Method for rapidly measuring and calculating carbon emission in full life cycle of transformer substation

Abstract

The invention relates to a method for rapidly measuring and calculating carbon emission in the whole life cycle of a transformer substation, and belongs to the field of carbon emission prediction. The method comprises the following steps: S1, decomposing a full life cycle and screening influence factors; s2, carrying out influence factor characteristic analysis and sensitivity analysis; and S3, constructing a general measurement and calculation model and carrying out accounting simulation. According to the method, the carbon emission influence factors in the whole life cycle of the transformer substation are delicately decomposed, key elements are accurately screened, and the correlation analysis and sensitivity analysis technologies are combined, so that a carbon emission measuring and calculating system which is high in universality and wide in applicability is successfully constructed.

Description

Technical Field

[0001] The present invention belongs to the field of carbon emission prediction, and specifically relates to a method for rapidly calculating the carbon emissions of a substation throughout its life cycle. The model constructed by this method can be widely applied to the carbon emission calculation and management of substations, helping power enterprises to quickly and accurately calculate and measure the carbon emission situation during the construction, operation, and decommissioning of substations, so as to support the monitoring, reporting, and verification (MRV) of carbon emissions. Background Art

[0002] As an important part of the power system, the carbon emissions during the operation of a substation cannot be ignored. Therefore, studying the carbon emission calculation model of a substation is of great significance for accurately measuring the carbon emission level of a substation and guiding energy conservation and emission reduction work. The development of the field of low-carbon calculation of substations has shown progress in many aspects. The attention and development in this field stem from the increasing global concern about climate change and sustainable development. Currently, the development of the low-carbon calculation model of substations presents several characteristics. From a technical perspective, the low-carbon calculation models of substations are becoming increasingly diverse and refined because substations of different types, scales, and operation characteristics have different requirements for calculation. The calculation models cover multiple aspects from carbon emission calculation to environmental impact measurement to meet a wide range of calculation needs. At the same time, the trend of data-driven and intelligent is becoming increasingly obvious. With the continuous development of big data and artificial intelligence technologies, the calculation models can use real-time monitoring data and advanced data analysis technologies to more accurately measure the low-carbon status and environmental impact of substations. The continuous progress of the low-carbon calculation models of substations provides important support for the low-carbon transformation and sustainable development of the energy industry. In the future, the calculation models will continue to evolve and optimize to address new challenges and needs. This will require more cooperation and innovation to jointly promote the development of this field. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for rapidly calculating the carbon emissions of a substation throughout its life cycle, aiming to provide an efficient, accurate, and life-cycle carbon emission calculation method for substations. The method decomposes the carbon emission impact factors of the substation throughout its life cycle, screens out the key impact factors, and combines the correlation analysis method and the sensitivity analysis model to construct a general carbon emission calculation model, so as to be able to quickly and accurately calculate the carbon emissions of substations of different scales (such as 110 kV).

[0004] To achieve the above purpose, the technical solution of the present invention is: a method for rapidly calculating the carbon emissions of a substation throughout its life cycle, including:

[0005] Step S1, decomposition throughout the life cycle and screening of impact factors;

[0006] Step S2, analysis of the characteristics of impact factors and sensitivity analysis;

[0007] Step S3: Construction of a general measurement model and accounting simulation.

[0008] In an example of the present invention, the whole life cycle of a substation is divided into five stages: production stage, transportation stage, construction and installation stage, operation and maintenance stage, and demolition and recycling stage.

[0009] In an example of the present invention, for 110 kV and 220 kV substations, factor reduction and principal component analysis methods are used to screen and extract the carbon emission impact factors of the substations, and the correlation between each impact factor and the carbon emissions in each stage is studied through correlation analysis. Finally, a measurement model is constructed based on the main impact factors and secondary impact factors.

[0010] In an example of the present invention, the specific content of step S1 is as follows:

[0011] Given the substation impact factor X, with m observed values x1, x2, …, x m , a total of n samples, the calculation steps of the principal component analysis are as follows:

[0012]

[0013] (1) Standardization processing: The average value of each column The variance of each column The standardized result

[0014] (2) Calculate the correlation coefficient to obtain the correlation coefficient matrix:

[0015]

[0016] (3) Calculate the eigenvalues and eigenvectors of R:

[0017] |R - λ i I| = 0

[0018] R is the correlation coefficient matrix, λ i is the eigenvalue, I is the identity matrix. Solve the above equation to obtain the eigenvalues λ1, λ2, …, λ m ; For each eigenvalue λ i , solve the equation:

[0019] (R - λ i I)a i = 0

[0020] In the formula: a i is the eigenvector corresponding to the eigenvalue λ i , solve the above eigenvector equation to obtain the eigenvectors a1, a2, …, a m ;

[0021] (4) Obtain the contribution rate of each component

[0022] The number of principal components is selected according to the cumulative contribution rate. Based on principal component analysis, the carbon emission impact factors of the substation can be screened out.

[0023] In an example of the present invention, the cumulative contribution rate threshold is 85%.

[0024] In an example of the present invention, the step S2 is specifically as follows:

[0025] The specific formula for the Pearson correlation coefficient studying the correlation between each carbon emission impact factor and the carbon emissions in each stage is as follows:

[0026]

[0027] In the formula: r represents the Pearson correlation coefficient. X i and Y i respectively represent the carbon emission value of the impact factor and the carbon emission value in this stage of the i-th sample. and respectively represent the mean values of the carbon emission value of the impact factor and the carbon emission value in this stage. n represents the number of samples.

