An ultra-high altitude wind power foundation dynamic stability evaluation method, device and storage medium

Abstract

The application provides a kind of super high altitude wind power foundation dynamic stability evaluation method, equipment and storage medium, method includes: collecting topographic data, historical meteorological data, wind power foundation material data and geological data;Terrain model, climate model, aging model and geological model are constructed;Terrain model, climate model, aging model and geological model are coupled to obtain wind power foundation structure dynamic simulation model;Simulation analysis is carried out using wind power foundation structure dynamic simulation model, the physical data of foundation structure under extreme working condition is calculated, and the stability of wind power foundation is evaluated based on physical data and aging trend.The simulation model coupled by multiple physical fields is constructed, which not only covers complex factors such as terrain, climate, material aging and geological conditions, but also can accurately calculate the physical data of wind power foundation under extreme working condition, so as to realize the comprehensive evaluation of wind power foundation dynamic stability, and improve the accuracy of evaluation result.

Description

Technical Field

[0001] This invention relates to the field of wind power foundation assessment technology, and in particular to a method, equipment and storage medium for dynamic stability assessment of ultra-high altitude wind power foundations. Background Technology

[0002] Wind power, as a clean and renewable energy source, is playing an increasingly important role in the global energy structure. However, with the continuous development of wind power technology and the expansion of its application, especially in the construction of wind farms in ultra-high altitude areas (such as above 4,000 meters), numerous technical challenges are faced. Ultra-high altitude areas, with their unique climatic conditions (such as low temperatures, strong winds, low air pressure, and thin air) and complex topography (such as steep ridges and complex geological structures), place higher demands on the dynamic stability of wind power foundations.

[0003] Existing methods for assessing the stability of wind power foundations are mostly designed based on low-altitude or flat terrain conditions, making it difficult to fully consider the special environmental factors in ultra-high-altitude areas. This results in certain limitations and inaccuracies in the application of existing assessment methods in ultra-high-altitude areas, leading to inaccurate assessment results. Summary of the Invention

[0004] This invention aims to at least solve the technical problem of inaccurate evaluation results in the prior art, and innovatively proposes a method, equipment and storage medium for dynamic stability evaluation of ultra-high altitude wind power foundations.

[0005] To achieve the above-mentioned objectives of this invention, this invention provides a method for dynamic stability assessment of ultra-high altitude wind power foundations, the method comprising:

[0006] S1. Collect topographic data, historical meteorological data, wind power foundation material data, and geological data, including seismic data;

[0007] S2. Based on the terrain data, historical meteorological data, wind power foundation material data and geological data, respectively construct a terrain model, a climate model, an aging model and a geological model. The aging model is used to predict the aging trend of wind power foundation materials, and the climate model is used to predict future climate data.

[0008] S3. Couple the terrain model, climate model, aging model and geological model using multiphysics to obtain a dynamic simulation model of the wind power foundation structure.

[0009] S4. Perform simulation analysis using the dynamic simulation model of the wind power foundation structure, calculate the physical data of the foundation structure under extreme working conditions, and conduct a stability assessment of the wind power foundation based on the physical data and the aging trend.

[0010] As an optional embodiment of the present invention, optionally, obtaining the dynamic simulation model of the wind power foundation structure in step S3 includes:

[0011] S301. Standardize the data format of the terrain model, climate model, aging model and geological model, and unify the input and output interfaces;

[0012] S302. The data from the terrain model, climate model, aging model and geological model are fused to obtain a multiphysics simulation dataset.

[0013] S303. Using a multiphysics simulation platform, import the multiphysics simulation dataset, set the physical field parameters and boundary conditions, and obtain a dynamic simulation model of the wind power foundation structure.

[0014] S304. Verify the dynamic simulation model of the wind power foundation structure, and optimize the dynamic simulation model of the wind power foundation structure based on the verification results.

[0015] As an optional embodiment of the present invention, optionally, calculating the physical data of the infrastructure under extreme operating conditions in step S4 includes:

[0016] S401. Calculate the stress and displacement of the foundation structure under extreme working conditions;

[0017] S402. Using the basic structure data, calculate the overturning force and the sliding force respectively.

[0018] As an optional embodiment of the present invention, the stability assessment of the wind power foundation based on the physical data and the aging trend in step S4 may include:

[0019] S403. Convert the aging trend into an aging factor;

[0020] S404. Based on aging factors, stress, displacement, overturning force and sliding force, the dynamic stability of wind power foundations is quantitatively scored using a stability assessment algorithm to obtain a stability score.

[0021] S405. Set a stability score threshold and determine whether the stability score is greater than the threshold. If so, determine that the wind power foundation has a dynamic stability risk under extreme operating conditions.

[0022] As an optional embodiment of the present invention, the expression of the stability evaluation algorithm is optionally:

[0023]

[0024] Where p represents the stability score, σ represents the stress under extreme conditions, and σ maxRepresents the maximum stress under extreme conditions, α, β, γ, and All represent weighting factors. This represents displacement under extreme conditions. f represents the maximum displacement under extreme conditions, and f represents the overturning resistance under extreme conditions. max F represents the maximum anti-overturning force under extreme conditions, and F represents the anti-slip force under extreme conditions. max τ represents the maximum anti-skid force under extreme conditions, and τ represents the aging factor.

