A vulnerability model construction method suitable for wind turbine tower structures

Abstract

The present invention relates to a method for constructing a vulnerability model suitable for a wind tower structure. The method includes the following steps: establishing a finite element model of the wind tower structure; judging the type of disaster that needs to be considered based on the geographical location and foundation form of the model; simulating the load history corresponding to the disaster that needs to be considered; defining the damage level of each component of the wind tower and the quantitative index corresponding to each damage level, and performing calculation and analysis on the quantitative index in the finite element numerical simulation; conducting nonlinear dynamic history analysis and incremental dynamic analysis based on the finite element model and the simulated load history; constructing a brittle model; determining the loss ratio probability distribution model corresponding to the performance level of each component of the wind tower; and establishing a vulnerability model based on the brittle model of each component of the wind tower and the loss ratio probability model or loss ratio constant. The present invention is directed to a method for assessing the vulnerability of a wind tower structure, filling the gap in the current technical field of catastrophic risk assessment of wind towers.

Description

Technical Field

[0001] The invention relates to a vulnerability model construction method applicable to a wind power structure. Background Art

[0002] With the adjustment of industrial structures and the increasing emphasis on environmental issues, wind power has rapidly developed in countries around the world, becoming the third largest energy source after thermal power and hydropower. Wind turbine towers are unique and specialized structures, often located in areas prone to earthquakes, typhoons, and tsunamis. Many wind farms are subject to high-intensity seismic, wind, and wave loads. Constructing a wind turbine tower vulnerability model can reflect the tower's resilience to risk, providing a path for improving wind power disaster prevention and mitigation capabilities and a reference for decision-making in disaster loss assessment.

[0003] Existing vulnerability modeling approaches primarily focus on other structures, such as buildings and bridges, but a systematic approach for wind turbine towers is lacking. Wind turbine towers require consideration of diverse load types, which significantly differ from the vulnerability modeling approaches used for other structures. Therefore, a vulnerability modeling approach specifically tailored for wind turbine structures is needed. Summary of the Invention

[0004] The purpose of the present invention is to overcome the problems existing in the prior art and provide a method for constructing a vulnerability model suitable for wind power structures. By distinguishing the geographical location and foundation form of the wind power tower, the risk of the wind power structure to different disasters is considered. After establishing a model for time-course analysis and IDA analysis, the component fragility model is fitted using maximum likelihood estimation. The cascade effect of damage and destruction of different components is considered through the rejection sampling algorithm. Based on the fragility model of each component of the wind power tower and the loss ratio probability distribution model or loss ratio constant, a vulnerability model is formed through two random simulation integrations, filling the technical gap in the current wind power tower catastrophic risk assessment method, providing a channel for improving the wind power disaster prevention and mitigation capabilities, and providing a decision-making reference for disaster loss assessment.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for constructing a vulnerability model for a wind power structure, comprising the following steps:

[0006] S1. Establish a finite element model of the wind tower structure;

[0007] S2. Determine the type of disaster that needs to be considered based on the geographical location and foundation form of the established wind turbine tower structure finite element model;

[0008] S3. Simulate and generate load time histories corresponding to the disaster types to be considered;

[0009] S4. Define the damage level of each component of the wind turbine tower and the corresponding quantitative indicators for each damage level, and perform calculation and analysis on the quantitative indicators in finite element numerical simulation;

[0010] S5. Based on the established finite element model of the wind turbine tower structure and the simulated load history, conduct nonlinear dynamic time history analysis and incremental dynamic analysis;

[0011] S6. Based on the results calculated in step S5, assuming that the probability of the wind tower exceeding the set safety level obeys a log-normal distribution, a brittle model is obtained by fitting using maximum likelihood estimation;

[0012]

[0013] Where, μ and β are the mean and standard deviation of the lognormal distribution corresponding to the brittle model, im Indicates the intensity of the load, N represents the total number of load cases for nonlinear dynamic time history analysis at each load intensity, a Indicates the number of operating conditions where structural damage exceeds the set safety level; m is the number of load intensities considered;

[0014] S7. Based on existing research and data accumulation, determine the loss ratio probability distribution model corresponding to the performance level of each component of the wind turbine tower or determine the loss ratio value based on expert experience;

[0015] S8. Construct the vulnerability model of each component and the vulnerability model of the entire wind turbine tower based on the loss ratio probability distribution model or loss ratio value of each component and the fragility curve of each component; discretize the load intensity value within the considered load intensity range, and perform at least one random simulation at each load intensity value; after completing multiple rounds of simulation calculations at each load intensity value, calculate the average value of the loss ratio of the multiple rounds of simulation results, and use the least squares method to fit the average value under all load intensity values to obtain the fragility curve.