[0028] On the basis of the correlation analysis, by carefully adjusting the equipment parameters and material properties, the sensitivity degree of the substation carbon emission to different input parameters is measured, and the sensitivity index of each equipment material is determined. The formula is as follows:

[0029]

[0030] f(x) is the output of the prediction model of the substation carbon emission, f0 represents the benchmark value of the model, S = h1,…,h j represents the combination set of input parameters, represents the input parameters x1,…,x i 's contribution to the model output due to their interaction, x1,…,x i represents the input parameters, that is, the equipment parameters and material properties affecting the substation carbon emission, n represents the number of samples;

[0031] The ratio of the decomposed partial variance to the total variance is the sensitivity; the first-order sensitivity index represents the influence of a single input parameter on the output, and the calculation formula is:

[0032]

[0033] S i represents the first-order sensitivity index of the i-th input parameter, D iThe partial variance of the i-th input parameter is denoted as, and D represents the total variance of the model output;

[0034] The global sensitivity index reflects the degree of influence of parameter interactions on the output parameter, and is expressed as:

[0035]

[0036] S Ti represents the global sensitivity index of the i-th input parameter, and D ～i represents the partial variance of the i-th input parameter and its interactions, and D represents the total variance of the model output.

[0037] In an example of the present invention, the step S3 is specifically:

[0038] (1) When calculating the carbon emissions of a substation, when the data of the main influencing factors and the secondary influencing factors are sufficient, the following calculation model is adopted:

[0039] ECE = ECE 主要 + ECE 次要

[0040] ECE is the total carbon emissions of the substation, which is divided into two parts: main and secondary

[0041] ECE 主要 = Y 材料 + Y 主设备 + Y 主能源 + Y 人力

[0042]

[0043] is the usage amount of the material, is the full life cycle factor of the material, EF k is the carbon emission factor of the material, r k is the demolition and recycling coefficient of the k-th material, D k is the transportation distance of the material, EF k is the carbon emission factor in the transportation stage;

[0044]

[0045] N k is the number of devices, E k is the production carbon emissions of the device, E t is the transportation carbon emissions of the device;

[0046]

[0047] N k is the number of devices, EF elis the carbon emission factor of electricity, P Fe is the no-load loss of the main transformer, P Cu is the load loss of the main transformer, P ad is the additional loss of the main transformer, T is the operating time, W other is the other electricity consumption loss in the station is the SF6 emission is the carbon emission factor of SF6, E t is the fuel consumption of the t-th type of equipment in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the number of the t-th type of equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline

[0048] Y 人力 = N worker × EF worker

[0049] N worker is the number of workers, EF worker is the carbon emission factor of labor

[0050] ECE 次要 = Y 次设备 + Y 次能源

[0051]

[0052] N k is the number of equipment, E k is the production carbon emission of equipment, r k is the demolition and recycling coefficient of the k-th type of material, E t is the transportation carbon emission of equipment

[0053]

[0054] Q C is the capacitor capacity, tanδ is the average dielectric loss coefficient of the capacitor, N C is the number of capacitors, P L is the capacity of the reactor, N L is the number of reactors, W other is other equipment consuming minor electricity, EF el is the carbon emission factor of electricity, T is the operating time, W k is the power of the k-th type of power-consuming equipment in the construction and installation stage, N K is the number of the k-th type of power-consuming equipment in the construction and installation stage, E t is the fuel consumption of the t-th type of equipment in the construction and installation stage, Q t is the average calorific value of gasoline, Nt is the quantity of the t-th type of equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline;

[0055] (2) When there is insufficient data for the secondary factor, the total carbon emission formula needs to be corrected. Remove the secondary carbon emissions from the formula and correct the equipment and energy in the main carbon emission formula:

[0056] ECE = ECE 主要 + ECE 次要

[0057] ECE is the total carbon emissions of the substation, divided into main and secondary parts. When the data of the secondary influencing factor is insufficient, it is simulated by the following formula:

[0058] ECE 主要 = Y 材料 + Y 设备 + Y 能源 + Y 人力

[0059]

[0060] MC k is the usage amount of the material, is the life cycle factor of the material, EF k is the carbon emission factor of the material, r k is the demolition and recycling coefficient of the k-th material, D k is the transportation distance of the material, is the carbon emission factor in the transportation stage;

[0061]

[0062] N k is the quantity of the equipment, E k is the production carbon emissions of the equipment, r k is the demolition and recycling coefficient of the k-th material, E t is the transportation carbon emissions of the equipment, M 设备 is the main equipment fitting coefficient;

[0063]

[0064] YE 次设备 is the carbon emissions of secondary equipment in the machine learning model database, and n is the number of this parameter in the database;

[0065]

[0066] N k is the quantity of the equipment, EF elis the carbon emission factor of electricity, P Fe is the no-load loss of the main transformer, P Cu is the load loss of the main transformer, P ad is the additional loss of the main transformer, T is the operation time, W other is the other electricity consumption loss in the substation is the SF6 emission is the carbon emission factor of SF6, E t is the fuel consumption of the t-th equipment in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the number of the t-th equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline, M 运维能源 is the operation and maintenance energy fitting coefficient, M 安装能源 is the installation energy fitting coefficient

[0067]

[0068] Q C is the capacitor capacity, tanδ is the average dielectric loss coefficient of the capacitor, N C is the number of capacitors, P L is the capacity of the reactor, N L is the number of reactors, W other is other equipment consuming minor electricity, EF el is the carbon emission factor of electricity, T is the operation time, W k is the power of the k-th power-consuming equipment in the construction and installation stage, N K is the number of the k-th power-consuming equipment in the construction and installation stage, E t is the fuel consumption of the t-th equipment in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the number of the t-th equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline

[0069] YE 次设备能源 is the carbon emission of secondary equipment energy in the machine learning model database, YE 次安装能源 is the carbon emission of secondary equipment energy in the machine learning model database

[0070] Y 人力 = N worker × EF worker

[0071] N worker is the number of workers, EF worker is the carbon emission factor of labor

[0072] The present invention also provides a computer-readable storage medium, on which computer program instructions capable of being run by a processor are stored. When the processor runs the computer program instructions, the method steps as described above can be implemented.

[0073] The present invention also provides an electronic device, which includes a processor and a memory. Among them, the memory stores a computer program. When the computer program is executed by the processor, the processor is caused to execute the method steps as described above.

