Full-life-cycle carbon emission metering and carbon reduction method and system suitable for transformer substation main power house

Abstract

The invention provides a full-life-cycle carbon emission metering and carbon reduction method and system suitable for a main power house of a transformer substation, and belongs to the field of low-carbon construction of electric power infrastructures. The method aims to solve the problems that carbon emission of building material production, transportation, construction and decommissioning links is neglected in an existing method, carbon footprint data of the whole life cycle is lost, and data support cannot be provided for comprehensive low-carbon transformation. According to the method, a material and equipment acquisition stage, a transportation stage, a construction stage, an operation stage and a decommissioning stage are covered, in the construction stage, a mechanical attitude sensor and a fuel sensor are installed, and the operation state of equipment is recognized through signals, so that dynamic metering of carbon emission is achieved; in the operation stage, a CEEMDAN-LSTM hybrid algorithm is adopted to predict the carbon emission per unit time, and support is provided for long-term carbon management; and finally, measuring and predicting a result according to the carbon emission of each stage. Quantitative, real-time and intelligent control over the whole process of carbon emission of the main plant of the transformer substation is achieved, and high precision, expandability and engineering application value are achieved.

Description

Technical Field

[0001] This invention relates to the field of low-carbon construction technology for power infrastructure, and more specifically, to a method and system for measuring and reducing carbon emissions throughout the entire life cycle of a substation main building. Background Technology

[0002] As global climate change becomes increasingly severe, governments and international organizations worldwide have set carbon peaking and carbon neutrality targets, urging various industries to implement emission reduction measures. As a key component of energy infrastructure, substations play a significant role in carbon emissions within the power system. Substations involve substantial consumption of building materials, machinery, and energy during construction, operation, and decommissioning, particularly during the construction phase. Existing carbon emission measurement methods largely focus on energy efficiency management during the operational phase, neglecting carbon emissions from building material production, transportation, construction, and decommissioning. This results in a lack of full life-cycle carbon footprint data, hindering comprehensive low-carbon transformation.

[0003] To address the above issues, this invention provides a method for carbon emission measurement and reduction throughout the entire life cycle. By introducing IoT sensing technology during the construction phase and combining it with deep learning algorithms for carbon emission prediction during the operation phase, a real-time, dynamically adjustable carbon emission management solution is provided. Summary of the Invention

[0004] The technical problem to be solved by this invention is:

[0005] To address the problem that existing carbon emission measurement methods focus on energy efficiency management during the operational phase, neglecting carbon emissions from building material production, transportation, construction, and decommissioning, resulting in a lack of full life-cycle carbon footprint data, and thus failing to provide data support for comprehensive low-carbon transformation.

[0006] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0007] This invention provides a method for measuring and reducing carbon emissions throughout the entire life cycle of a substation main building, comprising the following steps:

[0008] S100. Establish the carbon emission system boundary for the entire life cycle of the main plant, including the material and equipment acquisition phase, transportation phase, construction phase, operation phase, and decommissioning phase.

[0009] S200. In the material and equipment acquisition stage, by collecting energy consumption data generated during the production and processing of materials and equipment required for the substation project, the total carbon emissions of substation main structural materials, electrical equipment and auxiliary system equipment are calculated.

[0010] S300. During the transportation phase, carbon emissions generated during the entire process of transporting building materials and equipment from the production site to the construction site are calculated by collecting transportation activity data; the calculation includes carbon emissions corresponding to the energy consumption of different transportation modes.

[0011] S400 During the construction phase, for the energy consumption of mechanical equipment at the construction site, the operating parameters of the equipment are collected in real time through mechanical attitude sensors and fuel sensors, and uploaded to the cloud platform through the Internet of Things communication network. Carbon emissions are calculated based on fuel consumption and carbon factors.

[0012] S500. During the operation phase, the substation main plant's energy consumption monitoring system collects data on electricity, air conditioning, lighting, and equipment energy consumption during the main plant's operation. A carbon emission dataset is constructed based on carbon emission measurement methods to form a carbon emission time series. The time series is decomposed using the CEEMDAN decomposition method, decomposing the carbon emission data into several intrinsic mode functions and residual trend terms. The CEEMDAN decomposition and LSTM algorithm are integrated to predict future carbon emission trends. By comparing measured and predicted data, carbon emission trend prediction and error correction during the operation phase are achieved.