[0016] Preferably, in step S1, FAST is used to establish a linear elastic numerical model of the wind turbine tower, and the force time history results of the tower top and blades in FAST are extracted. Subsequently, general finite element software is used to perform refined modeling of the blades, nacelle, tower, and foundation, and the extracted force time history of the tower top and blades is applied as an external force load in the refined model.

[0017] Preferably, in step S2, the disaster types that need to be considered for the onshore wind power structure are strong winds and earthquakes.

[0018] Preferably, in step S2, the offshore wind power structure needs to select the disaster type that needs to be considered according to its foundation form. For a fixed foundation form, strong winds, earthquakes, waves and tsunamis need to be considered; for a floating foundation form, strong winds, waves and tsunamis need to be considered.

[0019] Preferably, for load simulation corresponding to wind disasters: use the Kaimal spectrum to simulate the three-dimensional wind field based on the common sense three-way wind speed coupling model and the wind profile model, calculate the wind loads on wind turbine blades and towers by the free vortex wake method, and use the generated load history for dynamic time history analysis of the finite element model; for wave simulation: use the JONSWAP / Pierson-Moskowitz spectrum and random wave theory to simulate the wave history; for earthquake load simulation: determine the acceleration design response spectrum according to the site where the wind tower is located and compare it with the design specifications, and then select the earthquake acceleration history from the natural earthquake wave database based on the acceleration design response spectrum.

[0020] Preferably, in step S5, if wind speed is used as the main incremental external load in the incremental dynamic analysis, working condition decomposition needs to be performed for different wind speed ranges: when the wind speed is less than the typhoon starting wind speed, the normal wind speed model + normal turbulence model or the normal wind speed model + extreme turbulence model is considered; when the wind speed is greater than the typhoon starting wind speed, the typhoon model needs to be considered.

[0021] Preferably, in step S6, the structural failure probability is calculated based on the 10,000-year disaster event set and the obtained brittle model, and compared with the failure probability value specified in the design specification, so as to verify the validity of the obtained brittle model.

[0022] Preferably, in step S8, the two random simulations in each round under each load intensity value include: the first random simulation is to randomly simulate the damage state of each component based on the brittleness model of each component under each load intensity value; according to the damage state generated by the first random simulation, a second random simulation is performed based on the loss ratio probability model corresponding to the damage state to generate the loss ratio value under this random event.

[0023] Preferably, in step S8, when the loss ratio probability model is not available, the second simulation is not performed and the loss ratio value determined by expert experience is directly used.

[0024] Preferably, the finite element software is selected from OpenSees, Abaqus, Ansys or any one with equivalent computational simulation functions.

[0025] Compared with the prior art, the beneficial effects of the present invention are embodied in:

[0026] This invention details a method for assessing the vulnerability of wind tower structures, filling a gap in the current technical field of wind tower vulnerability assessment. In particular, in the construction of a vulnerability model, a vulnerability curve is generated through two random simulations to account for the uncertainty of wind tower damage. The rejection sampling algorithm is used to consider the cascading effects of damage to different components, providing a channel for improving wind power disaster prevention and mitigation capabilities and a decision-making reference for disaster loss assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a flow chart of the method of the present invention;

[0028] Figure 2 This is the structural parameter information of a 1.5MW wind power tower in an embodiment of the present invention;

[0029] Figure 3 The earthquake acceleration response spectrum and median spectrum selected in step 3 of the method of the present invention;

[0030] Figure 4 The fragility curve generated in step 6 of the method of the present invention (taking the tower as an example);

[0031] Figure 5 This is the fragility curve finally obtained in step 7 of the method of the present invention. DETAILED DESCRIPTION

[0032] To facilitate understanding of the present invention, the present invention is described in more detail below with reference to the accompanying drawings and specific embodiments. Preferred embodiments of the present invention are shown in the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in this specification. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the present disclosure.