[0074] The present invention also provides a computer program product, including a computer program, where the computer program is stored in a computer-readable storage medium; when a processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, causing the electronic device to execute the method steps as described above.

[0075] Compared with the prior art, the present invention has the following beneficial effects: Through principal component analysis and sensitivity analysis, the present invention quickly screens out key influencing factors, reduces the processing of redundant data, thereby reducing the computational complexity and time consumption. Although this technical solution still requires certain data support, by screening and extracting the influencing factors, the requirements for the comprehensiveness and accuracy of the data are reduced, enabling relatively accurate calculations even when the data is relatively insufficient. Through system decomposition and detailed analysis, this technical solution constructs personalized calculation models for substations of different scales, fully considering factors such as the equipment, operating conditions, and geographical environment of the substations, improving the accuracy of the calculations. Although this technical solution also uses historical data for analysis, more importantly, it can identify key influencing factors through principal component analysis and sensitivity analysis, and construct a calculation model based on these factors, thereby reducing the dependence on historical data to a certain extent.

[0076] High efficiency: The rapid carbon emission calculation model for the whole life cycle of the substations of the present invention can significantly shorten the calculation cycle. Through principal component analysis and sensitivity analysis models, it quickly screens out key influencing factors, reduces the processing of redundant data, and improves the calculation efficiency.

[0077] Accuracy: Through the system decomposition and detailed analysis of the whole life cycle of the substation, the present invention can accurately identify the key factors affecting carbon emissions, and combine principal component analysis and sensitivity analysis to construct a precise calculation model to ensure the accuracy of the calculation results.

[0078] Versatility: The calculation model of the present invention is applicable to substations of different scales, such as 110 kV. By constructing a general calculation framework and modules, it realizes the general calculation of carbon emissions for different types of substations, improving the application scope of the model.

[0079] Dynamic update: The measurement model can be dynamically updated according to real-time data and on-site conditions, ensuring the timeliness and accuracy of the measurement results, and providing strong support for carbon emission management and low-carbon transformation decision-making.

[0080] Strong guidance: Through sensitivity analysis, the present invention can identify the key parameters for optimization and adjustment, provide theoretical support for the low-carbon transformation of substations, and guide the key areas and measures of carbon emission management. Description of the Drawings

[0081] Figure 1 Is the influence factor.

[0082] Figure 2 Is the flow chart of the main and secondary influence factor measurement models.

[0083] Figure 3 Is the flow chart of the measurement model for insufficient secondary influence factors.

[0084] Figure 4 Is the flow chart of a rapid carbon emission measurement method for the whole life cycle of a substation according to the present invention. Detailed Implementation Modes

[0085] To facilitate the understanding of the technical approach, innovation points, expected goals and effects adopted by the present invention, the following elaborates in detail the basic principle, operation process and practical links of the carbon emission efficiency measurement method based on the whole life cycle of power transmission and transformation project equipment in the present invention through implementation cases in conjunction with diagrams.

[0086] Case Explanation

[0087] The following further explains the content of the present invention in combination with diagrams and actual cases. It should be clear that the following explanations are all illustrative in nature and are intended to provide more background information for this application. Unless otherwise specified, the technical and scientific terms involved in the text follow the general understanding of ordinary practitioners in this technical field.

[0088] It is hereby stated that the terms used are only for specifically explaining the implementation details and are not intended to limit the scope of the exemplary embodiments of this application.

[0089] The present invention provides a rapid carbon emission measurement method for the whole life cycle of a substation, including:

[0090] Step S1, decomposition of the whole life cycle and screening of influence factors;

[0091] Step S2, analysis of influence factor characteristics and sensitivity analysis;

[0092] Step S3, construction of a general measurement model and accounting simulation.

[0093] The following is the specific implementation process of the present invention.

[0094] As Figure 4 shown, a rapid calculation method for the carbon emissions of a substation throughout its life cycle according to the present invention includes

[0095] Step S1: Life cycle decomposition and impact factor screening

[0096] The present invention first systematically decomposes the life cycle of the substation. The life cycle decomposition includes each stage from the construction, operation to the decommissioning of the substation. Specifically, through a detailed analysis of the life cycle of a 110 kV substation, each key factor affecting carbon emissions is determined, such as equipment type, operating load, energy consumption, maintenance cycle, etc. For different types of substations, the decomposition principle and stage division are slightly different to ensure the adaptability and accuracy of the model.

[0097] Combined with the actual results of the carbon emissions accounting for the life cycle of a 110 kV substation, we will focus on measuring the contribution of the carbon emissions in each stage, as well as the weight of the main equipment materials in the overall carbon emissions. There are many impact factors in each stage of the substation. When analyzing the production stage, transportation stage, construction and installation stage, and demolition and recycling stage of the substation, the factors with a carbon emission proportion greater than 0.1% in each stage are selected for display, and the factors with a proportion lower than 0.1% are no longer displayed in the chart. For the operation and maintenance stage of the substation, the carbon emission proportion is very large in the whole life cycle, and all factors are displayed.

[0098] In the production stage, the main focus is on the production and manufacturing of substation equipment. This includes the production of transformers, switchgear, building materials, cables, and other auxiliary equipment. For each piece of equipment, it is necessary to record in detail its raw material procurement, energy consumption, and related costs during the manufacturing process. At the same time, attention should also be paid to the quality control during the production process to ensure that the equipment has high reliability and stability when leaving the factory. Table 1 shows the carbon emissions and proportion in the production stage of a 110 kV substation.

[0099] Table 1 Carbon emissions and proportion in the production stage of a 110 kV substation

[0100]

[0101]

[0102] The transportation stage involves the process of transporting the completed substation equipment from the factory to the construction and installation site. In this stage, it is necessary to record in detail the transportation costs, including the rental or purchase costs of transportation tools, energy consumption, transportation equipment type, transportation distance, etc. Table 2 shows the carbon emissions and proportion in the transportation stage of a 110 kV substation.

