cumulative carbon emission value of each spatial unit in each life cycle stage, and the carbon emission intensity distribution results in the spatial dimension are obtained. The digital augmented twin is used to sort the carbon emission occurrence times in each life cycle stage and identify the peak carbon emission times when carbon emissions reach a local maximum in each life cycle stage. Calculate the inflection points of carbon emission growth and decline rates in each life cycle stage to generate carbon emission fluctuation ranges; Based on the carbon emission intensity distribution results, the peak carbon emission time points, and the carbon emission fluctuation range, the overlapping range of high carbon emission intensity areas and peak emission periods is analyzed to form the spatiotemporal distribution characteristics of carbon emissions.

[0010] In a further implementation scheme, the step of analyzing the carbon emission coupling effect between the substation main facilities and temporary buildings based on the spatiotemporal distribution characteristics of carbon emissions, and obtaining the synergistic carbon reduction path of the substation main facilities and temporary buildings, includes: Based on the spatiotemporal distribution characteristics of carbon emissions, a spatiotemporal overlay analysis was performed on the high carbon emission intensity areas and peak emission periods of each life cycle stage of the substation to obtain the spatiotemporal coupling hotspots of carbon emissions where there is mutual influence between the substation's main facilities and temporary buildings. Correlation analysis was conducted on the carbon emission transmission process between the substation main facilities and temporary buildings within the spatiotemporal coupling hotspot area to obtain the carbon emission coupling effect intensity index between the substation main facilities and temporary buildings. With the goal of minimizing the overall carbon emission peak in the spatiotemporal coupling hotspot region, multiple scenarios are extrapolated using the coupling effect strength index and the process evolution logic of each life cycle stage of the digital enhanced twin to generate several collaborative carbon reduction paths.

[0011] In a further implementation, the step of identifying resource competition risks in the collaborative carbon reduction path to obtain a set of resource conflict nodes includes: The resource demand information of the collaborative carbon reduction path during its execution is analyzed, and the resource supply ceiling for each life cycle stage is retrieved from the digital augmented twin. By comparing the resource demand information of collaborative carbon reduction pathway operation nodes within the same spatiotemporal range with the resource supply ceiling, resource competition conflict areas can be identified. Based on the resource competition conflict area, the resource competition events in the resource competition conflict area are traced and analyzed by utilizing the operational logic dependency relationship between the collaborative carbon reduction path operation nodes, and conflict path operation nodes with resource competition risks are identified. The conflict path operation nodes are deduplicated and integrated according to their life cycle stage, occurrence time sequence, and competing resource type to form a set of resource conflict nodes covering the entire process of the collaborative carbon reduction path.

[0012] In a further implementation, the step of simulating the carbon emission reduction trajectory of each collaborative carbon reduction path over its entire life cycle using a digital augmented twin based on the set of resource conflict nodes to obtain the target carbon reduction path includes: The resource conflict nodes are used to reconstruct the path sequence of the collaborative carbon reduction path to generate corresponding conflict-free alternative paths. The digital augmented twin is used to analyze the carbon emission impact correlation between adjacent life cycle stages of each conflict-free alternative path, and the cross-stage carbon emission reduction contribution is quantified. The net carbon emission reduction of the conflict-free alternative path relative to the baseline carbon emission trajectory is calculated based on the cross-stage carbon emission reduction contribution. Using the maximization of net carbon emission reduction as the screening criterion, a target carbon reduction path is selected from the conflict-free alternative paths.

[0013] Secondly, the present invention provides a dynamic management and control system for the carbon footprint of a substation throughout its entire life cycle, the system comprising: The spatiotemporal partitioning module is used to determine the spatiotemporal boundaries of carbon emissions at different life stages of a substation based on the physical structure data of the substation's main facilities and temporary buildings. The carbon footprint analysis module is used to identify carbon emission sources based on the spatiotemporal boundary of carbon emissions, obtain a set of carbon emission source items, and calculate the carbon emission amount of each carbon emission source based on the set of carbon emission source items to form an initial carbon footprint dataset. The twin association module is used to perform data association mapping between the initial carbon footprint dataset and the pre-constructed substation basic digital twin to construct a digitally enhanced twin; The feature extraction module is used to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary buildings at each stage of their life cycle using the digital augmented twin. The path construction module is used to analyze the carbon emission coupling effect between the substation main facilities and temporary buildings based on the spatiotemporal distribution characteristics of carbon emissions, obtain the collaborative carbon reduction path of the substation main facilities and temporary buildings, and identify the resource competition risk of the collaborative carbon reduction path to obtain a set of resource conflict nodes. The path determination module is used to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire life cycle based on the set of resource conflict nodes using a digital augmented twin, thereby obtaining the target carbon reduction path.

[0014] Thirdly, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0015] This invention provides a method, system, and medium for dynamic management of the carbon footprint of a substation throughout its entire lifecycle. The method determines the spatiotemporal boundaries of carbon emissions at different lifecycle stages of the substation based on the physical structure data of the substation's main facilities and temporary buildings. Based on these boundaries, carbon emission sources are identified to obtain a set of carbon emission source items. The carbon emissions of each source are then calculated to form an initial carbon footprint dataset. This initial carbon footprint dataset is then mapped to a pre-constructed digital twin of the substation's basic structure to construct an enhanced digital twin. The enhanced digital twin is used to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary buildings at each lifecycle stage. Based on these characteristics, the carbon emission coupling effect between the substation's main facilities and temporary buildings is analyzed to obtain collaborative carbon reduction paths. Resource competition risks are identified for these collaborative carbon reduction paths to obtain a set of resource conflict nodes. Based on this set, the enhanced digital twin is used to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire lifecycle to obtain the target carbon reduction path. Compared with existing technologies, this method accurately captures the spatiotemporal distribution characteristics and coupling effects of carbon emissions by fusing physical structure data and digital augmented twins, thereby achieving synergistic optimization of the carbon footprint of substations throughout their entire life cycle. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the dynamic management and control method for the carbon footprint of a substation throughout its entire life cycle, provided in an embodiment of the present invention. Figure 2 This is a block diagram of the dynamic management and control system for the carbon footprint of a substation throughout its entire life cycle, provided in an embodiment of the present invention.

[0017] Figure labeling: 101, Spatiotemporal partitioning module; 102, Carbon footprint analysis module; 103, Twin association module; 104, Feature extraction module; 105, Path construction module; 106, Path determination module. Detailed Implementation

[0018] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are given for illustrative purposes only and should not be construed as limiting the present invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0019] Figure 1 This is a schematic diagram of the dynamic management method for the carbon footprint of a substation throughout its entire lifecycle, provided by an embodiment of the present invention. The present invention provides a method for dynamic management of the carbon footprint of a substation throughout its entire lifecycle, such as... Figure 1 As shown, the method includes the following steps: S1. Determine the spatiotemporal boundaries of carbon emissions at different life stages of the substation based on the physical structure data of the substation's main facilities and temporary buildings.