[0033] Example 1 This example provides a method for constructing a vulnerability model for a wind tower structure. The process is as follows: Figure 1 As shown, the following steps are included:

[0034] S1. Use finite element software to establish a finite element model of the wind tower structure. Use FAST to establish a linear elastic finite element model of the wind tower, and use conventional finite element software to establish an elastic-plastic finite element model of the wind tower.

[0035] Conventional finite element software cannot account for blade aerodynamic effects, but can perform elastic-plastic analysis. FAST can account for blade aerodynamic effects, but only supports linear elastic solutions. Therefore, a nonlinear finite element model of the wind turbine tower was first established using conventional finite element software. Then, a linear elastic numerical model of the wind turbine tower was established using FAST. The force time history of the tower top and blades in FAST was extracted and applied to the established nonlinear finite element model of the wind turbine tower, resulting in a joint solution.

[0036] Finite element software options include OpenSees, Abaqus, and Ansys. This primarily involves detailed modeling of the blades, tower, and foundation. The nacelle can be simplified as a concentrated mass, and the base of the foundation can be considered rigidly or spring-connected to the ground, taking into account soil-structure interaction.

[0037] The established nonlinear finite element model of a wind turbine tower can be validated in two ways: 1) Dynamic characteristics: primarily comparing the consistency of modal periods. 2) Damage and failure characteristics under static or dynamic elastoplastic forces.

[0038] S2. Determine the type of disaster that needs to be considered based on the geographical location and foundation form of the nonlinear finite element model of the wind turbine tower established in step S1 above, so as to conduct a disaster risk analysis.

[0039] For onshore wind power, the disaster types considered are strong winds and earthquakes. For offshore wind power, the disaster types to consider are determined based on the type of foundation. For example, for a fixed foundation (nearshore), strong winds, earthquakes, waves, and tsunamis need to be considered; for a floating foundation (offshore), only strong winds, waves, and tsunamis generally need to be considered.

[0040] S3. Simulate and generate time histories of the load types that need to be considered.

[0041] For example, for wind load simulation, the Kaimal spectrum can be used to simulate the three-dimensional wind field based on the common sense three-dimensional wind speed coupling model and wind profile model. The wind loads on the wind turbine blades and tower are calculated using the free vortex wake method. The generated load time history is used for dynamic time history analysis of the finite element model, with the wind speed at hub height as the reference. For wave simulation, the JONSWAP / Pierson-Moskowitz spectrum and random wave theory are used to simulate wave time histories. For earthquake simulation, the acceleration design response spectrum is determined based on the site of the wind turbine tower and compared with the design code. The earthquake acceleration time history is then selected from the natural earthquake wave database based on the acceleration design response spectrum.

[0042] S4. Based on the existing research foundation and survey data, define the damage status of each component of the wind turbine tower, such as the tower, nacelle, blades, and foundation, determine the quantitative indicators of the corresponding status, and calculate and analyze the quantitative indicators in the finite element numerical simulation.

[0043] For example, the quantitative indicators of the tower are horizontal displacement, stress and deformation, which can be divided into four damage levels:

[0044] The tower top displacement of 0.5% of the tower height corresponds to damage state 1: basically intact;

[0045] The tower top displacement of 1.25% of the tower height corresponds to damage state 2: slight damage;

[0046] The stress of the tower exceeds the yield stress, corresponding to damage state 3: moderate damage;

[0047] The tower shows buckling deformation, corresponding to damage state 4: severe damage.

