Evaluation method for economic loss caused by bird strike on fan blades of offshore wind turbine

Abstract

The invention discloses a method for evaluating economic loss caused by the fact that a bird strikes fan blades of an offshore wind turbine, and relates to the technical field of economic loss evaluation.The method comprises the steps that whether a flying bird flight path meets a fan blade area of the offshore wind turbine or not is judged, if yes, flying bird impact evaluation is carried out, and if not, the risk index that the bird strikes the fan blades is set to be 0; the bird impact evaluation stage specifically comprises the steps of judging whether the bird can effectively and actively avoid, if so, endowing the risk index of the bird to impact the fan blade to be 0, and if not, calculating the probability of the bird crossing different linear velocity regions of the working surface of the fan blade; determining the time required by the bird to pass through the fan blades of the fan; determining the rotation angle of the fan blades when the bird passes through the fan blades; calculating the probability that the bird passes through the fan blades and impacts the fan blades; calculating a risk index of the bird impacting the fan blades; and analyzing the economic loss amount of the bird impacting the fan blades of the fan. The method has the advantage that the economic loss possibly caused by the bird strike event can be scientifically and quantitatively evaluated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of economic loss assessment, in particular to a method for assessing economic loss caused by bird strike on fan blades of offshore wind turbines. BACKGROUND

[0002] As an important clean energy form, offshore wind power has multiple advantages. First, the ocean has abundant wind energy resources, and the development potential is huge, which can effectively alleviate the energy shortage. Second, offshore wind turbines do not occupy land resources, and the wind speed is stable and the wind direction is concentrated, so the power generation efficiency is high. In addition, with the advancement of technology, the cost of offshore wind turbines is gradually decreasing, and large-scale development can help achieve energy structure transformation, reduce carbon emissions, and promote sustainable development, which is of great significance to energy security and climate change.

[0003] However, the vast sea area is often an important migration channel or habitat for birds, which significantly increases the risk of collision between the fan blades of offshore wind turbines and flying birds. The fan blades rotate at high speed (linear speed can reach about 160 meters per second), even if the birds flying at low altitude (usually at a height of 10-60 meters from the ground) collide with the fan blades, they will also be seriously injured or even killed due to high-speed impact. Bird strike incidents not only directly cause damage to the fan blades, resulting in high repair or replacement costs, but also cause power generation loss due to the shutdown of offshore wind turbines, which seriously affects the economic benefits of the wind farm. Although existing technologies attempt to reduce the frequency of collisions by using bird repelling devices or adjusting the operation strategy of offshore wind turbines, the application effect of these methods in the complex environment of the sea is limited, and there is generally a lack of means for fine and quantitative assessment of the direct and indirect economic losses that may be caused by bird strike incidents. SUMMARY

[0004] To solve the above technical problems, a kind of is provided, the technical scheme solves the above-mentioned problems.

[0005] To achieve the above purpose, the technical scheme adopted by the present application is: A method for assessing economic loss caused by bird strike on fan blades of offshore wind turbines, comprising: Real-time acquisition of the flight state of flying birds in the fan blade monitoring area of the offshore wind turbine, based on the flight state of the flying birds to determine whether the flying birds fly on the path of the offshore wind turbine fan blade area, if yes, then enter the bird strike assessment, if not, then assign the risk index of the bird strike on the fan blade to 0; The bird strike assessment stage is specifically: Based on the flight speed of the bird and the distance between the bird and the offshore wind turbine fan blade when the bird discovers the fan blade, determine whether the bird will effectively avoid, if yes, then assign the risk index of the bird strike on the fan blade to 0, if not, then calculate the probability of the bird crossing the different linear velocity zones of the fan blade working surface; determining a time required for the bird to pass through the fan blade based on the bird length and the bird speed; determining a rotation angle of the fan blade when the bird passes through the fan blade based on the fan rotation speed and the time required for the bird to pass through the fan blade; calculating a probability of the bird hitting the fan blade when passing through the fan blade; calculating a risk index of the bird hitting the fan blade based on the probability of the bird hitting the fan blade when passing through the fan blade and the probability of the bird passing through different linear velocity zones of the fan blade working surface; analyzing an economic loss amount of the bird hitting the fan blade based on the risk index of the bird hitting the fan blade.

[0006] Preferably, the determining whether the bird will effectively and actively avoid the offshore wind turbine blade based on the flight speed of the bird and the distance between the bird and the offshore wind turbine blade when the bird discovers the offshore wind turbine blade is specifically: calculating a time for the bird to reach the offshore wind turbine blade based on the flight speed of the bird and the distance between the bird and the offshore wind turbine blade when the bird discovers the offshore wind turbine blade, and if the time for the bird to reach the offshore wind turbine blade is greater than the avoidance interval, it is determined that the bird will effectively and actively avoid, and if not, it is determined that the bird will not effectively and actively avoid.

