A wind farm road and wind turbine platform optimization design method and system

Abstract

The application discloses a kind of wind farm road and wind turbine platform optimization design method and system, first obtain engineering data and design scheme, the engineering data is used to identify the environmental information at engineering area, then based on engineering data and design scheme is constructed multi-objective optimization model, the multi-objective optimization model includes engineering cost model, comprehensive environmental impact index model and engineering complexity model, wherein comprehensive environmental impact index model is used to identify the comprehensive influence of multiple environmental indicators on ecological environment, whereby, the implementation details of design scheme can be micro-regulated by engineering cost model and engineering complexity model, and the influence on ecological environment is comprehensively evaluated by combining comprehensive environmental impact index model, and then by solving multi-objective optimization model, the optimized design scheme is obtained, the trade-off between micro-design of engineering and ecological protection is realized.

Description

Technical Field

[0001] This application relates to the interdisciplinary field of engineering technology, environmental science and geographic information science, and specifically to an engineering design optimization method and system. Background Technology

[0002] As a major renewable energy source, wind power has experienced rapid development over the past two decades. In terms of existing capacity, China ranks first globally, with a cumulative installed capacity exceeding 520GW, accounting for approximately 45% of the global total. In terms of new capacity, 80GW of new installations were added in 2024, demonstrating extremely rapid growth. Looking ahead, as wind energy resources in the plains of central and eastern China gradually become saturated, mountainous and hilly areas (especially in the southwest and south) are increasingly becoming one of the main new growth directions for onshore wind power due to their abundant exploitable resources.

[0003] However, the large-scale, intensive construction of wind farms in mountainous and hilly areas will have a series of long-term and irreversible negative impacts on the regional ecological environment. These impacts mainly stem from land disturbance during the construction period, especially the construction of roads and turbine platforms within the wind farm. These construction projects require large-scale excavation, filling, and leveling operations, leading to a sharp increase in the area of ​​exposed slopes and surfaces, fragmentation of native vegetation, and a high risk of soil erosion, even triggering geological disasters such as landslides and mudslides. This creates a vicious cycle of "soil erosion - ecological degradation - geological risk," seriously threatening regional ecological security and the long-term stability of the project.

[0004] Traditional wind farm road and turbine platform planning usually focuses on minimizing engineering costs and meeting transportation requirements as the sole objectives, making it difficult to balance the micro-design of engineering projects with ecological protection. Summary of the Invention

[0005] In view of this, this application provides an optimized design method and system for wind farm roads and wind turbine platforms, which provides guidance for engineering design and achieves a balance between engineering design and ecological protection.

[0006] To solve the above problems, the technical solution provided in this application is as follows:

[0007] On the one hand, this application provides an optimized design method for wind farm roads and wind turbine platforms, the method comprising:

[0008] Acquire engineering data and proposed design schemes, wherein the engineering data is used to identify environmental information at the engineering area;

[0009] Based on the engineering data and the proposed design scheme, a multi-objective optimization model is constructed. The multi-objective optimization model includes an engineering cost model, a comprehensive environmental impact index model, and an engineering complexity model. The comprehensive environmental impact index model is used to evaluate the comprehensive impact of multiple environmental indicators on the ecological environment.

[0010] The multi-objective optimization model is solved to obtain the optimized design scheme.

[0011] In one possible implementation, the multiple environmental indicators include potential soil erosion, area of ​​permanently exposed slopes, vegetation disturbance and fragmentation index, geological hazard risk value, hydrological connectivity disruption index, and habitat fragmentation and isolation index; the method further includes:

[0012] Multiple environmental indicators are uniformly quantified and weighted using the analytic hierarchy process (AHP) to obtain the comprehensive environmental impact index model.

[0013] In one possible implementation, solving the multi-objective optimization model to obtain the optimized design scheme includes:

[0014] The multi-objective optimization model is iteratively solved using a non-dominated sorting genetic algorithm to obtain the Pareto optimal solution set;

[0015] Based on the Pareto optimal solution set, an optimized design scheme is obtained.