[0013] S600. During the decommissioning phase, carbon emissions are calculated for the main plant demolition, equipment transportation, and waste disposal. Carbon emissions during the decommissioning phase are calculated using the carbon emission factor method by statistically analyzing the fuel consumption of construction machinery, dismantling energy consumption, and waste transportation distance.

[0014] S700. Based on the carbon emission measurement and operation prediction results of each stage from S200 to S600, construct a phased carbon reduction strategy to achieve data-driven life cycle emission reduction.

[0015] Furthermore, in step S200, the carbon emissions during the material and equipment acquisition stage... for:

[0016]

[0017] Among them, M i Let be the consumption of the i-th type of material or equipment; n be the total number of materials or equipment; EF mat,i Let be the carbon emission factor of the i-th material or equipment.

[0018] Furthermore, in step S300, carbon emissions during the transportation phase... for:

[0019]

[0020] Among them, C transport Carbon emissions during the transportation phase; D represents the total mass of the i-th type of equipment or material; i Let EF be the transport distance for the i-th type of material or equipment; t,i The carbon emission factor is the transportation method used for the i-th material or equipment.

[0021] Furthermore, in step S400, carbon emissions during the construction phase... for:

[0022]

[0023] Among them, Q i T represents the quantity of work for the i-th sub-item; i，j The number of machine shifts used for the j-th type of construction machinery for the unit quantity of the i-th sub-item; R i，j The energy consumption per unit shift for the j-th type of construction machinery; EF i，j The emission factor of the energy used by the j-th type of construction machinery; η i，j q is the load correction factor, which is the ratio of the actual number of shifts of the construction machinery to the original number of shifts, determined by the real-time data collected by the sensors of the j-th type of construction machinery used in the unit quantity of the i-th sub-item of the project; i Let EF be the energy consumption of small machinery in the i-th sub-project, and its emission factor be EF. sm，i m represents the number of types of construction machinery. This represents the total number of sub-items.

[0024] Furthermore, in step S500, carbon emissions during the operation phase... for:

[0025]

[0026] Among them, C building Carbon emissions from building maintenance, cooling, heating, ventilation, and lighting during the substation operation phase; C electric Carbon emissions from transmission losses during the substation operation phase; C SF6 This refers to the emissions of sulfur hexafluoride (SF6) from the maintenance and decommissioning of SF6 equipment during the substation's operation phase, as well as the direct greenhouse gas emissions from air conditioning refrigerant leaks; C sink This refers to the carbon emission reductions generated by renewable energy and carbon sinks during the substation operation phase.

[0027] Furthermore, the CEEMDAN-LSTM algorithm is used to predict carbon emissions during the operation phase of the substation's main powerhouse. The steps include:

[0028] Perform CEEMDAN decomposition on the time series x(t):

[0029]

[0030] in, This is the original carbon emission time series; This is the i-th intrinsic mode component; b represents the residual trend term; b represents the total number of intrinsic modes.

[0031] Each intrinsic mode component is input into an LSTM (Long Short-Term Memory) network model, and the output is a predicted sequence:

[0032]

[0033]

[0034] in, This is a hidden layer state; For input samples; and Both are weight matrices; and All are bias terms; To predict carbon emission output values;

[0035] Final predicted value The sum of the reconstructions of each subsequence:

[0036]

[0037] in, This refers to the predicted i-th intrinsic mode component; This represents the predicted residual trend term.

[0038] Furthermore, in step S600, the carbon emissions during the decommissioning phase of the substation main plant are... for:

[0039]

[0040] in, For the emissions from demolition operations, This refers to the amount of waste disposed of.