[0007] Preferably, the calculating the probability of the bird passing through different linear velocity zones of the fan blade working surface is specifically: setting a linear velocity zoning radius based on the radius of the offshore wind turbine blade, 、 and wherein, a circular area surrounded by the low linear velocity zone, a circular ring area surrounded by the medium linear velocity zone, a circular ring area surrounded by the high linear velocity zone; defining a random event of the bird passing through the fan blade working surface as a uniform distribution of the high, medium, and low linear velocity zone areas of the fan blade, the probability of the bird passing through different linear velocity zones of the fan blade working surface is specifically calculated as: ; wherein, is the low linear velocity zone radius, is the medium linear velocity zone radius, is the high linear velocity zone radius, is the probability of the bird passing through the low linear velocity zone of the fan blade working surface, is the probability of the bird passing through the medium linear velocity zone of the fan blade working surface, is the probability of the bird passing through the high linear velocity zone of the fan blade working surface.

[0008] Preferably, the rotation angle of the fan blade when the bird passes through the fan blade is determined based on the rotation speed of the fan and the time required for the bird to pass through the fan blade, and the rotation angle of the fan blade when the bird passes through the fan blade is specifically: The angle between the widest part of the fan blade surface and the center of the fan circle in the low linear velocity zone, the medium linear velocity zone and the high linear velocity zone is respectively taken as the low linear velocity zone windward surface angle, the medium linear velocity zone windward surface angle and the high linear velocity zone windward surface angle; Then the specific calculation method of the rotation angle of the fan blade when the bird passes through the fan blade is: ; Wherein, is the rotation angle of the low linear velocity zone when the bird passes through the fan blade, is the rotation angle of the medium linear velocity zone when the bird passes through the fan blade, is the rotation angle of the high linear velocity zone when the bird passes through the fan blade, is the low linear velocity zone windward surface angle, is the medium linear velocity zone windward surface angle, is the high linear velocity zone windward surface angle, is the wind speed, is the fan tip speed ratio, and t is the time required for the bird to pass through the fan blade.

[0009] Preferably, the calculation of the probability of the bird passing through the fan blade and hitting the fan blade specifically includes: Based on the rotation angle of the fan blade in each linear velocity zone when the bird passes through the fan blade, the probability of the bird hitting the fan blade when passing through each linear velocity zone is obtained by comparing with 2π.

[0010] Preferably, the calculation of the risk index of the bird hitting the fan blade based on the probability of the bird hitting the fan blade when passing through the fan blade and the probability of the bird passing through the fan blade in different linear velocity zones specifically includes: The product of the probability of the bird hitting the fan blade when passing through each linear velocity zone and the probability of the bird passing through the fan blade in different linear velocity zones is taken as the risk index of the bird hitting the fan blade in different linear velocity zones.

[0011] Preferably, the analysis of the economic loss of the bird hitting the fan blade based on the risk index of the bird hitting the fan blade specifically includes: Based on the bird survey data, the species, size and flight height of the resident birds and migrant birds in the wind farm area are determined, the bird species with flight height within the working height of the fan blade are statistically evaluated according to the size, and the volume influence coefficient of different size bird species is determined; Based on the historical maintenance log of the fan blade, the economic loss of the bird hitting the fan blade in different linear velocity zones is determined; The economic loss estimation of the bird flying through the fan blade of the wind turbine once is obtained by comprehensively calculating the volume influence coefficient of the bird, the economic loss of the bird hitting the fan blade of the wind turbine in different linear velocity zones, and the risk index of the bird hitting the fan blade of the wind turbine in different linear velocity zones. The annual economic loss estimation of the bird of each type to the fan blade of the wind turbine is obtained by combining the economic loss of the bird of each type hitting the fan blade of the wind turbine once. The annual economic loss of the bird hitting the fan blade of the wind turbine is obtained by summing up the annual economic loss estimation of the bird of all types to the fan blade of the wind turbine.

[0012] Preferably, the types, volumes and flight heights of the resident birds and migrant birds in the wind farm area are determined based on the bird situation investigation data, the bird species with the flight height in the working height range of the fan blade are statistically evaluated according to the body size, and the specific calculation process of the volume influence coefficient of different volume bird species is as follows: ; wherein, is the volume influence coefficient of the economic loss caused by the bird hitting the low-speed working surface of the fan blade of the wind turbine, is the volume influence coefficient of the economic loss caused by the bird hitting the medium-speed working surface of the fan blade of the wind turbine, is the volume influence coefficient of the economic loss caused by the bird hitting the high-speed working surface of the fan blade of the wind turbine, is the average volume of the bird, is the average density of the bird, is the maximum wind speed in the wind farm area, is the maximum volume of the bird, is the maximum density of the bird.

[0013] Preferably, the specific calculation process of the economic loss estimation of the bird flying through the fan blade of the wind turbine once is as follows: ; is the economic loss estimation of the bird flying through the fan blade of the wind turbine once, is the risk index of the bird hitting the low linear velocity zone of the fan blade of the wind turbine, is the risk index of the bird hitting the medium linear velocity zone of the fan blade of the wind turbine, is the risk index of the bird hitting the high linear velocity zone of the fan blade of the wind turbine, is the economic loss of the bird hitting the low linear velocity zone of the fan blade of the wind turbine, is the economic loss of the bird hitting the medium linear velocity zone of the fan blade of the wind turbine, The economic loss amount of the high linear velocity zone of the fan blade of the wind turbine hit by the bird.