[0016] In one possible implementation, obtaining the optimized design scheme based on the Pareto optimal solution set includes:

[0017] The design scheme corresponding to the lowest score of the integrated environmental impact index model in the Pareto optimal solution set is taken as the optimal design scheme; or...

[0018] The design scheme that achieves cost-complexity-ecological balance in the Pareto optimal solution set is taken as the optimized design scheme.

[0019] In one possible implementation, the proposed design includes the alignment, slope, and cross-section of roads within the wind farm, as well as the location and slope design of the wind turbine platform.

[0020] In one possible implementation, the method further includes:

[0021] The data information from the construction process based on the optimized design scheme is input into the comprehensive environmental impact index model to obtain the evaluation results;

[0022] If the assessment result exceeds the preset risk threshold, an alarm will be issued.

[0023] In another aspect, this application provides an engineering design optimization system, which includes an acquisition unit, a construction unit, and an optimization unit:

[0024] The acquisition of engineering data and proposed design schemes, wherein the engineering data is used to identify environmental information at the engineering area;

[0025] Based on the engineering data and the proposed design scheme, a multi-objective optimization model is constructed. The multi-objective optimization model includes an engineering cost model, a comprehensive environmental impact index model, and an engineering complexity model. The comprehensive environmental impact index model is used to evaluate the comprehensive impact of multiple environmental indicators on the ecological environment.

[0026] The multi-objective optimization model is solved to obtain the optimized design scheme.

[0027] In one possible implementation, the multiple environmental indicators include potential soil erosion, area of ​​permanently exposed slopes, vegetation disturbance and fragmentation index, geological hazard risk value, hydrological connectivity disruption index, and habitat fragmentation and isolation index. The system also includes a computing unit.

[0028] The calculation unit is used to quantify multiple environmental indicators in a unified manner and perform weighted calculations using the analytic hierarchy process to obtain the comprehensive environmental impact index model.

[0029] In one possible implementation, the optimization unit is used to:

[0030] The multi-objective optimization model is iteratively solved using a non-dominated sorting genetic algorithm to obtain the Pareto optimal solution set;

[0031] Based on the Pareto optimal solution set, an optimized design scheme is obtained.

[0032] In one possible implementation, the optimization unit is used to:

[0033] The design scheme corresponding to the lowest score of the integrated environmental impact index model in the Pareto optimal solution set is taken as the optimal design scheme; or...

[0034] The design scheme that achieves cost-complexity-ecological balance in the Pareto optimal solution set is taken as the optimized design scheme.

[0035] In one possible implementation, the proposed design includes the alignment, slope, and cross-section of roads within the wind farm, as well as the location and slope design of the wind turbine platform.

[0036] In one possible implementation, the system further includes an evaluation unit and an alarm unit:

[0037] The evaluation unit is used to input data information from the construction process based on the optimized design scheme into the comprehensive environmental impact index model to obtain the evaluation results.

[0038] The alarm unit is used to issue an alarm if the evaluation result exceeds a preset risk threshold.

[0039] In another aspect, this application provides a computer device, which includes a processor and a memory:

[0040] The memory is used to store computer programs;

[0041] The processor is configured to execute the method described in any of the above-described embodiments according to the computer program.

[0042] In another aspect, this application provides a computer-readable storage medium for storing a computer program that, when executed by a computer device, implements the method described in any of the above-mentioned embodiments.

[0043] In another aspect, this application provides a computer program product including a computer program, which, when run on a computer device, causes the computer device to perform any of the methods described above.