[0103] Table 2 Carbon Emissions and Proportions during the Transportation Stage of 110 kV Substations

[0104]

[0105]

[0106] Construction and installation is the process of assembling and commissioning substation equipment on-site. During this stage, it is necessary to record in detail the construction and installation costs, including labor costs, material costs, mechanical equipment, etc. Table 3 shows the carbon emissions and proportions during the construction and installation stage of 110 kV substations.

[0107] Table 3 Carbon Emissions and Proportions during the Construction and Installation Stage of 110 kV Substations

[0108]

[0109]

[0110] The operation and maintenance stage is the longest stage in the entire life cycle of the substation. During this stage, it is necessary to continuously monitor the operation status of substation equipment and conduct regular maintenance and repairs to ensure the long-term stable operation of the equipment. At the same time, it is also necessary to record the operation and maintenance costs, including energy consumption, spare parts costs, etc. Table 4 shows the carbon emissions and proportions during the operation and maintenance stage of 110 kV substations.

[0111] Table 4 Carbon Emissions and Proportions during the Operation and Maintenance Stage of 110 kV Substations

[0112] Operation and maintenance stage Name Carbon emissions (t / year) Proportion (%) 1 Main transformer 523.52 52.48 2 Capacitor 224.25 22.45 3 Reactor 112.354 11.23 4 Station internal power consumption 77.38331 7.76 5 <![CDATA[SF6 leakage]]> 59.815 6.00 6 Gasoline 0.604195 0.06 7 Inspection 0.3312 0.03

[0113] The demolition and recycling stage is the last stage of the entire life cycle of the substation. During this stage, it is necessary to disassemble and recycle the waste equipment. It is necessary to record in detail the demolition and recycling costs, including the carbon emissions that may be generated during disassembly, material demolition and recycling, and waste treatment. Table 5 shows the carbon emissions and proportions during the demolition and recycling stage of 110 kV substations.

[0114] Table 5 Carbon Emissions and Proportions during the Demolition and Recycling Stage of 110 kV Substations

[0115]

[0116] Secondly, the present invention uses factor dimensionality reduction and principal component analysis (PCA) to screen and extract the carbon emission influencing factors of the substation. Through dimensionality reduction processing, the number of influencing factors is reduced, making the model more concise and operable. The principal component analysis helps to extract the main influencing factors, and based on this, a list of carbon emission influencing factors for 110 kV and 220 kV substations is established.

[0117] After understanding the principle of principal component analysis, it is necessary to solve it using an algorithm. Given the substation impact factor X, with m observed values x1, x2, …, x m , a total of n samples, the calculation steps of principal component analysis are as follows:

[0118]

[0119] (1) Standardization processing: The average value of each column The variance of each column The standardization result

[0120] (2) Calculate the correlation coefficient to obtain the correlation coefficient matrix:

[0121]

[0122] (3) Calculate the eigenvalues and eigenvectors of R:

[0123] |R - λ i I| = 0

[0124] R is the correlation coefficient matrix, λ i is the eigenvalue, I is the identity matrix. Solving the above equation gives the eigenvalues λ1, λ2, …, λ m .

[0125] For each eigenvalue λ i , solve the equation:

[0126] (R - λ i I)a i = 0

[0127] In the formula: a i is the eigenvector corresponding to the eigenvalue λ i . Solving the above eigen-equation gives the eigenvectors a1, a2, …, a m .

[0128] (4) Obtain the contribution rates of each component

[0129] The selection of the number of principal components is determined according to the cumulative contribution rate. Generally, it is required that the cumulative contribution rate reaches more than 85%, which can ensure that the new variables can include most of the information of the original variables.

[0130] The impact factor list is as Figure 1 shown.

[0131] Step S2: Analysis of impact factor characteristics and sensitivity analysis

[0132] To deeply understand the contribution of each influencing factor to carbon emissions, the present invention conducts a correlation analysis on the influencing factors. By establishing a correlation analysis model, the relationships between the influencing factors are calculated, and the correlations of the carbon emission influencing factors at different life cycle stages are found. The correlation analysis helps to reveal which factors have the greatest impact on carbon emissions at different stages, and further guides the key areas of carbon emission management.

[0133] Correlation analysis can not only understand the degree of closeness between variables, study the correlations between each influencing factor and carbon emissions at each stage, and facilitate the study of the data structure at each stage. The specific formula for the Pearson correlation coefficient is as follows:

[0134]

[0135] In the formula: r represents the Pearson correlation coefficient. X i and Y i respectively represent the carbon emission value of the influencing factor and the carbon emission value at this stage for the i-th sample. and respectively represent the mean values of the carbon emission value of the influencing factor and the carbon emission value at this stage. n represents the number of samples.

[0136] In addition, the present invention also adopts a Sobol sensitivity analysis model to quantitatively calculate the sensitivity of each influencing factor to the carbon emissions of the substation. This analysis helps to determine which factors have an important impact on carbon emissions, thus providing a basis for subsequent carbon emission reduction measures. Through sensitivity analysis, the present invention can identify the key parameters for optimization and adjustment, thus providing theoretical support for the low-carbon transformation of the substation.

[0137] Based on data analysis, we further focus on the main electrical equipment and materials and construct a sensitivity analysis model. By carefully adjusting the equipment parameters and material properties, we systematically calculate the sensitivity degree of the substation carbon emissions to different input parameters and scientifically determine the sensitivity index of each equipment and material.

[0138]

[0139] f(x) is the output of the prediction model of the substation carbon emissions, f0 represents the benchmark value of the model, S = h1,…,h j represents the set of combinations of input parameters, represents the contribution of the interaction of the input parameters x1,…,x i to the model output, x1,…,x i represents the input parameters, that is, the equipment parameters and material properties that affect the substation carbon emissions, and n represents the number of samples.

