A foundation carbon emission calculation method for overhead power transmission line construction

Abstract

The present application belongs to the technical field of basic carbon emission calculation of power transmission line construction, and discloses a kind of basic carbon emission calculation method of overhead power transmission line construction;The method comprises: S3: the data preprocessing is carried out to fixed emission data set and dynamic emission data set, and the characteristic vector for carbon emission prediction is obtained;S4: the characteristic vector is analyzed and calculated, and the carbon emission prediction value is obtained;S5: carbon emission prediction value is handled, and the emission early warning report is obtained according to the processing result;S6: the parameter of the largest carbon emission value is identified according to the carbon emission prediction value, and the accurate emission reduction suggestion report is obtained;S7: carbon emission prediction value, construction cost data and target duration data are combined to analyze, and the construction optimization combination report is obtained;S8: carbon emission prediction value is used to simulate construction environment change, and the carbon cost influence report is obtained, in general, the present application has the significant advantages of high carbon emission prediction accuracy, great real auxiliary effect and good data use storage security.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of basic carbon emission calculation of power transmission line construction, and more particularly to a basic carbon emission calculation method for overhead power transmission line construction. BACKGROUND

[0002] The power transmission line is used to realize the connection of the power transmission line by the transformer to the power transmission line through the circuit breaker and other control devices. The power transmission line is divided into overhead power transmission line and cable line in structure. The carbon emission refers to the greenhouse gas emission generated in the production, transportation, use and recycling of a product. Whether it is an overhead power transmission line or a cable tunnel line, a certain amount of carbon emission will be generated in the construction process. Therefore, how to accurately calculate and utilize the carbon emission value required for construction is an important link in the process of power grid management.

[0003] The patent with the application publication number CN119623834A discloses a basic carbon emission calculation method for overhead power transmission line construction. The effective calculation method for the basic carbon emission of the overhead power transmission line construction is proposed by combining the emission factor method with the characteristics of the power transmission line foundation engineering. The method is applied to the carbon emission calculation of the slab-column foundation and the excavated foundation, and the potential energy-saving and emission-reducing links and modes are explored.

[0004] However, the above-mentioned basic carbon emission calculation method for overhead power transmission line construction, although combining the emission factor method with the characteristics of the power transmission line foundation engineering, to a certain extent, realizes the calculation of the carbon emission in the construction process, but the existing carbon emission calculation method mostly depends on the real-time calculation. In the project construction, the carbon emission value is one of the important construction costs of the project. Single reliance on real-time calculation often causes the passivity of the related enterprises, and it is difficult to make prior cost planning. Moreover, the existing carbon emission calculation is mostly single carbon emission value calculation, and the carbon emission value is not deeply data-mined.

[0005] In view of this, the present application provides a basic carbon emission calculation method for overhead power transmission line construction to solve the above-mentioned problems. SUMMARY

[0006] In order to overcome the above-mentioned defects of the prior art, in order to achieve the above-mentioned purpose, the present application provides the following technical scheme. The method comprises:

[0007] S1: based on the sensor network, a fixed emission data set is collected; the step specifically comprises collecting the fixed emission data set related to the construction construction through the sensor network. The fixed emission data set includes line length data, tower quantity data, material weight data and tower type data;

[0008] S2: Collecting a dynamic emission dataset based on a sensor network; this step specifically includes collecting a dynamic emission dataset related to construction construction through a sensor network, and the dynamic emission dataset includes terrain difficulty data, construction process data and construction complexity data;

[0009] S3: Data preprocessing of the fixed emission dataset and the dynamic emission dataset to obtain a feature vector for carbon emission prediction; this step specifically includes quantifying the basic data items in the fixed emission dataset and the dynamic emission dataset, reducing the computational pressure of subsequent carbon emission prediction, and providing multiple interactive data for system calculation, thereby further improving the accuracy of system prediction;

[0010] S4: Analyzing and calculating the feature vector to obtain a carbon emission prediction value; this step specifically includes fusing the feature vector to obtain a carbon emission prediction value in the next time period, so that the system has the ability to predict carbon emissions in the future time period, provides core data support for the system to guide construction planning based on carbon emission conditions, and achieves the purpose of realizing the system to predict future carbon emissions, pre-adjust and avoid passive response;

[0011] S5: Processing the carbon emission prediction value to obtain an emission warning report according to the processing result; this step specifically includes classifying based on the carbon emission prediction value according to the carbon emission budget threshold, and providing a corresponding warning report according to the classification result, so that the system can convert system prediction data and classification results into decision-related information reports with auxiliary and forward-looking functions, effectively reducing the time and workload required for data calculation and information conversion by workers, thereby achieving the overall enhancement of the actual situation feedback ability and auxiliary guidance ability of data;