[0044] As can be seen from the above technical solution, the solution first acquires engineering data and proposed design schemes. The engineering data is used to identify environmental information in the engineering area. Then, based on the engineering data and proposed design schemes, a multi-objective optimization model is constructed. This multi-objective optimization model includes an engineering cost model, a comprehensive environmental impact index model, and an engineering complexity model. The comprehensive environmental impact index model is used to identify the comprehensive impact of multiple environmental indicators on the ecological environment. Thus, through the engineering cost model and the engineering complexity model, the implementation details of the proposed design scheme can be micro-controlled. Combined with the comprehensive environmental impact index model, the impact on the ecological environment can be comprehensively evaluated. Finally, by solving the multi-objective optimization model, an optimized design scheme is obtained, realizing the trade-off between the micro-design of the project and ecological protection. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1A flowchart illustrating an optimized design method for wind farm roads and wind turbine platforms provided in this application embodiment;

[0047] Figure 2 This is a schematic diagram of an optimized design system for wind farm roads and wind turbine platforms provided in an embodiment of this application. Detailed Implementation

[0048] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0049] As described in the background section, traditional wind farm road and turbine platform planning schemes typically focus on minimizing engineering costs and meeting transportation requirements as the sole objectives. This planning approach suffers from the following prominent problems:

[0050] First, the risk of soil erosion is high, and the economic cost is enormous. The construction of internal roads and the leveling of turbine platforms in wind farms require extensive earthwork excavation and backfilling, easily leading to large areas of exposed slopes, a major cause of soil erosion in mountainous wind farms. Current design methods lack mechanisms to incorporate soil erosion and exposed slope area as core constraints and optimization targets, resulting in extremely high ecological and environmental costs for the construction planning of internal roads and turbine platforms. Such high-risk schemes often lead to frequent work stoppages and rectifications during the construction phase, substantial investments in slope protection and subsequent soil and water conservation, and may even result in significant economic losses due to fines or project delays for failing to meet environmental protection requirements.

[0051] Second, there is insufficient quantification of ecological disturbances and a broken guidance chain. Vegetation destruction and slope exposure are important indicators of ecological degradation, but these indicators are often difficult to quantify, predict, and optimize during the micro-design phase of on-site roads and wind turbine platforms. Furthermore, ecological impact assessments for wind farm construction are mostly focused on post-hoc or macro-level environmental impact assessments, whose assessment indicators struggle to dynamically quantify the micro-level soil erosion risks and exposed areas resulting from on-site road and wind turbine platform planning. Commonly used remote sensing or climate models have low resolution (mostly at the kilometer level), failing to provide direct quantitative guidance and optimization for the alignment, slope, and cross-section of roads within wind farms, as well as the precise site selection and slope design of wind turbine platforms. This results in a significant technical disconnect and compliance dilemma between engineering design and ecological protection goals, despite national regulations requiring ecological protection to be integrated throughout the entire lifecycle of wind power projects. At the engineering design level, the interaction and difficulty in balancing multiple environmental indicators such as soil erosion, vegetation destruction, and geological risks, coupled with the lack of a unified and operational measurement standard, hinders the implementation of environmental protection requirements.

[0052] To guide engineering design schemes through micro-engineering design and the quantification of environmental indicators, this application provides an optimization design method and system for wind farm roads and wind turbine platforms. First, engineering data and proposed design schemes are acquired. The engineering data is used to identify environmental information at the engineering area. Then, a multi-objective optimization model is constructed based on the engineering data and the proposed design scheme. This multi-objective optimization model includes an engineering cost model, a comprehensive environmental impact index model, and an engineering complexity model. The comprehensive environmental impact index model is used to identify the combined impact of various environmental indicators on the ecological environment. Thus, the engineering cost model and the engineering complexity model allow for micro-control of the implementation details of the proposed design scheme, and the impact on the ecological environment is comprehensively assessed by combining the comprehensive environmental impact index model. Finally, by solving the multi-objective optimization model, an optimized design scheme is obtained, achieving a balance between micro-engineering design and ecological protection.

[0053] The solutions provided in this application involve the intersection of engineering technology, environmental science and geographic information science, and are specifically illustrated through the following embodiments.

[0054] See Figure 1 The diagram shown is a flowchart of an engineering design optimization method provided in an embodiment of this application. In this embodiment, it can be executed by a computer device.

