A method for arranging offshore floating wind turbine arrays based on wake turbulence operating characteristics

Abstract

The present invention discloses a method for arranging an offshore floating wind turbine array based on the running characteristics of wake turbulence, which relates to the technical field of offshore wind power generation, and includes the following steps: analyzing various environmental loads on the offshore floating wind turbines, and establishing a dynamic wind turbine array model of the offshore floating wind turbines based on the coupling of large eddy simulation and FAST. The present invention calculates the wake influence range of each floating wind turbine and optimizes the relative positions between the floating wind turbines, which not only reduces the influence of the wake effect on the downstream floating wind turbines, but also ensures the maximization of the wind energy utilization rate of the entire wind farm, avoids the wake directly impacting the downstream floating wind turbines, reduces energy loss, and utilizes the turbulent energy in the wake to improve the wind capture capacity and power generation efficiency of the floating wind turbines, which not only helps to improve the output power of a single floating wind turbine, but also can achieve more efficient energy conversion within the entire wind farm.

Description

Technical Field

[0001] The present invention relates to the technical field of offshore wind power generation, and in particular to an offshore floating wind turbine array arrangement method based on wake turbulence operating characteristics. Background Art

[0002] With the continuous growth of global energy demand and the increasing awareness of environmental protection, the development and utilization of renewable energy has become the focus of attention of all countries. Offshore wind energy, as a clean and renewable energy source, has huge development potential. The operating characteristics of wind turbines are affected by many factors, among which wake turbulence is an important aspect. When the fluid flows through the wind turbine blades, a wake area will be formed. The fluid velocity in this area decreases and the turbulence intensity increases. This wake turbulence will not only affect the operating stability of the floating wind turbine itself, but also affect the inflow conditions of the downstream floating wind turbines, thereby affecting the power generation efficiency of the entire floating wind turbine array. Therefore, in-depth research on the operating characteristics of wake turbulence is of great significance for optimizing the layout of floating wind turbine arrays and improving power generation efficiency.

[0003] In the prior art, the speed loss in the wake zone is often overestimated when simulating the speed loss in the wake zone, resulting in insufficient accuracy, which limits the optimization effect of the floating wind turbine array layout. Therefore, how to improve the accuracy of the wake model and enhance the optimization effect of the floating wind turbine array layout is the problem we need to solve. To this end, a method for offshore floating wind turbine array layout based on the wake turbulence operation characteristics is proposed. Summary of the invention

[0004] The object of the present invention is to provide a method for arranging an offshore floating wind turbine array based on the wake turbulence operating characteristics, so as to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for arranging an offshore floating wind turbine array based on wake turbulence operating characteristics comprises the following steps:

[0007] Step 1: Analyze various environmental loads on offshore floating wind turbines, and establish a dynamic wind turbine array model for offshore floating wind turbines based on the coupling of large eddy simulation and FAST to simulate the dynamic response of floating wind turbines during actual operation, including the aerodynamic characteristics of the blades, the dynamic characteristics of the structure, and the wake effect;

[0008] Step 2, using the vortex filament method and blade element momentum theory under the large eddy simulation framework, simulate the wake field under the interaction of multiple wind turbine wakes and analyze the aerodynamic performance of the floating wind turbine;

[0009] Step 3: Based on the changes in the wake expansion coefficient, turbulence intensity, and the rotation effect of the floating wind turbine blades, the wake model is modified and optimized to more accurately simulate the speed loss in the wake area, thereby avoiding the problem of overestimating the speed loss in the wake area;

[0010] Step 4: Based on the optimized wake model, the layout of the floating wind turbine array in the wind farm in the designated area is optimized by using an optimization algorithm to improve the power generation efficiency and economic benefits of the entire wind farm;

[0011] Step 5: Use the large eddy simulation method to perform numerical simulation of the offshore wind farm, compare and analyze the calculation results with the analytical wake model, and verify the optimized floating wind turbine array layout.

[0012] A further improvement of the technical solution of the present invention is that in step 1, the construction process of the offshore floating wind turbine dynamic wind turbine array model is:

[0013] Analyze various environmental loads on offshore floating wind turbines, including wind loads, wave loads, and flow loads;

[0014] The large eddy simulation is coupled with FAST software to fully simulate the dynamic response of offshore floating wind turbines. Large eddy simulation is used to capture large-scale vortex structures in the fluid. In the simulation of offshore floating wind turbines, large eddy simulation is used to simulate the flow field distribution around the floating wind turbine, including changes in wind speed and wind direction and the influence of wake effects. FAST software is used to simulate the aerodynamic characteristics, structural dynamic characteristics and fatigue life of floating wind turbines. In the simulation of offshore floating wind turbines, FAST establishes a mathematical model of floating wind turbines, including the dynamic equations of blades, towers, and floating platform structures, as well as calculation models for wind loads, wave loads and environmental loads.

