Power transmission and transformation project full life cycle carbon emission design system based on multi-objective optimization

Abstract

The invention provides a power transmission and transformation project full-life-cycle carbon emission design system based on multi-objective optimization, and the system comprises a full-life-cycle carbon emission database module which is used for storing carbon emission factors and technological parameters of a power transmission and transformation project in each stage; the engineering scheme modeling module is used for generating an engineering scheme including a standardized bill of materials and a construction list based on the carbon emission factors and the process parameters in combination with engineering parameters and design data; the carbon emission evaluation module is used for evaluating the full-life-cycle carbon emission of the engineering scheme; the multi-objective optimization module is used for realizing synchronous optimization of the carbon emission and various constraint conditions to obtain a plurality of engineering scheme solution sets; and the decision support and visualization module is used for visually displaying the target optimization solution set and the carbon emission of the whole life cycle, automatically generating an engineering scheme for comparative analysis, and assisting a decision maker to quickly select an optimal scheme. And through a multi-objective collaborative optimization method, synchronous optimization of full-life-cycle carbon emission and economic objectives is realized.

Description

Technical Field

[0001] This invention relates to the field of power transmission and transformation engineering design technology, specifically to a carbon emission design system for the entire life cycle of power transmission and transformation engineering based on multi-objective optimization. Background Technology

[0002] As a crucial component of the power system, power transmission and transformation projects significantly impact the carbon footprint of the overall energy industry through their construction and operation. Traditional power transmission and transformation project design primarily focuses on meeting the safety, reliability, and economic requirements of power transmission; however, it pays less attention to the quantification and control of carbon emissions during the design phase and lacks systematic carbon emission assessment and optimization methods.

[0003] Currently, carbon emission assessments for most power transmission and transformation projects are typically conducted late in the project implementation phase, representing ex-post accounting and failing to provide timely guidance for design decisions. Carbon emission data largely relies on empirical parameters and calculations for single stages, lacking a comprehensive lifecycle perspective covering material production, transportation, construction, operation and maintenance, and decommissioning and recycling. Furthermore, multi-objective optimization of engineering design schemes usually only considers cost and technical indicators, lacking a mechanism to incorporate carbon emissions into a comprehensive evaluation, making it difficult to achieve a balance between low carbon emissions and economic benefits in the design schemes.

[0004] International research has increasingly incorporated Life Cycle Assessment (LCA) methods to quantify the carbon footprint of power transmission and transformation projects, and has attempted to design integrated solutions for carbon reduction and cost control using multi-objective optimization algorithms. For example, techniques such as genetic algorithms and particle swarm optimization are employed to automatically adjust design parameters and minimize carbon emissions. However, these studies often lack specialized database support and dynamic update mechanisms tailored to the characteristics of power transmission and transformation projects, and are largely focused on theoretical models, lacking integrated design platforms for practical engineering projects. Summary of the Invention

[0005] To scientifically and rationally conduct carbon emission optimization design throughout the entire life cycle of power transmission and transformation projects, taking into account both economic efficiency and environmental impact, and to achieve intelligent and low-carbon design processes, this invention provides a multi-objective optimization-based carbon emission design system for power transmission and transformation projects throughout their entire life cycle. The system includes: a life-cycle carbon emission database module, an engineering scheme modeling module, a carbon emission assessment module, a multi-objective optimization module, and a decision support and visualization module.

[0006] The whole life cycle carbon emission database module is used to store carbon emission factors and process parameters of power transmission and transformation projects at each stage;

[0007] The engineering scheme modeling module is used to receive power transmission and transformation engineering parameters and design data; based on the carbon emission factor and process parameters, combined with the power transmission and transformation engineering parameters and design data, it generates an engineering scheme including a standardized bill of materials and a construction list;

[0008] The carbon emission assessment module is used to assess the carbon emissions of the power transmission and transformation project throughout its entire life cycle based on the standardized bill of materials and construction process list.

[0009] The multi-objective optimization module is used to simultaneously optimize the carbon emissions and multiple constraints by employing an improved non-dominated sorting genetic algorithm, combined with convergence acceleration and adaptive weight adjustment mechanisms, to obtain the Pareto optimal solution set for the engineering scheme.

[0010] The decision support and visualization module is used to visualize the carbon emissions of the entire life cycle of the power transmission and transformation project, which is evaluated and optimized for the target, automatically generate comparative analysis of the project schemes, and assist decision-makers in quickly selecting the optimal solution.

[0011] Furthermore, the carbon emission factors and process parameters of power transmission and transformation projects at each stage include:

[0012] Carbon emission factors and process parameters at each stage of raw material production, transportation, construction, maintenance and decommissioning; data for operation and maintenance and decommissioning recycling stages can be obtained from industry databases, operation and maintenance statistical models and typical recycling process factor libraries.

[0013] Furthermore, the full life-cycle carbon emissions database module also includes the following functions:

[0014] The parameters are adjusted according to regional differences and the carbon emission factors and process parameters of the power transmission and transformation project are dynamically updated over time. The data is also synchronized with the external database through the API interface.

[0015] Furthermore, the engineering scheme modeling module is used to receive power transmission and transformation engineering parameters and design data, including:

[0016] It receives power transmission and transformation engineering parameters input by the user and design data imported from the CAD / GIM platform, and parses the design data.