[0020] In some implementations, the step of determining the spatiotemporal boundaries of carbon emissions at different lifecycle stages of a substation based on the physical structural data of the substation's main facilities and temporary buildings includes: Based on the physical structure data of the substation main facilities and temporary buildings, the spatial existence status of the substation main facilities and temporary buildings at different life cycle stages is analyzed to obtain the spatial boundary data of the substation main facilities and temporary buildings in each life cycle stage. Extract the start and end times, duration, and connection relationships between each life cycle stage of the substation to generate basic time sequence data of the substation's main facilities. Extract the erection time, usage period, demolition time, and predicted turnover and relocation time of temporary buildings during construction to generate time-series dynamic data of temporary buildings; Based on the time-series basic data of the substation main facilities and the time-series dynamic data of the temporary buildings, the temporal coupling relationship between the intervention period of the temporary buildings and the procedures of the substation main facilities is analyzed to obtain the time boundary data of the substation main facilities and temporary buildings in each life cycle stage. Based on the spatial boundary data and the temporal boundary data, the geographic spatial boundaries and statistical time intervals corresponding to carbon emission accounting in each life cycle stage are analyzed to obtain the spatiotemporal boundaries of carbon emissions in different life cycle stages of the substation.

[0021] Specifically, this embodiment obtains the physical structure data of the substation main facilities and the geometric and material configuration data of temporary buildings from the substation engineering design scheme, forming the physical structure data of the substation main facilities and temporary buildings. The physical structure data of the substation main facilities may include, but is not limited to, the geometric dimensions, structural forms and building material usage information of the main transformer, various switchgear, busbar frame, supporting foundation, main control building and other auxiliary buildings. The geometric and material configuration data of temporary buildings may include, but is not limited to, the land area, building volume, structural type and service life parameters of temporary construction prefabricated houses, material processing sheds and temporary roads. At the same time, this embodiment divides the various stages included in the entire life cycle of the substation based on the standard process flow of power engineering construction. For example, according to the installation procedures and service life of various equipment and structures in the main facilities, this embodiment divides the entire life cycle of the substation into the planning and design stage, equipment and material production stage, on-site construction stage, operation and maintenance stage and demolition and disposal stage.

[0022] This embodiment extracts the geometric dimensions, spatial layout coordinates, design locations of each functional unit, and the footprint and height information of various equipment and buildings from the physical structure data of the substation's main facilities (including transformers, frames, and main control buildings, etc., permanent structures), generating a basic spatial dataset of the substation's main facilities. It also extracts the footprint, building volume, structural type, and their placement and timing during construction from the physical structure data of the substation's temporary buildings (including temporary prefabricated houses, construction fences, and other detachable structures), generating a dynamic spatial dataset of temporary buildings. Based on the basic spatial dataset of the substation's main facilities and the substation project's design drawings and land boundary lines, the permanent spatial scope occupied by the substation's main facilities during the operation and maintenance phase is determined. Simultaneously, based on the dynamic spatial dataset of temporary buildings and the construction organization design plan, the activity space scope of temporary facilities during the construction phase and the temporary storage and transfer of waste during the demolition and disposal phase are determined. The required operating space range integrates the space range permanently occupied by the substation main facilities during the operation and maintenance phase, the activity space range of temporary facilities during the construction phase, and the operating space range required for waste storage and transfer during the demolition and disposal phase. This yields the spatial boundary data of the substation main facilities and temporary buildings in each life cycle phase. Then, this embodiment extracts the start and end time nodes, duration, and connection relationships between each life cycle phase of the overall schedule plan of the substation project from the planning and design, equipment and material production, on-site construction, operation and maintenance, and demolition and disposal phases to generate basic time sequence data of the substation main facilities. Based on the standard unit usage cycle, erection and demolition process duration, and temporary building turnover and allocation scheme in the construction organization design of the temporary building erection and demolition scheme, the erection time point, usage cycle, demolition time point, and possible turnover and relocation time point of the temporary building in each life cycle phase are extracted to generate temporary building time sequence dynamic data.

[0023] Then, this embodiment analyzes the temporal coupling relationship between the intervention period of the temporary building and the procedures of the substation main facilities based on the time-series basic data of the substation main facilities and the time-series dynamic data of the temporary buildings. This yields the time boundary data for the substation main facilities and temporary buildings within each lifecycle stage. Specifically, this embodiment maps the time window of the equipment and material production stage to the manufacturing cycle of the main facility building materials and equipment; the time window of the on-site construction stage to the parallel cycle of main facility installation and temporary building erection and use; the time window of the operation and maintenance stage to the continuous service cycle of various equipment in the main facilities; and the time window of the demolition and disposal stage to the termination cycle of main facility dismantling and temporary building demolition, thereby determining each lifecycle stage. The time start and end intervals and stage division nodes covered by the internal carbon emission accounting are used to obtain the time boundary data of the substation's main facilities and temporary buildings in each life cycle stage. Based on the spatial boundary data and the time boundary data, the geographic spatial boundaries and statistical time intervals of carbon emission accounting in each life cycle stage are integrated and calibrated to obtain the carbon emission spatiotemporal boundaries of different life cycle stages of the substation. For example, the carbon emission spatiotemporal boundaries may include, but are not limited to, the building material production area and manufacturing time window corresponding to the equipment and material production stage, the main body and temporary building construction operation area and construction cycle window corresponding to the construction stage, the equipment operation space and service time window corresponding to the operation and maintenance stage, and the dismantling operation and waste temporary storage area and dismantling cycle window corresponding to the dismantling and disposal stage.

[0024] S2. Based on the spatiotemporal boundary of carbon emissions, identify carbon emission sources to obtain a set of carbon emission source items, and calculate the carbon emission amount of each carbon emission source based on the set of carbon emission source items to form an initial carbon footprint dataset.

[0025] In some embodiments, the step of identifying carbon emission sources based on the spatiotemporal boundary of carbon emissions to obtain a set of carbon emission source items includes: Based on the aforementioned carbon emission spatiotemporal boundary, the effective time interval and effective spatial range for carbon emission accounting at each stage of the substation's life cycle are extracted to generate the effective spatiotemporal range for carbon emissions. Based on the physical structure data of the substation's main facilities and temporary buildings, and the planning of the mechanical operation area, the carbon emission sources within the effective time and space range of carbon emissions are located to obtain the carbon emission activity targets. The carbon emission behavior of the carbon emission activity targets within the effective time and space range of carbon emission is analyzed to obtain the carbon emission activity type; The carbon emission activity objects are structurally labeled based on the carbon emission activity type to generate a set of carbon emission source items.