[0041] Furthermore, in step S700, the carbon reduction strategy includes,

[0042] S710, Materials and Equipment Stage: Select low-carbon materials and green manufacturing equipment;

[0043] S720, Transportation Phase: Reduce fuel consumption through route optimization and increased load capacity, and promote electric transport vehicles;

[0044] S730, Construction Phase: Optimize machinery scheduling and reduce idling time based on real-time monitoring results from the Internet of Things, and promote electric drive equipment;

[0045] S740, Operational Phase: Adjust the energy consumption structure based on forecast results, adopt high-efficiency HVAC systems, LED lighting and distributed photovoltaic power generation systems, and establish a real-time carbon emission monitoring and feedback mechanism;

[0046] S750, Decommissioning Phase: Adopting a dismantled design, classified recycling process and carbon compensation mechanism to achieve resource-efficient and low-carbon decommissioning.

[0047] A life-cycle carbon emission metering and carbon reduction system applicable to the main building of a substation is provided. The system has program modules corresponding to the above steps and executes the steps in the above-described life-cycle carbon emission metering and carbon reduction method applicable to the main building of a substation during operation.

[0048] A computer-readable storage medium storing a computer program configured to, when invoked by a processor, implement the steps of a life-cycle carbon emission metering and reduction method applicable to a substation main plant.

[0049] Compared with the prior art, the beneficial effects of the present invention are:

[0050] This invention provides a method and system for carbon emission measurement and reduction throughout the entire life cycle of a substation main building, and formulates carbon reduction strategies in stages based on measurement results and predicted data. The method covers five stages: material and equipment acquisition, transportation, construction, operation, and decommissioning, realizing full-process monitoring and control of carbon emissions from building material production to building decommissioning.

[0051] This invention introduces an IoT-based real-time monitoring system for construction machinery to obtain more accurate carbon emission data during the construction phase. By installing mechanical attitude sensors and fuel sensors on major construction machinery such as excavators and cranes, real-time data on machinery operating parameters and fuel consumption is collected. This data is then uploaded to a cloud platform using IoT technology. The server receives fuel consumption and attitude data for each time period of the construction equipment, calculates the total carbon emissions for the construction phase, and can break it down to each piece of equipment and each construction process. During the analysis, the actual operating time and load recorded by the sensors can be compared and verified with traditional construction logs to correct the basic carbon emission data and ensure its reliability.

[0052] This invention, after obtaining a certain amount of operational carbon emission data through a full life-cycle carbon emission model, employs a CEEMDAN-LSTM hybrid algorithm to predict carbon emissions during future operational phases. This invention focuses on predicting the carbon emissions of the main plant per unit of operational time (e.g., annually). The model can be calibrated and trained using carbon emission data from similar currently operating substations, and then the annual carbon emission trend of the target substation for the next few years can be predicted. By employing a hybrid strategy of signal decomposition and deep learning, the prediction accuracy can be effectively improved, overcoming the limitations of single models in predicting highly volatile carbon emission sequences. The prediction results will be used to assess the carbon emission level of the main plant during its operational period in advance, providing a basis for developing long-term emission reduction plans.

[0053] This invention combines carbon emission data and prediction results from each stage to construct carbon reduction solutions including low-carbon material selection, green transportation, energy-saving dispatch, and energy structure optimization. This promotes carbon emission reduction in the main substation building throughout the material and equipment, transportation, construction, operation, and decommissioning stages, minimizing carbon emissions throughout the entire process from construction to decommissioning. This provides technical support for achieving carbon peaking and carbon neutrality goals. Based on measured and predicted carbon emission data at each stage, this invention develops targeted carbon reduction strategies for material selection, logistics and transportation, construction organization, energy efficiency optimization, and resource recycling, achieving data-driven, full life-cycle low-carbon optimization. Attached Figure Description

[0054] Figure 1 This is a flowchart of a method for measuring and reducing carbon emissions throughout the entire life cycle of a substation main plant, as described in an embodiment of the present invention.

[0055] Figure 2 This is a flowchart illustrating the carbon emission data collection and processing during the construction phase in an embodiment of the present invention.

[0056] Figure 3 This is a flowchart illustrating the prediction of carbon emissions during the operational phase based on the CEEMDAN-LSTM algorithm in an embodiment of the present invention. Detailed Implementation

[0057] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0058] Specific Implementation Plan 1: Combining Figures 1 to 3 As shown, this invention provides a method for measuring and reducing carbon emissions throughout the entire life cycle of a substation main building, comprising the following steps:

[0059] S100. Establish the carbon emission system boundary for the entire life cycle of the main plant, including the material and equipment acquisition phase, transportation phase, construction phase, operation phase, and decommissioning phase.