[0012] S6: Identifying the parameter with the largest carbon emission value based on the carbon emission prediction value to obtain a precise emission reduction suggestion report; this step specifically includes calculating the contribution degree of all sub-data items in the fixed emission dataset and the dynamic emission dataset based on the carbon emission prediction value, so that the system can quickly identify and locate the key link of emission reduction, and compare with the corresponding contribution degree threshold, so that the system can quickly issue a corresponding emission reduction optimization report after identification and positioning according to the different emission reduction links, thereby achieving the purpose of effectively reducing the cost required in the carbon emission reduction process;

[0013] S7: Analyzing the carbon emission prediction value, construction cost data and target construction period data to obtain a construction optimization combination report; this step specifically includes multi-objective optimization of construction cost and construction date based on the carbon emission prediction value, so that the system not only has the effect of balancing the quantified carbon emission value, construction cost and construction date, but also supports the system to differentiate the decision target through the construction optimization algorithm, so that the system can quickly find the optimal combination and reduce the time required for decision-making;

[0014] S8: Simulate construction environment changes according to the carbon emission prediction value, and obtain a carbon cost influence report; this step specifically includes further quantifying the carbon emission prediction value based on construction environment changes, so that the system can have the ability to adjust the individual carbon cost according to the dynamic changes of the market environment, thereby achieving the purpose of assisting the staff to quickly complete the pre-specified hedging strategy;

[0015] S9: Store the key data set to the database, display the emission warning report and the construction optimization combination report through the visualization panel, and output the precise emission reduction suggestion report and the construction optimization combination report;

[0016] Further, step S1 includes:

[0017] Collecting fixed emission data sets based on a sensor network;

[0018] Collecting the total length value of the planned path in the specified area through the vehicle-mounted laser range finder to obtain the line length data;

[0019] Collecting the number of towers to be built in the specified area through aerial photography by a drone to obtain the tower quantity data;

[0020] Collecting the weight value and material type data of the material transport vehicle in the specified area through the intelligent weighbridge and RFID tag tools to obtain the material weight data;

[0021] Collecting the structure type of the required construction tower in the specified area through the BIM database, and assigning values to the structure type to obtain the tower type data;

[0022] Further, step S2 includes:

[0023] Collecting dynamic emission data sets based on a sensor network;

[0024] Collecting topographic data to generate a digital elevation model in the specified area through a laser radar of a drone, and automatically calculating the average slope, assigning values according to the average slope, and obtaining the terrain difficulty data;

[0025] Collecting construction signals of construction equipment in the specified area through construction machinery control sensors, and assigning values to obtain construction process data;

[0026] Collecting personnel distribution in the specified area through UWB positioning work cards in cooperation with construction management tools, and assigning values to obtain construction complexity data;

[0027] Further, step S3 includes:

[0028] S3.1: Eliminate line length data and material weight data through a data standardization formula The influence of dimensions;

[0029] S3.2: By using terrain difficulty data Multiply by construction process data To obtain coupling feature data ;

[0030] S3.3: Composite feature extraction is performed on material weight data and construction complexity data. The specific calculation formula for composite feature extraction is as follows:

[0031] ;

[0032] Obtain composite feature data ,in, Data on construction complexity;

[0033] S3.4: The comprehensive load on the iron towers is quantified using data on the number of towers, tower types, and terrain difficulty. The specific calculation formula for this quantification is as follows:

[0034] ;

[0035] Obtain comprehensive feature data ,in, For the number of iron towers, For tower type data, This refers to terrain difficulty data;

[0036] S3.5: By summing the squares of the terrain difficulty data and performing logarithmic calculations on the construction complexity data, nonlinear terrain difficulty data and nonlinear construction complexity data are obtained. The expression for the nonlinear construction complexity data is: ;

[0037] S3.6: Combined feature data, composite feature data, integrated feature data, standardized line length data, standardized material weight data, nonlinear terrain difficulty data, and nonlinear construction complexity data to obtain feature vectors;

[0038] Further, step S4 includes:

[0039] A carbon emission prediction algorithm is constructed based on feature vectors. The algorithm takes a feature vector as input and outputs a predicted carbon emission value that reflects the carbon emission values ​​for the next time period. The specific formula for the carbon emission prediction algorithm is as follows:

[0040] ;

[0041] Obtain carbon emission forecasts ,in, The standard carbon emission constant, For the first The weight factors of each feature vector subvector. For the first Subvectors of eigenvectors, As feature weighting factors, This refers to the interaction term between coupled feature data and integrated feature data;

[0042] Further, step S5 includes:

[0043] Based on the carbon emission budget threshold, an emission safety report is generated when the predicted carbon emission value is less than the carbon emission budget threshold, and an emission hazard report is generated when the predicted carbon emission value is greater than or equal to the carbon emission budget threshold.

[0044] The emissions safety report includes a statement indicating that the predicted carbon emissions are normal, and requests that staff proceed with construction according to the pre-set work schedule.

[0045] The emissions hazard report includes an explanation of the anomalies in the predicted carbon emissions values, and requests that staff reduce the values ​​for terrain difficulty data by optimizing transportation routes, reducing the values ​​for construction process data by increasing the use of prefabricated assembly processes, and reducing the values ​​for material weight data by reducing the use of high-carbon materials.