[0025] As an optional embodiment of the present invention, the expression for calculating the overturning resistance force in step S402 is optionally:

[0026] f=∫ A q(x,y)×(x×cosθ+y×sinθ)dA

[0027] Where f represents the overturning resistance under extreme conditions, A represents the area of ​​the foundation bottom, q(x,y) represents the soil pressure at point (x,y), and θ represents the angle between the line connecting the center of moment and point (x,y) and the horizontal direction.

[0028] As an optional embodiment of the present invention, the expression for calculating the anti-slip force in step S402 is optionally:

[0029]

[0030] Where F represents the anti-slip force under extreme conditions, Indicates the dynamic friction enhancement factor. Let A represent the coefficient of kinetic friction, A represent the area at the bottom of the foundation, and q(x,y) represent the soil pressure at point (x,y).

[0031] As an optional embodiment of the present invention, optionally, constructing the aging model in step S2 includes:

[0032] S201. Obtain environmental data and load data of wind power foundations;

[0033] S202. Construct a wind power foundation structure model based on the wind power foundation material data and load data;

[0034] S203. Based on the environmental data and wind power foundation material data, establish a Weibull distribution model;

[0035] S204. The wind power foundation structure model and the Weibull distribution model are standardized and merged in sequence to obtain the aging model.

[0036] The beneficial effects of this invention lie in its construction of a multi-physics coupled simulation model. This model not only encompasses complex factors such as topography, climate, material aging, and geological conditions, but also enables precise calculation of the physical data of wind power foundations under extreme operating conditions. This allows for a comprehensive assessment of the dynamic stability of wind power foundations, improving the accuracy and reliability of the assessment results. Furthermore, this invention provides early warning of potential stability risks to wind power foundations in ultra-high altitude areas, offering a scientific basis for the design, construction, and operation of wind farms. Simultaneously, through continuous optimization of the simulation model and assessment algorithm, this invention can adapt to different types of wind power foundations and the specific conditions of ultra-high altitude areas, ensuring the broad applicability and accuracy of the assessment results.

[0037] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0038] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0039] Figure 1 This is a flowchart of a dynamic stability assessment method for ultra-high altitude wind power foundations according to the present invention. Detailed Implementation

[0040] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0041] Example 1

[0042] like Figure 1 As shown, a method for dynamic stability assessment of ultra-high altitude wind power foundations is provided, the method comprising:

[0043] S1. Collect topographic data, historical meteorological data, wind power foundation material data, and geological data, including seismic data;

[0044] It should be noted that in step S1, when collecting terrain data, this embodiment uses high-precision UAV aerial photography technology combined with ground surveying equipment to ensure comprehensive capture and accurate description of complex terrain. The UAV flies in ultra-high altitude areas, utilizing its onboard high-definition camera and multispectral sensor to capture subtle changes in the terrain, including slope, landform features, and potential landslide risk areas. Simultaneously, the ground surveying team uses GPS positioning systems and total stations to conduct on-site measurements of key areas, ensuring the accuracy and completeness of the terrain data. When collecting historical meteorological data, this embodiment pays particular attention to meteorological factors closely related to the stability assessment of wind power foundations, such as extreme wind speed, wind direction, temperature, humidity, and the frequency and intensity of extreme weather events (such as blizzards and hail). This data comes from long-term accumulated observations at local meteorological stations and is combined with meteorological model predictions, providing a reliable basis for assessing the performance of wind power foundations under extreme climatic conditions. The collection of wind power foundation material data focuses on the physical and mechanical properties, durability, and aging characteristics of the materials under different environmental conditions. This embodiment collaborated closely with material suppliers to obtain detailed technical specifications for the materials used in the wind turbine foundation and conducted necessary material performance tests. Simultaneously, this embodiment collected aging test data on the materials under different temperature, humidity, and ultraviolet radiation conditions, providing strong support for constructing an accurate aging model. Geological data collection is one of the key steps in assessing the stability of wind turbine foundations. In addition to seismic data, this embodiment also collected detailed information on soil type, soil layer thickness, groundwater level, rock properties, and potential geological hazards (such as landslides, earthquakes, and debris flows). This data was obtained through geological exploration, drilling, and in-situ testing, providing important evidence for analyzing the interaction between the wind turbine foundation and the foundation soil. This embodiment, by comprehensively collecting topographic data, historical meteorological data, wind turbine foundation material data, and geological data, laid a solid foundation for the dynamic stability assessment of ultra-high altitude wind turbine foundations. This data not only covers various aspects of the environment in which the wind turbine foundation is located but also provides the necessary input conditions for subsequent simulation model construction, simulation analysis, and stability assessment.

[0045] S2. Based on the terrain data, historical meteorological data, wind power foundation material data and geological data, respectively construct a terrain model, a climate model, an aging model and a geological model. The aging model is used to predict the aging trend of wind power foundation materials, and the climate model is used to predict future climate data.

[0046] It should be noted that in constructing the terrain model in step S2, this embodiment employs advanced Geographic Information System (GIS) technology to perform three-dimensional modeling of the collected terrain data, accurately reproducing the complex terrain features of ultra-high altitude areas. This model not only includes the undulations of the land surface but also takes into account the microstructure of the terrain, such as gullies and rock distribution, providing accurate terrain references for the design and installation of wind power foundations. Simultaneously, the combination of the terrain model and the climate model can simulate wind field changes under different climatic conditions, providing an important basis for assessing the operational stability of wind power foundations.