[0060] S200. During the material and equipment acquisition phase, by collecting energy consumption data generated during the production and processing of materials and equipment required for the substation project, the total carbon emissions of substation main structural materials (such as steel bars, concrete, and steel structures), electrical equipment (such as transformers and GIS switchgear), and auxiliary system equipment (such as cables, protective cabinets, and grounding materials) are calculated; among which, the carbon emissions during the material and equipment acquisition phase... According to the formula:

[0061]

[0062] Among them, M i Let EF be the consumption of the i-th type of material or equipment (in tons, m³, or units), and n be the total number of materials or equipment; mat,i is the carbon emission factor of the i-th material (kgCO2e / unit amount);

[0063] S300. During the transportation phase, carbon emissions generated throughout the entire process of transporting building materials and equipment from the production site to the construction site are calculated by collecting transportation activity data (the product of the transport weight and transport distance of various materials). The calculation includes the carbon emissions corresponding to the energy consumption of different modes of transportation (such as road and rail). The carbon emissions during the transportation phase are also calculated. According to the formula:

[0064]

[0065] Among them, C transport Carbon emissions during the transportation phase (kg CO2e); D represents the total mass (t) of the i-th type of equipment or material. i For the transportation distance (km) of the i-th type of material or equipment, the actual transportation distance is preferred; EF t,i The carbon emission factor [kg CO2e / (t·km)] for the transportation mode (road, rail, etc.) used for the i-th material or equipment can be selected according to the "Building Carbon Emission Calculation Standard" or enterprise experience data when the transportation distance cannot be obtained.

[0066] S400. During the construction phase, for energy consumption including electricity, diesel, and gasoline consumed by construction site machinery and equipment (such as cranes, excavators, and welding machines), equipment operating parameters are collected in real time using mechanical attitude sensors and fuel sensors. This data is then uploaded to a cloud platform via an IoT communication network, and carbon emissions are calculated based on fuel consumption and carbon factors. For energy consumption during the construction phase where sensors are not installed, carbon emissions are calculated according to the carbon emission factor method specified in the regulations. The carbon emissions during the construction phase are... According to the formula:

[0067]

[0068] Among them, Q i T represents the quantity of work for the i-th sub-item; i，j The number of machine shifts used for the j-th type of construction machinery for the unit quantity of the i-th sub-item; R i，j Energy consumption per unit shift for the j-th type of construction machinery (kWh / shift or kg / shift); EF i，j The emission factor of the energy used by the j-th type of machinery (kg CO2e / kWh or kg CO2e / kg); η i，j η is the load correction factor, which is the ratio of the actual number of shifts of the construction machinery used in the i-th sub-item of the project to the original number of shifts, determined by the real-time data collected by the sensors of the j-th type of construction machinery. If no sensors are installed, η i，j =1; q i The energy consumption (kWh / unit of work) of small machinery in the i-th sub-item project has an emission factor of EF. sm，i m represents the number of types of construction machinery. This represents the total number of sub-items;

[0069] Combination Figure 2 As shown, during sensor deployment and data acquisition, mechanical attitude sensors and fuel sensors are installed on major construction machinery such as excavators and cranes. Mechanical attitude sensors detect the operating status of the machinery, such as parameters like vibration, tilt angle, start / stop, and speed, to identify the machinery's working posture and condition, thereby determining whether the equipment is in working, idling, overspeeding, or standby mode. Simultaneously, fuel level / flow sensors are installed in the fuel tank or engine fuel lines of the construction machinery to monitor changes in fuel consumption in real time. By combining these two types of sensors, detailed records of the construction machinery's fuel consumption and operating status can be obtained.