[0017] Furthermore, the engineering scheme modeling module also includes the following functions:

[0018] Receive a draft bill of materials provided by an external party and cross-validate the draft bill of materials with the standardized bill of materials and the construction process list;

[0019] For missing, abnormal, or unquantified items, automatic calculation and completion are performed based on the built-in standardized construction process library and parametric modeling rules.

[0020] Furthermore, the engineering scheme modeling module also includes the following functions:

[0021] Based on the standardized bill of materials and construction process list, different versions of engineering plans are derived, and the differences between the versions are compared.

[0022] Furthermore, the carbon emission assessment module is used to assess the carbon emissions of the power transmission and transformation project throughout its entire life cycle based on the standardized bill of materials and construction process list, including:

[0023] Based on the standardized bill of materials and construction process list, a life cycle assessment algorithm is adopted, combined with a phased weighting calculation strategy, to calculate and analyze the carbon emissions of the project throughout its entire life cycle.

[0024] It outputs carbon emission assessment results based on multiple dimensions, including material type, construction process, and life cycle stage, and also has uncertainty analysis capabilities.

[0025] Furthermore, a multi-objective optimization module is used to simultaneously optimize carbon emissions and multiple constraints using an improved non-dominated sorting genetic algorithm, combined with convergence acceleration and adaptive weight adjustment mechanisms; the output is a Pareto optimal solution set, including:

[0026] An optimization method combining an improved non-dominated sorting genetic algorithm (NSGA-II) with particle swarm optimization (PSO) is adopted, along with convergence acceleration and adaptive weight adjustment mechanisms, to achieve simultaneous optimization of carbon emissions and engineering costs.

[0027] Based on the dynamic adjustment of constraints according to policy changes and supply chain changes, the Pareto optimal solution set of the engineering scheme is output, which simultaneously optimizes the carbon emissions and multiple constraints.

[0028] Furthermore, the decision support and visualization module displays the target optimization solution set and the carbon emissions of the power transmission and transformation project throughout its entire life cycle through two-dimensional or three-dimensional visualization.

[0029] The target optimization solution set is pattern-recognized using a machine learning model to assist decision-makers in quickly selecting the optimal solution.

[0030] Furthermore, the decision support and visualization module also includes the ability to automatically generate technical reports.

[0031] This invention provides a carbon emission design system for the entire life cycle of power transmission and transformation projects based on multi-objective optimization. Under the premise of meeting the requirements of engineering safety and power supply reliability, the system achieves simultaneous optimization of carbon emissions and economic objectives throughout the entire life cycle through multi-objective collaborative optimization methods, thereby promoting the low-carbon development of power transmission and transformation project design. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the overall structure of a carbon emission design system for the entire life cycle of power transmission and transformation projects based on multi-objective optimization, provided in an embodiment of the present invention.

[0033] Figure 2 This is a flowchart of the multi-objective optimization process involved in the embodiments of the present invention;

[0034] Figure 3 This is a complete flowchart related to the embodiments of the present invention;

[0035] Figure 4 This is an example of a Pareto curve, a typical optimization result involved in an embodiment of the present invention. Detailed Implementation

[0036] Numerous specific details are set forth in the following description to provide a full understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0037] like Figure 1 As shown, this invention provides a multi-objective optimization-based carbon emission design system for the entire lifecycle of power transmission and transformation projects. Under the premise of meeting the requirements of project safety and power supply reliability, this system achieves a comprehensive balance and optimization of carbon emissions and project construction costs through a multi-objective collaborative optimization method. The system includes: a full lifecycle carbon emission database module, an engineering scheme modeling module, a carbon emission assessment module, a multi-objective optimization module, and a decision support and visualization module. These modules interact with each other through standardized data interfaces, forming a closed-loop optimization system.

[0038] The whole life cycle carbon emission database module is used to store carbon emission factors and process parameters of power transmission and transformation projects at each stage;

[0039] The engineering scheme modeling module is used to receive power transmission and transformation engineering parameters and design data; based on the carbon emission factor and process parameters, combined with the power transmission and transformation engineering parameters and design data, it generates an engineering scheme including a standardized bill of materials and a construction process list;

[0040] The carbon emission assessment module is used to assess the carbon emissions of the power transmission and transformation project throughout its entire life cycle based on the standardized bill of materials and construction process list.

[0041] The multi-objective optimization module is used to achieve the target optimization solution set of multiple Pareto engineering schemes that simultaneously optimize carbon emissions and multiple constraints by employing an improved non-dominated sorting genetic algorithm and combining convergence acceleration and weight adaptation adjustment mechanism.

[0042] The decision support and visualization module is used to visualize the carbon emissions of the entire life cycle of the power transmission and transformation project, which is evaluated and optimized for the target, automatically generate comparative analysis of the project schemes, and assist decision-makers in quickly selecting the optimal solution.

[0043] The full lifecycle carbon emission database module stores carbon emission factors and process parameters for power transmission and transformation projects at each stage of raw material production, transportation, construction, operation, maintenance, and decommissioning. It supports parameter adjustments based on regional differences and achieves dynamic updates via API interfaces and scheduled tasks, maintaining data synchronization with external databases. The database employs a hierarchical structure and version management mechanism, allowing for the traceability of historical parameters and ensuring comparability and consistency across different stages.