[0046] By combining the emission safety report and the emission hazard report, an emission warning report can be obtained.

[0047] Further, step S6 includes:

[0048] The contribution of sub-data items in the stationary emission dataset and dynamic emission dataset is calculated based on the carbon emission prediction values. The specific formula for calculating the contribution is as follows:

[0049] ;

[0050] Get the first Contribution of each sub-data item ,in, The partial derivative of the predicted carbon emissions value. For the first Partial derivatives of each sub-data item, This is the collection of all sub-data items in the fixed emissions dataset and the dynamic emissions dataset;

[0051] Based on the comparison results between the contribution value and the corresponding data contribution threshold, a corresponding data optimization report is output. The specific comparison method is as follows:

[0052] when Greater than At that time, generate Data optimization report, in which, For the first Contribution threshold of each data item

[0053] Packaging Data optimization report, get accurate emission reduction suggestion report;

[0054] Further, step S7 comprises:

[0055] Based on the target optimization algorithm, the carbon emission prediction value, the construction cost data and the target duration data are calculated, and the specific expression of the target optimization algorithm is:

[0056] ;

[0057] Among them, is the decision vector, is the standard carbon emission data, is the construction cost data, is the standard construction cost data, is the target duration data, is the standard duration data, , and is the optimization weight factor, and satisfies ;

[0058] By minimizing the carbon emission prediction value, the low-carbon scheme is output;

[0059] By minimizing the construction cost data, the economic scheme is output;

[0060] By minimizing the target duration data, the speed-up scheme is output;

[0061] Packaging low-carbon scheme, economic scheme and speed-up scheme, get construction optimization combination report;

[0062] Further, step S8 comprises:

[0063] Based on the carbon emission prediction value combined with the construction environment change, the final carbon cost simulation calculation is carried out, when the carbon emission tax rate increases and the steel price increases %, the specific formula of simulation calculation is:

[0064] ;

[0065] Get the final carbon cost value , wherein, is the tax rate increase range, is the ratio of steel to material cost;

[0066] Packaging carbon emission tax rate increase , steel price increase and the final carbon cost value, to obtain a carbon cost impact report;

[0067] Further, the key data sets include a fixed emission data set, a dynamic emission data set, a feature vector, a carbon emission prediction value, an emission early warning report, a precise emission reduction suggestion report, a construction optimization combination report, and a carbon cost impact report;

[0068] The output mode of the precise emission reduction suggestion report and the construction optimization combination report includes:

[0069] The precise emission reduction suggestion report and the construction optimization combination report are sent to the staff mailbox through the mailbox.

[0070] The technical effects and advantages of the method for calculating the basic carbon emission of the overhead power transmission line construction are as follows:

[0071] The application collects the fixed emission data set based on the sensor network, collects the dynamic emission data set based on the sensor network, performs data preprocessing on the fixed emission data set and the dynamic emission data set, obtains the feature vector for carbon emission prediction, analyzes and calculates the feature vector, obtains the carbon emission prediction value, processes the carbon emission prediction value, obtains the emission early warning report according to the processing result, identifies the parameter with the largest carbon emission value according to the carbon emission prediction value, obtains the precise emission reduction suggestion report, analyzes the carbon emission prediction value, the construction cost data, and the target construction period data, obtains the construction optimization combination report, simulates the construction environment change according to the carbon emission prediction value, obtains the carbon cost impact report, stores the key data set to the database, displays the emission early warning report and the construction optimization combination report through the visual panel, processes the precise emission reduction suggestion report and the construction optimization combination report, and outputs according to the processing result, so that the system can accurately predict the carbon emission value in the future time period, provides core data support for cost accounting and prior response of the staff, in addition, the application also provides the staff with the emission early warning, precise emission reduction, construction direction optimization, and carbon cost impact multi-aspect auxiliary report according to the carbon emission prediction value, thereby effectively improving the auxiliary nature of the system to the physical world decision measures, and through the storage and transmission of important data, the safety and usability of the data can be effectively guaranteed, and overall, the application has the remarkable advantages of high carbon emission prediction accuracy, great real auxiliary effect, and good data use and storage safety. BRIEF DESCRIPTION OF DRAWINGS

[0072] Figure 1 The figure is a schematic diagram of the method for calculating the basic carbon emission of the overhead power transmission line construction. DETAILED DESCRIPTION

[0073] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described below, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0074] Embodiment 1

[0075] Please refer to Figure 1 The embodiment described a kind of overhead transmission line construction's basic carbon emission calculation method, the method includes:

[0076] S1: based on sensor network, collection fixed emission dataset;This step specifically includes through sensor network collection construction construction related fixed emission dataset, fixed emission dataset includes line length data, tower quantity data, material weight data and tower type data;

[0077] S2: based on sensor network, collection dynamic emission dataset;This step specifically includes through sensor network collection construction construction related dynamic emission dataset, dynamic emission dataset includes terrain difficulty data, construction technology data and construction complexity data;