[0048] The quantitative indicator of the cabin is the absolute acceleration response at the cabin location, which can be divided into three damage levels:

[0049] 7.5m / s 2 The absolute acceleration response at the cabin corresponds to damage state 1: slight damage;

[0050] 10m / s 2 The absolute acceleration response at the cabin corresponds to damage state 2: moderate damage;

[0051] 12.5m / s 2 The absolute acceleration response at the cabin corresponds to damage state 3: severe damage;

[0052] The quantitative indicators of blades are the tip displacement response and the root stress response, which can be divided into three damage levels:

[0053] A tip displacement of 10% of the blade length corresponds to damage state 1: slight damage;

[0054] The tip displacement of 15% of the blade length corresponds to damage state 2: moderate damage;

[0055] When the blade root stress is greater than the yield stress or the blade tip displacement is large, resulting in collision with the tower, the corresponding damage state is 3: severe damage;

[0056] The quantitative indicators of the foundation are the relative displacement response of the top of the foundation relative to the bottom and the stress response of the bottom of the foundation, which can be divided into four damage levels:

[0057] The relative displacement response of the top of the foundation relative to the bottom is 0.5%, corresponding to damage state 1: basically intact;

[0058] The relative displacement response of the top of the foundation relative to the bottom is 1%, which corresponds to damage state 2: slight damage;

[0059] The force at the bottom of the base is greater than the ultimate bearing capacity, corresponding to damage state 3: moderate damage;

[0060] The relative displacement response of the top of the substrate relative to the bottom exceeds 5%, corresponding to damage state 4: severe damage.

[0061] The quantitative indicators corresponding to the damage status of the above components and the limit values corresponding to the quantitative indicators should be adjusted through refined structural modeling analysis based on the specific characteristics of the wind turbine tower (including but not limited to installed capacity, blade length, tower height, foundation form, and mechanical equipment in the nacelle).

[0062] S5. Based on the nonlinear finite element model of the wind turbine tower established in the above steps S1, S2, and S3 and the simulated load history, nonlinear dynamic history analysis (NHA) and incremental dynamic analysis (IDA) are carried out.

[0063] In an IDA analysis, if wind speed is the primary incremental external load, and the turbine operates normally within the cut-in and cut-out wind speed range, with the yaw system automatically aligning to the wind, the wind and wave loads are applied perpendicular to the rotor plane. When the wind speed exceeds the cut-out speed, the turbine shuts down and yaw locks. Two main wind and wave load directions are considered: 1) perpendicular to the rotor plane; 2) parallel to the rotor plane.

[0064] In addition, the operating conditions need to be decomposed for different wind speed ranges: when the wind speed is less than the typhoon's starting wind speed, the normal wind speed model + normal turbulence model or the normal wind speed model + extreme turbulence model should be considered; when the wind speed is greater than the typhoon's starting wind speed, the typhoon model should be considered.

[0065] S6. Based on the results calculated in step S5, assuming that the probability of the wind tower exceeding the set safety level (each level of damage state defined in step S4) follows a log-normal distribution, a brittleness model is fitted using maximum likelihood estimation, as shown in Formula 1:

[0066] (Formula 1)

[0067] In formula 1, μ and β are the mean and standard deviation of the lognormal distribution corresponding to the brittle model, im Indicates the intensity of the load (wind or earthquake), N represents the total number of load cases for nonlinear dynamic time history analysis at each load intensity, a Indicates the number of operating conditions where structural damage exceeds the set safety level; m is the number of load intensities considered, m The value range is 30-50.

[0068] Based on the 10,000-year disaster event set and the aforementioned brittleness model (Equation 1), the structural failure probability is calculated and compared with the failure probability value specified in the design code to verify the validity of the constructed brittleness model. Some design codes specify the failure probability of wind turbine towers. For example, ISO 2394-2015 requires annual failure probabilities for wind turbines under different damage states. When the calculated structural failure probability is close to the failure probability value specified in the design code (the ratio between the two is generally not less than 0.1 times and not more than 10 times), the constructed brittleness model is considered valid and reasonable.

[0069] S7. Based on existing research and accumulated data, determine or assume a loss ratio probability distribution model and corresponding parameters (such as mean and standard deviation) corresponding to the performance level of each wind tower component (tower, nacelle, blades, foundation). The loss ratio is defined as the ratio of the economic loss incurred due to earthquake damage to the wind tower components to the cost of renovation and reconstruction. The loss ratio probability distribution model should be determined by fitting or empirically obtaining actual historical disaster loss data. If actual historical disaster loss data is insufficient, the loss ratio probability model parameters should be assumed based on disaster loss data or construction cost data of engineering structures similar to wind towers.