[0047] This embodiment constructs a climate model based on meteorological data and historical climate trends, employing statistical methods and climate modeling algorithms, such as time series analysis, regression analysis, or machine learning algorithms, to predict key climate parameters such as wind speed, wind direction, temperature, and humidity over a future period. Specifically, the model has been optimized and adjusted to address extreme weather phenomena in ultra-high-altitude regions, such as strong winds, low temperatures, and blizzards, to improve prediction accuracy. The climate model construction not only considers seasonal variations but also incorporates the possibility of abrupt climate changes and extreme events, providing comprehensive data support for the performance evaluation of wind power foundations under extreme climate conditions. This embodiment fully utilizes historical meteorological data and the predictive capabilities of meteorological models. Through statistical analysis of historical data, this embodiment identifies climate patterns unique to ultra-high-altitude regions, such as the frequency, intensity, and distribution of extreme weather events. Subsequently, combined with advanced numerical weather prediction models, this embodiment predicts the climate conditions of the region over a future period, including key parameters such as wind speed, wind direction, temperature, and humidity, providing timely and accurate climate data support for the dynamic stability assessment of wind power foundations.

[0048] The construction of an aging model is a crucial step in assessing the long-term stability of wind turbine foundations. This embodiment uses a Weibull distribution model to simulate the aging process of wind turbine foundation materials based on material and load data. This model fully considers the aging characteristics of materials under different environmental conditions, such as the impact of temperature, humidity, and ultraviolet radiation on material performance. By standardizing and integrating the wind turbine foundation structure model and the Weibull distribution model, this embodiment obtains an aging model that can accurately predict the aging trend of wind turbine foundation materials. This model provides a scientific basis for assessing the stability of wind turbine foundations during long-term use.

[0049] The geological model construction focuses on analyzing the interaction between the wind turbine foundation and the foundation soil. This embodiment, based on geological data, constructs a detailed geological model including soil type, soil layer thickness, groundwater level, and rock properties. By simulating the foundation stress under different geological conditions, this embodiment evaluates the stability performance of the wind turbine foundation under various operating conditions. Simultaneously, the geological model also considers potential geological hazard risks, such as landslides and debris flows, providing crucial protection for the safe operation of the wind farm. This embodiment constructs a multi-physics coupled simulation model by comprehensively collecting and deeply analyzing data on topography, climate, materials, and geology. This model can accurately calculate the physical data of the wind turbine foundation under extreme operating conditions, achieving a comprehensive assessment of the dynamic stability of the wind turbine foundation. Through continuous optimization of the simulation model and evaluation algorithm, this invention can adapt to the specific conditions of different wind turbine foundation types and ultra-high altitude areas, providing a scientific basis and strong support for the design, construction, and operation of wind farms.

[0050] S3. Couple the terrain model, climate model, aging model and geological model using multiphysics to obtain a dynamic simulation model of the wind power foundation structure.

[0051] It should be noted that in step S3, when performing multiphysics coupling, this embodiment employs numerical simulation technology to tightly integrate the four major physical fields—topography, climate, aging, and geology—within a unified simulation framework. This process not only requires seamless data exchange between the various physical field models but also ensures that the interactions between the physical fields during the simulation accurately reflect the real-world situation.

[0052] First, the terrain model provides accurate spatial coordinates and terrain features for the simulation, enabling the layout and installation of wind turbine foundations to be based on real terrain. The climate model, on the other hand, dynamically adjusts parameters such as wind speed, wind direction, temperature, and humidity in the simulation environment based on future climate forecasts to simulate the operating status of wind turbine foundations under different climatic conditions.

[0053] The aging model predicts the aging trend of wind power foundation materials during long-term use based on the performance degradation law of the materials. This model not only considers the aging of materials under normal operating conditions, but also incorporates the accelerating effect of extreme climatic conditions on the aging process, making the simulation results closer to reality.

[0054] The geological model assesses the stability of wind turbine foundations under different geological conditions by simulating the mechanical properties and geological structure of the foundation soil. This model considers not only the static properties of soil and rock but also the impact of dynamic loads such as earthquakes on the stability of wind turbine foundations, providing an important guarantee for the safe operation of wind turbine foundations.

[0055] In the multiphysics coupling process, this embodiment also employs an efficient data exchange and synchronization mechanism to ensure that data between various physics models can be updated and shared in real time. Simultaneously, by optimizing simulation algorithms and parallel computing techniques, this embodiment significantly improves the efficiency and accuracy of simulation calculations, providing strong support for the dynamic stability assessment of wind power foundations.

[0056] Ultimately, the dynamic simulation model of wind power foundation structure obtained through multiphysics coupling can comprehensively reflect the dynamic response characteristics of wind power foundations under ultra-high altitude and extreme climate conditions. This dynamic simulation model not only provides a scientific basis for the design, construction, and operation of wind farms, but also offers important reference for the innovation and development of wind power technology.

[0057] S4. Perform simulation analysis using the dynamic simulation model of the wind power foundation structure, calculate the physical data of the foundation structure under extreme working conditions, and conduct a stability assessment of the wind power foundation based on the physical data and the aging trend.