[0044] The engineering scheme modeling module receives user-input power transmission and transformation engineering parameters and design data imported from the CAD / GIM platform, and parses the design data. Specifically, based on the design data imported from the CAD / GIM platform, it automatically generates a bill of materials (BOM) and a process list, supports multi-version scheme management, and enables design scheme switching based on differentiated storage and version backtracking, facilitating carbon emission assessment and comparative analysis between different versions. It can also receive externally provided draft BOMs, cross-validating these drafts with the standardized BOM and construction process lists; for missing, abnormal, or unquantified items, it automatically calculates and completes them based on the built-in standardized construction process library and parametric modeling rules; and derives different versions of engineering schemes based on the standardized BOM and construction process lists, performing version differentiation comparisons.

[0045] The carbon emission assessment module, based on the standardized bill of materials and construction process list, employs a life cycle assessment algorithm and combines it with a phased weighting calculation strategy to calculate and analyze the carbon emissions of the engineering scheme throughout its entire life cycle. It outputs carbon emission assessment results across multiple dimensions, including material category, construction process, and life cycle. More specifically, the carbon emission assessment module, based on the Life Cycle Assessment (LCA) method and combined with a phased weighting calculation strategy, calculates and analyzes the carbon emissions of the engineering scheme throughout its entire life cycle, and can output assessment results across multiple dimensions such as material category, construction process, and life cycle stage. It also possesses uncertainty analysis capabilities.

[0046] The multi-objective optimization module employs an improved non-dominated sorting genetic algorithm, combined with convergence acceleration and adaptive weight adjustment mechanisms, to achieve simultaneous optimization of carbon emissions and engineering costs. Based on policy changes and supply chain variations, it dynamically adjusts the corresponding constraints and outputs the Pareto optimal solution set of the engineering scheme that simultaneously optimizes carbon emissions and multiple constraints.

[0047] The decision support and visualization module displays the target optimization solution set and the carbon emissions of the power transmission and transformation project throughout its entire life cycle through two-dimensional or three-dimensional visualization; it also performs pattern recognition on the target optimization solution set through a machine learning model to assist decision-makers in quickly selecting the optimal solution.

[0048] The following details the functions, key technologies, and input / output interfaces of each module:

[0049] 1. Full life cycle carbon emission data collection and factor management module

[0050] 1) Functional positioning:

[0051] This system is used to store and manage carbon emission factors and related process parameters for power transmission and transformation projects during the material production, transportation, construction, operation and maintenance, and decommissioning and recycling stages, and to dynamically update these parameters. Data for the operation and maintenance and decommissioning and recycling stages can be sourced from industry statistics, annual operation and maintenance workload models, equipment lifespan databases, and typical decommissioning and recycling process factor libraries.

[0052] It has dynamic update capabilities and can automatically update carbon emission parameters based on changes in regional policies, energy structure, and supply chain data.

[0053] 2) Key technical points:

[0054] Phased data model design and standardized storage of carbon emission factors;

[0055] Data version management and historical data tracing;

[0056] External database (Ecoinvent, CLCD, etc.) integration and automatic updates;

[0057] Regional energy structure correction algorithm;

[0058] API data synchronization and scheduled task queue update mechanism.

[0059] 3) Input interface:

[0060] External carbon emission factor databases (Ecoinvent, CLCD, etc.);

[0061] Energy consumption and transportation mileage data collected by IoT sensors;

[0062] Project Bill of Materials (BOM) and Process Parameter Table.

[0063] Industry operation and maintenance statistics and decommissioning and recycling process factor library.

[0064] 4) Output interface:

[0065] Provides query and calculation parameters for the carbon emission assessment module;

[0066] Provide input data for the multi-objective optimization module.

[0067] 2. Engineering Scheme Modeling Module

[0068] 1) Functional positioning:

[0069] It is used to receive engineering parameters input by users and power transmission and transformation engineering design data imported from CAD / GIM platforms, and automatically parse and generate standardized bill of materials (BOM) and construction process list.

[0070] This module can simultaneously receive draft material lists provided externally and cross-validate them with the list generated from the design data. For missing, abnormal, or unquantified items, it automatically calculates and completes them based on the built-in standardized construction process library and parametric modeling rules to ensure the integrity and consistency of the data.

[0071] It supports multi-version scheme management, which can quickly derive different design versions without modifying the original design files, save them and compare the differences between versions, which facilitates subsequent carbon emission assessment and optimization analysis.

[0072] 2) Key technical points:

[0073] Algorithms for CAD / GIM data parsing and geometric feature extraction;

[0074] Material classification mapping and process parameter modeling;

[0075] A multi-version management mechanism based on differentiated storage and version rollback.

[0076] 3) Input interface:

[0077] CAD / GIM files, engineering design parameter files;

[0078] Users manually adjust the parameters.

[0079] 4) Output interface:

[0080] The Bill of Materials (BOM) and process parameter tables are available for use by the carbon emission assessment module.

[0081] A visual solution model is provided for reference in optimization and decision-making modules.

[0082] 3. Carbon Emission Assessment Module

[0083] 1) Functional positioning:

[0084] Based on the Life Cycle Assessment (LCA) method, the carbon emissions of the design scheme are calculated over the entire life cycle, supporting single-stage and full-stage cumulative analysis.