[0026] Specifically, this embodiment extracts the effective time intervals and effective spatial ranges corresponding to the carbon emission spatiotemporal boundaries of different life cycle stages of the substation, respectively, for the equipment and material production stage, on-site construction stage, operation and maintenance stage, and demolition and disposal stage, to generate the effective spatiotemporal ranges of carbon emissions for each stage. The effective time interval is the statistical time window for carbon emission accounting at each stage, and the effective spatial range is the geographical spatial limit for carbon emission accounting at each stage. Then, based on the effective spatiotemporal ranges of carbon emissions at each life cycle stage, and combined with the physical structure data of the substation's main facilities, the geometric and material configuration data of temporary buildings, and the mechanical operations in the construction organization design scheme, the process is further refined. Regional planning involves locating and screening carbon emission sources within the effective time and space range. Specifically, in this embodiment, during the equipment and material production stage, the production equipment and process devices within the building material production plant and equipment manufacturing workshop are located; during the on-site construction stage, construction machinery, temporary buildings, and on-site office and living quarters within the construction operation area are located; during the operation and maintenance stage, main transformers, switchgear, station power systems, and auxiliary facilities within the equipment operating space are located; and during the demolition and disposal stage, demolition machinery, waste storage sites, and transportation equipment within the dismantling operation area are located. Through the above-mentioned location screening, carbon emission activities involved in each life cycle stage are identified.

[0027] For the identified carbon-emitting activities at each stage of their life cycle, this embodiment analyzes the carbon emission behavior of each activity within a corresponding time window based on its operating principles, work methods, and energy consumption characteristics. For example, for construction and demolition machinery, this embodiment can analyze the energy consumption behavior generated by fuel combustion or electric drive; for temporary buildings and office buildings, this embodiment can analyze the electricity consumption behavior generated by lighting, air conditioning, and equipment operation, as well as the carbon emission behavior implicit in building materials; for electrical equipment such as main transformers, this embodiment can analyze the indirect carbon emission behavior generated by power loss during operation; for building material production equipment and process devices, this embodiment can analyze the fossil fuel combustion, process reactions, and electricity consumption. The carbon emission behavior generated by consumption is analyzed to determine the specific carbon emission activity type corresponding to each carbon emission activity object. Subsequently, this embodiment associates the analyzed carbon emission activity type with the corresponding carbon emission activity object, and classifies and codes and marks the source according to the life cycle stage, emission type (direct emission or indirect emission), source attribute (substation main facilities, temporary buildings, mechanical operation) and carbon emission activity type. Carbon emission activity objects that are not within the effective time and space range or are repeatedly identified are eliminated. Each emission source is assigned a unique identifier and its name, stage, spatial location, time window, carbon emission activity type and emission attribute are recorded. After the above structured annotation process, a set of carbon emission source items covering the entire life cycle of the substation is finally formed.

[0028] For the generated set of carbon emission source items, this embodiment analyzes the carbon emission activity type corresponding to each emission source in the set. Specifically, it uses the structured annotation information of the carbon emission source to read its corresponding carbon emission activity type, such as construction machinery operation activities, temporary building operation energy consumption activities, and permanent equipment operation wear and tear activities. This embodiment determines the basic activity data type required to calculate the carbon emission amount of the carbon emission source based on the carbon emission activity type. In specific implementation, this embodiment divides carbon emission sources into two categories: direct emission sources and indirect emission sources. Direct emission sources refer to emission sources that directly generate carbon dioxide emissions due to fossil fuel combustion, chemical reactions in process processes, or waste treatment. The required basic activity data includes the consumption of various fossil fuels, the amount of carbon dioxide emitted during process processes, etc. The consumption of specific raw materials and the total amount of waste treated; indirect emission sources refer to emission sources that indirectly generate carbon emissions by consuming secondary energy such as electricity and heat. The basic activity data required for these sources include electricity consumption and heat consumption. In this embodiment, based on the life cycle stage and spatial location of the emission source, a corresponding statistical time window is associated with each emission source to form a list of activity data collection requirements for each emission source. For example, for concrete pouring machinery of the main facility during the construction phase, the statistical time window is the start and end dates of the actual operation of the machinery; for the main transformer during the operation and maintenance phase, the statistical time window is the time interval of continuous operation after the substation is put into operation; for temporary prefabricated houses during the construction phase, the statistical time window is the usage period from the time the temporary prefabricated houses are put into use until they are demolished.

[0029] Finally, this embodiment calls a preset carbon emission factor database, which stores carbon emission factor values ​​and their applicable ranges for various energy sources, materials, and processes. For each carbon emission source in the set of carbon emission source items, this embodiment retrieves matching carbon emission factors from the carbon emission factor database based on its carbon emission activity type and basic activity data type. For example, for direct emission sources, this embodiment matches fuel combustion emission factors or process emission factors; for indirect emission sources, this embodiment matches emission factors from upstream production stages corresponding to electricity or heat. This embodiment associates and binds the successfully matched carbon emission factors with the corresponding carbon emission sources to ensure that each carbon emission source has a corresponding carbon emission factor, and uses the carbon emission factors to calculate the carbon emissions. For direct emission sources, this embodiment multiplies the total amount of various fossil fuels consumed by the emission source within the statistical time window by its corresponding fuel combustion carbon emission factor to obtain the fuel combustion carbon emission amount; multiplies the total amount of raw materials consumed in the process by its corresponding process carbon emission factor to obtain the process carbon emission amount; multiplies the total amount of waste treated by its corresponding waste treatment carbon emission factor to obtain the waste treatment carbon emission amount; and sums the calculated results of fuel combustion carbon emission amount, process carbon emission amount, and waste treatment carbon emission amount to obtain the total carbon emission amount of the direct emission source.

[0030] For indirect emission sources, this embodiment multiplies the total amount of electricity consumed by the emission source within the statistical time window by the carbon emission factor of the upstream production process corresponding to the electricity to obtain the electricity carbon emission amount; multiplies the total amount of heat consumed by the carbon emission factor of the upstream production process corresponding to the heat to obtain the heat carbon emission amount. This embodiment adds the electricity carbon emission amount and the heat carbon emission amount to obtain the total carbon emission amount of the indirect emission source.

[0031] This embodiment categorizes and summarizes the total carbon emissions of various emission sources according to their respective life cycle stages, forming carbon footprint subsets for the equipment and material production stage, on-site construction stage, operation and maintenance stage, and demolition and disposal stage. Within each life cycle stage, this embodiment further subdivides emissions into substation facility emissions, temporary building emissions, and mechanical operation emissions based on source attributes. This embodiment assigns the carbon emissions of each emission source to its corresponding stage and spatial categories, obtaining a stage- and space-specific carbon footprint classification and summary result. The carbon footprint classification and summary result is then integrated and formatted, recording each emission source's unique code, life cycle stage, source attribute, activity type, basic activity data, carbon emission factor value, and carbon emission value. Ultimately, this forms an initial carbon footprint dataset covering the entire life cycle of the substation and containing detailed carbon emissions from each type of emission source at each life cycle stage.

[0032] S3. Perform data association mapping between the initial carbon footprint dataset and the pre-constructed substation basic digital twin to construct a digital augmented twin.