[0015] Large eddy simulation is used to simulate the flow field distribution around the floating wind turbine to obtain the spatial distribution and temporal variation of wind speed and wind direction parameters. The wind speed and wind direction parameters obtained by large eddy simulation are used as input conditions and input into the FAST software to calculate the aerodynamic characteristics and structural dynamic characteristics of the floating wind turbine, analyze the influence of wave loads and flow loads, conduct dynamic analysis on the floating platform, obtain the displacement and shaking response of the platform, and couple the aerodynamic characteristics, structural dynamic characteristics and response of the floating wind turbine with the floating platform to obtain the dynamic response of the floating wind turbine during actual operation.

[0016] Simulate the deformation and vibration response of blades under wind loads, as well as the impact of changes in blade angle of attack and camber parameters on aerodynamic characteristics, analyze the impact of wake effects, and simulate the operating conditions of downstream floating wind turbine blades in the wake area of ​​upstream floating wind turbines, including the phenomenon of wind speed drop and turbulence intensity increase;

[0017] Simulate the displacement and sway response of tower and floating platform structures under wind load, wave load and environmental load, and analyze the nonlinear and coupling effects of the structure, such as the interaction between the tower and the blades, and the interaction between the floating platform and the mooring system;

[0018] Large eddy simulation is used to capture the flow characteristics of the wake zone, including the decrease in wind speed and the increase in turbulence intensity. The influence of the wake effect on the operating conditions of the downstream floating wind turbines is analyzed, including the reduction in input wind speed and the decrease in power generation. Based on the optimization problem of the wind farm layout, the distance and arrangement between the floating wind turbines are adjusted to reduce the impact of the wake effect and improve the overall power generation efficiency of the wind farm.

[0019] A further improvement of the technical solution of the present invention is that in step 2, the analysis process of the aerodynamic performance of the floating wind turbine is:

[0020] According to the layout and parameters of multiple wind turbines (including floating wind turbine diameter, speed, and number of blades), a three-dimensional floating wind turbine model is established using the modeling function of fluid dynamics (CFD) software. The floating wind turbine model includes key components such as blades, hubs, and towers to ensure the accuracy of the simulation;

[0021] In the framework of large eddy simulation, set the computational domain, mesh division, and boundary conditions to prepare for the simulation process. Mesh the computational domain and generate discrete points for simulation. The density and resolution of the mesh should be determined according to the accuracy requirements of the simulation. In the vicinity of the floating wind turbine and in the wake area, a denser mesh should be used to capture details. Set the boundary conditions of the computational domain, including the inlet, outlet, side, and top boundary conditions. The inlet boundary conditions are set to the incoming wind speed, wind direction parameters, and turbulence characteristics (such as turbulence intensity and turbulence scale). The outlet boundary conditions are set to free flow conditions or pressure outlet conditions. The side and top boundary conditions are set to symmetric boundary conditions or far-field boundary conditions.

[0022] Before simulation, the flow field is initialized, including setting the incoming wind speed, wind direction parameters, turbulence intensity and turbulence scale;

[0023] Using the vortex filament method and blade element momentum theory, the large eddy simulation program is run. During the simulation, the vortex structure in the fluid, wind speed distribution, and force parameters of the floating wind turbine are calculated;

[0024] After the simulation is completed, relevant data is extracted from the simulation results, and the simulation results are post-processed and analyzed. By analyzing the simulation results, the wake field characteristics under the interaction of multiple wind turbine wakes are obtained, including the wind speed distribution in the wake area, the turbulence intensity variation parameters, and the influence of the wake on the downstream floating wind turbines. Based on the simulation results, the power output and thrust aerodynamic performance parameters of each floating wind turbine are calculated;

[0025] By comparing the performance differences between different floating wind turbines, the performance difference evaluation index is calculated, and the impact of multi-wind turbine wake interaction on the performance of floating wind turbines is evaluated.