[0070] When disaster loss data or project cost data are severely missing, the loss ratio probability distribution model cannot be obtained. A fixed loss ratio value should be determined based on expert experience to replace the loss ratio probability distribution model.

[0071] S8. Based on the loss ratio probability distribution model of each component and the fragility model of each component, a fragility model of each component and a fragility model of the entire wind turbine tower are constructed.

[0072] Discretize the load intensity (IM) within the considered range, for example, into 30-50 IM values, and perform two random simulations at each IM value. The first random simulation randomly simulates the damage state at each IM based on the brittleness model of each component. Based on the damage state generated in the first random simulation, a second random simulation is performed using the corresponding loss ratio probability model to generate the loss ratio for this random event. If the loss ratio probability model is unavailable, this simulation can be omitted and the loss ratio determined by expert experience can be used directly.

[0073] In the first random simulation, after simulating the damage states of the blades, nacelle, tower, and foundation of the wind turbine tower respectively, the rejection sampling algorithm should be used to consider the cascade effect of seismic damage to the above four components of the wind turbine tower. For example, when the damage state of the foundation is severe damage, the blades, nacelle, and tower are directly defined as severe damage; when the damage state of the tower is severe damage, the nacelle and blades are directly defined as severe damage; when the damage state of the nacelle is severe damage, the blades are directly defined as severe damage; when the damage state of the blade is severe damage due to collision with the tower, the damage state of the tower is increased by one level, for example, from simulated moderate damage to severe damage.

[0074] After completing 1000 rounds of simulation calculations at each IM (two random simulations per round), the average loss ratio of the 1000 simulation results was calculated, and the least squares method was used to fit the average value under 30-50 IM values to finally obtain the vulnerability curve.

[0075] Example 2 This example provides a specific application example of the method of the present invention.

[0076] In this embodiment, the wind turbine tower structure used is an existing Nordex S70, 1.5 MW, three-blade horizontal axis onshore wind turbine tower with a height of 65m. Its basic structural parameters are shown in Table 1. The wind turbine tower is welded from 22 thin-walled cylindrical structures. The outer diameter of the conical tower is 4035mm (base) to 2955mm (top), and the wall thickness is 25mm (base) to 10mm (top). Figure 2 shown.

[0077] Table 1 Wind tower structural parameters

[0078] type parameter type parameter Number of blades 3 Speed / (r / min) 10.6~19.0 Blade length 34 Hub height / m 65 Power / MW 1.5 Cabin mass / t 60 Cut-in wind speed / (m / s) 3.5 Blade mass / t 30 Cut-out wind speed (m / s) 25 Total mass / t 183.8

[0079] The above-mentioned method for constructing a vulnerability model of a wind turbine tower structure comprises the following steps:

[0080] S1. Use finite element software to establish a finite element model of the wind turbine tower structure.

[0081] OpenSees was used to establish an elastic-plastic finite element model of the wind turbine tower, and FAST was used to establish a linear elastic numerical model of the wind turbine tower. The time history of the blade forces at the top of the tower extracted from FAST was applied to the established nonlinear finite element model of the wind turbine tower, and a joint solution was obtained. The results were then compared with experimental modal results for verification.

[0082] S2. Based on the geographical location and foundation form of the wind tower structure finite element model established in the above steps, determine the type of load that needs to be considered for disaster risk analysis.

[0083] The onshore wind turbine tower has a pile foundation and is located in a relatively hard soil, so soil-structure interaction is ignored. The wind turbine tower is located in an earthquake-prone area, so the main load type considered in this embodiment is earthquake disasters.

[0084] S3. Simulate and generate earthquake load history.

[0085] The seismic inputs are 22 sets of far-field ground motions. All seismic motions are taken from larger magnitude earthquake events, with moment magnitudes between 6.5 and 7.5. The acceleration response spectra and median spectra of the 22 sets of seismic motion samples are shown in Figure 3 .