[0033] In some implementations, the step of mapping the initial carbon footprint dataset to a pre-built digital twin of the substation infrastructure to construct a digitally enhanced twin includes: Extract all associated physical entity nodes and process nodes from the pre-built substation basic digital twin to form a twin node information database; The association mapping relationship between the initial carbon footprint dataset and the twin node information database is established by using a spatiotemporal dual matching mapping rule; The initial carbon footprint dataset is written into the corresponding physical entity nodes and process nodes in the substation basic digital twin using the aforementioned association mapping relationship, thereby obtaining a digitally enhanced twin.

[0034] Specifically, this embodiment extracts the spatial coordinates, life cycle stage, source attribute, and carbon emission value corresponding to each carbon emission source record in the initial carbon footprint dataset. The spatial coordinates are determined based on the specific location of the carbon emission source within the substation's main facilities or temporary structures. The life cycle stage includes equipment and material production, on-site construction, operation and maintenance, and demolition / disposal. After parsing, carbon emission data units with spatial coordinates and life cycle stage labels are generated. Then, this embodiment calls a pre-constructed substation basic digital twin. This pre-constructed substation basic digital twin is a three-dimensional digital model based on the physical structure of the substation's main facilities and temporary structures, integrating the project construction progress and operation and maintenance sequence. This substation basic digital twin adopts a hierarchical structure, where physical entity nodes correspond to various objects actually existing throughout the substation's entire life cycle, and process nodes correspond to the operational activities occurring at each stage. Physical entity nodes may include substation... Each physical entity node in the digital twin has a unique identifier, three-dimensional spatial coordinates, geometric dimensions, material attributes, and life cycle stage information for each component of the substation's main facilities, each unit of temporary buildings, equipment units, and mechanical units. Process nodes can include material preparation processes in the building material production stage, operation processes in the construction stage, maintenance processes in the operation and maintenance stage, and demolition processes in the demolition and disposal stage. Each process node in the digital twin has a unique identifier, planned start and end times, actual execution time, a set of associated physical entity nodes, and process logic relationships. The substation's basic digital twin fully maps the physical structure, equipment parameters, process flow, and spatial location relationships of the substation's main facilities and temporary buildings. In this embodiment, all associatable physical entity nodes and process nodes are extracted from the substation's basic digital twin, and the spatial coordinates, equipment number, life cycle stage, and node type attributes are recorded for each node, forming a twin node information database.

[0035] Using the spatial coordinates and life cycle stage of a carbon emission data unit as matching keywords, a search and comparison is performed in the twin node information database. Physical entity nodes or process nodes with the same spatial coordinate range and belonging to the same life cycle stage as the carbon emission data unit are identified as corresponding nodes. For each carbon emission data unit, this embodiment records its correspondence with the corresponding twin node. The correspondence includes the carbon emission data unit code, the twin node code, the association type, and the matching basis, generating a carbon emission-twin association mapping relationship. Based on the association mapping relationship, the carbon emission values ​​and activity types of each carbon emission data unit in the initial carbon footprint dataset are converted into structured data fields compatible with the twin node data format. These fields are then written one by one into the attribute storage area of ​​the corresponding physical entity node and process node in the substation basic digital twin. After writing is completed, the substation... In the digital twin of the power plant foundation, nodes that originally only contained geometric structure, physical attributes, and temporal information are now equipped with corresponding carbon emission data, achieving deep integration of carbon emission data with the engineering scenario. Furthermore, this embodiment configures a dynamic update interface for carbon emission data at each node. This interface supports automatic synchronization of carbon emission changes caused by subsequent design changes, construction schedule adjustments, or real-time monitoring data access to the corresponding nodes in the twin. This embodiment performs data integrity verification on the twin with embedded carbon emission data and dynamic interface settings to ensure that all emission sources in the initial carbon footprint dataset have been successfully mapped to their corresponding physical entity nodes or process nodes, and that the carbon emission data relationships between nodes conform to engineering logic. After verification, this embodiment encapsulates the written substation foundation digital twin as a whole, ultimately generating a digitally enhanced twin integrating carbon emission data dimensions.

[0036] S4. Use the digital augmented twin to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary buildings at each stage of their life cycle.

[0037] In some embodiments, the step of using the digital augmented twin to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary structures at each stage of their life cycle includes: Based on the three-dimensional spatial coordinate system built into the digital augmented twin, the spatial occupancy range of the substation main facilities and temporary buildings at each stage of their life cycle is divided into spatial grids, and the continuous space in the digital augmented twin is discretized into several spatial units. The carbon emission intensity per unit area is calculated based on the cumulative carbon emission value of each spatial unit in each life cycle stage, and the carbon emission intensity distribution results in the spatial dimension are obtained. The digital augmented twin is used to sort the carbon emission occurrence times in each life cycle stage and identify the peak carbon emission times when carbon emissions reach a local maximum in each life cycle stage. Calculate the inflection points of carbon emission growth and decline rates in each life cycle stage to generate carbon emission fluctuation ranges; Based on the carbon emission intensity distribution results, the peak carbon emission time points, and the carbon emission fluctuation range, the overlapping range of high carbon emission intensity areas and peak emission periods is analyzed to form the spatiotemporal distribution characteristics of carbon emissions.

[0038] Specifically, this embodiment, based on the three-dimensional spatial coordinate system built into the digital augmented twin, divides the spatial occupancy range of the substation's main facilities and temporary buildings at each stage of their life cycle into a spatial grid. It should be noted that the spatial occupancy range is determined based on the spatial coordinates and geometric dimensions of the physical entity nodes in the digital augmented twin. This includes the projection areas of each building structure of the main facilities, the layout areas of each unit of the temporary buildings, the machinery operation areas, and the material storage areas, etc. The spatial grid division can set the grid unit size according to the specific facility type and spatial scale, thereby discretizing the continuous space in the digital augmented twin into several units with unique spatial codes. The statistically significant spatial units generate a spatial grid system covering the entire substation area. For each life cycle stage, this embodiment retrieves the carbon emission data associated with each physical entity node and process node from the digital augmented twin. Based on the spatial location of each carbon emission source, its carbon emissions are aggregated into the corresponding spatial grid unit. The cumulative carbon emission value of each spatial grid unit in this life cycle stage is calculated, and the carbon emission intensity per unit area is calculated in combination with the area of ​​the spatial grid unit. This embodiment arranges and interpolates the carbon emission intensity values ​​of each spatial grid unit according to the spatial coding order to generate the carbon emission intensity distribution result in the spatial dimension of this life cycle stage.