[0055] S101: Obtain engineering data and proposed design schemes.

[0056] Among them, engineering data is used to identify environmental information in the engineering area.

[0057] The project area refers to the site selected for the project. Environmental information about the project area is needed in the early stages of the project to facilitate engineering design or to evaluate the engineering design scheme.

[0058] The proposed design scheme refers to the preliminary technical path and implementation framework formed based on engineering objectives and constraints, such as expected costs, expected project cycle, and the design of roads or wind turbine platforms for the proposed wind farm.

[0059] In one possible implementation, the proposed design scheme includes the alignment, slope, and cross-section of roads within the wind farm, as well as the location and slope design of the wind turbine platforms.

[0060] Therefore, a comprehensive and accurate evaluation can be conducted on the proposed design scheme with detailed implementation details.

[0061] This application does not limit the specific content of the engineering data. For example, engineering data may include geographic information, soil and water information, disaster data, vegetation information, air quality, etc.

[0062] Specifically, high-precision digital elevation models (resolution better than 5m), geological maps, hydrological maps, vegetation / land use data, historical disaster data, and distribution data of biologically sensitive species within the engineering area can be collected. Then, the engineering data and the proposed design scheme can be imported into a Geographic Information System (GIS) platform.

[0063] S102: Based on engineering data and proposed design schemes, construct a multi-objective optimization model.

[0064] This application does not impose specific limitations on various environmental indicators, such as water environmental indicators, soil environmental indicators, vegetation environmental indicators, etc. Further, it may include soil erosion, exposed slope area, vegetation disturbance and fragmentation index, etc. These various environmental indicators are determined based on the proposed design scheme and are used to identify engineering data after the proposed design scheme is implemented.

[0065] Among them, the multi-objective optimization model includes the engineering cost model, the comprehensive environmental impact index model, and the engineering complexity model.

[0066] The Integrated Environmental Impact Index (EI) model is used to assess the combined impact of various environmental indicators on the ecological environment when carrying out engineering projects. The Engineering Cost Model is used to assess the human and material costs required to carry out engineering projects, including assessments of the number of equipment and skilled workers. The Engineering Complexity Model is used to assess the difficulty of carrying out engineering projects, including assessments of the project duration, project size, technical difficulty, and management difficulty. It can also be defined as the number of curves per unit length, the fluctuation rate of earthwork volume, etc., to constrain the selection of models that are too convoluted or extreme in design.

[0067] Specifically, engineering data and proposed design schemes can be analyzed through a GIS platform to determine various environmental indicators within the engineering area. For example, through GIS spatial analysis functions, slope, slope length factor, catchment area, etc., can be extracted and calculated from the DEM as inputs for environmental indicators in the EI model.

[0068] Then, based on environmental indicators and initial constraints, a comprehensive environmental impact index (EI) model is constructed to quantify and weight multiple environmental indicators such as soil erosion, exposed area, hydrological damage, and habitat fragmentation. Next, based on the proposed design scheme, an engineering cost model is constructed to assess engineering costs, and an engineering complexity model is constructed to assess engineering complexity. Finally, the engineering cost model, EI model, and engineering complexity model are combined to obtain a multi-objective optimization model.

[0069] S103: Solve the multi-objective optimization model to obtain the optimal design scheme.

[0070] The multi-objective optimization model can take minimizing the comprehensive score of the multi-objective optimization model as the optimization objective, or take minimizing the score of the EI model as the objective, etc., and this application does not limit it in this regard.

[0071] As an example, taking minimizing the overall score of a multi-objective optimization model as the optimization objective, the objective function of this multi-objective optimization model is as follows:

[0072]

[0073] Where Cost represents the project cost model, and Complexity represents the project complexity model. The coefficients... , as well as The weighting coefficients of the model can be set according to user preferences. For example, when a project requires ecological optimization and engineering feasibility, they can be assigned weights accordingly. as well as Larger value.