[0086] S4. Define damage levels, determine quantitative indicators of corresponding performance levels, and perform calculations and analysis of these indicators in finite element numerical simulations. Based on existing research foundations and survey data, define 3-4 damage states for each structural component.

[0087] S5. Based on the finite element model established in the above steps S1, S2, and S3 and the simulated load history, nonlinear dynamic history analysis (NHA) and incremental dynamic analysis (IDA) are carried out.

[0088] In the incremental dynamic analysis, the acceleration median response spectra of 22 groups of earthquake motions at the first cycle of the structural design are first scaled down to the intensity of the rare earthquake response spectrum, and the scaling factor is determined as Sa (𝑇1, MCE) / Ŝa ( T 1, GMs). Then, set the earthquake intensity increment to 20%. Sa ( T 1, MCE), the strength variation range in incremental dynamic analysis is 20% - 300% Sa ( T 1, MCE). 22 groups of time-history dynamic analyses of earthquake motions were performed at each earthquake motion intensity, for a total of 30 earthquake motion intensities. Therefore, in this embodiment, a total of 660 (22×30) time-history dynamic analyses were performed.

[0089] S6. Based on the results calculated in step S5 above, the brittleness model is fitted using maximum likelihood estimation. The resulting brittleness curve of the tower is as follows: Figure 4 shown.

[0090] S7. Based on the brittleness results obtained in step S6 above, determine the loss ratio probability distribution model corresponding to the performance level of each component of the wind tower (tower, nacelle, blades, foundation).

[0091] S8. Based on the loss ratio probability distribution model of each component and the fragility curve of each component, a fragility model of each component and a fragility model of the entire wind turbine tower are constructed.

[0092] For each of the 30 seismic intensities, two random simulations were performed. The first random simulation randomly simulated the damage state at each seismic intensity based on the brittleness model of each component. Based on the damage state generated in the first random simulation, a second random simulation was performed based on the corresponding loss ratio probability model to generate the loss ratio for that random event. In the first random simulation, after simulating the damage states of the wind tower's blades, nacelle, tower, and foundation, a rejection sampling algorithm was used to consider the cascading effects of seismic damage to the four components above the wind tower. After completing 1,000 simulations at each seismic intensity (two random simulations per round), the average loss ratio of the 1,000 simulation results was calculated, and the least squares method was used to fit the average values at the 30 seismic intensity values to obtain the fragility curve.

[0093] In this embodiment, a vulnerability model is constructed for a 1.5MW wind turbine tower according to the above process, and the vulnerability curve of the wind turbine tower structure under earthquake disasters is obtained, as shown in FIG. Figure 5 shown.

[0094] Wind turbine towers are subject to a wide variety of loads. Existing vulnerability models have primarily been developed for other structures, such as buildings and bridges, but a systematic approach for wind turbine towers has yet to be established. This paper details a vulnerability assessment method for wind turbine towers, filling a gap in the current field of catastrophic risk assessment for wind turbine towers. This approach provides a pathway for improving wind power disaster prevention and mitigation capabilities and offers a decision-making basis for disaster loss assessment.

[0095] The above description is only used to illustrate the technical solution of the present invention and is not intended to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in this field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A vulnerability model construction method applicable to wind power tower structures, characterized in that: The following steps are involved: S1. Establish a finite element model of the wind tower structure; S2. Determine the type of disaster that needs to be considered based on the geographical location and foundation form of the established wind turbine tower structure finite element model; S3. Simulate and generate load time histories corresponding to the disaster types to be considered; S4. Define the damage level of each component of the wind turbine tower and the corresponding quantitative indicators for each damage level, and perform calculation and analysis on the quantitative indicators in finite element numerical simulation; S5. Based on the established finite element model of the wind turbine tower structure and the simulated load history, conduct nonlinear dynamic time history analysis and incremental dynamic analysis; S6. Based on the result calculated in step S5, a brittleness model is obtained by fitting using maximum likelihood estimation; Where, μ and β are the mean and standard deviation of the lognormal distribution corresponding to the brittle model, im Indicates the intensity of the load, N represents the total number of load cases for nonlinear dynamic time history analysis at each load intensity, a Indicates the number of operating conditions where structural damage exceeds the set safety level; m is the number of load intensities considered; S7. Based on existing research and data accumulation, determine the loss ratio probability distribution model corresponding to the performance level of each component of the wind turbine tower or determine the loss ratio value based on expert experience; S8. Construct the vulnerability model of each component and the vulnerability model of the entire wind turbine tower based on the loss ratio probability distribution model or loss ratio value of each component and the fragility curve of each component; discretize the load intensity value within the considered load intensity range, and perform at least one random simulation at each load intensity value; after completing multiple rounds of simulation calculations at each load intensity value, calculate the average value of the loss ratio of the multiple rounds of simulation results, and use the least squares method to fit the average value under all load intensity values to obtain the fragility curve.