[0039] This embodiment discretizes the time interval of each life cycle stage based on the time window attributes of each carbon emission source in the initial carbon footprint dataset. It then calculates the total carbon emissions in each spatial region within each time unit, generating a sequence curve of carbon emissions changing over time. Based on this sequence curve, it identifies the time points when carbon emissions reach local maxima in each life cycle stage, thus obtaining the peak carbon emission time points. Simultaneously, this embodiment calculates the first difference of the carbon emission sequence curve to identify the inflection points where carbon emissions change from growth to decline and from decline to growth. The time interval between two adjacent inflection points determines the carbon emission fluctuation range, which reflects the periods of continuous increase or decrease in carbon emissions. Finally, this embodiment overlays the carbon emission intensity distribution results in the spatial dimension of each life cycle stage with the peak carbon emission time point to identify the overlapping range of high carbon emission intensity areas and peak emission periods. At the same time, it analyzes the spatial distribution variation of major carbon emission sources within each carbon emission fluctuation interval to obtain the major emission areas corresponding to the carbon emission fluctuation interval. The above data are integrated to form the spatiotemporal distribution characteristics of carbon emissions of substation main facilities and temporary buildings in each life cycle stage. The spatiotemporal distribution characteristics of carbon emissions include the spatial location and range of high carbon emission intensity areas in each life cycle stage, the distribution pattern of peak carbon emission time points, the start and end times of carbon emission fluctuation intervals and the corresponding major emission areas, and the overlapping range of high intensity areas and peak periods.

[0040] S5. Based on the spatiotemporal distribution characteristics of carbon emissions, analyze the carbon emission coupling effect between the substation main facilities and temporary buildings, obtain the collaborative carbon reduction path of the substation main facilities and temporary buildings, and identify the resource competition risk of the collaborative carbon reduction path to obtain a set of resource conflict nodes.

[0041] In some implementations, the step of analyzing the carbon emission coupling effect between the substation main facilities and temporary buildings based on the spatiotemporal distribution characteristics of carbon emissions to obtain a synergistic carbon reduction path for the substation main facilities and temporary buildings includes: Based on the spatiotemporal distribution characteristics of carbon emissions, a spatiotemporal overlay analysis was performed on the high carbon emission intensity areas and peak emission periods of each life cycle stage of the substation to obtain the spatiotemporal coupling hotspots of carbon emissions where there is mutual influence between the substation's main facilities and temporary buildings. Correlation analysis was conducted on the carbon emission transmission process between the substation main facilities and temporary buildings within the spatiotemporal coupling hotspot area to obtain the carbon emission coupling effect intensity index between the substation main facilities and temporary buildings. With the goal of minimizing the overall carbon emission peak in the spatiotemporal coupling hotspot region, multiple scenarios are extrapolated using the coupling effect strength index and the process evolution logic of each life cycle stage of the digital enhanced twin to generate several collaborative carbon reduction paths.

[0042] Specifically, this embodiment performs spatiotemporal overlay analysis on high carbon emission intensity areas and peak emission periods based on the spatiotemporal distribution characteristics of carbon emissions. It identifies emission sources from main facilities and temporary buildings that simultaneously appear in the same spatial range within the same time window. These areas with spatiotemporal overlap are marked as carbon emission spatiotemporal coupling hotspots. These areas characterize the basic spatial and temporal range of mutual carbon emission influence between main facilities and temporary buildings. For the identified carbon emission spatiotemporal coupling hotspots, this embodiment retrieves the carbon emission data of all substation main facility emission sources and temporary building emission sources within the range of the identified hotspot from a digital augmented twin. By combining emission time-series data and spatial coordinate information, and further analyzing the impact path of emission changes in the substation's main facilities on emissions from adjacent temporary buildings, as well as the feedback effect of temporary building emission changes on the main facilities' emissions, the direction and intensity of carbon emission transmission between the two are identified. By statistically analyzing the synchronous fluctuation frequency, peak superposition degree, and delay time of one change causing the other's response within the spatiotemporal coupling hotspot area of ​​carbon emissions, the carbon emission coupling effect intensity index between the substation's main facilities and temporary buildings is obtained. The carbon emission coupling effect intensity index reflects the degree of interdependence and mutual reinforcement between the two in terms of carbon emissions.

[0043] With the goal of minimizing the peak carbon emissions within the spatiotemporal coupling hotspot area, this embodiment selects hotspot areas with significant coupling effects and potential for synergistic carbon reduction based on the carbon emission coupling effect intensity index. For the selected areas, this embodiment uses the life cycle stage evolution logic of a digital augmented twin to simulate the linkage changes in carbon emissions between the substation main facilities and temporary buildings under different work sequence adjustments, spatial layout optimizations, or resource sharing schemes. Through multi-scenario simulation and comparison, it identifies synergistic adjustment methods that can effectively reduce the overall peak emissions of the coupling area without affecting the normal implementation of the project, forming synergistic carbon reduction measures for each coupling hotspot area. The synergistic carbon reduction measures for each area are integrated according to their life cycle stage, applicable objects, and implementation methods to generate synergistic carbon reduction paths for the substation main facilities and temporary buildings. The synergistic carbon reduction paths include spatial layout optimization paths, work sequence staggered peak paths, energy facility sharing paths, and dynamic response adjustment paths.

[0044] Due to the limited resources in substation engineering, the collaborative carbon reduction path generated in this embodiment may experience delays in actual implementation due to resource competition, leading to additional carbon emissions such as the prolonged operation of old equipment or increased energy consumption of temporary facilities. Therefore, this embodiment modifies the collaborative carbon reduction path by using a set of resource conflict nodes as constraints to ensure that the final target carbon reduction path is resource-feasible in engineering implementation. In some embodiments, the step of identifying resource competition risks in the collaborative carbon reduction path to obtain a set of resource conflict nodes includes: The resource demand information of the collaborative carbon reduction path during its execution is analyzed, and the resource supply ceiling for each life cycle stage is retrieved from the digital augmented twin. By comparing the resource demand information of collaborative carbon reduction pathway operation nodes within the same spatiotemporal range with the resource supply ceiling, resource competition conflict areas can be identified. Based on the resource competition conflict area, the resource competition events in the resource competition conflict area are traced and analyzed by utilizing the operational logic dependency relationship between the collaborative carbon reduction path operation nodes, and conflict path operation nodes with resource competition risks are identified. The conflict path operation nodes are deduplicated and integrated according to their life cycle stage, occurrence time sequence, and competing resource type to form a set of resource conflict nodes covering the entire process of the collaborative carbon reduction path.