[0014] Preferably, the annual economic loss estimation amount of each kind of bird to the fan blade of the wind turbine is evaluated by combining the number of each kind of bird in the wind farm area with the economic loss estimation amount of each kind of bird hitting the fan blade of the wind turbine once. According to the set proportion, the digital twin model of the wind farm area is constructed; Based on the number of each kind of bird in the wind farm area, a corresponding number of trajectory points are set in the digital twin model of the wind farm area, and the movement logic of the trajectory points is set based on the flight habit of each kind of bird. Simulate 1 year in the digital twin model of the wind farm area, observe the number of times that each kind of bird corresponding to the trajectory point passes through the fan blade of the wind turbine in the wind farm area, and record it as the simulation evaluation number; Multiply the simulation evaluation number by the economic loss estimation amount of the bird passing through the fan blade of the wind turbine once to obtain the annual economic loss estimation amount of the corresponding kind of bird to the fan blade of the wind turbine.

[0015] Compared with the prior art, the beneficial effects of the present application are: The evaluation method of the economic loss caused by the bird hitting the fan blade of the offshore wind turbine can realize scientific and quantitative evaluation of the economic loss caused by the bird hitting event. The method can accurately calculate the risk index of the bird hitting the fan blade by real-time monitoring and analyzing the flight path of the bird and the potential meeting relationship with the fan blade, comprehensively considering the active avoidance possibility of the bird, the probability of the bird passing through different linear velocity zones of the fan blade, and the dynamic matching relationship between the bird passing time and the rotation angle of the fan blade. Furthermore, the method integrates the volume characteristics of the bird, the historical maintenance cost data and the detailed bird population information, converts the probabilistic risk index into a specific single impact economic loss estimation amount, and simulates the annual activity trajectory of different birds by means of the digital twin model of the wind farm area, and finally accurately predicts the total annual economic loss of the bird hitting in a specific wind farm area. This comprehensive and detailed evaluation process effectively overcomes the challenges of difficult monitoring in offshore environment, high maintenance cost and difficult calculation of power generation loss, and provides objective and reliable data basis and risk management basis for the wind farm to develop economic and efficient anti-bird measures, optimize insurance strategy and support investment decision-making, which significantly improves the economy and sustainability of offshore wind power project operation. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 The evaluation method flow chart of the economic loss caused by the bird hitting the fan blade of the offshore wind turbine is provided.

[0017] Figure 2 The front parameter description diagram of the offshore wind turbine is provided.

[0018] Figure 3 A schematic diagram for side parameter of offshore wind turbine.

[0019] Figure 4 A flow chart of the method for evaluating the annual economic loss estimation of each kind of flying bird to the fan blade of the wind turbine in the present application. DETAILED DESCRIPTION

[0020] The following description is provided to enable those skilled in the art to implement the present application. The preferred embodiments in the following description are only examples and other obvious modifications can be made by those skilled in the art.

[0021] Reference Figure 1 As shown in the figure, a method for evaluating the economic loss caused by bird strike fan blade of offshore wind turbine, comprising: Real-time acquisition of the flight state of flying bird in the monitoring area of offshore wind turbine fan blade, based on the flight state of flying bird, judge whether the flying path of flying bird meets the offshore wind turbine fan blade area, if yes, enter the flying bird impact evaluation, if not, assign the risk index of flying bird impact fan blade to 0, in this step, if the flight activity height of flying bird is not in the offshore wind turbine fan blade area, it is considered that the flight path of flying bird will not meet the offshore wind turbine fan blade area, so there is no risk of impacting the offshore wind turbine fan blade; Reference Figures 2-3 As shown in the figure, the parameters used in the flying bird impact evaluation stage include: Wind speed v f , flying bird flight speed v bird , flying bird flight length l bird , distance D between flying bird and offshore wind turbine fan blade when flying bird discovers fan blade, flying bird flight height from sea level H, fan blade rotating area lower edge height from sea level h, fan blade rotating high linear velocity zone radius r3, fan blade rotating middle linear velocity zone radius r2, fan blade rotating low linear velocity zone radius r1, tip speed ratio λ, bird impact fan blade position probability p, flying bird crossing fan blade time t, fan blade windward surface angle θ, flying bird impact fan risk index β, bird species volume influence coefficient φ, economic loss amount ε of different regions of fan blade after bird strike; Specifically, the steps of flying bird impact evaluation stage are: Based on the flight speed of flying bird and the distance between flying bird and offshore wind turbine fan blade when flying bird discovers fan blade, judge whether flying bird will effectively avoid, if yes, assign the risk index of flying bird impact fan blade to 0, if not, calculate the probability of flying bird crossing different linear velocity zones of fan blade working surface, by analyzing the avoidance ability of flying bird in flight process, evaluate whether flying bird will impact offshore wind turbine fan blade due to difficult to avoid; Based on the length of the flying bird and the flying bird speed, the time required for the flying bird to pass through the fan blade of the wind turbine is determined, and the calculation formula is as follows: ; In the formula, l bird is the flying length of the flying bird, v bird is the flying speed of the flying bird, and L is the thickness of the fan blade.