[0078] S3: data preprocessing is carried out to fixed emission dataset and dynamic emission dataset, and the feature vector for carbon emission prediction is obtained;This step specifically includes by quantifying the basic data items in fixed emission dataset and dynamic emission dataset, reduce the calculation pressure of subsequent carbon emission prediction, and provide multiple interactive data for system calculation, to further improve the accuracy of system prediction;

[0079] S4: analysis and calculation are carried out to the feature vector, and the carbon emission prediction value is obtained;This step specifically includes by fusing feature vector, the carbon emission prediction value in next time period is obtained, so that the system has the ability to predict carbon emission in future time period, provides core data support for system to guide construction planning according to carbon emission condition, to achieve the purpose of realizing system to predict future carbon emission required, pre-adjustment and passive response is avoided;

[0080] S5: carbon emission prediction value is handled, and emission early warning report is obtained according to the processing result;This step specifically includes based on carbon emission prediction value, grading is carried out according to carbon emission budget threshold, corresponding early warning report is provided according to the grading result, so that the system can convert system prediction data and grading result into decision-related information report with auxiliary and forward-looking, effectively reduce the time and workload required by staff for data calculation and information conversion, to achieve the overall enhancement of the actual situation feedback ability and auxiliary guidance ability of data;

[0081] S6: Identify the parameter with the largest carbon emission value based on the carbon emission prediction value, and obtain a precise emission reduction suggestion report; this step specifically includes contribution degree calculation of all sub-data items in the fixed emission data set and the dynamic emission data set based on the carbon emission prediction value, so that the system can quickly identify and locate the key link of emission reduction, and cooperate with the corresponding contribution degree threshold comparison, so that the system can quickly issue the corresponding emission reduction optimization report after identification and location, so as to achieve the purpose of effectively reducing the cost required in the carbon emission reduction process;

[0082] S7: Analyze the carbon emission prediction value, construction cost data and target construction period data to obtain a construction optimization combination report; this step specifically includes multi-objective optimization of construction cost and construction date based on the carbon emission prediction value, so that the system can not only balance the quantitative carbon emission value, construction cost and construction date, but also support the system to differentially process the decision target through the construction optimization algorithm, so that the system can quickly find the optimal combination and reduce the time required for decision-making;

[0083] S8: Simulate construction environment changes based on the carbon emission prediction value to obtain a carbon cost impact report; this step specifically includes further quantification of the carbon emission prediction value based on the construction environment changes, so that the system can have the ability to adjust the single carbon cost according to the dynamic changes of the market environment, thereby achieving the purpose of assisting the staff to quickly complete the specified hedging strategy in advance;

[0084] S9: Store the key data set to the database, display the emission warning report and the construction optimization combination report through the visual panel, and output the precise emission reduction suggestion report and the construction optimization combination report;

[0085] The core of the present application is that the fixed data set and the dynamic data set related to carbon emission are obtained through the sensor network, the corresponding feature extraction is carried out, the extracted feature vector is used to realize the purpose of accurately predicting the carbon emission required for construction, the basic data support for data fusion in step S3 is provided based on the basic data acquisition in steps S1 and S2, the carbon emission value in the future time period is calculated through the carbon emission prediction algorithm in step S4 based on the feature vector after data fusion, the core data support for steps S5, S6, S7 and S8 is provided through the carbon emission prediction value in step S4, the emission warning report obtained in step S5 can directly show whether the predicted carbon emission value in the future time period exceeds the carbon emission budget, the accurate emission reduction suggestion report obtained in step S6 can accurately identify the link that the carbon emission exceeds the budget, the construction optimization combination report obtained in step S7 can assist the staff to complete the balance among carbon emission, construction cost and construction date, the carbon cost influence report obtained in step S8 can feedback the cost increase problem after the policy change and market change in advance, and finally the results obtained in all steps are processed correspondingly through step S9, so that the system can have the predictability, auxiliary nature and data security related to carbon emission.

[0086] Step S1 comprises:

[0087] The fixed emission data set is collected based on the sensor network;

[0088] The total length value of the planned path in the specified area is collected through the vehicle-mounted laser range finder, and the line length data is obtained;

[0089] The number of towers to be constructed in the specified area is collected through the unmanned aerial vehicle aerial photography, and the tower quantity data is obtained;

[0090] The weight value and material type data of the material transport vehicle in the specified area are collected through the intelligent weighbridge and RFID tag tool, and the material weight data is obtained;

[0091] The structure type of the required construction tower in the specified area is collected through the BIM database, and the structure type is valued, and the tower type data is obtained;

[0092] It should be explained that the structure type valuation means that when the structure type of the tower is a right-angle tower, the tower type data is valued as 1, and when the structure type of the tower is a corner tower, the tower type data is valued as 1.5;

[0093] The core of the embodiment is that the basic carbon emission related data required for overhead transmission line construction is collected through the sensor network, which provides solid basic data support for subsequent carbon emission prediction;

[0094] Step S2 comprises:

[0095] Collecting a dynamic emission dataset based on a sensor network;