[0058] It should be noted that in step S4, this embodiment employs simulation analysis technology, using a dynamic simulation model of the wind power foundation structure as the core to perform detailed simulation calculations. Specifically, this embodiment first sets a series of extreme conditions as simulation inputs based on the actual operating conditions of the wind farm, including but not limited to simulations of extreme wind speeds, strong wind shear, extreme low temperatures, and natural disasters such as earthquakes. These input conditions are carefully designed to comprehensively test the wind power foundation's ability to withstand and maintain stability under ultra-high altitude and extreme climatic conditions.

[0059] During the simulation, physical data such as stress, displacement, vibration damage, fatigue damage, overturning force, and anti-slip force of the wind turbine foundation structure under extreme conditions are calculated. These data not only reflect the immediate response of the wind turbine foundation under extreme conditions but also reveal potential problems in its long-term operation. By comparing the simulation results with preset safety standards, this embodiment can objectively assess the stability of the wind turbine foundation and identify potential risk points.

[0060] Based on the physical data obtained from simulation analysis, this embodiment further combines the aging trend of wind turbine foundation materials predicted by the aging model to comprehensively evaluate the stability of the wind turbine foundation. This evaluation process not only considers the immediate response of the wind turbine foundation under extreme conditions but also covers its performance evolution during long-term service, providing a more comprehensive and long-term perspective for the safe operation of wind farms. Specifically, this embodiment evaluates the stability level of the wind turbine foundation under extreme conditions by comparing key indicators such as stress distribution, deformation, and potential failure modes in the simulation results. Simultaneously, by combining the data from the aging model, it can also predict the performance change trend of the wind turbine foundation over a period of time, providing a scientific basis for its maintenance and upgrading. This comprehensive evaluation method improves the accuracy of wind turbine foundation evaluation.

[0061] like Figure 1 As shown above, this embodiment first constructs a terrain model, a climate model, an aging model, and a geological model using terrain data, historical meteorological data, wind power foundation material data, and geological data, respectively. Then, these models are coupled using multiphysics to construct a highly refined dynamic simulation system for wind power foundation structures. This system can simulate the behavior of wind power foundations in complex and variable environments in real time, including the dynamic response under wind loads, the impact of temperature changes on material properties, the constraints of geological conditions on foundation stability, and the erosion of structural integrity by long-term aging. In the simulation analysis phase, this embodiment not only focuses on the immediate performance of wind power foundations under extreme conditions but also delves into their long-term performance evolution under these conditions. By simulating the physical response of wind power foundations at different time scales, this embodiment can predict their stability trends throughout their entire life cycle, thus providing more accurate guidance for the design, construction, and maintenance of wind farms. Furthermore, to further improve the accuracy and reliability of the assessment, this embodiment also introduces an adaptive optimization algorithm. This algorithm can automatically adjust the parameters and boundary conditions of the simulation model based on simulation results and real-time data feedback to ensure a high degree of consistency between the simulation process and actual conditions. Through this adaptive optimization mechanism, this embodiment can promptly identify and resolve potential problems, thereby further improving the prediction accuracy and practicality of the dynamic simulation model of wind power foundation structures.

[0062] As an optional embodiment of the present invention, optionally, obtaining the dynamic simulation model of the wind power foundation structure in step S3 includes:

[0063] S301. Standardize the data format of the terrain model, climate model, aging model and geological model, and unify the input and output interfaces;

[0064] It should be noted that in step S301, standardizing the data formats of each physics model (terrain model, climate model, aging model, and geological model) is crucial to ensure smooth multiphysics coupling and efficient operation of the simulation model. This step aims to eliminate compatibility issues caused by format differences between different data sources, ensuring unimpeded data flow between models. By establishing a unified data format standard, the data exchange process can be simplified, data processing efficiency improved, and errors caused by format conversion reduced. Furthermore, a unified input / output interface is also a key step in achieving multiphysics coupling. It ensures that each model follows the same specifications and protocols when receiving and outputting input and output data, thereby achieving seamless data integration and real-time sharing. In this way, data between different physics models can be rapidly transmitted and fed back, enabling the entire simulation system to respond to changes in external conditions in real time, improving the real-time performance and accuracy of the simulation.

[0065] S302. The data from the terrain model, climate model, aging model and geological model are fused to obtain a multiphysics simulation dataset.

[0066] It should be noted that in step S302, data fusion processing is the core step in constructing the dynamic simulation model of the wind power foundation structure. This embodiment uses data fusion technology to comprehensively analyze and integrate a large amount of data from the terrain model, climate model, aging model, and geological model, forming a complete, consistent, and highly refined multiphysics simulation dataset. This dataset not only contains the physical parameters of the wind power foundation under different environmental conditions but also reveals the interrelationships and variation patterns among these parameters, providing a solid foundation for subsequent simulation analysis.

[0067] In the data fusion process, the data from each model is first preprocessed, including data cleaning, denoising, and interpolation, to eliminate outliers and missing values ​​and improve data quality. Then, a multi-source data fusion algorithm is used to effectively integrate data from different fields such as topography, climate, aging, and geology, forming a multi-dimensional, multi-scale simulation dataset. This dataset not only covers the physical state of wind power foundations at different time and spatial scales but also reflects their dynamic response characteristics under different environmental conditions. Through data fusion processing, the multiphysics simulation dataset constructed in this embodiment has several significant advantages: First, comprehensiveness and consistency: the dataset covers all aspects of wind power foundations in complex and changing environments, ensuring the comprehensiveness and accuracy of the simulation analysis; second, high precision and high resolution: advanced algorithms and technologies enable refined data processing, improving the prediction accuracy and resolution of the dynamic simulation model of wind power foundation structures; third, real-time performance and dynamism: the dataset can reflect the physical state of wind power foundations under different environmental conditions in real time, providing timely and accurate monitoring and early warning for the safe operation of wind farms.