[0140] The ratio of the decomposed partial variance to the total variance is the sensitivity; the first-order sensitivity index represents the impact of a single input parameter on the output, and the calculation formula is:

[0141]

[0142] S i represents the first-order sensitivity index of the i-th input parameter, D i represents the partial variance of the i-th input parameter, and D represents the total variance of the model output.

[0143] The global sensitivity index reflects the degree of influence of the interaction of parameters on the output parameter, and is expressed as:

[0144]

[0145] S Ti represents the global sensitivity index of the i-th input parameter, D ～i represents the partial variance of the i-th input parameter and its interaction, and D represents the total variance of the model output.

[0146] According to the formulas listed above, calculate the first-order sensitivity index and the overall sensitivity index at each stage of the substation. The specific values are shown in Table 6-10 below.

[0147] Table 6 Sensitivity of Influence Factors in the Production Stage of the Substation

[0148]

[0149]

[0150] Table 7 Sensitivity of Influence Factors in the Transportation Stage of the Substation

[0151] Influence factor First-order sensitivity index Overall sensitivity index Concrete 0.6577 0.6385 Steel 0.0952 0.0967 Cement 0.2132 0.2070 Transformer transportation carbon emissions 0.0173 0.0177 Number of transformers 0.0126 0.0122 GIS equipment transportation carbon emissions 0.0001 0.0015 Number of GIS equipment 0.0044 0.0040 Capacitor transportation carbon emissions 0.0003 0.0004 Number of capacitors 0.0005 0.0006 Reactor transportation carbon emissions 0.0024 0.0009 Number of reactors 0.0208 0.0220 High-voltage switchgear transportation carbon emissions 0.0003 0.0003 Number of high-voltage switchgear 0.0004 0.0005

[0152] Table 8 Sensitivity of Influence Factors in the Construction and Installation Stage of the Substation

[0153]

[0154]

[0155] Table 9 Sensitivity of Influence Factors in the Operation and Maintenance Stage of the Substation

[0156] Influence factor First-order sensitivity index Overall sensitivity index <![CDATA[SF6 emissions]]> 0.0492 0.0432 Annual power consumption per unit transformer 0.1869 0.2008 Number of transformers 0.4000 0.4266 Power consumption per unit reactor 0.0026 0.0029 Number of reactors 0.1434 0.1364 Power consumption per unit capacitor 0.0061 0.0071 Number of capacitors 0.0960 0.0997 Other internal power consumption in the station 0.1107 0.1074

[0157] Table 10 Sensitivity of Influence Factors in the Demolition and Recycling Stage of the Substation

[0158]

[0159]

[0160] Step S3: Construction of General Measurement Model and Accounting Simulation

[0161] Based on the results of correlation analysis and sensitivity analysis, the present invention further constructs a general carbon emission measurement model for substations. By extracting the main and secondary influencing factors, this model accurately accounts for the carbon emissions of substations. The measurement model includes a measurement module based on the main influencing factors and a measurement model for secondary influencing factors. For 110 kV substations, different measurement models are established respectively to ensure the accuracy and applicability of carbon emission measurement for different types of substations. Table 11 shows the main and secondary influencing factors.

[0162] Table 11 Main and Secondary Influencing Factors

[0163] Main influencing factors Minor influencing factors Concrete, steel, cement Power-consuming construction equipment Internal power consumption in the station Carbon emissions from the production of minor electrical equipment Relevant parameters of the main transformer Power consumption of minor electrical equipment Relevant parameters of GIS equipment Manpower and fuel-consuming trucks SF6 leakage

[0164] (1) Flowcharts of the measurement models for main and secondary influencing factors are as Figure 2 shown

[0165] When calculating the carbon emissions of substations, when the data of main and secondary influencing factors are sufficient, the following calculation model can be used:

[0166] ECE = ECE 主要 + ECE 次要

[0167] ECE is the total carbon emissions of the substation, divided into main and secondary parts

[0168] ECE 主要 = Y 材料 + Y 主设备 + Y 主能源 + Y 人力

[0169]

[0170] is the usage amount of the material (t, m 3 , m 2 ), is the life cycle factor of the material, EF k is the carbon emission factor of the material (kgCO2 / t, m 3 , m 2 ), r k is the demolition and recycling coefficient of the k-th material, D k is the transportation distance of the material, EF k is the carbon emission factor in the transportation stage (kgCO2 / t, m 3 , m 2 )

[0171]

[0172] N k is the number of devices, E k is the production carbon emission of the device (kgCO2), r k is the demolition and recycling coefficient of the k-th material, E t is the transportation carbon emission of the device (kgCO2).

[0173]

[0174] N k is the number of devices, EF el is the carbon emission factor of electricity (kgCO2 / t), P Fe is the no-load loss of the main transformer, P Cu is the load loss of the main transformer, P ad is the additional loss of the main transformer, T is the operating time, W other is the other electricity consumption loss in the station, is the SF6 emission, is the SF6 carbon emission factor (kgCO2 / t). E t is the fuel consumption of the t-th device during construction and installation, Q t is the average calorific value of gasoline, N t is the number of the t-th device during construction and installation, EF oil is the carbon emission factor of gasoline (kgCO2 / t).

[0175] Y 人力 = N worker × EF worker

[0176] N worker is the number of workers, EF worker is the carbon emission factor of labor.

[0177] ECE 次要 = Y 次设备 + Y 次能源

[0178]

[0179] N k is the number of devices, E k is the production carbon emission of the device (kgCO2), r k is the demolition and recycling coefficient of the k-th material, E t is the transportation carbon emission of the device (kgCO2).

[0180]

[0181] Q Cis the capacitance of the capacitor, tanδ is the average dielectric loss factor of the capacitor, N C is the number of capacitors, P L is the capacity of the reactor, N L is the number of reactors, W other is other equipment consuming minor power, EF el is the carbon emission factor of electricity (kgCO2 / t), T is the operating time, W k is the power of the k-th power-consuming equipment in the construction and installation stage, N K is the number of the k-th power-consuming equipment in the construction and installation stage, E t is the fuel consumption of the t-th equipment in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the number of the t-th equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline (kgCO2 / t).