[0096] Collecting terrain data in a specified area through a UAV laser radar to generate a digital elevation model, and automatically calculating the average slope to assign values according to the average slope to obtain terrain difficulty data;

[0097] It needs to be explained that the assignment includes identifying flat ground when the average slope is less than 5 degrees, and the terrain difficulty data output value is 1; identifying hilly when the average slope is greater than or equal to 5 degrees and less than 15 degrees, and the terrain difficulty data output value is 1.3; identifying mountainous when the average slope is greater than or equal to 15 degrees, and the terrain difficulty data output value is 1.8;

[0098] Collecting construction signals of construction equipment in a specified area through construction machinery control sensors, and assigning values to obtain construction technology data;

[0099] It needs to be explained that assigning values to construction signals means, for example, when the construction machinery control sensor detects a concrete vibrating rod signal, it is determined as a traditional pouring construction technology, and the construction technology data is assigned a value of 1.2; when the construction machinery control sensor detects a hoisting machinery hydraulic signal, it is determined as a prefabricated assembly construction technology, and the construction technology data is assigned a value of 0.9;

[0100] Collecting personnel distribution in a specified area through UWB positioning cards in combination with construction management tools, and assigning values to obtain construction complexity data;

[0101] It needs to be explained that assigning values according to the distribution means that when the distribution is scattered personnel positioning, the construction complexity data is assigned a value of 1; when the distribution is highly concentrated personnel, the construction complexity data is assigned a value of 1.4; when the distribution is linear personnel distribution, the construction complexity data is assigned a value of 1.6;

[0102] The core of this embodiment is to collect dynamic carbon emission related impact data required for overhead transmission line construction through a sensor network, to provide dynamic impact related data support for subsequent carbon emission prediction, thereby further improving the accuracy of carbon emission prediction value;

[0103] Step S3 includes:

[0104] S3.1: Eliminate the dimensional influence of line length data and material weight data through a data standardization formula; ;

[0105] It needs to be explained that the data standardization formula is, for example, line length data, subtract the mean of line length data from line length data and divide by the standard deviation of line length data to obtain standardized line length data;​

[0106] S3.2: Coupling feature data is obtained by multiplying terrain difficulty data by construction process data ;

[0107] S3.3: Composite feature data is obtained by composite feature extraction on material weight data and construction complexity data, and the specific calculation formula of the composite feature extraction is:

[0108] ;

[0109] ;

[0110] S3.4: The comprehensive load of the tower is quantified by the tower number data, the tower type data and the terrain difficulty data, and the specific calculation formula of the quantification is:

[0111] ;

[0112] ;

[0113] S3.5: Nonlinear terrain difficulty data and nonlinear construction complexity data are obtained by squaring the terrain difficulty data and logarithmically calculating the construction complexity data, and the expression of the nonlinear construction complexity data is: ;

[0114] S3.6: The feature vector is obtained by packing the coupling feature data, the composite feature data, the comprehensive feature data, the standardized line length data, the standardized material weight data, the nonlinear terrain difficulty data and the nonlinear construction complexity data.

[0115] The core of the embodiment is that the standardization and data interaction feature extraction are performed based on the fixed emission data set and the dynamic emission data set, so that the system can achieve the purpose of quantifying and predicting the related data by calculating the basic data items, and provide more accurate and convenient data basis and stronger interactive feedback for subsequent prediction calculation. Specifically, the dimensional difference of the basic data is eliminated by the standardization formula, the hidden relationship between the data is revealed by the data interaction calculation, and the nonlinear fitting ability of the basic data is increased by the nonlinear transformation, so that the contribution of the basic data is made explicit, and the data basis for improving the prediction accuracy is laid.

[0116] Step S4 comprises:​​​​​​​

[0117] The carbon emission prediction algorithm is constructed based on the feature vector, the feature vector is input, and a carbon emission prediction value reflecting the carbon emission value in the next time period is obtained. The specific formula of the carbon emission prediction algorithm is:

[0118]

[0119] The carbon emission prediction value is obtained , wherein, is a standard carbon emission constant, is a weight factor of the i-th feature vector sub-vector, is the i-th feature vector sub-vector, is a feature weight factor, is a coupling feature data and comprehensive feature data interaction term; The core of this embodiment is that, by calculating the feature vector, a carbon emission prediction value reflecting the carbon emission value in the next time period is obtained, so that the system has the ability to predict the carbon emission value in the future time period. Specifically, this embodiment is to construct a carbon emission prediction algorithm, capture complex effects such as the interaction between the coupling feature data and the comprehensive feature data, and quantify the total carbon emission between the carbon emission according to the construction environment and the construction process and the single tower construction, so that the system can take into account the comprehensive influence between the basic data during prediction and calculation, compared with the traditional single data calculation, thereby greatly improving the reliability of the data obtained by the system prediction.

[0120] Step S5 includes:

[0121] Based on the carbon emission budget threshold, when the carbon emission prediction value is less than the carbon emission budget threshold, an emission safety report is generated, and when the carbon emission prediction value is greater than or equal to the carbon emission budget threshold, an emission danger report is generated.