[0068] After obtaining the multiphysics simulation dataset, this embodiment inputs it into the dynamic simulation model of the wind power foundation structure for detailed simulation analysis and stability assessment. By simulating the physical response of the wind power foundation under different extreme conditions, its stability and durability in complex and variable environments are evaluated, providing a scientific basis and technical support for the design, construction, and operation of wind farms. Simultaneously, by combining the aging trend of wind power foundation materials predicted by the aging model, the long-term performance of the wind power foundation is predicted and assessed, providing an important reference for its maintenance and upgrading.

[0069] S303. Using a multiphysics simulation platform, import the multiphysics simulation dataset, set the physical field parameters and boundary conditions, and obtain a dynamic simulation model of the wind power foundation structure.

[0070] It should be noted that the use of the multiphysics simulation platform in step S303 ensures the accurate construction and operation of the dynamic simulation model of the wind power foundation structure. This platform integrates simulation technologies from multiple disciplines, including computational fluid dynamics and structural mechanics, and can simultaneously handle the interactions and influences of multiple physical fields. By importing the multiphysics simulation dataset obtained in step S302 into this platform, this embodiment can establish a highly realistic and detailed simulation environment for the wind power foundation structure. After importing the data, the key step is to set the physical field parameters and boundary conditions. These parameters and conditions directly affect the accuracy and reliability of the simulation results. Specifically, this embodiment requires precisely setting the parameters of physical fields such as wind load, temperature field, humidity field, and soil mechanical properties based on the actual working conditions and environmental conditions of the wind power foundation. Simultaneously, it is also necessary to clarify the interaction boundaries between the wind power foundation and the surrounding environment, such as the contact interface between the foundation and the soil, and the flow boundary between the wind turbine tower and the air. Through meticulous parameter adjustments and boundary condition settings, this embodiment ensures that the simulation model can realistically reflect the physical behavior of the wind power foundation in actual operation. After setting the physical field parameters and boundary conditions, the multiphysics simulation platform will automatically start the calculation process to perform dynamic simulation analysis of the wind power foundation structure. This process will comprehensively consider the combined effects of various factors such as terrain, climate, aging, and geology, simulating the physical response and performance evolution of the wind power foundation under different operating conditions. By monitoring the changes in various physical indicators and parameters during the simulation process in real time, it is possible to gain a deeper understanding of the key performance characteristics of the wind power foundation, such as stability, durability, and safety.

[0071] S304. Verify the dynamic simulation model of the wind power foundation structure, and optimize the dynamic simulation model of the wind power foundation structure based on the verification results.

[0072] It should be noted that in step S304, verification and optimization are crucial steps in ensuring the accuracy and reliability of the dynamic simulation model of wind power foundation structures. This embodiment comprehensively evaluates the predictive capability of the simulation model through a series of rigorous verification steps. The verification process includes, but is not limited to, comparative analysis with measured data, verification of simulation results under different operating conditions, and expert review. By comparing the simulation results with measured data, the prediction accuracy and error range of the simulation model can be intuitively evaluated. Simultaneously, by simulating the physical response of wind power foundations under different operating conditions, the applicability and stability of the simulation model under different conditions can be further verified. During the verification process, if prediction deviations or deficiencies are found in the simulation model, the causes will be analyzed promptly, and corresponding optimization measures will be taken. Optimization measures include adjusting physical field parameters, improving boundary condition settings, and optimizing simulation algorithms. Through continuous optimization of the simulation model, its prediction accuracy and reliability can be gradually improved, providing more accurate and scientific support for the design, construction, and operation of wind farms. Furthermore, the verification and optimization process also needs to fully consider the aging characteristics of wind power foundation materials. The aging model plays a vital role in predicting changes in the performance of wind power foundation materials. By incorporating aging models, the structural performance of wind turbine foundations at different aging stages can be predicted and evaluated, providing an important reference for the long-term operation and maintenance of wind farms. During the verification and optimization process, the impact of the aging model will be fully considered, and the simulation model will be adjusted and optimized accordingly to ensure that it accurately reflects the performance changes of wind turbine foundations during long-term use.

[0073] As an optional embodiment of the present invention, optionally, calculating the physical data of the infrastructure under extreme operating conditions in step S4 includes:

[0074] S401. Calculate the stress and displacement of the foundation structure under extreme working conditions;

[0075] It should be noted that in step S401, during the calculation process, it is first necessary to determine the specific parameters of the extreme working conditions, such as wind speed, wind direction, temperature, humidity, and seismic waves. These parameters will be used as input conditions and input into the dynamic simulation model of the wind power foundation structure. Subsequently, the model will perform detailed simulation calculations based on the multiphysics simulation dataset and preset physical field parameters and boundary conditions. When calculating stress and displacement, numerical analysis methods, such as the finite element method and the boundary element method, can be used. These methods can fully consider the geometry of the wind power foundation structure, boundary conditions, and the interactions between various physical fields, thereby obtaining high-precision calculation results. Through calculation, stress distribution diagrams and displacement contour maps of the wind power foundation structure under extreme working conditions can be obtained. These charts will intuitively show the stress situation of different parts of the foundation structure.