[0085] 2) Key technical points:

[0086] LCA calculation engine and stage weight allocation strategy;

[0087] High-speed matching and retrieval algorithm for carbon emission factors;

[0088] Multi-dimensional output of carbon emission results (by material, by process, by stage);

[0089] Uncertainty analysis and confidence interval calculation.

[0090] 3) Input interface:

[0091] BOM and process parameters (from the modeling module);

[0092] Carbon emission factor data (from the database module).

[0093] 4) Output interface:

[0094] Carbon emission report and breakdown table of the design scheme;

[0095] Intermediate computational data provided to the optimization and visualization modules.

[0096] 4. Multi-objective optimization module

[0097] 1) Functional positioning:

[0098] While meeting electrical safety and engineering specifications, comprehensively optimize the entire life cycle carbon emissions, engineering costs, and other objectives (such as construction period and operation and maintenance costs).

[0099] 2) Key technical points:

[0100] A multi-objective optimization framework based on the improved NSGA-II and particle swarm optimization algorithm (integrating convergence acceleration strategy and adaptive weight adjustment);

[0101] Pareto front optimal solution selection mechanism based on crowding distance;

[0102] Dynamic constraint handling (adjusted in real time based on policy, energy structure and supply chain changes).

[0103] 3) Input interface:

[0104] Carbon emission assessment results (from the assessment module).

[0105] Cost data and engineering constraints.

[0106] 4) Output interface:

[0107] Multi-objective optimal solution set and optimization path;

[0108] Results of parameter change trend analysis.

[0109] 5. Decision Support and Visualization Module

[0110] 1) Functional positioning:

[0111] It provides multi-dimensional visualization of optimization results and carbon emission assessment data, supports scheme comparison and decision analysis, and automatically generates technical reports.

[0112] 2) Key technical points:

[0113] Two-dimensional and three-dimensional visualization engine (showing the relationship between carbon emissions, cost, and construction period);

[0114] Interactive solution comparison tool;

[0115] Automatically generate engineering carbon emission and optimization reports in PDF / Word format;

[0116] Pattern recognition is performed by combining historical optimization results from machine learning.

[0117] 3) Input interface:

[0118] Multi-objective optimization results;

[0119] Design scheme structural model and evaluation data.

[0120] 4) Output interface:

[0121] Visual charts and comparative analysis reports;

[0122] Recommended design scheme and technical report.

[0123] Specific application examples:

[0124] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0125] The present invention provides a multi-objective optimization-based carbon emission design system for the entire life cycle of power transmission and transformation projects. This system comprises a life-cycle carbon emission database module, an engineering scheme modeling module, a carbon emission assessment module, a multi-objective optimization module, and a decision support and visualization module. The modules communicate and transfer parameters through standardized data interfaces, forming a closed-loop workflow from data acquisition, scheme modeling, carbon emission assessment, optimization calculation to result display and decision support. This ensures the continuity, traceability, and efficiency of the carbon emission optimization process.

[0126] Example 1: System Architecture and Operating Principles

[0127] This invention provides a multi-objective optimization-based carbon emission design system for the entire lifecycle of power transmission and transformation projects. The system includes a lifecycle carbon emission database module, an engineering scheme modeling module, a carbon emission assessment module, a multi-objective optimization module, and a result visualization and decision support module. Its system architecture is as follows: Figure 1 As shown.

[0128] The workflow is as follows:

[0129] 1. Full life cycle carbon emission database module

[0130] This module establishes a carbon emission factor database according to the life cycle stage, covering material production, equipment manufacturing, transportation, construction, operation and maintenance, and decommissioning and recycling. It can output carbon emission factor data for each stage of power transmission and transformation projects, from raw material acquisition, processing and manufacturing, construction and installation, operation and maintenance to decommissioning and recycling, forming a standardized and scalable life cycle carbon emission database.

[0131] The database covers the collection and storage of engineering information at the following stages:

[0132] ① Material production and equipment manufacturing stage: types, quantities, and specifications of raw materials; origin and manufacturing process of major equipment (supports, conductors, poles, etc.); carbon emission factor per unit mass of materials; carbon emission factor per unit of equipment; energy structure data of manufacturers and production locations (electricity, natural gas, fuel oil, etc.); proportion of recycled materials and recycling rate.

[0133] ② Transportation stage: transportation mode (road, rail, waterway, etc.), transportation distance and route, carbon emission factor per unit of transportation volume (in tons per kilometer), loading rate, etc.

[0134] ③ Construction stage: Construction technology type (foundation pouring, tower construction, conductor erection, etc.), construction machinery type and shift power, construction energy consumption (fuel, electricity, etc.), and construction material consumption.

[0135] ④ Operation and Maintenance Phase: Annual maintenance workload, maintenance frequency, materials and quantities of replaced parts, operating status (transmission record) parameters, etc. Data in this phase primarily comes from industry statistics and typical engineering parameters in the database, and can also be corrected by incorporating regional experience parameters or user input.

[0136] ⑤ Retirement and Recycling Phase: This includes the proportion of recyclable materials, carbon emission factors related to recycling processes, emission treatment methods (landfill, weight, reuse), and carbon emission coefficients. This data is constructed based on industry experience and case parameters and allows for adjustments according to regional standards.