[0045] Specifically, this embodiment extracts the types of operational activities, implementation sequence, and resource requirements involved in different lifecycle stages from each collaborative carbon reduction path, generating resource demand information for each path. The types of operational activities include construction machinery, manpower, workspace, and energy supply. Simultaneously, this embodiment retrieves the preset resource supply limits for each lifecycle stage from the digital augmented twin. These limits reflect the maximum available quantity of various resources that can be simultaneously allocated at each stage. This embodiment compares the resource demand of each collaborative carbon reduction path within different time windows with the resource supply limits within the same spatial range for the corresponding time period. When the resource demand exceeds the resource supply limit, the spatiotemporal unit is marked as a resource competition conflict area. This resource competition conflict area includes the time window, spatial range, and types of competing resources. For each identified resource competition conflict area, this embodiment extracts the operational logic dependencies between multiple collaborative carbon reduction paths involved in that resource competition conflict area from the digital augmented twin. These operational logic dependencies include the sequence of procedures, etc. To address the constraints of parallel operations and spatial avoidance requirements, this embodiment performs source analysis on resource competition events within conflict areas based on operational logic dependencies. It identifies specific path operations and their associated paths that cause resource demand to exceed limits. Each identified specific operation is marked as a conflict path node with resource competition risk. Each node corresponds to a path operation that may not be implemented as planned within a specific spatiotemporal unit due to resource competition. This embodiment categorizes all marked conflict path nodes according to their lifecycle stage, occurrence time sequence, and competing resource type. Pseudo-conflict nodes that are actually adjustable due to natural peak shifting caused by operational logic dependencies are eliminated. Multiple conflict records caused by the same resource type within the same path during the same time period are merged. This process forms a resource conflict node set covering the entire process of the collaborative carbon reduction path. The resource conflict node set includes a unique identifier for each resource conflict node, its associated path name, operation content, occurrence stage, conflict time window, competing resource type, and demand exceedance value, which is then used for subsequent time-series reconstruction and optimization of the collaborative carbon reduction path.

[0046] S6. Based on the set of resource conflict nodes, use a digital augmented twin to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire life cycle to obtain the target carbon reduction path.

[0047] In some implementations, the step of simulating the carbon emission reduction trajectory of each collaborative carbon reduction path over its entire life cycle using a digital augmented twin based on the set of resource conflict nodes to obtain the target carbon reduction path includes: The resource conflict nodes are used to reconstruct the path sequence of the collaborative carbon reduction path to generate corresponding conflict-free alternative paths. The digital augmented twin is used to analyze the carbon emission impact correlation between adjacent life cycle stages of each conflict-free alternative path, and the cross-stage carbon emission reduction contribution is quantified. The net carbon emission reduction of the conflict-free alternative path relative to the baseline carbon emission trajectory is calculated based on the cross-stage carbon emission reduction contribution. Using the maximization of net carbon emission reduction as the screening criterion, a target carbon reduction path is selected from the conflict-free alternative paths.

[0048] Specifically, due to the limited resources in substation construction, resource conflict nodes in the collaborative carbon reduction path will prevent conflicting operations from being carried out in parallel as planned, leading to delays, idle time, or equipment downtime. These engineering disturbances will cause extended operating time for temporary facilities, extended service life of old equipment, or additional energy consumption, ultimately resulting in unplanned carbon emission rebounds. Therefore, this embodiment considers each node in the resource conflict node set as a potential risk point for carbon emission rebounds and uses it as a constraint to modify the collaborative carbon reduction path. Specifically, this embodiment, based on the conflict time window, competing resource type, and associated operation recorded in the resource conflict node set, combined with the real-time status data of engineering resources and the operational logic dependencies in the digital augmented twin, performs time-series rearrangement or spatial avoidance processing on the operation segments that trigger resource competition in the collaborative carbon reduction path based on resource availability. This adjusts the planned start time, operation sequence, or spatial occupancy of conflicting operations, eliminates the risk of idle time and equipment downtime caused by resource competition, and generates several conflict-free alternative paths that meet the hard constraints of resource supply and maintain the carbon reduction target.

[0049] Then, in this embodiment, the adjusted operation sequence, resource allocation scheme, and spatial layout information of each conflict-free alternative path are input into a digital augmented twin. The digital augmented twin is then used to simulate the carbon emission changes of the substation's main facilities and temporary buildings at each lifecycle stage, generating a full lifecycle carbon emission time-series curve corresponding to the conflict-free alternative path. Based on this full lifecycle carbon emission time-series curve, the mutual influence relationship between carbon emission states of adjacent lifecycle stages is analyzed. Specifically, this embodiment quantifies the degree to which carbon reduction measures in the previous stage (such as equipment energy efficiency improvement) improve the carbon emission baseline in the subsequent stage, and the relationship between subsequent operational activities (such as demolition and disposal) and the carbon emission continuation of legacy facilities in the previous stage. This embodiment quantifies the degree of influence between the above-mentioned different lifecycle stages as cross-stage carbon emission reduction contribution. The stage carbon emission reduction contribution characterizes the impact of current stage carbon reduction measures on the reduction of carbon footprint in subsequent stages. Specifically, this embodiment uses a digital augmented twin to simulate the total carbon emissions of the conflict-free alternative path in adjacent life cycle stages, which are denoted as the carbon emissions of the previous stage and the carbon emissions of the next stage, respectively. Next, the carbon emissions of the next stage under the conflict-free alternative path are compared with the baseline carbon emission trajectory (i.e., the carbon emissions of the next stage when the path is not implemented), and the change in carbon emissions in the next stage due to the implementation of the conflict-free alternative path is calculated. The change in carbon emissions is attributed to the carbon reduction measures taken in the previous stage and is used as the cross-stage carbon emission reduction contribution of the conflict-free alternative path between adjacent life cycle stages. If the change is negative, the contribution is positive (emission reduction); if the change is positive, the contribution is negative (emission increase).

[0050] For each conflict-free alternative route, this embodiment sums the carbon emissions of each life cycle stage in its full life cycle carbon emission time-series curve to obtain the total full life cycle carbon emissions of the alternative route. Simultaneously, this embodiment extracts the corresponding stage carbon emissions from the baseline carbon emission trajectory that has not implemented any carbon reduction measures to obtain the baseline full life cycle carbon emissions. Subtracting the total full life cycle carbon emissions of the alternative routes from the baseline full life cycle carbon emissions yields the gross carbon reduction of the conflict-free alternative route over its entire life cycle. Based on this, this embodiment identifies the carbon emission rebound caused by route adjustments (such as extending the construction period or changing the operation method to avoid resource conflicts) by combining cross-stage carbon reduction contribution. The carbon emission rebound originates from the additional operating energy consumption of temporary facilities due to process delays, and the old... For excess emissions caused by equipment operating beyond its service life, this embodiment subtracts the carbon emission rebound from the gross carbon emission reduction over the entire life cycle to obtain the net carbon emission reduction of the conflict-free alternative path. The net carbon emission reduction reflects the actual carbon emission reduction effect achieved by the conflict-free alternative path after eliminating resource conflicts. Finally, this embodiment sorts the net carbon emission reductions of each conflict-free alternative path, taking the maximization of net carbon emission reduction as the primary screening indicator. Under the premise of meeting resource constraints and engineering feasibility, the conflict-free alternative path with the largest net carbon emission reduction is selected as the target carbon reduction path. The target carbon reduction path includes a list of specific carbon reduction control measures for each stage, an implementation schedule, an expected carbon emission reduction curve, and dynamic adjustment strategies for key nodes, providing an executable optimal implementation plan for the dynamic management of the substation's carbon footprint throughout its entire life cycle.