[0076] S402. Using the basic structure data, calculate the overturning force and the sliding force respectively.

[0077] It should be noted that in step S402, the overturning resistance refers to the wind turbine foundation's ability to resist overall overturning when subjected to external forces such as lateral wind loads; while the sliding resistance refers to the frictional force between the foundation and the soil, used to prevent the foundation from sliding horizontally. When calculating the overturning resistance, multiple factors must be considered, including wind load, the foundation's self-weight, and the soil's supporting force on the foundation. These factors will act collectively, affecting the overall stability of the wind turbine foundation. Through numerical calculation, the required overturning resistance of the wind turbine foundation under specific operating conditions can be accurately determined.

[0078] Similarly, when calculating anti-sliding force, it is crucial to focus on the physical and mechanical properties of the soil, such as the internal friction angle and cohesion. These parameters directly affect the magnitude of the frictional force between the foundation and the soil. Based on soil mechanics theory, and combined with the boundary conditions and soil parameters set in the simulation model, the anti-sliding force of the wind turbine foundation under extreme conditions can be calculated to assess its ability to prevent sliding.

[0079] In summary, through the calculations in steps S401 and S402, this embodiment obtained key physical data such as stress, displacement, overturning force, and sliding force of the wind turbine foundation under extreme operating conditions. This data will provide important reference for the design, construction, and operation of wind farms, helping to optimize the design scheme of wind turbine foundation structures and improve their stability and durability. At the same time, this data will also provide a scientific basis for the maintenance and upgrading of wind turbine foundations, ensuring the safe operation and long-term benefits of wind farms.

[0080] As an optional embodiment of the present invention, the stability assessment of the wind power foundation based on the physical data and the aging trend in step S4 may include:

[0081] S403. Convert the aging trend into an aging factor;

[0082] It should be noted that in step S403, the aging factor is a parameter used to quantify the performance degradation of wind turbine foundation materials over time. It comprehensively considers the aging mechanism of the material, environmental factors (such as temperature, humidity, and ultraviolet radiation), and the initial performance of the material. By converting the aging trend into an aging factor, the impact of aging over time can be incorporated into the stability assessment, thereby more accurately predicting the performance changes of the wind turbine foundation during future operation. Specifically, a mathematical model can be established based on existing aging experimental data or empirical formulas to relate the aging factor to aging time and environmental conditions. Then, the corresponding aging factor is calculated based on the actual operating environment and expected service life of the wind turbine foundation. This aging factor will serve as an important input parameter for evaluating the stability of the wind turbine foundation.

[0083] S404. Based on aging factors, stress, displacement, overturning force and sliding force, the dynamic stability of wind power foundations is quantitatively scored using a stability assessment algorithm to obtain a stability score.

[0084] S405. Set a stability score threshold and determine whether the stability score is greater than the threshold. If so, determine that the wind power foundation has a dynamic stability risk under extreme operating conditions.

[0085] It should be noted that the stability score threshold set in step S405 is based on a comprehensive consideration of engineering safety standards and industry experience. This threshold aims to ensure that the wind turbine foundation can maintain sufficient dynamic stability under extreme operating conditions, avoiding safety accidents caused by structural instability. By comprehensively analyzing the stress, displacement, overturning force, sliding force, and aging factors of the wind turbine foundation, the stability score obtained using the stability assessment algorithm can intuitively reflect the dynamic stability level of the wind turbine foundation under extreme operating conditions. If the stability score is greater than the set threshold, it indicates that the wind turbine foundation has a dynamic stability risk under the current conditions. At this time, corresponding measures should be taken in a timely manner to reduce the risk, such as optimizing the foundation structure design, strengthening the interaction between the foundation and the soil, and improving the anti-aging performance of the foundation materials. At the same time, the operating status of the wind turbine foundation also needs to be continuously monitored to ensure its safety under extreme operating conditions.

[0086] In summary, by conducting stability assessments of wind power foundations based on aging trends, physical data, and stability evaluation algorithms, potential dynamic stability risks can be identified and addressed in a timely manner, providing strong guarantees for the safe operation and long-term benefits of wind farms. Simultaneously, it also provides important reference data for the design, construction, and operation of wind power foundations.

[0087] As an optional embodiment of the present invention, the expression of the stability evaluation algorithm is optionally:

[0088]

[0089] Where p represents the stability score;

[0090] σ represents the stress under extreme conditions;

[0091] σ max This represents the maximum stress under extreme conditions;

[0092] α, β, γ and All represent weighting factors;

[0093] This represents displacement under extreme conditions;

[0094] This represents the maximum displacement under extreme conditions;

[0095] f represents the overturning resistance under extreme conditions;

[0096] f max This indicates the maximum resistance to overturning under extreme conditions;

[0097] F represents the anti-slip force under extreme conditions;

[0098] F max This indicates the maximum anti-skid force under extreme conditions;

[0099] τ represents the aging factor.