[0074] Furthermore, by adjusting the implementation details of the proposed design scheme through the engineering cost model and engineering complexity model in the multi-objective optimization model, and by combining the EI model to evaluate the comprehensive impact of the adjusted proposed design scheme on the ecological environment, an optimized design scheme can be obtained, thereby determining the best design scheme for the road alignment and wind turbine platform site selection within the wind farm.

[0075] Therefore, by using engineering cost models and engineering complexity models, the implementation details of the proposed design scheme can be micro-controlled, and the impact on the ecological environment can be comprehensively assessed by combining the comprehensive environmental impact index model. Then, by solving the multi-objective optimization model, the optimized design scheme can be obtained, thus realizing the trade-off between the micro-design of the project and ecological protection.

[0076] In one possible implementation, multiple environmental indicators include potential soil erosion, area of ​​permanently exposed slopes, vegetation disturbance and fragmentation index, geological hazard risk value, hydrological connectivity disruption index, and habitat fragmentation and isolation index. The method also includes:

[0077] Multiple environmental indicators are quantified in a unified manner, and a weighted calculation is performed using the analytic hierarchy process to obtain a comprehensive environmental impact index model.

[0078] Analysis using a GIS platform yields values ​​for various indicators. For instance, by employing models such as the Modified Universal Soil Loss Equation (RUSLE) and incorporating slope cover management factors and supporting practice factors as key optimization variables, potential soil erosion can be calculated. By quantifying the degree to which roads and platforms disrupt or converge natural runoff paths, a hydrological connectivity disruption index can be obtained. Based on landscape ecology principles, the degree of fragmentation and impact on core habitat patches can be calculated, resulting in a habitat fragmentation and isolation index.

[0079] Then, each of the multiple environmental indicators is normalized (converted to the [0-1] interval) to achieve a unified dimension for the multiple environmental indicators. Finally, the analytic hierarchy process or other multi-criteria decision-making methods are used to determine the environmental indicators. weight This weight reflects the sensitivity of the local ecological environment to various environmental indicators, and the EI model is finally obtained through weighted calculation. Specifically, it can be expressed by the following formula:

[0080]

[0081] For example, indicators such as soil erosion, exposed area, hydrological damage, and habitat fragmentation can be assigned higher weights to reflect the project's comprehensive attention to multiple environmental factors. These weights can be adjusted within the range of 0.05 to 0.7 based on the project's environmental priorities and regional ecological sensitivity.

[0082] Therefore, by using the analytic hierarchy process (AHP) to analyze multiple environmental indicators and constructing a comprehensive environmental impact assessment model, the impact of the proposed design scheme on the ecological environment can be comprehensively and accurately evaluated, thereby providing guidance for the implementation details of the engineering design.

[0083] In one possible implementation, S103 includes:

[0084] A1: The non-dominated sorting genetic algorithm is used to iteratively solve the multi-objective optimization model to obtain the Pareto optimal solution set.

[0085] A2: Based on the Pareto optimal solution set, the optimized design scheme is obtained.

[0086] Specifically, a multi-objective optimization model, such as a non-dominated sorting genetic algorithm, is used for iterative solution. In each iteration, the engineering cost, engineering complexity, and EI model are calculated for the candidate solutions until the model converges to a stable Pareto optimal front, yielding the Pareto optimal solution set. The tuning parameters in this model include population size, number of iterations, crossover probability, and mutation probability.

[0087] The Pareto optimal solution set refers to a set of optimal solutions (i.e., a set of solutions that cannot improve the objective of one model without lowering the objective of another model), and then an optimal design scheme can be obtained by selecting an outcome from the Pareto optimal solution set.

[0088] Therefore, based on the inherent advantages of the non-dominated sorting genetic algorithm, there is no need to design the weights of multiple models in the multi-objective optimization model. It can perform objective sorting, avoid decision-maker bias, and make decisions more reliable, thus effectively improving decision-making efficiency.

[0089] In one possible implementation, A2 includes:

[0090] The design scheme corresponding to the lowest score of the integrated environmental impact index model in the Pareto optimal solution set is taken as the optimal design scheme; or...