[0022] Based on the rotating speed of the wind turbine and the time required for the flying bird to pass through the fan blade of the wind turbine, the rotating angle of the fan blade of the wind turbine when the flying bird passes through the fan blade of the wind turbine is determined. The probability of the flying bird colliding with the fan blade of the wind turbine when passing through the fan blade of the wind turbine is calculated. Based on the probability of the flying bird colliding with the fan blade of the wind turbine when passing through the fan blade of the wind turbine and the probability of the flying bird passing through the working surface of the fan blade in different linear velocity zones, the risk index of the flying bird colliding with the fan blade of the wind turbine is calculated. Based on the risk index of the flying bird colliding with the fan blade of the wind turbine, the economic loss amount of the flying bird colliding with the fan blade of the wind turbine is analyzed. Specifically, the steps of analyzing the economic loss amount of the flying bird colliding with the fan blade of the wind turbine are as follows: Based on the bird research data, the species, volume and flight height of the resident birds and migrant birds in the wind farm area are determined, the bird species with the flight height in the working height range of the fan blade are statistically evaluated according to the body size, and the volume influence coefficient of different volume bird species is determined. Based on the historical maintenance log of the fan blade of the wind turbine, the economic loss amount of the flying bird colliding with the fan blade of the wind turbine in different linear velocity zones is determined. Based on the volume influence coefficient of the flying bird, the economic loss amount of the flying bird colliding with the fan blade of the wind turbine in different linear velocity zones and the risk index of the flying bird colliding with the fan blade of the wind turbine in different linear velocity zones, the economic loss estimation amount of the flying bird passing through the fan blade of the wind turbine once is comprehensively calculated. Based on the number of each species of flying bird in the wind farm area and the economic loss amount of each species of flying bird colliding with the fan blade of the wind turbine once, the annual economic loss estimation amount of each species of flying bird to the fan blade of the wind turbine is evaluated. The annual economic loss amount of the flying bird colliding with the fan blade of the wind turbine is obtained by summarizing the annual economic loss estimation amount of all species of flying bird to the fan blade of the wind turbine.

[0023] The present scheme proposes an evaluation method for the economic loss caused by the bird strike fan blade of the offshore wind turbine, which has the following beneficial effects: From the perspective of risk assessment and management, the prediction can help the wind farm operator to plan in advance, reasonably arrange maintenance and repair, avoid high-risk period operation, reduce potential loss, communicate with the insurance company, reasonably determine the insurance limit and premium, ensure accident compensation, and reduce insurance cost.

[0024] In terms of optimizing operation strategy, the prediction helps the operator to choose shutdown during low wind speed or frequent bird activity period, reduces the risk of collision, and at the same time tries to reduce power generation loss, reasonably allocates operation and maintenance resources, and improves operation and maintenance efficiency.

[0025] Environmental protection and compliance, predict help operators comply with environmental regulations, reduce environmental disputes.

[0026] Technical improvement and innovation, predict to make operators and related technology companies invest resources in the development of anti-bird impact technology.

[0027] Economic decision support, predictions help investors assess the economic feasibility of projects, decide to invest or expand, and wind farm operators can also optimize layout and operating strategies to control costs and improve economic efficiency.

[0028] Specifically, the probability of flying birds crossing the different linear velocity zones of the fan working surface is calculated as follows: Based on the radius of the fan blade of the offshore wind turbine, the linear velocity partition radius is set, 、 and where, the circular area enclosed is the low linear velocity zone, the circular ring area is the medium linear velocity zone, and the circular ring area is the high linear velocity zone. The random event of flying birds crossing the fan working surface is defined as the uniform distribution of the areas of the high, medium and low linear velocity zones of the fan blade, and the specific calculation method of the probability of flying birds crossing the different linear velocity zones of the fan working surface is as follows: ; where, is the low linear velocity zone radius, is the medium linear velocity zone radius, is the high linear velocity zone radius, is the probability of flying birds crossing the low linear velocity zone of the fan working surface, is the probability of flying birds crossing the medium linear velocity zone of the fan working surface, is the probability of flying birds crossing the high linear velocity zone of the fan working surface.