[0122] The emission safety report includes that the predicted carbon emission value is normal, and the staff is requested to carry out construction construction according to the preset work progress.

[0123] The emission danger report includes that the predicted carbon emission value is abnormal, and the staff is requested to reduce the value of the terrain difficulty data by optimizing the transportation route, to reduce the value of the construction process data by increasing the number of prefabricated assembly processes, and to reduce the value of the material weight data by reducing the use amount of high-carbon type materials.

[0124] The emission safety report and the emission danger report are packaged to obtain an emission warning report.

[0125] The emission safety report and the emission danger report are packaged to obtain an emission warning report.

[0126] ​​The core of this implementation lies in classifying carbon emission forecasts by a carbon emission budget threshold. This allows the system to identify whether carbon emission forecasts for a future period exceed the carbon emission budget. When the carbon emission budget is exceeded, corresponding action measures are generated. This further enhances the intuitiveness of the system for assisting staff and provides them with intuitive and reliable action measures. Specifically, this implementation classifies carbon emission forecasts by a carbon emission budget threshold and provides corresponding action measures based on the different classification results. This not only effectively enhances the ability of the system to transform data into decisions but also effectively reduces the time staff spend on passive decision-making when facing insufficient carbon emission budgets, thereby greatly improving the practicality of the system's auxiliary role.

[0127] Step S6 includes:

[0128] The contribution of sub-data items in the stationary emission dataset and dynamic emission dataset is calculated based on the carbon emission prediction values. The specific formula for calculating the contribution is as follows:

[0129] ;

[0130] Get the first Contribution of each sub-data item ,in, The partial derivative of the predicted carbon emissions value. For the first Partial derivatives of each sub-data item, This is the collection of all sub-data items in the fixed emissions dataset and the dynamic emissions dataset;

[0131] Based on the comparison results between the contribution value and the corresponding data contribution threshold, a corresponding data optimization report is output. The specific comparison method is as follows:

[0132] when Greater than At that time, generate Data optimization report, in which, For the first The contribution threshold of each sub-data item;

[0133] It needs to be explained that, Data optimization reports include, for example, generating a terrain data optimization report when the sub-data item is the terrain difficulty coefficient. The terrain data optimization report includes suggestions for staff to replan transportation routes to avoid mountainous areas.

[0134] Pack The data optimization report yields a precise emission reduction recommendation report;

[0135] The core of the embodiment is that by combining the carbon emission prediction value, the contribution degrees of the sub-data items in the fixed emission data set and the dynamic emission data set are calculated respectively, the contribution degree values of the sub-data items are compared with the contribution degree thresholds of the corresponding data items, and the corresponding data optimization report is generated according to the comparison result, so that the system can quickly identify and locate the construction link with the lowest cost, avoid the production of invalid emission reduction resource investment, and effectively reduce the emission reduction cost in the carbon emission reduction process;

[0136] Step S7 comprises:

[0137] Based on the target optimization algorithm, the carbon emission prediction value, the construction cost data and the target duration data are calculated, and the specific expression of the target optimization algorithm is:

[0138] ;

[0139] Wherein, is a decision vector, is standard carbon emission data, is construction cost data, is standard construction cost data, is target duration data, is standard duration data, , and are optimization weight factors, and satisfy ;

[0140] It should be explained that the decision vector includes material weight data, terrain difficulty data, construction technology data and construction complexity data.

[0141] By minimizing the carbon emission prediction value, a low-carbon scheme is output;

[0142] By minimizing the construction cost data, an economic scheme is output;

[0143] By minimizing the target duration data, a speed-up scheme is output;

[0144] Packing the low-carbon scheme, the economic scheme and the speed-up scheme, a construction optimization combination report is obtained;

[0145] The core of the embodiment is that by minimizing the carbon emission prediction value, a low-carbon scheme is output;

[0146] Step S8 comprises:

[0147] Based on the carbon emission prediction value combined with the construction environment change to simulate and calculate the final carbon cost, when the carbon emission tax rate increases and the steel price increases , the specific formula of simulation calculation is:

[0148] ;

[0149] to obtain the final carbon cost value , wherein is the increase rate of the tax rate, is the ratio of steel to material cost;

[0150] The final carbon cost value is obtained by increasing the carbon emission tax rate, increasing the steel price, and obtaining the carbon cost impact report.

[0151] The core of this embodiment is that by calculating the carbon emission prediction value combined with the construction environment change, the system can accurately quantify the policy and market risk, thereby enhancing the risk resistance ability of the construction project and providing prior data support for the staff to make cost-related strategies in advance.

[0152] Step S9 includes:

[0153] The key data set includes a fixed emission data set, a dynamic emission data set, a feature vector, a carbon emission prediction value, an emission warning report, a precise emission reduction recommendation report, a construction optimization combination report, and a carbon cost impact report.

[0154] The output mode of the precise emission reduction recommendation report and the construction optimization combination report includes:

[0155] The precise emission reduction recommendation report and the construction optimization combination report are sent to the staff's mailbox through the mailbox.