[0182] According to the above calculation model, the present invention calculates and shows the carbon emission accounting results of 18 110kV substations. The carbon emission contributions of the main factors are significantly greater. It can be seen that in each substation, the carbon emission proportion of the main factors is much higher than that of the secondary factors. This indicates that the main influencing factors (such as concrete, steel, transformer equipment, etc.) play a dominant role in the carbon emissions throughout the life cycle of the substation and are the core objectives of carbon emission optimization.

[0183] The carbon emission contributions of the secondary factors show certain fluctuations. Although the carbon emissions of the secondary factors in each substation are significantly lower than those of the main factors in absolute value, the proportion is relatively high in some substations (such as Substation No. 7 and Substation No. 18). This indicates that although the overall impact of the secondary factors is small, they may have a certain impact on the optimization of the overall carbon emissions in specific scenarios. Table 12 shows the model accounting results of 110kV substations.

[0184] Table 12 Model Accounting Results of 110kV Substations

[0185]

[0186]

[0187] Table 13 shows the contribution ratios of the main factors and secondary factors to the total carbon emissions. It can be seen from Table 13 that among the 18 substations, the carbon emissions of the main energy generally account for the highest proportion, ranging from 64.20% (No. 15) to 89.12% (No. 2), which is the main source of carbon emissions in substations. This indicates that the usage intensity of the main energy directly determines the overall carbon emission level of the substation. Especially in substations with high proportions (such as No. 2, No. 7, and No. 18), there is the greatest room for optimization. In addition, although the proportion of materials is relatively low, it reaches nearly 10% in some substations (such as No. 17, 8.96%), reflecting the indirect impact of material usage on carbon emissions. It is worth noting that the proportion of secondary energy is still significant even when it is less than 10%, reaching a maximum of 27.69% (No. 15), indicating that secondary energy makes a non-negligible contribution to the total emissions of some substations.

[0188] On the other hand, the carbon emissions of the main equipment, secondary equipment, and manpower all account for relatively low proportions. The proportion of the main equipment ranges from 0.37% (No. 7) to 1.16% (No. 15), making a relatively limited contribution to the overall carbon emissions. The proportion of secondary equipment is usually less than 1%, with a maximum of only 0.75% (No. 17). The proportion of the manpower factor is the lowest, not exceeding 0.03%, indicating that it has the least impact on the total carbon emissions of the substation. In summary, the optimization of substation carbon emissions should prioritize the efficient use of the main energy and the emission reduction strategy of materials. At the same time, secondary energy also needs to be appropriately concerned in some substations with high proportions, while the optimization of the main equipment, secondary equipment, and manpower can be regarded as secondary goals.

[0189] Table 13 Proportion distribution of each part of the 110 kV substation model

[0190]

[0191]

[0192] (2) The flowchart of the measurement model for insufficient secondary influencing factors is as Figure 3 shown

[0193] When there is insufficient data for secondary factors, the total carbon emission formula needs to be corrected by removing the secondary carbon emissions from the formula and correcting the equipment and energy in the main carbon emission formula:

[0194] ECE = ECE 主要 + ECE 次要

[0195] ECE is the total carbon emissions of the substation, divided into main and secondary parts. When there is insufficient data for secondary factors, it can be simulated by the following formula:

[0196] ECE = Y 材料 + Y设备 +Y 能源 +Y 人力

[0197]

[0198] MC k For the usage amount of materials (t, m 3 , m 2 ), For the life cycle factor of materials, EF k For the carbon emission factor of materials (kgCO2 / t, m 3 , m 2 ), r k For the demolition and recycling coefficient of the k-th material, D k is the transportation distance of the materials, For the carbon emission factor in the transportation stage (kgCO2 / t, m 3 , m 2 )

[0199]

[0200] N k For the number of equipment, E k For the production carbon emission of the equipment (kgCO2), r k For the demolition and recycling coefficient of the k-th material, E t is the transportation carbon emission of the equipment (kgCO2), M 设备 is the main equipment fitting coefficient.

[0201]

[0202] YE 次设备 For the carbon emission of secondary equipment in the machine learning model database, n is the number of this parameter in the database.

[0203]

[0204] N k For the number of equipment, EF el For the carbon emission factor of electricity (kgCO2 / t), P Fe For the no-load loss of the main transformer, P Cu For the load loss of the main transformer, P ad For the additional loss of the main transformer, T is the operation time, W other For the other electricity consumption losses in the station, For the SF6 emission amount, For the SF6 carbon emission factor (kgCO2 / t). E t For the fuel consumption of the t-th equipment in the construction and installation stage, Q tis the average calorific value of gasoline, N t is the quantity of the t-th type of equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline (kgCO2 / t). M 运维能源 is the operation and maintenance energy fitting coefficient. M 安装能源 is the installation energy fitting coefficient.

[0205]

[0206] Q C is the capacitor capacity, tanδ is the average dielectric loss coefficient of the capacitor, N C is the number of capacitors, P L is the capacity of the reactor, N L is the number of reactors, W other is other equipment consuming minor electricity, EF el is the carbon emission factor of electricity (kgCO2 / t), T is the operation time, W k is the power of the k-th type of power-consuming equipment in the construction and installation stage, N K is the quantity of the k-th type of power-consuming equipment in the construction and installation stage, E t is the fuel consumption of the t-th type of equipment in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the quantity of the t-th type of equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline (kgCO2 / t).

[0207] YE 次设备能源 is the carbon emissions of secondary equipment energy in the machine learning model database, YE 次安装能源 is the carbon emissions of secondary equipment energy in the machine learning model database.

[0208] Y 人力 = N worker × EF worker

[0209] N worker is the number of workers, EF worker is the carbon emission factor of labor.