[0091] The design scheme that achieves cost-complexity-ecological balance in the Pareto optimal solution set is taken as the optimal design scheme.

[0092] Therefore, selecting the design scheme with the lowest EI model score as the optimal design scheme can maximize the protection of the ecological environment, and selecting the design scheme that achieves cost-complexity-ecological balance as the optimal design scheme can achieve a balance between cost, complexity, and ecology. In this way, design schemes can be selected based on different needs.

[0093] In one possible implementation, the method further includes:

[0094] B1: Input the data information from the construction process based on the optimized design scheme into the comprehensive environmental impact index model to obtain the evaluation results.

[0095] B2: If the assessment result exceeds the preset risk threshold, an alarm will be issued.

[0096] Specifically, the optimized design scheme will be imported into the construction management system to continuously monitor actual data during construction. This data will be used as input for the EI model for dynamic calculation and real-time early warning. When the monitored EI value exceeds the preset risk threshold, the system will immediately issue an early warning, guiding the construction team to adjust soil and water conservation measures and project progress in a timely manner.

[0097] Therefore, by inputting real data information from construction based on optimized design schemes into GIS, the total impact on the ecological environment can be assessed in real time, avoiding errors in the early assessment and enabling precise control over the actual construction process.

[0098] Compared with related technologies, the engineering design optimization method provided in this application focuses on solving the problems of multi-objective optimization design of wind turbine platforms and on-site roads, quantitative control of soil and water conservation, and dynamic management of ecological risks in the entire site during the construction of wind farms in high mountains and hills. It can couple the micro-engineering design with quantitative environmental indicators to achieve optimization and management of wind farm construction with low ecological disturbance and high compliance, and has the following advantages:

[0099] (1) It solves the problem of disconnect between ecological protection and engineering design: The EI model quantitatively couples micro-engineering parameters (such as road slope and earthwork volume) with macro-environmental indicators, providing direct and operable ecological constraint targets for road and platform design.

[0100] (2) Achieved multi-objective quantitative trade-offs: For the first time, the EI index was used as the core constraint, which achieved comprehensive and fair quantification and optimization of economic costs, ecological risks and engineering feasibility, ensuring the ecological friendliness and engineering feasibility of the scheme.

[0101] (3) Improved project compliance and stability: It can identify and avoid high-risk areas in advance, reduce the risk of geological disasters and soil erosion from the source, and can be applied to dynamic early warning and management during the construction phase, which greatly improves the environmental compliance and long-term engineering stability of wind power projects.

[0102] Based on the above embodiments, this application provides an optimized design system for wind farm roads and wind turbine platforms, with reference to... Figure 2 The diagram shown is a schematic of an optimization design system for wind farm roads and wind turbine platforms provided in an embodiment of this application. The system 200 includes an acquisition unit 201, a construction unit 202, and an optimization unit 203.

[0103] The acquisition of engineering data and proposed design schemes, wherein the engineering data is used to identify environmental information at the engineering area;

[0104] Based on the engineering data and the proposed design scheme, a multi-objective optimization model is constructed. The multi-objective optimization model includes an engineering cost model, a comprehensive environmental impact index model, and an engineering complexity model. The comprehensive environmental impact index model is used to evaluate the comprehensive impact of multiple environmental indicators on the ecological environment.

[0105] The multi-objective optimization model is solved to obtain the optimized design scheme.

[0106] Therefore, by using engineering cost models and engineering complexity models, the implementation details of the proposed design scheme can be micro-controlled, and the impact on the ecological environment can be comprehensively assessed by combining the comprehensive environmental impact index model. Then, by solving the multi-objective optimization model, the optimized design scheme can be obtained, thus realizing the trade-off between the micro-design of the project and ecological protection.

[0107] In one possible implementation, the multiple environmental indicators include potential soil erosion, area of ​​permanently exposed slopes, vegetation disturbance and fragmentation index, geological hazard risk value, hydrological connectivity disruption index, and habitat fragmentation and isolation index. The system also includes a computing unit.