[0100] As an optional embodiment of the present invention, the expression for calculating the overturning resistance force in step S402 is optionally:

[0101] f=∫ A q(x,y)×(x×cosθ+y×sinθ)dA

[0102] Where f represents the overturning resistance under extreme conditions;

[0103] A represents the area of ​​the foundation base;

[0104] q(x,y) represents the soil pressure at point (x,y);

[0105] θ represents the angle between the line connecting the center of torque and point (x,y) and the horizontal direction.

[0106] As an optional embodiment of the present invention, the expression for calculating the anti-slip force in step S402 is optionally:

[0107]

[0108] Where F represents the anti-slip force under extreme conditions;

[0109] Indicates the dynamic friction enhancement factor;

[0110] A represents the coefficient of dynamic friction, and A represents the area of ​​the foundation base.

[0111] q(x,y) represents the soil pressure at point (x,y).

[0112] As an optional embodiment of the present invention, optionally, constructing the aging model in step S2 includes:

[0113] S201. Obtain environmental data and load data of wind power foundations;

[0114] S202. Construct a wind power foundation structure model based on the wind power foundation material data and load data;

[0115] S203. Based on the environmental data and wind power foundation material data, establish a Weibull distribution model;

[0116] S204. The wind power foundation structure model and the Weibull distribution model are standardized and merged in sequence to obtain the aging model.

[0117] It should be noted that the specific environmental conditions and load characteristics of the wind turbine foundation must be fully considered when constructing the aging model. Environmental data, such as temperature, humidity, and wind speed, have a significant impact on the aging process of wind turbine foundation materials. Furthermore, wind turbine foundations are subjected to various dynamic and static loads during operation, which are also important factors leading to material aging.

[0118] In step S201, accurate environmental data and wind power foundation load data are obtained through on-site monitoring or historical data collection. These data form the basis for building the model, and their accuracy and completeness directly affect the model's reliability and prediction accuracy.

[0119] In step S202, based on the material data (such as the physical and chemical properties of the materials) and load data of the wind turbine foundation, a structural model of the wind turbine foundation is constructed using finite element analysis or other structural analysis methods. This model can simulate the stress conditions of the wind turbine foundation under actual working conditions, providing a basis for subsequent aging analysis.

[0120] In step S203, the Weibull distribution model is used to describe the aging process of wind turbine foundation materials. The Weibull distribution is a reliability analysis model that can effectively reflect the aging trend of materials over time. At this stage, based on environmental data and wind turbine foundation material data, relevant parameters in the Weibull distribution model, such as shape parameters and scale parameters, need to be determined.

[0121] In step S204, the wind power foundation structure model and the Weibull distribution model are standardized to ensure consistency and comparability during the fusion process. Standardization includes steps such as dimensionless data conversion and normalization. After standardization, the two models are fused to obtain the aging model of the wind power foundation. This model comprehensively considers the structural characteristics and material aging process of the wind power foundation, providing an important basis for subsequent stability assessments.

[0122] Finally, it should be noted that the aging model requires extensive experimental verification and data analysis. By comparing and validating the model with operational data from actual wind power foundations, the model parameters and algorithms are continuously optimized and improved to enhance the predictive accuracy and reliability of the aging model. Furthermore, with the continuous development of wind power technology and the application of new materials, the aging model also needs constant updating and improvement to adapt to new technological demands and challenges.

[0123] Example 2

[0124] A computer device, comprising:

[0125] processor;

[0126] Memory used to store processor-executable instructions;

[0127] The processor is configured to implement a dynamic stability assessment method for ultra-high altitude wind power foundations in Embodiment 1 when executing the executable instructions.

[0128] It should be noted that the computer device includes a processor, a memory, and may also include one or more of a multimedia component, an input / output (I / O) interface, and a communication component.

[0129] The processor controls the overall operation of the computer device to complete all or part of the steps in the above-mentioned automated testing method for factory equipment based on big data.

[0130] Memory is used to store various types of data to support the operation of the computer device. This data may include, for example, instructions for any application or method used to operate on the computer device, as well as application-related data. Memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0131] The multimedia component may include a screen and an audio component, wherein the screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals; for example, the audio component may include a microphone for receiving external audio signals, the received audio signals may be further stored in memory or transmitted via a communication component; the audio component may also include at least one speaker for outputting audio signals.

[0132] I / O interfaces provide interfaces between the processor and other interface modules, such as keyboards, mice, buttons, etc.; these buttons can be virtual buttons or physical buttons.

[0133] The communication component is used for wired or wireless communication between the computer device and other devices; wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G or 5G, or one or more combinations thereof, and the corresponding communication component may include: Wi-Fi module, Bluetooth module, NFC module, mobile communication module.

[0134] As a preferred embodiment, the computer device may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the above-described automated testing method for factory equipment based on big data.

[0135] Example 3

[0136] A computer-readable storage medium comprising:

[0137] A memory on which computer programs are stored;

[0138] A processor is used to execute the program in the memory to implement a dynamic stability assessment method for ultra-high altitude wind power foundations in Embodiment 1.

[0139] It should be noted that the electronic device disclosed in this embodiment includes a processor and a memory for storing processor-executable instructions. The processor is configured to implement any of the aforementioned methods for dynamic stability assessment of ultra-high altitude wind power foundations when executing the executable instructions.

[0140] It should be noted here that the number of processors can be one or more. Furthermore, the electronic device in this embodiment may also include input devices and output devices. The processor, memory, input devices, and output devices can be connected via a bus or other means, without specific limitations herein.