[0156] The core of this embodiment is that by storing the key data set, the system can form data sedimentation to provide data reference for subsequent project construction, display the emission warning report and the construction optimization combination report through the visual panel, and can convey the system processing result in real time. The system can transmit the data obtained by the system conversion to the physical world through the visual panel, and by outputting the precise emission reduction recommendation report and the construction optimization combination report, the core data processed by the system can be transmitted to the staff's personal receiving end for multiple core data backup.

[0157] ​​The embodiment has the beneficial effects of collecting a fixed emission data set based on a sensor network, collecting a dynamic emission data set based on a sensor network, performing data preprocessing on the fixed emission data set and the dynamic emission data set to obtain a feature vector for carbon emission prediction, performing analysis and calculation on the feature vector to obtain a carbon emission prediction value, processing the carbon emission prediction value to obtain an emission early warning report according to the processing result, identifying a parameter with the largest carbon emission value according to the carbon emission prediction value to obtain a precise emission reduction suggestion report, analyzing the carbon emission prediction value, construction cost data and target construction period data to obtain a construction optimization combination report, simulating construction environment changes according to the carbon emission prediction value to obtain a carbon cost impact report, storing key data sets to a database, displaying the emission early warning report and the construction optimization combination report through a visual panel, processing the precise emission reduction suggestion report and the construction optimization combination report, and outputting according to the processing result, so that the system can accurately predict the carbon emission value in the future time period, provide core data support for cost accounting and prior response of the staff, in addition, the application also provides the staff with emission early warning, precise emission reduction, construction direction optimization and carbon cost impact multi-aspect auxiliary report according to the carbon emission prediction value, thereby effectively improving the auxiliary nature of the system to the physical world decision measures, and through storage and transmission of important data, the safety and usability of the data can be effectively guaranteed, and overall, the application has the significant advantages of high carbon emission prediction accuracy, great real auxiliary effect and good data use and storage safety.

[0158] It is apparent for a person skilled in the art that the application is not limited to the details of the above-described exemplary embodiments, but that the application can be implemented in other concrete forms without departing from the spirit or essential characteristics of the application.

[0159] Therefore, the embodiments should be considered in all respects as illustrative and not restrictive, the scope of the application being defined by the appended claims rather than the above description, and all changes falling within the meaning and range of equivalents of the claims are intended to be embraced therein. Any reference signs in the claims should not be construed as limiting the claims to the figures in which the reference signs are used.

[0160] Furthermore, it is clear that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Multiple units or devices also can be presented by a single unit or device, either by software or hardware. The terms "first", "second", etc. do not denote any order. They are used to distinguish between different units.

[0161] Finally, it should be noted that the above examples are merely intended to illustrate the technical solutions of the present application and not to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the present application.

Claims

1. A basic carbon emission calculation method for the construction of overhead transmission lines, characterized in that, The method includes: S1: Collect stationary emission datasets based on sensor networks; S2: Based on sensor networks, collect dynamic emission datasets; S2 includes: Dynamic emission datasets are collected using sensor networks; By using drone lidar to collect terrain data within a designated area, a digital elevation model is generated, and the average slope is automatically calculated. Based on the average slope, a value is assigned to obtain terrain difficulty data. By using construction machinery control sensors, construction signals from construction equipment within a designated area are collected and assigned values ​​to obtain construction process data. By using UWB location badges in conjunction with construction management tools, the distribution of personnel in a designated area is collected and assigned values ​​to obtain construction complexity data. S3: Perform data preprocessing on the stationary emission dataset and the dynamic emission dataset to obtain feature vectors for carbon emission prediction; S3 includes: S3.1: Eliminate line length data through data standardization formula and material weight data The influence of dimensions; S3.2: By using terrain difficulty data Multiply by construction process data To obtain coupling feature data ; S3.3: Composite feature extraction is performed on material weight data and construction complexity data. The specific calculation formula for composite feature extraction is as follows: ； Obtain composite feature data ,in, Data on construction complexity; S3.4: The comprehensive load on the iron towers is quantified using data on the number of towers, tower types, and terrain difficulty. The specific calculation formula for this quantification is as follows: ； Obtain comprehensive feature data ,in, For the number of iron towers, For tower type data, This refers to terrain difficulty data; S3.5: By summing the squares of the terrain difficulty data and performing logarithmic calculations on the construction complexity data, nonlinear terrain difficulty data and nonlinear construction complexity data are obtained. The expression for the nonlinear construction complexity data is: ; S3.6: Combined feature data, composite feature data, integrated feature data, standardized line length data, standardized material weight data, nonlinear terrain difficulty data, and nonlinear construction complexity data to obtain feature vectors; S4: Analyze and calculate the eigenvectors to obtain the predicted carbon emissions; S4 includes: A carbon emission prediction algorithm is constructed based on feature vectors. The algorithm takes a feature vector as input and outputs a predicted carbon emission value that reflects the carbon emission values ​​for the next time period. The specific formula for the carbon emission prediction algorithm is as follows: ； Obtain carbon emission forecasts ,in, The standard carbon emission constant, For the first The weight factors of each feature vector subvector. For the first Subvectors of eigenvectors, As feature weighting factors, This refers to the interaction term between coupled feature data and integrated feature data; S5: Process the carbon emission forecast values ​​and generate an emission early warning report based on the processing results; S6: Identify the parameter with the largest carbon emission value based on the carbon emission forecast and obtain a precise emission reduction recommendation report; S7: Combine carbon emission forecasts, construction cost data, and target schedule data to generate a construction optimization combination report; S8: Based on the carbon emission forecast, simulate the changes in the construction environment to obtain a carbon cost impact report; S9: Store key datasets in the database, display emission warning reports and construction optimization combination reports through a visualization panel, and output precise emission reduction recommendation reports and construction optimization combination reports.