[0108] The calculation unit is used to quantify multiple environmental indicators in a unified manner and perform weighted calculations using the analytic hierarchy process to obtain the comprehensive environmental impact index model.

[0109] Therefore, by using the analytic hierarchy process (AHP) to analyze multiple environmental indicators and constructing a comprehensive environmental impact assessment model, the impact of the proposed design scheme on the ecological environment can be comprehensively and accurately evaluated, thereby providing guidance for the implementation details of the engineering design.

[0110] In one possible implementation, the optimization unit is used to:

[0111] The multi-objective optimization model is iteratively solved using a non-dominated sorting genetic algorithm to obtain the Pareto optimal solution set;

[0112] Based on the Pareto optimal solution set, an optimized design scheme is obtained.

[0113] Therefore, based on the inherent advantages of the non-dominated sorting genetic algorithm, there is no need to design the weights of multiple models in the multi-objective optimization model. It can perform objective sorting, avoid decision-maker bias, and make decisions more reliable, thus effectively improving decision-making efficiency.

[0114] In one possible implementation, the optimization unit is used to:

[0115] The design scheme corresponding to the lowest score of the integrated environmental impact index model in the Pareto optimal solution set is taken as the optimal design scheme; or...

[0116] The design scheme that achieves cost-complexity-ecological balance in the Pareto optimal solution set is taken as the optimized design scheme.

[0117] Therefore, selecting the design scheme with the lowest EI model score as the optimal design scheme can maximize the protection of the ecological environment, and selecting the design scheme that achieves cost-complexity-ecological balance as the optimal design scheme can achieve a balance between cost, complexity, and ecology. In this way, design schemes can be selected based on different needs.

[0118] In one possible implementation, the proposed design includes the alignment, slope, and cross-section of roads within the wind farm, as well as the location and slope design of the wind turbine platform.

[0119] Therefore, a comprehensive and accurate evaluation can be conducted on the proposed design scheme with detailed implementation details.

[0120] In one possible implementation, the system further includes an evaluation unit and an alarm unit:

[0121] The evaluation unit is used to input data information from the construction process based on the optimized design scheme into the comprehensive environmental impact index model to obtain the evaluation results.

[0122] The alarm unit is used to issue an alarm if the evaluation result exceeds a preset risk threshold.

[0123] Therefore, by inputting real data information from construction based on optimized design schemes into GIS, the total impact on the ecological environment can be assessed in real time, avoiding errors in the early assessment and enabling precise control over the actual construction process.

[0124] Based on the above embodiments, this application provides a computer device, which includes a processor and a memory:

[0125] The memory is used to store computer programs;

[0126] The processor is used to execute the above-mentioned optimized design method for wind farm roads and wind turbine platforms according to the computer program.

[0127] Based on the above embodiments, this application provides a computer-readable storage medium for storing a computer program, which, when executed by a computer device, implements the above-described optimized design method for wind farm roads and wind turbine platforms.

[0128] Based on the above embodiments, this application provides a computer program product including a computer program, which, when run on a computer device, causes the computer device to execute the above-mentioned optimization design method for wind farm roads and wind turbine platforms.

[0129] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems or apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and relevant parts can be referred to the method section.