[0137] The database employs a phased data model to accurately map different raw materials and construction processes to their corresponding carbon emission factors. It also features version management to adapt to policy adjustments, changes in energy structure, and supply chain fluctuations. It supports differentiated adjustments to factors by region (e.g., different provinces or countries) and can automatically update carbon emission coefficients annually, facilitating long-term tracking of changes in carbon emission benchmarks.

[0138] This module can achieve bidirectional data synchronization with third-party databases (such as Ecoinvent and CLCD) via external API interfaces, and receive real-time data from on-site IoT sensors, including energy consumption, transportation mileage, and inventory usage, enabling dynamic updates of carbon emission parameters. To improve data retrieval efficiency, the module adopts a hierarchical data structure and an efficient indexing mechanism (such as a B+ tree index), and has a historical version tracking function to ensure the comparability and repeatability of solutions at different points in time.

[0139] 2. Engineering Scheme Modeling Module

[0140] This module is used to receive basic engineering parameters input by the user (such as line voltage level, line length, terrain type, tower type, conductor cross-section, transformer equipment type, etc.), and parse CAD / GIM and other design documents to automatically extract engineering geometric parameters, material information and construction process flow.

[0141] To achieve automated data extraction, this module can combine image recognition and natural language processing technologies to identify key engineering data in design drawings and text descriptions, and generate standardized bills of materials (BOM) and process parameter tables.

[0142] The module has a built-in multi-version scheme management function, which can quickly generate and save multiple derivative design scheme versions without modifying the original design data, enabling rapid switching and differentiation between schemes, and facilitating subsequent full life cycle carbon emission assessment and optimization analysis.

[0143] This module maps data to the database module, automatically matching the extracted material and process information with the corresponding carbon emission factors, and directly transmitting the modeling results to the carbon emission assessment module for calculation.

[0144] 3. Carbon Emission Assessment Module

[0145] This module is based on the Life Cycle Assessment (LCA) method and supports multiple system boundary selections (such as "cradle to gate" and "cradle to grave") to calculate and summarize the carbon emissions of engineering projects under different boundary conditions in stages. The carbon emission results can be further broken down into stages such as material production, transportation, construction, operation, and decommissioning, and statistical analysis can be performed on a stage-by-stage basis.

[0146] During the operation, maintenance, and decommissioning phases, the assessment module calls upon typical factors or prediction parameters built into the database and allows users to make corrections based on regional standards, industry experience, or actual project conditions, thereby ensuring the rationality and applicability of carbon emissions during this phase.

[0147] To address uncertainty, this module introduces the Monte Carlo method to perform random sampling calculations on the input factors and outputs the confidence interval of the carbon emission results, thereby improving the reliability of the assessment results.

[0148] The module supports both full calculations and rapid incremental calculations after design changes, and provides the latest carbon emission results to the optimization module in real time.

[0149] 4. Multi-objective optimization module

[0150] This module simultaneously optimizes multiple objectives, such as carbon emissions and project cost, while meeting the requirements of electrical safety, structural strength, and relevant engineering specifications.

[0151] The optimization algorithm combines an improved non-dominated sorting genetic algorithm (NSGA-II) with particle swarm optimization (PSO). It optimizes the initial population by introducing carbon emission sensitivity analysis to improve convergence speed and solution set diversity.

[0152] During the optimization process, the module can dynamically adjust the constraints (such as adjustments to carbon emission benchmarks caused by policy changes, changes in the availability of low-carbon materials in the supply chain, etc.) to ensure the applicability of the optimization results under different external conditions.

[0153] Ultimately, the module outputs a Pareto frontier solution set, encompassing optimal combinations across multiple dimensions such as low carbon emissions, low cost, and construction period. The results are then transmitted to the decision support and visualization module for display and solution selection. Figure 2 As shown, the core process is as follows:

[0154] (1) Problem Modeling and Objective Function

[0155] ① Decision variables: Key parameters in power transmission and transformation engineering design, including tower type selection, conductor type, insulator material, foundation type, construction process parameters, transportation scheme and route, etc.

[0156] ② Optimization objectives: Minimize the total life cycle carbon emissions f1(x); minimize the total project cost f2(x).

[0157] ③ Constraints: Meet power grid safety or industry design specifications (structure, electrical safety, power, etc.).

[0158] (2) Population initialization

[0159] Typical solutions are extracted from the historical engineering solution database as the initial individuals of the population, and random perturbations are applied to some individuals to generate the remaining individuals, thereby ensuring the diversity and broad coverage of the initial solution set.

[0160] (3) Fitness assessment

[0161] ① For each individual (scheme), call the carbon emission assessment module to calculate its total life cycle carbon emissions f1(x);

[0162] ②At the same time, calculate the project construction cost f2(x) based on the unit price of materials, labor costs, transportation costs, and construction machinery shift costs;

[0163] ③ For individuals who violate the constraints, a penalty function or a feasibility-first strategy should be used to handle them.

[0164] (4) Selection, crossover and mutation

[0165] ① Selection operator: A selection mechanism based on non-dominated sorting and crowding distance is adopted to maintain the diversity of solution sets;

[0166] ② Crossover operator: Adaptive two-point crossover is adopted, and the crossover probability \(P_c\) is dynamically adjusted with the iteration progress (higher in the early stage to enhance exploration, and lower in the later stage to promote convergence);

[0167] ③ Mutation operator: Gaussian perturbation and other continuous / discrete mutation strategies are adopted. The mutation probability \(P_m\) takes a higher value in the early stage of evolution to expand the search range, and then gradually decays to refine the local search.