[0029] The fan blade working surface is divided into low linear velocity zone, middle linear velocity zone and high linear velocity zone, and the probability of the flying bird crossing each zone is calculated according to the area proportion of the partition, so as to realize the fine modeling of the impact risk space distribution. This design fully considers the characteristics of the linear velocity gradient distribution in the actual rotation process of the fan blade, replaces the subjective experience assumption with the objective geometric area proportion, and significantly improves the scientificity and reliability of the impact position prediction. By establishing the mapping relationship between the partition probability and the flying bird motion characteristics, the key data foundation for subsequent dynamic calculation of the matching of the flying bird crossing time and the blade rotation angle is laid, and finally the quantitative evaluation of the difference of the potential damage in different regions is more in line with the actual physical process. This method effectively solves the error problem caused by the randomness of the impact position in the traditional evaluation, and makes the economic loss prediction model have stronger engineering guidance value.

[0030] Based on the fan rotating speed and the time required for the flying bird to pass through the fan blade, the rotation angle of the fan blade when the flying bird passes through the fan blade is determined as follows: The angles between the widest part of the fan blade surface in the low linear velocity zone, the middle linear velocity zone and the high linear velocity zone and the center of the fan are respectively taken as the low linear velocity zone windward surface angle, the middle linear velocity zone windward surface angle and the high linear velocity zone windward surface angle; The specific calculation method of the rotation angle of the fan blade when the flying bird passes through the fan blade is as follows: ; Wherein, is the rotation angle of the low linear velocity zone when the flying bird passes through the fan blade, is the rotation angle of the middle linear velocity zone when the flying bird passes through the fan blade, is the rotation angle of the high linear velocity zone when the flying bird passes through the fan blade, is the low linear velocity zone windward surface angle, is the middle linear velocity zone windward surface angle, is the high linear velocity zone windward surface angle, is the wind speed, is the blade tip speed ratio, and t is the time required for the flying bird to pass through the fan blade.

[0031] By establishing the quantitative mapping relationship between the flying bird crossing the fan blade time and the dynamic rotation angle of the fan, the spatio-temporal accuracy of bird strike risk prediction is significantly improved. The method innovatively introduces the unique windward face angle parameter in each linear velocity zone, combined with the fan tip speed ratio characteristic value of wind speed self-adaptive adjustment, to accurately calculate the actual rotation angle of the fan in low, medium and high different linear velocity zones during the flying bird crossing process. This dynamic coupling mechanism effectively solves the impact position deviation problem caused by ignoring the continuous rotation characteristics of the fan in the traditional static model, ensuring that the real matching relationship between the flying bird flight trajectory and the fan rotation position in the three-dimensional space can be accurately restored. This breakthrough enables the subsequent impact probability calculation to accurately reflect the differentiated impact of different rotating speed regions on the impact possibility in the actual working condition, providing key dynamic parameter support for the gradient evaluation of bird strike economic loss, and greatly enhancing the engineering applicability and prediction reliability of the entire evaluation method in complex wind field environment.

[0032] The probability of the flying bird crossing the fan blade impacting the fan blade includes: based on the flying bird crossing the fan blade, the rotation angle of the fan blade in each linear velocity zone is compared with 2π to obtain the probability of the flying bird impacting the fan blade when crossing each linear velocity zone.

[0033] By proportionally converting the actual rotation angle of the fan blade when the flying bird passes through each linear velocity zone into a complete circular angle, the complex dynamic impact event is converted into an intuitive probability problem. This design creatively converts the spatial displacement of the fan blade during the flying bird passing time into its "effective risk angle" exposed in the corresponding region, and then accurately quantifies the potential coverage probability of the blade to the flying bird in the rotation period through angle proportion. Based on the combination of physical laws and probability principles, this method effectively avoids the calculation complexity of simulating three-dimensional motion trajectories in traditional modeling, revealing the interaction mechanism between the flying bird and the rotating blade in the key space-time with a simple mathematical relationship. By calculating the probability in different regions and correlating the damage characteristics of different rotating speed regions, the subsequent economic loss evaluation can accurately reflect the loss gradient change caused by the difference in impact position, laying a core calculation foundation for building a multi-level quantitative risk model, and greatly improving the engineering implementation efficiency and actual prediction accuracy of the entire evaluation method.

[0034] Based on the probability of the flying bird crossing the fan blade impacting the fan blade and the probability of the flying bird crossing the fan blade working surface in different linear velocity zones, the risk index of the flying bird impacting the fan blade is calculated, which includes: The product of the probability of the flying bird impacting the fan blade when crossing each linear velocity zone and the probability of the flying bird crossing the fan blade working surface in different linear velocity zones is taken as the risk index of the flying bird impacting the fan blade in different linear velocity zones.

[0035] The dynamic characteristics and hazard level differences of the impact risk in the spatial distribution are accurately quantified by multiplying the probability of the flying bird crossing a certain linear velocity area with the probability of its impact in the area. This fusion design effectively breaks through the limitations of traditional single probability evaluation, not only reflecting the spatial possibility of the flying bird entering different fan working surfaces, but also capturing the temporal conditionality of the impact caused by the rotating position of the blades in the area when the flying bird passes through. Through this "regional distribution probability x regional dynamic impact probability" coupling model, the risk index calculated in each linear velocity area can scientifically represent the comprehensive risk intensity of the flying bird not only entering the area, but also being hit by the rotating fan blades when crossing the area. This core calculation method provides high-fidelity risk input data for subsequent fine assessment of damage modes and economic losses in different regions and levels, greatly improves the description ability and prediction accuracy of the bird strike risk of offshore wind turbines in actual operation, and effectively supports the development of more targeted safety protection and economic management strategies for wind farms.