[0130] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An optimized design method for wind farm roads and wind turbine platforms, characterized in that, The method includes: Acquire engineering data and proposed design schemes. The engineering data is used to identify environmental information in the engineering area, and the proposed design schemes include the alignment, slope, and cross-section of roads within the wind farm, as well as the location and slope design of wind turbine platforms. Based on the engineering data and the proposed design scheme, a multi-objective optimization model is constructed. The multi-objective optimization model includes an engineering cost model, a comprehensive environmental impact index model, and an engineering complexity model. The comprehensive environmental impact index model is used to evaluate the comprehensive impact of multiple environmental indicators on the ecological environment. The multiple environmental indicators are determined based on the proposed design scheme and are used to identify the engineering data after the proposed design scheme is implemented. The engineering complexity model includes the number of curves per unit length and the earthwork volume fluctuation rate. The multiple environmental indicators include potential soil and water loss, permanent exposed slope area, vegetation disturbance and fragmentation index, geological disaster risk value, hydrological connectivity destruction index, and biological habitat fragmentation and isolation index. The comprehensive environmental impact index model is calculated in the following manner: The potential soil and water loss is calculated using a modified general soil loss equation model, and the cover management factor and supporting practice factor of the slope design are the key optimization variables of the modified general soil loss equation model. The hydrological connectivity disruption index is obtained by quantifying the degree to which the roads and wind turbine platforms interrupt or converge natural runoff paths. The various environmental indicators are uniformly quantified and weighted using the analytic hierarchy process to obtain the comprehensive environmental impact index model. The multi-objective optimization model is solved to obtain the optimized design scheme.

2. The method according to claim 1, characterized in that, Solving the multi-objective optimization model to obtain the optimized design scheme includes: The multi-objective optimization model is iteratively solved using a non-dominated sorting genetic algorithm to obtain the Pareto optimal solution set; Based on the Pareto optimal solution set, an optimized design scheme is obtained.

3. The method according to claim 2, characterized in that, The optimized design scheme obtained based on the Pareto optimal solution set includes: The design scheme corresponding to the lowest score of the integrated environmental impact index model in the Pareto optimal solution set is taken as the optimal design scheme; or... The design scheme that achieves cost-complexity-ecological balance in the Pareto optimal solution set is taken as the optimized design scheme.

4. The method according to claim 1, characterized in that, The method further includes: The data information from the construction process based on the optimized design scheme is input into the comprehensive environmental impact index model to obtain the evaluation results; If the assessment result exceeds the preset risk threshold, an alarm will be issued.

5. An optimized design system for wind farm roads and wind turbine platforms, characterized in that, The system includes an acquisition unit, a construction unit, a calculation unit, and an optimization unit: The acquisition unit is used to acquire engineering data and proposed design schemes. The engineering data is used to identify environmental information in the engineering area, and the proposed design schemes include the alignment, slope, and cross-section of roads inside the wind farm, as well as the location and slope design of wind turbine platforms. The construction unit is used to construct a multi-objective optimization model based on the engineering data and the proposed design scheme. The multi-objective optimization model includes an engineering cost model, a comprehensive environmental impact index model, and an engineering complexity model. The comprehensive environmental impact index model is used to evaluate the comprehensive impact of multiple environmental indicators on the ecological environment. The multiple environmental indicators are determined based on the proposed design scheme and are used to identify the engineering data after the proposed design scheme is implemented. The engineering complexity model includes the number of curves per unit length and the earthwork volume fluctuation rate. The multiple environmental indicators include potential soil erosion, permanent exposed slope area, vegetation disturbance and fragmentation index, geological disaster risk value, hydrological connectivity destruction index, and biological habitat fragmentation and isolation index. The computing unit is used for: The potential soil and water loss is calculated using a modified general soil loss equation model, and the cover management factor and supporting practice factor of the slope design are the key optimization variables of the modified general soil loss equation model. The hydrological connectivity disruption index is obtained by quantifying the degree to which the roads and wind turbine platforms interrupt or converge natural runoff paths. The various environmental indicators are uniformly quantified and weighted using the analytic hierarchy process to obtain the comprehensive environmental impact index model. The optimization unit is used to solve the multi-objective optimization model to obtain an optimized design scheme.

6. A computer device, characterized in that, The computer device includes a processor and memory: The memory is used to store computer programs; The processor is configured to perform the method according to any one of claims 1-4 according to the computer program.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program that, when executed by a computer device, performs the method described in any one of claims 1-4.

8. A computer program product comprising a computer program, characterized in that, When it is run on a computer device, it causes the computer device to perform the method described in any one of claims 1-4.

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