2. The basic carbon emission calculation method for the construction of overhead transmission lines according to claim 1, characterized in that, S1 includes: Collect stationary emission datasets using sensor networks; By using a vehicle-mounted laser rangefinder, the total length of the planned path within a designated area is collected to obtain the route length data; By using drones for aerial photography, the number of iron towers that need to be built in a designated area is collected, and data on the number of iron towers is obtained. By using smart weighbridges and RFID tags, the weight values ​​and material type data of material transport vehicles within a designated area are collected to obtain material weight data; By using the BIM database, the structural types of the towers to be built within the specified area are collected, and values ​​are assigned to the structural types to obtain tower type data.

3. The basic carbon emission calculation method for the construction of overhead transmission lines according to claim 1, characterized in that, S5 includes: Based on the carbon emission budget threshold, an emission safety report is generated when the predicted carbon emission value is less than the carbon emission budget threshold, and an emission hazard report is generated when the predicted carbon emission value is greater than or equal to the carbon emission budget threshold. The emissions safety report includes a statement indicating that the predicted carbon emissions are normal, and requests that staff proceed with construction according to the pre-set work schedule. The emissions hazard report includes an explanation of the anomalies in the predicted carbon emissions values, and requests that staff reduce the values ​​for terrain difficulty data by optimizing transportation routes, reducing the values ​​for construction process data by increasing the use of prefabricated assembly processes, and reducing the values ​​for material weight data by reducing the use of high-carbon materials. The emission safety report and emission hazard report are packaged together to obtain the emission warning report.

4. The basic carbon emission calculation method for the construction of overhead transmission lines according to claim 1, characterized in that, S6 includes: The contribution of sub-data items in the stationary emission dataset and dynamic emission dataset is calculated based on the carbon emission prediction values. The specific formula for calculating the contribution is as follows: ； Get the first Contribution of each sub-data item ,in, The partial derivative of the predicted carbon emissions value. For the first Partial derivatives of each sub-data item, This is the collection of all sub-data items in the fixed emissions dataset and the dynamic emissions dataset; Based on the comparison results between the contribution value and the corresponding data contribution threshold, a corresponding data optimization report is output. The specific comparison method is as follows: when Greater than At that time, generate Data optimization report, in which, For the first The contribution threshold for each sub-data item; Pack The data optimization report yields a precise emission reduction recommendation report.

5. The basic carbon emission calculation method for the construction of overhead transmission lines according to claim 1, characterized in that, S7 includes: Based on the objective optimization algorithm, the predicted carbon emissions, construction cost data, and target construction period data are calculated. The specific expression of the objective optimization algorithm is as follows: ； in, Let be the decision vector. For standard carbon emission data, For construction cost data, For standard construction cost data, Target project duration data For standard project duration data, , and To optimize the weighting factors and satisfy the following conditions: ; Output low-carbon solutions by minimizing predicted carbon emissions; By minimizing construction cost data, an economical solution is output; Output a quick solution by minimizing the target timeframe data; By packaging low-carbon solutions, economical solutions, and quick-fix solutions, a construction optimization combination report is obtained.

6. The basic carbon emission calculation method for the construction of overhead transmission lines according to claim 1, characterized in that, S8 includes: The final carbon cost simulation calculation is based on carbon emission forecasts combined with changes in the construction environment. This is done when the carbon emission tax rate increases. And steel prices increased When %, the specific formula for simulation calculation is: ； To obtain the final carbon cost value ,in, For the increase in tax rate, This represents the ratio of steel to total material costs. Increased carbon emission tax rate Steel prices increased The percentage and the final carbon cost value are used to obtain a carbon cost impact report.

7. The basic carbon emission calculation method for the construction of overhead transmission lines according to claim 1, characterized in that, S9 includes: Key datasets include stationary emissions datasets, dynamic emissions datasets, feature vectors, carbon emission forecasts, emission warning reports, precise emission reduction recommendation reports, construction optimization combination reports, and carbon cost impact reports; The methods for outputting precise emission reduction recommendation reports and construction optimization combination reports include: The precise emission reduction recommendation report and the construction optimization combination report were sent to the staff's email address.

Images