[0070] In IoT communication and edge computing, data collected by mechanical attitude sensors and fuel sensors are transmitted in real time via low-power wide-area networks. Edge devices perform preliminary processing on the raw data, such as filtering outliers, summarizing fuel consumption, and calculating the carbon emissions of each machine in real time based on a preset carbon emission calculation model (e.g., multiplying fuel consumption by a carbon emission factor to obtain CO2 emissions). The use of local edge computing reduces network transmission pressure and improves the real-time performance of data processing. The processed data is then uploaded to a cloud-based carbon monitoring platform for storage and comprehensive analysis.

[0071] During carbon emission data analysis, the server receives fuel consumption and attitude data of construction equipment at various times, accumulates and calculates the total carbon emissions for the construction phase, and can break it down to each piece of equipment and each construction procedure. During the analysis, the actual operating time and load of the machinery recorded by sensors can be compared and verified with traditional construction logs to ensure data reliability. This IoT monitoring system enables real-time monitoring of carbon emissions at the construction site, providing a basis for subsequent improvements. Compared to previous methods of estimating carbon emissions based on machine shifts and rated fuel consumption, this invention provides a more accurate and detailed source of construction carbon emission data.

[0072] S500. During the operation phase, the substation main plant's energy consumption monitoring system collects data on electricity, air conditioning, lighting, and equipment energy consumption during the main plant's operation. A carbon emission dataset is constructed based on carbon emission measurement methods, forming a carbon emission time series. The time series is then decomposed using the Fully Integrated Empirical Mode Decomposition with Noise (CEEMDAN) method, decomposing the carbon emission data into several intrinsic mode functions. With residual trend item This method integrates CEEMDAN decomposition and LSTM algorithms to predict future carbon emission trends. By comparing measured and predicted data, it achieves carbon emission trend prediction and error correction during the operational phase. (The text also mentions carbon emissions during the operational phase, but this seems unrelated to the main point about carbon emissions.) According to the formula:

[0073]

[0074] Among them, C building Carbon emissions (kgCO2e) from building maintenance, cooling, heating, ventilation, and lighting during the substation operation phase; C electric Carbon emissions (kgCO2e) from transmission losses during substation operation; C SF6 This refers to the direct greenhouse gas emissions (kgCO2e) from sulfur hexafluoride (SF6) equipment maintenance and decommissioning processes during the substation operation phase, as well as from air conditioning refrigerant leaks. sink Carbon emission reductions (kgCO2e) generated by renewable energy and carbon sinks during the substation operation phase.

[0075] Carbon emission prediction during the operation phase of the substation main plant uses the CEEMDAN-LSTM algorithm, and the steps include:

[0076] Perform CEEMDAN decomposition on the time series x(t):

[0077]

[0078] in, This is the original carbon emission time series; This is the i-th intrinsic mode component; b represents the residual trend term; b represents the total number of intrinsic modes.

[0079] Inputting each intrinsic mode component (IMF) into a Long Short-Term Memory (LSTM) network model, the output is a predicted sequence:

[0080]

[0081]

[0082] in, This is a hidden layer state; The input sample (the decomposed subsequence); and Both are weight matrices; and All are bias terms; To predict carbon emission output values;

[0083] Final predicted value The sum of the reconstructions of each subsequence:

[0084]

[0085] in, This refers to the predicted i-th intrinsic mode component; This refers to the predicted residual trend term;

[0086] S600. During the decommissioning phase, carbon emissions are calculated for the main plant demolition, equipment transportation, and waste disposal. Carbon emissions during the decommissioning phase are calculated using the carbon emission factor method by statistically analyzing the fuel consumption of construction machinery, dismantling energy consumption, and waste transportation distance. The carbon emissions during the decommissioning phase of the substation's main plant are calculated. According to the formula:

[0087]

[0088] in, For the emissions from demolition operations, Waste disposal emissions;

[0089] S700, based on the carbon emission measurement and operational forecast results at each stage, constructs a phased carbon reduction strategy to achieve data-driven lifecycle emission reduction; the carbon reduction strategy includes:

[0090] S710, Materials and Equipment Stage: Select low-carbon materials (low-carbon cement, recycled steel) and green manufacturing equipment (low-carbon certified equipment or equipment produced by carbon market compliant enterprises).