[0141] As a computer-readable storage medium, the memory can be used to store software programs, computer-executable programs, and various modules, such as the program or module corresponding to the dynamic stability assessment method for ultra-high altitude wind power foundations in this disclosure. The processor executes various functional applications and data processing of the electronic device by running the software programs or modules stored in the memory.

[0142] Input devices can be used to receive input digital numbers or signals. These signals can be key signals related to user settings and function control of the device / terminal / server. Output devices can include display devices such as screens.

[0143] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for evaluating the dynamic stability of wind power foundations at ultra-high altitudes, characterized in that, The method includes: S1. Collect topographic data, historical meteorological data, wind power foundation material data, and geological data, including seismic data; S2. Based on the terrain data, historical meteorological data, wind power foundation material data and geological data, respectively construct a terrain model, a climate model, an aging model and a geological model. The aging model is used to predict the aging trend of wind power foundation materials, and the climate model is used to predict future climate data. S3. Couple the terrain model, climate model, aging model and geological model using multiphysics to obtain a dynamic simulation model of the wind power foundation structure. S4. Perform simulation analysis using the dynamic simulation model of the wind power foundation structure, calculate the physical data of the foundation structure under extreme working conditions, and conduct a stability assessment of the wind power foundation based on the physical data and the aging trend.

2. The method for dynamic stability assessment of ultra-high altitude wind power foundations as described in claim 1, characterized in that, The dynamic simulation model of the wind power foundation structure obtained in step S3 includes: S301. Standardize the data format of the terrain model, climate model, aging model and geological model, and unify the input and output interfaces; S302. The data from the terrain model, climate model, aging model and geological model are fused to obtain a multiphysics simulation dataset. S303. Using a multiphysics simulation platform, import the multiphysics simulation dataset, set the physical field parameters and boundary conditions, and obtain a dynamic simulation model of the wind power foundation structure. S304. Verify the dynamic simulation model of the wind power foundation structure, and optimize the dynamic simulation model of the wind power foundation structure based on the verification results.

3. The method for dynamic stability assessment of ultra-high altitude wind power foundations as described in claim 1, characterized in that, Step S4 involves calculating the physical data of the foundation under extreme conditions, including: S401. Calculate the stress and displacement of the foundation structure under extreme working conditions; S402. Using the basic structure data, calculate the overturning force and the sliding force respectively.

4. The method for dynamic stability assessment of ultra-high altitude wind power foundations as described in claim 3, characterized in that, Step S4, which involves conducting a stability assessment of the wind power foundation based on the physical data and the aging trend, includes: S403. Convert the aging trend into an aging factor; S404. Based on aging factors, stress, displacement, overturning force and sliding force, the dynamic stability of wind power foundations is quantitatively scored using a stability assessment algorithm to obtain a stability score. S405. Set a stability score threshold and determine whether the stability score is greater than the threshold. If so, determine that the wind power foundation has a dynamic stability risk under extreme operating conditions.

5. The method for evaluating the dynamic stability of ultra-high altitude wind power foundations as described in claim 4, characterized in that, The expression for the stability evaluation algorithm is: Where p represents the stability score, σ represents the stress under extreme conditions, and σ max Represents the maximum stress under extreme conditions, α, β, γ, and All represent weighting factors. This represents displacement under extreme conditions. f represents the maximum displacement under extreme conditions, and f represents the overturning resistance under extreme conditions. max F represents the maximum anti-overturning force under extreme conditions, and F represents the anti-slip force under extreme conditions. max τ represents the maximum anti-skid force under extreme conditions, and τ represents the aging factor.

6. The method for dynamic stability assessment of ultra-high altitude wind power foundations as described in claim 3, characterized in that, The expression for calculating the overturning resistance in step S402 is: f=∫ A q(x,y)×(x×cosθ+y×sinθ)dA Where f represents the overturning resistance under extreme conditions, A represents the area of ​​the foundation bottom, q(x,y) represents the soil pressure at point (x,y), and θ represents the angle between the line connecting the center of moment and point (x,y) and the horizontal direction.

7. The method for evaluating the dynamic stability of ultra-high altitude wind power foundations as described in claim 3, characterized in that, The expression for calculating the anti-skid force in step S402 is: Where F represents the anti-slip force under extreme conditions, Indicates the dynamic friction enhancement factor. Let A represent the coefficient of kinetic friction, A represent the area at the bottom of the foundation, and q(x,y) represent the soil pressure at point (x,y).

8. The method for evaluating the dynamic stability of ultra-high altitude wind power foundations as described in claim 1, characterized in that, The aging model is constructed in step S2, which includes: S201. Obtain environmental data and load data of wind power foundations; S202. Construct a wind power foundation structure model based on the wind power foundation material data and load data; S203. Based on the environmental data and wind power foundation material data, establish a Weibull distribution model; S204. The wind power foundation structure model and the Weibull distribution model are standardized and merged in sequence to obtain the aging model.

9. A computer device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to implement, when executing the executable instructions, a dynamic stability assessment method for ultra-high altitude wind power foundations as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, include: A memory on which computer programs are stored; A processor is configured to execute the program in the memory to implement a dynamic stability assessment method for ultra-high altitude wind power foundations according to any one of claims 1 to 8.

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