[0168] (5) Elite Retention

[0169] Retain some individuals from the previous generation that are at the non-dominant frontier or have the best fitness to avoid losing high-quality solutions during generational replacement.

[0170] (6) Termination Conditions

[0171] ① Reach the preset maximum algebra (G_{max});

[0172] ② Or the early termination condition is met (e.g., the target value of the Pareto front changes below the set threshold ε for several consecutive generations).

[0173] (7) Output of Results

[0174] ① Output the Pareto front solution set (the set of non-dominated optimal solutions);

[0175] ② It can also perform multi-dimensional visualization (two-dimensional or three-dimensional graphics) of the solution set, such as low carbon emissions, cost, and construction period, and submit the optimization results to the decision support and visualization module for users to filter and make decisions.

[0176] Example 2: Optimization Case of Transmission Line Project

[0177] Taking a new 220kV transmission line construction project as an example, this embodiment illustrates the application method and optimization effect of the system of the present invention in a practical project. The process is as follows: Figure 3 As shown.

[0178] 1. Input of basic engineering parameters

[0179] The transmission line project has a total length of approximately 35 km. It is designed as a single-circuit line with angle steel towers and J / G1A-300 / 40 conductors. The terrain is predominantly hilly with some shallow gullies. The foundation type is spread foundations. The climate is temperate, and the design life is 30 years. The average transportation radius from the construction area to the main material supply points is approximately 120 km.

[0180] 2. Initial Scheme Modeling and Data Generation

[0181] Users can import their design drawings (DWG format) and bill of materials into the engineering scheme modeling module of this invention.

[0182] The system first automatically parses the imported drawings and lists:

[0183] Geometric identification and parameter extraction are performed on the structures such as towers, conductors, insulators, grounding devices, and foundations in the drawings;

[0184] The system automatically reads known material and equipment information from the bill of quantities drafting process and cross-validates it with the results of drawing analysis.

[0185] For items that have been removed or not measured (such as the weight of a single piece of a certain type of tower material, or the total amount of concrete used in the mix design), the system automatically calculates and completes the data using a standardized built-in construction process library and a parametric model.

[0186] For missing or unquantified items (such as the weight of a single tower material or the total amount of concrete used in the mix design), the system automatically calculates and completes the missing items using a built-in standardized construction process library and parametric model.

[0187] Through the above steps, the system generates a standardized initial bill of materials (BOM) and construction process list that meet the requirements of full life cycle carbon emission accounting.

[0188] According to calculations, the initial material composition of this project is as follows: the total weight of steel is approximately 420 tons, the total weight of conductors is approximately 92 tons, the total weight of insulators is approximately 5.6 tons, the total volume of foundation concrete is approximately 2,800 cubic meters, and auxiliary materials and hardware account for approximately 3% of the total weight.

[0189] 2. Lifecycle carbon emission calculation

[0190] The carbon emission assessment module accesses the full life-cycle carbon emission database to perform carbon emission calculations under "cradle-to-grave" boundary conditions for the initial scenario. The calculation results show:

[0191] Materials production stage: Carbon emissions are approximately 5,960 tons of CO2e, accounting for about 78% of total emissions;

[0192] Transportation phase: Carbon emissions are approximately 250 tons of CO2e, accounting for about 3% of total emissions;

[0193] Construction phase: Carbon emissions are approximately 1,140 tons of CO2e, accounting for about 15% of total emissions;

[0194] Operation and maintenance phase: Carbon emissions are approximately 380 tons of CO2e, accounting for about 5% of total emissions;

[0195] Retirement and recycling phase: Carbon emissions are approximately 150 tons of CO2e, accounting for about 2% of total emissions.

[0196] Among them, the carbon emissions during the material production, transportation and construction stages are directly calculated based on the BOM and process list obtained from the analysis of the design documents;

[0197] Carbon emissions during the operation, maintenance, and decommissioning phases are estimated based on typical parameters in the database;

[0198] During the operation and maintenance phase, factors such as routine inspections, parts replacements, and vehicle energy consumption are considered, and the database provides maintenance frequency and energy consumption factors.

[0199] The decommissioning and recycling phase considers equipment dismantling, material recovery rate, and treatment methods (reuse, landfill, etc.), with the database providing recycling process factors and regional average recovery rates;

[0200] Meanwhile, this parameter can be adjusted according to user input or regional standards to ensure the applicability and accuracy of the results.

[0201] 3. Multi-objective optimization and scheme comparison

[0202] The multi-objective optimization module uses "minimizing total life-cycle carbon emissions" and "minimizing total project cost" as objective functions, and sets the following constraints:

[0203] The project must meet the requirements of national and industry standards and specifications regarding electrical safety and structural safety;

[0204] The increase in project cost shall not exceed 5%;

[0205] The carbon emission reduction rate is no less than 10%. The optimization algorithm is based on an improved NSGA-II and PSO fusion strategy, and the population is initialized using historical project data. The system generates 38 candidate schemes in the Pareto front solution set, and compares the carbon emission and cost relationship curves of each scheme through an interactive interface.