[0051] This invention provides a method for dynamic management of the carbon footprint of a substation throughout its entire lifecycle. The method determines the spatiotemporal boundaries of carbon emissions at different lifecycle stages of the substation based on the physical structure data of the substation's main facilities and temporary buildings. Based on these boundaries, carbon emission sources are identified to obtain a set of carbon emission source items. The carbon emissions of each source are then calculated to form an initial carbon footprint dataset. This initial carbon footprint dataset is then mapped to a pre-constructed digital twin of the substation's basic structure to construct an enhanced digital twin. The enhanced digital twin is used to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary buildings at each lifecycle stage. Based on these characteristics, the carbon emission coupling effect between the substation's main facilities and temporary buildings is analyzed to obtain collaborative carbon reduction paths. Resource competition risks are identified for these collaborative carbon reduction paths to obtain a set of resource conflict nodes. Finally, based on this set, the enhanced digital twin is used to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire lifecycle to obtain the target carbon reduction path. Compared with existing technologies, this method accurately captures the spatiotemporal distribution characteristics and coupling effects of carbon emissions by fusing physical structure data and digital augmented twins, thereby achieving synergistic optimization of the carbon footprint of substations throughout their entire life cycle.

[0052] It should be noted that the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0053] In one embodiment, such as Figure 2 As shown in the figure, this embodiment of the invention provides a dynamic management and control system for the carbon footprint of a substation throughout its entire life cycle. The system includes: The spatiotemporal division module 101 is used to determine the spatiotemporal boundaries of carbon emissions at different life stages of the substation based on the physical structure data of the substation's main facilities and temporary buildings. The carbon footprint analysis module 102 is used to identify carbon emission sources based on the spatiotemporal boundary of carbon emissions, obtain a set of carbon emission source items, and calculate the carbon emission amount of each carbon emission source based on the set of carbon emission source items to form an initial carbon footprint dataset. The twin association module 103 is used to perform data association mapping between the initial carbon footprint dataset and the pre-constructed substation basic digital twin to construct a digitally enhanced twin; The feature extraction module 104 is used to extract the spatiotemporal distribution characteristics of carbon emissions of the substation main facilities and temporary buildings at each stage of their life cycle using the digital augmented twin. The path construction module 105 is used to analyze the carbon emission coupling effect between the substation main facilities and temporary buildings based on the spatiotemporal distribution characteristics of carbon emissions, obtain the collaborative carbon reduction path of the substation main facilities and temporary buildings, and identify the resource competition risk of the collaborative carbon reduction path to obtain a set of resource conflict nodes. The path determination module 106 is used to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire life cycle based on the set of resource conflict nodes using a digital augmented twin, so as to obtain the target carbon reduction path.

[0054] For specific limitations regarding a dynamic management system for the carbon footprint of a substation throughout its entire lifecycle, please refer to the above-described limitations regarding a dynamic management method for the carbon footprint of a substation throughout its entire lifecycle, which will not be repeated here. Those skilled in the art will recognize that the various modules and steps described in conjunction with the embodiments disclosed in this application can be implemented in hardware, software, or a combination of both. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0055] This invention provides a dynamic management system for the carbon footprint of a substation throughout its entire lifecycle. The system's spatiotemporal partitioning module determines the spatiotemporal boundaries of carbon emissions at different lifecycle stages of the substation based on the physical structure data of the substation's main facilities and temporary buildings. The carbon footprint analysis module identifies carbon emission sources based on these boundaries, obtaining a set of carbon emission source items, and calculates the carbon emissions of each source based on this set, forming an initial carbon footprint dataset. The twin association module maps the initial carbon footprint dataset to a pre-constructed basic digital twin of the substation, constructing a digitally enhanced twin. The feature extraction module uses a digital augmented twin to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary buildings at each stage of their life cycle. The path construction module analyzes the carbon emission coupling effect between the substation's main facilities and temporary buildings based on these spatiotemporal distribution characteristics, obtaining collaborative carbon reduction paths for these facilities and buildings. It also identifies resource competition risks for these collaborative carbon reduction paths, resulting in a set of resource conflict nodes. The path determination module, based on this set of resource conflict nodes, uses a digital augmented twin to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire life cycle, thus obtaining the target carbon reduction path. Compared to existing technologies, this system achieves collaborative optimization of the substation's carbon footprint throughout its entire life cycle by accurately capturing the spatiotemporal distribution characteristics and coupling effects of carbon emissions through the fusion of physical structure data and digital augmented twins.

[0056] In one embodiment, 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 above-described method.

[0057] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., SSD), etc.

[0058] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed, it can include the processes of the embodiments of the above methods.

[0059] The embodiments described above are merely preferred embodiments of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the technical principles of this invention, and these improvements and substitutions should also be considered within the scope of protection of this application. Therefore, the scope of protection of this patent application should be determined by the scope of the claims.

Claims

1. A method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle, characterized in that, Includes the following steps: The spatial and temporal boundaries of carbon emissions at different life stages of the substation are determined based on the physical structure data of the substation's main facilities and temporary buildings. Carbon emission sources are identified based on the spatiotemporal boundaries of carbon emissions to obtain a set of carbon emission source items. The carbon emission amount of each carbon emission source is calculated based on the set of carbon emission source items to form an initial carbon footprint dataset. The initial carbon footprint dataset is mapped to the pre-built digital twin of the substation infrastructure to construct a digital augmented twin. The digital augmented twin was used to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary buildings at each stage of their life cycle. Based on the spatiotemporal distribution characteristics of carbon emissions, the carbon emission coupling effect between the substation main facilities and temporary buildings is analyzed to obtain the collaborative carbon reduction path of the substation main facilities and temporary buildings. Resource competition risk is identified for the collaborative carbon reduction path to obtain a set of resource conflict nodes. Based on the set of resource conflict nodes, a digital augmented twin is used to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire life cycle, thereby obtaining the target carbon reduction path.

2. The method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle as described in claim 1, characterized in that, The steps for determining the spatiotemporal boundaries of carbon emissions at different life stages of a substation based on the physical structure data of the substation's main facilities and temporary buildings include: Based on the physical structure data of the substation main facilities and temporary buildings, the spatial existence status of the substation main facilities and temporary buildings at different life cycle stages is analyzed to obtain the spatial boundary data of the substation main facilities and temporary buildings in each life cycle stage. Extract the start and end times, duration, and connection relationships between each life cycle stage of the substation to generate basic time sequence data of the substation's main facilities. Extract the erection time, usage period, demolition time, and predicted turnover and relocation time of temporary buildings during construction to generate time-series dynamic data of temporary buildings; Based on the time-series basic data of the substation main facilities and the time-series dynamic data of the temporary buildings, the temporal coupling relationship between the intervention period of the temporary buildings and the procedures of the substation main facilities is analyzed to obtain the time boundary data of the substation main facilities and temporary buildings in each life cycle stage. Based on the spatial boundary data and the temporal boundary data, the geographic spatial boundaries and statistical time intervals corresponding to carbon emission accounting in each life cycle stage are analyzed to obtain the spatiotemporal boundaries of carbon emissions in different life cycle stages of the substation.