[0036] Based on the bird survey data, the species, size, and flight height of the resident and migratory birds in the wind farm area are determined. The bird species with flight height within the working height of the fan blades are statistically evaluated according to the size to determine the volume influence coefficient of different size bird species. The specific calculation process is as follows: ; wherein, is the volume influence coefficient of the economic loss caused by the bird strike on the low-speed working surface of the fan blades, is the volume influence coefficient of the economic loss caused by the bird strike on the medium-speed working surface of the fan blades, is the volume influence coefficient of the economic loss caused by the bird strike on the high-speed working surface of the fan blades, is the average volume of the bird, is the average density of the bird, is the maximum wind speed in the wind farm area, is the maximum volume of the bird, is the maximum density of the bird.

[0037] Based on the volume influence coefficient of the bird, the economic loss caused by the bird strike on the fan blades in different linear velocity areas, and the risk index of the bird strike on the fan blades in different linear velocity areas, the economic loss estimation of the bird passing through the fan blades once is comprehensively calculated. The specific calculation process is as follows: ; is the economic loss estimation of the bird passing through the fan blades once, is the risk index of the bird strike on the low linear velocity area of the fan blades, is the risk index of the bird strike on the medium linear velocity area of the fan blades, a risk index of a flying bird hitting a high linear velocity zone of a fan blade of a wind turbine, an economic loss amount of a flying bird hitting a low linear velocity zone of a fan blade of a wind turbine, an economic loss amount of a flying bird hitting a middle linear velocity zone of a fan blade of a wind turbine, an economic loss amount of a flying bird hitting a high linear velocity zone of a fan blade of a wind turbine.

[0038] By triple coupling operation of the partition risk index, historical economic loss data and biological characteristic influence coefficient, multi-dimensional dynamic estimation of economic loss of a single bird strike event is realized. The method innovatively constructs a risk-loss three-dimensional correlation model of the flying bird passing process in the low, middle and high linear velocity zones: the impact possibility of the region is accurately quantified by using the partition risk index, the benchmark loss parameter is constructed by combining the historical maintenance cost of the same region, and the physical damage intensity of different birds is dynamically corrected by the volume influence coefficient, and finally the potential loss value of each region is fused in a weighted superposition manner. This design first realizes the four-dimensional quantification of the probability risk, i.e. whether it will hit, the mechanical characteristics, i.e. where to hit, the biological attributes, i.e. what kind of bird to hit, and the operation and maintenance data, i.e. the actual maintenance cost in a single event. It can not only reflect the extreme damage scenario of low probability but high loss in high-speed area, but also reflect the cumulative effect of high frequency but low damage in low-speed area, so that the estimation result is more in line with the real load characteristics and maintenance economy of the fan blade. Especially in the complex scene of large rare bird strikes in offshore wind farms, the model accurately captures the impact risk multiplication effect of large birds on the high-speed area of the blade tip through dynamic correction of the volume influence coefficient, avoiding underestimation of loss due to lack of historical data. This fine classification prediction capability provides an irreplaceable scientific basis for wind power operators to develop differentiated maintenance and spare parts strategies, determine the optimal insurance scheme, and evaluate the implementation priority of bird prevention measures, significantly improving the risk management efficiency and economic operation level of offshore wind power assets.

[0039] Referring to Figure 4 As shown in the figure, based on the number of flying birds of each species in the wind farm area and the economic loss amount of a single bird strike on the fan blade of a wind turbine, the annual economic loss estimation amount of each species of flying bird to the fan blade of a wind turbine includes: According to the set proportion, a digital twin model of the wind farm area is constructed; Based on the number of flying birds of each species in the wind farm area, a corresponding number of trajectory points are set in the digital twin model of the wind farm area, and the motion logic of the trajectory points is set based on the flight habits of each species of flying bird; Simulate 1 year in the digital twin model of the wind farm area, observe the number of times each species of flying bird passes through the fan blade of a wind turbine in the wind farm area, which is recorded as the simulation evaluation times; The annual economic loss estimation of the corresponding type of flying bird to the fan blade of the wind turbine is obtained by multiplying the simulation evaluation times and the economic loss estimation of the flying bird single passing through the fan blade of the wind turbine.