2. The vulnerability model construction method applicable to wind turbine tower structures according to claim 1, characterized in that: In step S1, FAST is used to establish a linear elastic numerical model of the wind turbine tower, and the force time history results of the tower top and blades in FAST are extracted. Subsequently, general finite element software is used to fine-tune modeling of the blades, nacelle, tower, and foundation, and the extracted force time history of the tower top and blades is applied as an external force load in the refined model.

3. The vulnerability model construction method applicable to wind turbine tower structures according to claim 1, characterized in that: In step S2, the disaster types that need to be considered for onshore wind power structures are strong winds and earthquakes.

4. The vulnerability model construction method applicable to wind turbine tower structures according to claim 1, characterized in that: In step S2, the offshore wind power structure needs to select the disaster type that needs to be considered according to its foundation form. For a fixed foundation form, strong winds, earthquakes, waves and tsunamis need to be considered; for a floating foundation form, strong winds, waves and tsunamis need to be considered.

5. The vulnerability model construction method applicable to wind power tower structures according to claim 3 or 4, characterized in that: In step S3, the load simulation corresponding to the wind disaster is as follows: the Kaimal spectrum is used to simulate the three-dimensional wind field based on the common sense three-way wind speed coupling model and the wind profile model, the wind loads on the wind turbine blades and tower are calculated by the free vortex wake method, and the generated load time history is used for the dynamic time history analysis of the finite element model; the wave load simulation is as follows: the wave time history simulation is performed using the JONSWAP / Pierson-Moskowitz spectrum and the random wave theory; the earthquake load simulation is as follows: the acceleration design response spectrum is determined according to the site where the wind turbine tower is located and compared with the design specifications, and then the earthquake acceleration time history is selected from the natural earthquake wave database based on the acceleration design response spectrum.

6. The vulnerability model construction method applicable to wind power tower structures according to claim 3 or 4, characterized in that: In step S5, if wind speed is used as the main incremental external load in the IDA analysis, working condition decomposition needs to be performed for different wind speed ranges: when the wind speed is less than the typhoon starting wind speed, the normal wind speed model + normal turbulence model or the normal wind speed model + extreme turbulence model is considered; when the wind speed is greater than the typhoon starting wind speed, the typhoon model needs to be considered.

7. The vulnerability model construction method applicable to wind power tower structures according to claim 1, characterized in that: In step S6, the structural failure probability is calculated based on the 10,000-year disaster event set and the obtained brittle model, and compared with the failure probability value specified in the design code, thereby verifying the validity of the obtained brittle model.

8. The method for constructing a vulnerability model for a wind turbine tower structure according to claim 1, characterized in that: In step S8, two random simulations are performed in each round under each load intensity value, including: a first random simulation is to randomly simulate the damage state of each component based on the brittleness model of each component under each load intensity value; based on the damage state generated by the first random simulation, a second random simulation is performed based on the loss ratio probability model corresponding to the damage state to generate the loss ratio value under this random event.

9. The method for constructing a vulnerability model for a wind turbine tower structure according to claim 8, characterized in that: In step S8, when the loss ratio probability distribution model is not available, the second simulation is not performed and the loss ratio value determined by expert experience is directly used.

10. A method for constructing a vulnerability model for a wind turbine tower structure according to any one of claims 1 to 9, characterized in that: The finite element software is selected from OpenSees, Abaqus, Ansys or any one with equivalent computational simulation functions.

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