[0210] From Table 14, there is a high degree of consistency between the actual carbon emissions values and the fitting results of the 110 kV substations, indicating that the model has a good overall prediction effect on carbon emissions. In the figure, the blue bar chart represents the actual carbon emissions values of each substation, and the orange bar chart represents the fitting results of the model. The trends of the two almost overlap, indicating that the model can accurately reflect the carbon emission characteristics of the substations. However, in some individual substations (such as No. 7 and No. 18), the fitting results are slightly higher than the actual values, showing an overestimation tendency of the model in some scenarios. Overall, the fitting result deviations of the vast majority of substations are small, reflecting the overall robustness and reliability of the model. In particular, substations such as No. 2, No. 5, and No. 14 have extremely high degrees of coincidence between the fitting results and the actual values, fully verifying the applicability of the model.

[0211] Table 14 Fitting Effect of the Calculation Model for 110 kV Substations

[0212] Substation serial number True value of carbon emissions (t) Fitted value of carbon emissions (t) Fitting degree 1 94743.45 95576.92 1.0088 2 133309.74 135314.28 1.0150 3 86456.52 83156.58 0.9618 4 57073.11 59463.45 1.0419 5 90772.80 86587.30 0.9539 6 61350.25 60607.78 0.9879 7 152980.82 148279.87 0.9693 8 65953.55 63530.52 0.9633 9 55921.41 50948.97 0.9111 10 72224.49 73143.25 1.0127 11 53943.51 52480.88 0.9729 12 70865.62 74313.67 1.0487 13 54943.32 52800.14 0.9610 14 76260.46 74337.55 0.9748 15 44120.44 43009.55 0.9748 16 55639.51 55431.59 0.9963 17 49559.83 52179.88 1.0529 18 131355.38 126032.25 0.9595

[0213] As a measure of the prediction accuracy of the model, the fitting degree reflects the relative error between the fitting result and the actual value. From the fitting degree data, the fitting degrees of most substations are concentrated between 0.9 and 1.05, indicating that the model has a high prediction accuracy for the carbon emissions of substations. Among them, the substation No. 18 has the highest fitting degree (1.0529), indicating that the model has a certain degree of overestimation of the carbon emissions of this substation; while the substation No. 9 has the lowest fitting degree (0.9111), indicating that the predicted value of the model in this substation is slightly lower than the actual value. Although there are deviations in some individual substations, the fitting degree generally remains within a reasonable range, highlighting the strong generalization ability of the model.

[0214] The present invention also provides a computer-readable storage medium, on which computer program instructions capable of being run by a processor are stored. When the processor runs the computer program instructions, the method steps as described above can be implemented.

[0215] The present invention also provides an electronic device, which includes a processor and a memory. Among them, the memory stores a computer program. When the computer program is executed by the processor, the processor is caused to execute the method steps as described above.

[0216] The present invention also provides a computer program product, including a computer program, and the computer program is stored in a computer-readable storage medium; when the processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, causing the electronic device to execute the method steps as described above.

[0217] The above are the preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention in terms of the functions and effects produced shall fall within the protection scope of the present invention.

Claims

1. A rapid calculation method for the carbon emissions throughout the life cycle of a substation, characterized in that, Including: Step S1, full life cycle decomposition and impact factor screening; Step S2, impact factor characteristic analysis and sensitivity analysis; Step S3, general measurement model construction and accounting simulation.

2. The rapid carbon emission calculation method for the whole life cycle of a substation according to claim 1, wherein The full life cycle of the substation is divided into 5 stages: production stage, transportation stage, construction and installation stage, operation and maintenance stage, and demolition and recycling stage.

3. A rapid calculation method for the carbon emissions of a substation throughout its life cycle according to claim 1, characterized in that, For 110kV and 220kV substations, factor reduction and principal component analysis methods are used to screen and extract the carbon emission impact factors of the substation, and the correlation between each impact factor and the carbon emissions in each stage is studied through correlation analysis. Finally, a measurement model is constructed based on the main impact factors and secondary impact factors.

4. A rapid calculation method for the carbon emissions of a substation throughout its life cycle according to claim 1, characterized in that, The specific content of the said Step S1 is as follows: Given the substation impact factor X, among which there are m observed values x1, x2, …, x m , a total of n samples, and the calculation steps of its principal component analysis are as follows: (1) Standardization: Mean value of each column Variance of each column Standardization result (2) Calculate the correlation coefficient to obtain the correlation coefficient matrix: (3) Calculate the eigenvalues and eigenvectors of R: |R - λ i |I| = 0 Let \(R\) be the correlation coefficient matrix, \(\lambda\) i be the eigenvalue, and \(I\) be the identity matrix. Solving the above equation gives the eigenvalues \(\lambda_1,\lambda_2,\cdots,\lambda\) m ; For each eigenvalue λ i , solve the equation: (R-λ i I)a i =0 a i is the eigenvector corresponding to the eigenvalue λ i . Solving the above characteristic equation gives the eigenvectors a1, a2, …, a m ; (4) Obtain the contribution rate of each component The selection of the number of principal components is determined according to the cumulative contribution rate. Based on principal component analysis, the carbon emission impact factors of the substation can be screened out.

5. A rapid carbon emission calculation method for the entire life cycle of a substation according to claim 4, characterized in that, The cumulative contribution rate threshold is 85%.