[0040] By constructing a digital twin model of the wind farm and simulating the annual activity trajectory of birds, the ecological data is converted into dynamic risk parameters, and the trajectory points of different bird species are set in the virtual space according to their migration rules and flight habits. Through the whole year simulation, the frequency distribution of birds crossing the working surface of the wind turbine is accurately captured. This technical path based on real biological behavior modeling completely overcomes the inherent difficulty of continuous observation of bird activities in offshore wind farms, making the annual crossing frequency prediction both ecologically realistic and statistically reliable. By directly coupling the economic loss estimation of a single impact with the dynamically simulated crossing frequency, the final output of the annual loss of different bird species reflects the differences in biological characteristics of different species and quantifies the cumulative economic impact of their activity rules on the wind farm. This design first constructs a full-chain evaluation closed loop of "ecological behavior-mechanical interaction-operation economy" in the field of wind power, providing an irreplaceable decision basis for developing a full life cycle bird strike risk management strategy for offshore wind farms, optimizing operation budget allocation, and evaluating the economic benefits of environmental protection measures, significantly improving the sustainability and economy of large-scale wind power assets operating in ecologically sensitive areas.

[0041] In summary, the advantages of the present application are that the economic loss caused by bird strike events can be scientifically quantified and evaluated. This method accurately calculates the risk index of bird impact on the fan blade by real-time monitoring and analyzing the flight path of flying birds and the potential encounter relationship with the fan blade, and comprehensively considering the possibility of bird active avoidance, the probability of bird crossing different linear velocity partitions of the fan blade, and the dynamic matching relationship between bird crossing time and fan rotation angle. Furthermore, this method integrates the volume characteristics of flying birds, historical maintenance cost data, and detailed bird population information, converts the probabilistic risk index into a specific single impact economic loss estimation, and simulates the annual activity trajectory of different birds with the help of a digital twin model of the wind farm area. Finally, the total annual economic loss of bird strike in a specific wind farm area is accurately predicted. This comprehensive and detailed evaluation process effectively overcomes the challenges of difficult monitoring in offshore environments, high maintenance costs, and difficult calculation of power generation losses, providing objective and reliable data basis and risk management foundation for developing economically efficient anti-bird measures, optimizing insurance strategies, and supporting investment decisions for wind farms, significantly improving the economy and sustainability of offshore wind power projects.

[0042] The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only the principles of the present application. Various changes and improvements can be made without departing from the spirit and scope of the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for assessing economic losses caused by bird strikes on offshore wind turbine blades, characterized in that, include: The flight status of birds in the monitoring area of ​​offshore wind turbine blades is acquired in real time. Based on the flight status of the birds, it is determined whether the flight path of the birds encounters the area of ​​offshore wind turbine blades. If so, the bird collision assessment is initiated. If not, the risk index of bird collision with blades is assigned to 0. The bird strike assessment phase specifically includes: Based on the bird's flight speed and the distance between the bird and the offshore wind turbine blade when the bird spots the blade, determine whether the bird will effectively take the initiative to avoid it. If so, assign the risk index of the bird hitting the blade to 0. If not, calculate the probability of the bird crossing different linear velocity zones of the blade's working surface. Based on the bird's length and speed, determine the time required for the bird to pass through the fan blades; Based on the fan speed and the time required for a bird to pass through the fan blades, determine the rotation angle of the fan blades when the bird passes through them. Calculate the probability that a bird will fly through the fan blades and collide with them; Based on the probability of a bird colliding with the fan blades and the probability of a bird traversing different linear velocity zones on the working surface of the fan blades, the risk index of a bird colliding with the fan blades is calculated. Analysis of the economic losses caused by bird strikes on fan blades.

2. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 1, characterized in that, The method of determining whether a bird will effectively take active avoidance based on its flight speed and the distance between the bird and the offshore wind turbine blades when the bird spots them is as follows: Based on the bird's flight speed and the distance between the bird and the offshore wind turbine blades when the bird spots them, the time it takes for the bird to reach the offshore wind turbine blades is calculated. If the time it takes for the bird to reach the offshore wind turbine blades is greater than the bird's avoidance interval, then it is determined that the bird will effectively take active avoidance; otherwise, it is determined that the bird will not effectively take active avoidance.

3. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 2, characterized in that, The specific calculation of the probability of a bird passing through different linear velocity zones of the fan blade working surface is as follows: The linear velocity partition radius is set based on the radius of the offshore wind turbine blades. , and ,in, The enclosed circular region is the low linear velocity region. The enclosed circular region is the midline velocity region. The enclosed circular region is the high linear velocity region; If the random event of a bird flying through the working surface of a wind turbine blade is defined as a uniform distribution of the areas of the high, medium, and low linear velocity zones of the wind turbine blade, then the specific calculation method for the probability of a bird flying through different linear velocity zones of the working surface of the blade is as follows: ； in, The radius of the low linear velocity region. The radius of the midline velocity region, The radius of the high linear velocity region, The probability of a bird flying through the low linear velocity region of the fan blade working surface. The probability of a bird crossing the centerline velocity region of the fan blade's working surface. The probability of a bird flying through the high linear velocity region of the fan blade working surface.

4. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 3, characterized in that, Based on the fan speed and the time required for a bird to pass through the fan blades, the specific rotation angle of the fan blades when the bird passes through them is determined as follows: The angle between the widest point of the fan blade's windward surface and the center of the fan is defined as the windward surface angle for the low-speed zone, the medium-speed zone, and the high-speed zone, respectively. The specific calculation method for the rotation angle of the fan blades when a bird flies through them is as follows: ； in, The rotation angle of a bird in the low linear velocity region when it flies through the fan blades. The rotation angle of the bird in the centerline velocity zone when it flies through the fan blades. The rotation angle of a bird in the high linear velocity region when it flies through the fan blades. For the angle of the windward side in the low linear velocity region, The angle between the windward side and the centerline velocity region. The angle between the windward surfaces in the high linear velocity region. For wind speed, t is the tip speed ratio of the fan blades, and t is the time required for a bird to pass through the fan blades.

5. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 4, characterized in that, The calculation of the probability of a bird colliding with the fan blades specifically includes: Based on the ratio of the rotation angle of the fan blades in each linear velocity zone to 2π when a bird passes through the fan blades, the probability of the bird colliding with the fan blades when passing through each linear velocity zone can be obtained.

6. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 5, characterized in that, The calculation of the risk index for bird impact with fan blades, based on the probability of a bird colliding with the fan blades while passing through them and the probability of a bird traversing different linear velocity zones on the working surface of the fan blades, specifically includes: The risk index for birds colliding with the fan blades at different linear velocity zones is calculated by multiplying the probability of birds colliding with the fan blades at different linear velocity zones on the working surface of the fan blades.

7. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 6, characterized in that, The risk index analysis based on bird strikes against fan blades specifically includes the economic losses from bird strikes against fan blades: Based on bird survey data, the species, size, and flight altitude of resident and transient birds in the wind farm area were determined. Bird species whose flight altitude is within the working height range of the wind turbine blades were statistically evaluated according to their body size to determine the volume influence coefficient of bird species with different sizes. Based on the historical maintenance logs of the wind turbine blades, the economic losses in different linear velocity zones of bird strikes on the wind turbine blades were determined. Based on the volume influence coefficient of birds, the economic losses of birds hitting the fan blades at different linear velocity zones, and the risk index of birds hitting the fan blades at different linear velocity zones, the estimated economic losses of a single bird passing through the fan blades are calculated. Based on the number of each bird species in the wind farm area and the economic loss of each bird species from a single collision with the wind turbine blades, the estimated annual economic loss of each bird species to the wind turbine blades is assessed. By summarizing the estimated annual economic losses of all types of birds to the fan blades, the annual economic losses from bird strikes on the fan blades can be obtained.

8. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 7, characterized in that, The process of determining the species, size, and flight altitude of resident and transient birds in the wind farm area based on bird survey data, and statistically evaluating bird species whose flight altitude falls within the working height range of the wind turbine blades according to their body size, to determine the volume influence coefficient of bird species of different sizes, is as follows: ； in, The volumetric impact coefficient of economic losses caused by bird strikes on the low-speed working surface of the fan blades. The volumetric impact coefficient for economic losses caused by bird strikes on the medium-speed working surface of the fan blades. The volumetric impact coefficient for economic losses caused by bird strikes on the high-speed working surface of fan blades. This represents the average volume of birds in flight. This represents the average density of birds. Maximum wind speed within the wind farm area This represents the maximum volume of the bird. This represents the maximum density of birds.

9. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 8, characterized in that, The economic loss from a single bird strike through a fan blade is estimated based on the bird's volume influence coefficient, the economic loss from bird strikes at different linear velocity zones of the fan blade, and the risk index of bird strikes at different linear velocity zones of the fan blade. The specific calculation process is as follows: ； Estimate the economic loss from a single bird flying through a wind turbine blade. The risk index for bird strikes in the low linear velocity range of wind turbine blades. The risk index for birds colliding with the centerline velocity zone of the fan blades. The risk index of birds colliding with wind turbine blades in the high linear velocity range. The economic loss caused by birds colliding with fan blades in the low linear velocity region. The economic loss in the centerline velocity zone of a bird striking a fan blade. The economic loss caused by a bird striking a fan blade in the high linear velocity zone.

10. The method for assessing economic losses caused by bird strikes on offshore wind turbine blades according to claim 9, characterized in that, The assessment of the estimated annual economic loss to wind turbine blades for each bird species, based on the number of each bird species within the wind farm area and the economic loss from a single impact on the wind turbine blades, specifically includes: Construct a digital twin model of the wind farm area according to the set proportions; Based on the number of each type of bird in the wind farm area, a corresponding number of trajectory points are set in the digital twin model of the wind farm area, and the motion logic of the trajectory points is set based on the flight habits of each type of bird. Simulate for one year within a digital twin model of the wind farm area, and observe the number of times the trajectory points corresponding to each type of bird cross the wind turbine blades within the wind farm area. This number is recorded as the simulation evaluation count. Multiply the number of simulation assessments by the estimated economic loss of a single bird flying through the wind turbine blades to obtain the estimated annual economic loss of the corresponding bird species to the wind turbine blades.

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