[0091] S720, Transportation Phase: Reduce fuel consumption through route optimization and increased load capacity, and promote electric transport vehicles;

[0092] S730, Construction Phase: Optimize machinery scheduling and reduce idling time based on real-time monitoring results from the Internet of Things, and promote electric drive equipment;

[0093] S740, Operational Phase: Adjust the energy consumption structure based on forecast results, adopt high-efficiency HVAC systems, LED lighting and distributed photovoltaic power generation systems, and establish a real-time carbon emission monitoring and feedback mechanism;

[0094] S750, Retirement Phase: Prioritize the adoption of detachable design, classified recycling processes, and carbon offset mechanisms to achieve resource-efficient and low-carbon retirement.

[0095] Specific Implementation Scheme 2: The present invention provides a life-cycle carbon emission metering and carbon reduction system applicable to the main plant of a substation. The system has program modules corresponding to the above steps and executes the steps in the above-mentioned life-cycle carbon emission metering and carbon reduction method applicable to the main plant of a substation during operation.

[0096] The other combinations and connections in this implementation scheme are the same as in Specific Implementation Scheme 1.

[0097] Specific Implementation Scheme 3: The present invention provides a computer-readable storage medium storing a computer program configured to, when called by a processor, implement the steps of a method for measuring and reducing carbon emissions throughout the entire life cycle of a substation main plant.

[0098] The other combinations and connections in this implementation scheme are the same as in Specific Implementation Scheme 1.

[0099] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for measuring and reducing carbon emissions throughout the entire life cycle of a substation main building, characterized in that, Includes the following steps: S100. Establish the carbon emission system boundary for the entire life cycle of the main plant, including the material and equipment acquisition phase, transportation phase, construction phase, operation phase, and decommissioning phase. S200. In the material and equipment acquisition stage, by collecting energy consumption data generated during the production and processing of materials and equipment required for the substation project, the total carbon emissions of substation main structural materials, electrical equipment and auxiliary system equipment are calculated. S300. During the transportation phase, carbon emissions generated during the entire process of transporting building materials and equipment from the production site to the construction site are calculated by collecting transportation activity data; the calculation includes carbon emissions corresponding to the energy consumption of different transportation modes. S400 During the construction phase, for the energy consumption of mechanical equipment at the construction site, the operating parameters of the equipment are collected in real time through mechanical attitude sensors and fuel sensors, and uploaded to the cloud platform through the Internet of Things communication network. Carbon emissions are calculated based on fuel consumption and carbon factors. S500. During the operation phase, the substation main plant's energy consumption monitoring system collects data on electricity, air conditioning, lighting, and equipment energy consumption during the main plant's operation. A carbon emission dataset is constructed based on carbon emission measurement methods to form a carbon emission time series. The time series is decomposed using the CEEMDAN decomposition method, decomposing the carbon emission data into several intrinsic mode functions and residual trend terms. The CEEMDAN decomposition and LSTM algorithm are integrated to predict future carbon emission trends. By comparing measured and predicted data, carbon emission trend prediction and error correction during the operation phase are achieved. S600. During the decommissioning phase, carbon emissions are calculated for the main plant demolition, equipment transportation, and waste disposal. Carbon emissions during the decommissioning phase are calculated using the carbon emission factor method by statistically analyzing the fuel consumption of construction machinery, dismantling energy consumption, and waste transportation distance. S700. Based on the carbon emission measurement and operation prediction results of each stage from S200 to S600, construct a phased carbon reduction strategy to achieve data-driven life cycle emission reduction.

2. The method for full life-cycle carbon emission measurement and reduction applicable to the main building of a substation according to claim 1, characterized in that: In step S200, carbon emissions during the material and equipment acquisition stage for: Among them, M i Let be the consumption of the i-th type of material or equipment; n be the total number of materials or equipment; EF mat,i Let be the carbon emission factor of the i-th material or equipment.

3. The method for full life-cycle carbon emission measurement and reduction applicable to the main building of a substation according to claim 2, characterized in that: In step S300, carbon emissions during the transportation phase for: Among them, C transport Carbon emissions during the transportation phase; D represents the total mass of the i-th type of equipment or material; i Let EF be the transport distance for the i-th type of material or equipment; t,i The carbon emission factor is the transportation method used for the i-th material or equipment.