6. A rapid carbon emission calculation method for the entire life cycle of a substation according to claim 1, characterized in that The specific content of the said Step S2 is as follows: The specific formula for the Pearson correlation coefficient studying the correlation between each carbon emission impact factor and the carbon emissions in each stage is as follows: r represents the Pearson correlation coefficient; X i and Y i respectively represent the impact factor carbon emission value and the carbon emission value at this stage of the i-th sample, and respectively represent the mean values of the impact factor carbon emission value and the carbon emission value at this stage, and n represents the number of samples; On the basis of the correlation analysis, by adjusting the equipment parameters and material characteristics, the sensitivity degree of the substation carbon emissions to different input parameters is measured, and the sensitivity index of each equipment material is determined. The formula is as follows: f(x) is the output of the prediction model for substation carbon emissions, f0 represents the baseline value of the model, S = h1,…,h j represents the set of combinations of input parameters, represents the contributions of the interactions of the input parameters x1,…,x i to the model output, x1,…,x i represents the input parameters, i.e., the equipment parameters and material characteristics that affect substation carbon emissions, and n represents the number of samples; The ratio of the decomposed partial variance to the total variance is the sensitivity; the first-order sensitivity index represents the influence of a single input parameter on the output, and the calculation formula is: S i represents the first-order sensitivity index of the i-th input parameter, D i represents the partial variance of the i-th input parameter, and D represents the total variance of the model output; The global sensitivity index reflects the influence degree of the interaction of parameters on the output parameter, and is expressed as: S Ti represents the global sensitivity index of the i-th input parameter, D ～i represents the partial variance of the i-th input parameter and its interactions, and D represents the total variance of the model output.

7. A rapid calculation method for the carbon emissions of a substation throughout its life cycle according to claim 1, characterized in that The specific content of the said Step S3 is as follows: (1) When calculating the carbon emissions of the substation, when the data of the main impact factors and secondary impact factors are sufficient, the following calculation model is adopted: ECE = ECE 主要 + ECE 次要 ECE is the total carbon emissions of the substation, divided into two parts: main and secondary ECE 主要 = Y 材料 + Y 主设备 + Y 主能源 + Y 人力 is the usage amount of the material, is the life cycle factor of the material, EF k is the carbon emission factor of the material, r k is the demolition and recycling coefficient of the k-th material, D k is the transportation distance of the material, EF k is the carbon emission factor in the transportation stage; N k is the number of devices, E k is the production carbon emissions of the devices, E t is the transportation carbon emissions of the devices; N k is the number of devices, EF el is the carbon emission factor of electricity, P Fe is the no-load loss of the main transformer, P Cu is the load loss of the main transformer, P ad is the additional loss of the main transformer, T is the operating time, W other is the other electricity consumption loss in the substation, is the SF6 emission volume, is the SF6 carbon emission factor, E t is the fuel consumption of the t-th device in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the number of the t-th device in the construction and installation stage, EF oil is the carbon emission factor of gasoline; Y 人力 = N worker × EF worker N worker is the number of workers, EF worker is the carbon emission factor of labor; ECE 次要 = Y 次设备 + Y 次能源 N k is the number of devices, E k is the production carbon emission of the device, r k is the demolition and recycling coefficient of the k-th material, E t is the transportation carbon emission of the device; Q C is the capacitance of the capacitor, tanδ is the average dielectric loss factor of the capacitor, N C is the number of capacitors, P L is the capacity of the reactor, N L is the number of reactors, W other is other equipment consuming minor power, EF el is the carbon emission factor of electricity, T is the operating time, W k is the power of the k-th power-consuming equipment in the construction and installation stage, N K is the number of the k-th power-consuming equipment in the construction and installation stage, E t is the fuel consumption of the t-th equipment in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the number of the t-th equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline; (2) When there is insufficient data for the secondary factors, the total carbon emission formula needs to be corrected, removing the secondary carbon emissions in the formula, and correcting the equipment and energy in the main carbon emission formula: ECE = ECE 主要 + ECE 次要 ECE is the total carbon emissions of the substation, divided into main and secondary parts. When the data of the secondary impact factors are insufficient, the simulation is carried out through the following formula: ECE 主要 = Y 材料 + Y 设备 + Y 能源 + Y 人力 MC k is the usage amount of the material, is the life cycle factor of the material, EF k is the carbon emission factor of the material, r k is the demolition and recycling coefficient of the k-th material, D k is the transportation distance of the material, is the carbon emission factor in the transportation stage; N k is the number of devices, E k is the production carbon emission of the device, r k is the demolition and recycling coefficient of the k-th material, E t is the transportation carbon emission of the device, M 设备 is the main device fitting coefficient; YE 次设备 For the carbon emissions of the secondary device of the machine learning model database, n is the number of such parameters in the database; N k is the number of devices, EF el is the carbon emission factor of electricity, P Fe is the no-load loss of the main transformer, P Cu is the load loss of the main transformer, P ad is the additional loss of the main transformer, T is the operating time, W other is the other electricity consumption loss in the station is the SF6 emission is the carbon emission factor of SF6, E t is the fuel consumption of the t-th device in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the number of the t-th device in the construction and installation stage, EF oil is the carbon emission factor of gasoline, M 运维能源 is the operation and maintenance energy fitting coefficient, M 安装能源 is the installation energy fitting coefficient Q C is the capacitance of the capacitor, tanδ is the average dielectric loss factor of the capacitor, N C is the number of capacitors, P L is the capacity of the reactor, N L is the number of reactors, W other is other equipment consuming minor power, EF el is the carbon emission factor of electricity, T is the operating time, W k is the power of the kth power-consuming equipment in the construction and installation stage, N K is the number of the kth power-consuming equipment in the construction and installation stage, E t is the fuel consumption of the tth equipment in the construction and installation stage, Q t is the average calorific value of gasoline, N t is the number of the tth equipment in the construction and installation stage, EF oil is the carbon emission factor of gasoline; YE 次设备能源 For the secondary device energy carbon emissions of the machine learning model database, YE 次安装能源 For the secondary device energy carbon emissions of the machine learning model database; Y 人力 = N worker × EF worker N worker is the number of workers, EF worker is the carbon emission factor of labor.

8. A computer-readable storage medium, on which computer program instructions that can be run by a processor are stored. When the processor runs the computer program instructions, the method steps described in any one of claims 1-7 can be implemented.

9. An electronic device, comprising a processor and a memory, wherein, The memory stores a computer program. When the computer program is executed by the processor, the processor is caused to execute the method steps described in any one of claims 1-7.

10. A computer program product, including a computer program, the computer program is stored in a computer-readable storage medium; when the processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, causing the electronic device to execute the method steps described in any one of claims 1-7.

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