[0206] The results show that the low-carbon priority approach reduces carbon emissions by approximately 18% over the entire life cycle, while increasing costs by approximately 3%.

[0207] The overall balanced solution reduces carbon emissions by approximately 14% and construction costs by approximately 2%.

[0208] Economic priority option: Costs are reduced by about 6%, but carbon emissions are reduced by only about 9%.

[0209] 4. Scheme Selection and Result Output

[0210] The user ultimately selects a comprehensive balanced solution, and the system automatically generates a construction proposal, which includes:

[0211] It is recommended to use some high-strength low-alloy steel to replace traditional Q235 steel in order to reduce material usage;

[0212] Centralized prefabricated foundation components are used to reduce the amount of on-site concrete pouring;

[0213] The transportation process has been optimized to include segmented centralized delivery to reduce empty runs;

[0214] Electric or hybrid power equipment should be given priority in the selection of construction machinery.

[0215] Finally, the system will export the optimization results in multiple formats:

[0216] PDF format optimization design report;

[0217] DWG format construction drawings;

[0218] Optimized bill of materials and carbon emission inventory in XLSX format;

[0219] The IFC format 3D Engineering Information Model (GIM) is used for subsequent construction and operation and maintenance management.

[0220] Example 3: Software Implementation and Human-Computer Interaction

[0221] 1. System Architecture Design

[0222] The system of this invention adopts a distributed microservice architecture to ensure high stability and scalability under conditions of large-scale engineering data processing and multi-user concurrent access. The system backend is developed using a hybrid Python and Java approach, with Python modules used for lifecycle carbon emission assessment and multi-objective optimization algorithm calculations, and Java modules used for business logic control, data scheduling, and task management.

[0223] 2. Visualization technology implementation

[0224] The system integrates a WebGL 3D rendering engine to visualize the optimization results of power transmission and transformation engineering schemes. The 3D view is based on a simplified engineering structure model and can display the main components of transmission and transformation lines or substations in layers, and use color, transparency, and other methods to indicate the relative contribution ratio of carbon emissions at each stage (such as material production, transportation, construction, operation and maintenance, decommissioning and recycling).

[0225] The module supports synchronized updates with two-dimensional charts (such as Pareto frontier curves, stage emission bar charts, and cost comparison line charts). When users select different optimization schemes, the carbon emission distribution in the three-dimensional model will change synchronously, making it easy to intuitively compare the differences between the schemes from both spatial and numerical dimensions.

[0226] In addition, the visualization module supports multiple filtering modes such as by stage, by material category, and by construction process, helping users quickly locate high carbon emission areas and generate technical reports based on optimization suggestions.

[0227] 3. Data Management and Storage

[0228] The data storage portion uses a combination of PostgreSQL relational database and TimescaleDB time-series database.

[0229] PostgreSQL is used to store static engineering data, bills of materials, carbon emission factor libraries, etc.

[0230] TimescaleDB is used to store dynamic data such as construction energy consumption, transportation mileage, and equipment operating status collected in real time.

[0231] 4. Security Mechanism

[0232] The system communication layer is based on the HTTPS security protocol and uses the JWT (JSON Web Token) mechanism to implement user authentication and access control. All data is encrypted with AES-256 during transmission and storage to ensure the security and integrity of engineering data during transmission and storage.

[0233] 5. User Interaction Flow

[0234] Users input engineering parameters or import design files through a PC or web-based human-computer interaction interface. The system automatically performs scheme modeling, carbon emission assessment, and multi-objective optimization calculations, and provides real-time feedback to the visualization interface. The visualization interface supports two-dimensional charts (such as...). Figure 4 The Pareto frontier curve and stage emission bar chart shown are updated synchronously with the 3D model.

[0235] 6. Result Output

[0236] The system supports multiple output formats, including:

[0237] PDF format optimization report;

[0238] DWG format construction drawings;

[0239] XLSX format bill of materials and carbon emission inventory;

[0240] The IFC format Engineering Information Model (GIM) facilitates subsequent construction and operation management on the GIM platform.

[0241] 7. Deployment Mode

[0242] The system supports three deployment methods:

[0243] Cloud deployment: Supports cross-regional, multi-unit collaborative design and optimization;

[0244] Local deployment: Suitable for internal network environments such as power design institutes and construction companies, ensuring that data does not leave the internal network and meeting confidentiality or data security requirements;

[0245] Hybrid deployment: Sensitive data is stored locally, while computation and visualization are performed in the cloud to balance security and computing performance.

[0246] This invention provides a carbon emission design system for the entire life cycle of power transmission and transformation projects based on multi-objective optimization. Compared with the existing methods where carbon emission accounting for power transmission and transformation projects is mostly carried out in the later stages of construction or scientific research and experimentation and relies on manual calculation, this invention realizes the prediction and multi-objective optimization of carbon emissions throughout the entire life cycle during the design stage, which greatly improves the feasibility and implementation of low-carbon design.

[0247] This invention establishes a dynamic and scalable carbon emission factor database, combined with CAD / GIM automatic parsing technology, to achieve rapid extraction and factor mapping of engineering materials and construction process information, reducing manual statistical errors and improving efficiency. The carbon emission assessment model based on the LCA method can output phased emission data under different boundary conditions, and combines Monte Carlo or LHS sampling for uncertainty analysis, improving the reliability of the results.