4. The method for full life-cycle carbon emission measurement and reduction applicable to the main building of a substation according to claim 3, characterized in that: In step S400, carbon emissions during the construction phase for: Among them, Q i T represents the quantity of work for the i-th sub-item; i，j The number of machine shifts used for the j-th type of construction machinery for the unit quantity of the i-th sub-item; R i，j The energy consumption per unit shift for the j-th type of construction machinery; EF i，j The emission factor of the energy used by the j-th type of construction machinery; η i，j q is the load correction factor, which is the ratio of the actual number of shifts of the construction machinery to the original number of shifts, determined by the real-time data collected by the sensors of the j-th type of construction machinery used in the unit quantity of the i-th sub-item of the project; i Let EF be the energy consumption of small machinery in the i-th sub-project, and its emission factor be EF. sm，i m represents the number of types of construction machinery. This represents the total number of sub-items.

5. The method for full life-cycle carbon emission measurement and reduction applicable to the main building of a substation according to claim 4, characterized in that: In step S500, carbon emissions during the operation phase for: Among them, C building Carbon emissions from building maintenance, cooling, heating, ventilation, and lighting during the substation operation phase; C electric Carbon emissions from transmission losses during the substation operation phase; C SF6 This refers to the emissions of sulfur hexafluoride (SF6) from the maintenance and decommissioning of SF6 equipment during the substation's operation phase, as well as the direct greenhouse gas emissions from air conditioning refrigerant leaks; C sink This refers to the carbon emission reductions generated by renewable energy and carbon sinks during the substation operation phase.

6. The method for full life-cycle carbon emission measurement and reduction applicable to the main building of a substation according to claim 5, characterized in that: Carbon emission prediction during the operation phase of the substation main plant uses the CEEMDAN-LSTM algorithm, and the steps include: Perform CEEMDAN decomposition on the time series x(t): in, This is the original carbon emission time series; This is the i-th intrinsic mode component; b represents the residual trend term; b represents the total number of intrinsic modes. Each intrinsic mode component is input into an LSTM (Long Short-Term Memory) network model, and the output is a predicted sequence: in, This is a hidden layer state; For input samples; and Both are weight matrices; and All are bias terms; To predict carbon emission output values; Final predicted value The sum of the reconstructions of each subsequence: in, This refers to the predicted i-th intrinsic mode component; This represents the predicted residual trend term.

7. The method for full life-cycle carbon emission measurement and reduction applicable to the main building of a substation according to claim 6, characterized in that: In step S600, the carbon emissions during the decommissioning phase of the substation main plant are... for: in, For the emissions from demolition operations, This refers to the amount of waste disposal emissions.

8. The method for full life-cycle carbon emission measurement and reduction applicable to the main building of a substation according to claim 7, characterized in that: In step S700, the carbon reduction strategy includes, S710, Materials and Equipment Stage: Select low-carbon materials and green manufacturing equipment; S720, Transportation Phase: Reduce fuel consumption through route optimization and increased load capacity, and promote electric transport vehicles; S730, Construction Phase: Optimize machinery scheduling and reduce idling time based on real-time monitoring results from the Internet of Things, and promote electric drive equipment; S740, Operational Phase: Adjust the energy consumption structure based on forecast results, adopt high-efficiency HVAC systems, LED lighting and distributed photovoltaic power generation systems, and establish a real-time carbon emission monitoring and feedback mechanism; S750, Decommissioning Phase: Adopting a dismantled design, classified recycling process and carbon compensation mechanism to achieve resource-efficient and low-carbon decommissioning.

9. A life-cycle carbon emission metering and carbon reduction system suitable for the main building of a substation, characterized in that: The system has a program module corresponding to the steps of any one of the claims 1-8 above, and executes the steps in the above-described method for full life cycle carbon emission measurement and carbon reduction applicable to the main plant of a substation when it is run.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program configured to, when invoked by a processor, implement the steps of any one of claims 1-8, a method for measuring and reducing carbon emissions throughout the entire life cycle of a substation main plant.

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