3. The method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle as described in claim 1, characterized in that, The step of identifying carbon emission sources based on the spatiotemporal boundary of carbon emissions to obtain a set of carbon emission source items includes: Based on the aforementioned carbon emission spatiotemporal boundary, the effective time interval and effective spatial range for carbon emission accounting at each stage of the substation's life cycle are extracted to generate the effective spatiotemporal range for carbon emissions. Based on the physical structure data of the substation's main facilities and temporary buildings, and the planning of the mechanical operation area, the carbon emission sources within the effective time and space range of carbon emissions are located to obtain the carbon emission activity targets. The carbon emission behavior of the carbon emission activity targets within the effective time and space range of carbon emission is analyzed to obtain the carbon emission activity type; The carbon emission activity objects are structurally labeled based on the carbon emission activity type to generate a set of carbon emission source items.

4. The method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle as described in claim 1, characterized in that, The step of mapping the initial carbon footprint dataset with the pre-constructed digital twin of the substation infrastructure to construct a digitally enhanced twin includes: Extract all associated physical entity nodes and process nodes from the pre-built substation basic digital twin to form a twin node information database; The association mapping relationship between the initial carbon footprint dataset and the twin node information database is established by using a spatiotemporal dual matching mapping rule; The initial carbon footprint dataset is written into the corresponding physical entity nodes and process nodes in the substation basic digital twin using the aforementioned association mapping relationship, thereby obtaining a digitally enhanced twin.

5. The method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle as described in claim 1, characterized in that, The steps for extracting the spatiotemporal distribution characteristics of carbon emissions from substation main facilities and temporary buildings at each stage of their life cycle using the digital augmented twin include: Based on the three-dimensional spatial coordinate system built into the digital augmented twin, the spatial occupancy range of the substation main facilities and temporary buildings at each stage of their life cycle is divided into spatial grids, and the continuous space in the digital augmented twin is discretized into several spatial units. The carbon emission intensity per unit area is calculated based on the cumulative carbon emission value of each spatial unit in each life cycle stage, and the carbon emission intensity distribution results in the spatial dimension are obtained. The digital augmented twin is used to sort the carbon emission occurrence times in each life cycle stage and identify the peak carbon emission times when carbon emissions reach a local maximum in each life cycle stage. Calculate the inflection points of carbon emission growth and decline rates in each life cycle stage to generate carbon emission fluctuation ranges; Based on the carbon emission intensity distribution results, the peak carbon emission time points, and the carbon emission fluctuation range, the overlapping range of high carbon emission intensity areas and peak emission periods is analyzed to form the spatiotemporal distribution characteristics of carbon emissions.

6. The method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle as described in claim 1, characterized in that, The steps for analyzing the carbon emission coupling effect between substation main facilities and temporary buildings based on the spatiotemporal distribution characteristics of carbon emissions, and obtaining the synergistic carbon reduction path of substation main facilities and temporary buildings, include: Based on the spatiotemporal distribution characteristics of carbon emissions, a spatiotemporal overlay analysis was performed on the high carbon emission intensity areas and peak emission periods of each life cycle stage of the substation to obtain the spatiotemporal coupling hotspots of carbon emissions where there is mutual influence between the substation's main facilities and temporary buildings. Correlation analysis was conducted on the carbon emission transmission process between the substation main facilities and temporary buildings within the spatiotemporal coupling hotspot area to obtain the carbon emission coupling effect intensity index between the substation main facilities and temporary buildings. With the goal of minimizing the overall carbon emission peak in the spatiotemporal coupling hotspot region, multiple scenarios are extrapolated using the coupling effect strength index and the process evolution logic of each life cycle stage of the digital enhanced twin to generate several collaborative carbon reduction paths.

7. The method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle as described in claim 1, characterized in that, The step of identifying resource competition risks in the collaborative carbon reduction pathway to obtain a set of resource conflict nodes includes: The resource demand information of the collaborative carbon reduction path during its execution is analyzed, and the resource supply ceiling for each life cycle stage is retrieved from the digital augmented twin. By comparing the resource demand information of collaborative carbon reduction pathway operation nodes within the same spatiotemporal range with the resource supply ceiling, resource competition conflict areas can be identified. Based on the resource competition conflict area, the resource competition events in the resource competition conflict area are traced and analyzed by utilizing the operational logic dependency relationship between the collaborative carbon reduction path operation nodes, and conflict path operation nodes with resource competition risks are identified. The conflict path operation nodes are deduplicated and integrated according to their life cycle stage, occurrence time sequence, and competing resource type to form a set of resource conflict nodes covering the entire process of the collaborative carbon reduction path.

8. The method for dynamic management and control of the carbon footprint of a substation throughout its entire life cycle as described in claim 1, characterized in that, The step of simulating the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire life cycle using a digital augmented twin based on the set of resource conflict nodes to obtain the target carbon reduction path includes: The resource conflict nodes are used to reconstruct the path sequence of the collaborative carbon reduction path to generate corresponding conflict-free alternative paths. The digital augmented twin is used to analyze the carbon emission impact correlation between adjacent life cycle stages of each conflict-free alternative path, and the cross-stage carbon emission reduction contribution is quantified. The net carbon emission reduction of the conflict-free alternative path relative to the baseline carbon emission trajectory is calculated based on the cross-stage carbon emission reduction contribution. Using the maximization of net carbon emission reduction as the screening criterion, a target carbon reduction path is selected from the conflict-free alternative paths.

9. A dynamic management and control system for the carbon footprint of a substation throughout its entire life cycle, characterized in that, The system includes: The spatiotemporal partitioning module is used to determine the spatiotemporal boundaries of carbon emissions at different life stages of a substation based on the physical structure data of the substation's main facilities and temporary buildings. The carbon footprint analysis module is used to identify carbon emission sources based on the spatiotemporal boundary of carbon emissions, obtain a set of carbon emission source items, and calculate the carbon emission amount of each carbon emission source based on the set of carbon emission source items to form an initial carbon footprint dataset. The twin association module is used to perform data association mapping between the initial carbon footprint dataset and the pre-constructed substation basic digital twin to construct a digitally enhanced twin; The feature extraction module is used to extract the spatiotemporal distribution characteristics of carbon emissions from the substation's main facilities and temporary buildings at each stage of their life cycle using the digital augmented twin. The path construction module is used to analyze the carbon emission coupling effect between the substation main facilities and temporary buildings based on the spatiotemporal distribution characteristics of carbon emissions, obtain the collaborative carbon reduction path of the substation main facilities and temporary buildings, and identify the resource competition risk of the collaborative carbon reduction path to obtain a set of resource conflict nodes. The path determination module is used to simulate the carbon emission reduction trajectory of each collaborative carbon reduction path throughout its entire life cycle based on the set of resource conflict nodes using a digital augmented twin, thereby obtaining the target carbon reduction path.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 8.

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