[0248] The improved NSGA-II and PSO fusion algorithm significantly enhances convergence speed and solution set diversity, making it possible to simultaneously optimize carbon emissions and engineering costs. Practical applications show that, without compromising safety and regulations, a 10%–20% reduction in life-cycle carbon emissions can be achieved, while cost variations are controlled within ±5%.

[0249] Furthermore, the visualization decision support module uses two-dimensional / three-dimensional Pareto curves and scheme comparison tables to intuitively display the trade-offs between different schemes in terms of carbon emissions, cost, and construction period, shortening the design decision-making cycle and improving the transparency and traceability of the schemes. This system has the potential to be extended to various power transmission and transformation projects and is of great significance for achieving the "dual carbon" goals of the power industry.

[0250] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0251] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0252] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0253] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0254] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A multi-objective optimization-based carbon emission design system for the whole life cycle of a power transmission and transformation project, characterized in that, The application relates to a carbon emission evaluation and optimization system for power transmission and transformation engineering, which comprises a full life cycle carbon emission database module, an engineering scheme modeling module, a carbon emission evaluation module, a multi-objective optimization module and a decision support and visualization module. The full life cycle carbon emission database module is used for storing carbon emission factors and process parameters of power transmission and transformation engineering at various stages. The engineering scheme modeling module is used for receiving power transmission and transformation engineering parameters and design data. Based on the carbon emission factors and process parameters, power transmission and transformation engineering parameters and design data are combined to generate engineering schemes including standardized bill of materials and construction lists. The carbon emission evaluation module is used for evaluating the full life cycle carbon emission of power transmission and transformation engineering according to the standardized bill of materials and construction lists. The multi-objective optimization module is used for realizing the synchronous optimization of the carbon emission and multi-objective functions under the condition of meeting various constraints by adopting an improved non-dominated sorting genetic algorithm and combining a convergence acceleration and weight self-adaptive adjustment mechanism, so that a Pareto optimal engineering scheme solution set is obtained. The decision support and visualization module is used for visually displaying the target optimization solution set and the evaluated full life cycle carbon emission of power transmission and transformation engineering, automatically generating the engineering scheme comparative analysis and assisting decision makers in quickly selecting the optimal scheme. The carbon emission factors and process parameters of power transmission and transformation engineering at various stages comprise carbon emission factors and process parameters at raw material production, transportation, construction, maintenance and retirement stages.

2. The system of claim 1, wherein, The carbon emission factors and process parameters at raw material production, transportation, construction, maintenance and retirement stages can be sourced from an industry database, operation and maintenance statistical data or a typical recycling process factor library. The functions of the full life cycle carbon emission database module further comprise the following steps:

3. The system of claim 1, wherein, The parameters of the full life cycle carbon emission database module are corrected according to regional differences and stored dynamically according to time. The engineering scheme modeling module is used for receiving power transmission and transformation engineering parameters and design data, which comprises the following steps:

4. The system of claim 1, wherein, User-input power transmission and transformation engineering parameters and design data imported from a CAD / GIM platform are received and parsed to generate a BOM and a construction process list. The functions of the engineering scheme modeling module further comprise the following steps:

5. The system of claim 1, wherein, A draft bill of materials provided by an external source is received, and the draft bill of materials is cross-checked with the standardized bill of materials and the construction process list. For missing, abnormal or unquantified items, automatic calculation and completion are performed based on a built-in standardized construction process library and parameterized modeling rules. The functions of the engineering scheme modeling module further comprise the following steps:

6. The system of claim 1, wherein, Different versions of engineering schemes are derived according to the standardized bill of materials and the construction process list, and are differentially compared. The carbon emission evaluation module is used for evaluating the full life cycle carbon emission of power transmission and transformation engineering according to the standardized bill of materials and the construction process list, which comprises the following steps:

7. The system of claim 1, wherein, A life cycle assessment algorithm is adopted to calculate and analyze the life cycle carbon emission of the engineering scheme according to the standardized bill of materials and the construction process list, and a stage-by-stage weight calculation strategy is combined. The carbon emission evaluation results are output in multiple dimensions including material categories, construction processes and life cycle stages. ​ 8. The system of claim 1, wherein, A multi-objective optimization module is used to adopt an improved non-dominated sorting genetic algorithm, combined with a convergence acceleration and weight self-adaptive adjustment mechanism, to realize the simultaneous optimization of the carbon emissions and multi-objective functions under multiple constraint conditions, and obtain a Pareto optimal multiple engineering scheme solution set, including: An improved non-dominated sorting genetic algorithm is used, combined with a convergence acceleration and weight self-adaptive adjustment mechanism, to realize the simultaneous optimization of the carbon emissions and engineering cost; According to policy changes and supply chain changes, the corresponding constraint conditions are dynamically adjusted, and the Pareto optimal engineering scheme solution set is output, which is simultaneously optimized under the carbon emissions and multiple constraint conditions.

9. The system of claim 1, wherein, A decision support and visualization module displays the target optimization solution set and the full life cycle carbon emissions of the evaluated power transmission and transformation project through two-dimensional or three-dimensional visualization. A machine learning model is used for pattern recognition of the target optimization solution set to assist decision-makers in quickly selecting the optimal scheme.

10. The system of claim 1, wherein, The decision support and visualization module also includes the function of automatically generating a technical report.

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