[0026] A further improvement of the technical solution of the present invention is that the calculation formula of the performance difference evaluation index is:

[0027] ;

[0028] Among them, PEI is the performance difference evaluation index, is the performance parameter (power output or thrust) of the ith floating wind turbine under actual wake interaction, is the benchmark performance parameter of the ith floating wind turbine without wake interaction, is the time of the i-th floating wind turbine under the actual wake interaction, is the reference time of the i-th floating wind turbine without wake interaction, and n is the total number of floating wind turbines.

[0029] A further improvement of the technical solution of the present invention is that in step 3, the process of correcting and optimizing the wake model is:

[0030] Collect the diameter, speed, and number of blades of floating wind turbines, and analyze the operating data of the wind farm wake expansion coefficient and turbulence intensity;

[0031] Based on the simulation results, combined with the roughness and turbulence intensity conditions in the flow field, the wind farm was numerically simulated using computational fluid dynamics software to obtain the wake expansion coefficient under different roughness and turbulence intensity conditions. The relationship between the wake expansion coefficient and the roughness and turbulence intensity was fitted through regression analysis, and the wake expansion coefficient was dynamically adjusted to more accurately reflect the actual flow field conditions.

[0032] The rotation effect of floating wind turbine blades is introduced into the wake model to capture the changes in vortices and wake structure caused by blade rotation. Through numerical simulation results, the changes in turbulence intensity in the wake area are captured, and the impact of floating wind turbine blade rotation on turbulence intensity is analyzed. Based on the analysis results of the blade rotation model and turbulence intensity changes, the wake model is optimized to improve the accuracy of the simulation results.

[0033] The modified and optimized wake model is used to perform numerical simulation of the wake area in the wind farm. The input parameters (such as wind speed, wind direction, floating wind turbine layout, etc.) are adjusted to simulate the speed loss in the wake area under different conditions.

[0034] A further improvement of the technical solution of the present invention is that the relationship between the wake expansion coefficient, roughness and turbulence intensity is fitted through regression analysis to dynamically adjust the wake expansion coefficient, and its expression is:

[0035] ;

[0036] Where k is the wake expansion coefficient, which indicates the rate at which the wind speed in the wake area recovers. is the turbulence intensity at the jth calculation point, is the baseline turbulence intensity, measured in the free stream region, is the height of the jth calculation point from the ground, As the reference height, take the hub height, is the surface roughness correlation coefficient, which is inversely proportional to the surface roughness, m is the total number of calculation points, and the value of k is between 0 and 0.1.

[0037] A further improvement of the technical solution of the present invention is that in step 4, the process of optimizing the layout of the floating wind turbine array in the wind farm in the designated area is as follows:

[0038] Collect data on topography and meteorological conditions in the wind farm area, analyze the operating data of the wind farm wake expansion coefficient and turbulence intensity, and obtain the technical parameters of the floating wind turbines, including rated power, rotor diameter, speed, number of blades, and tower height;

[0039] Using the optimized wake model, combined with topography and meteorological conditions, the three-dimensional flow field model of the wind farm is re-established;

[0040] Use an optimization algorithm to optimize the layout of the floating wind turbines in the wind farm, define the objective function of the layout optimization, set constraints, divide the wind farm area into multiple potential floating wind turbine locations, and use a genetic algorithm to search for the optimal floating wind turbine layout solution under the constraints. In each iteration, use a three-dimensional flow field model to evaluate the power generation of the current layout solution, and adjust the floating wind turbine location according to the evaluation results until the convergence condition is reached.

[0041] Compare the floating wind turbine layout schemes before and after optimization, analyze the improvements in power generation, wind speed distribution, and wake effect, evaluate the impact of the optimization scheme on the economic benefits of the wind farm, verify the optimization results using actual data to ensure the feasibility and accuracy of the optimization scheme, and fine-tune the optimization scheme based on the verification results to further improve power generation efficiency and economic benefits.

[0042] A further improvement of the technical solution of the present invention is that in step 5, the process of verifying the optimized arrangement of the floating wind turbine array is as follows:

[0043] Based on the large eddy simulation method, a numerical simulation model of the offshore wind farm is established, and the simulation parameters are set according to the actual situation of the offshore wind farm, and then the large eddy simulation model is run to perform numerical simulation of the offshore wind farm;

[0044] Analyze the simulation results and extract key information such as wake expansion coefficient, turbulence intensity and wind speed distribution for subsequent comparative analysis with analytical wake models and verification of floating wind turbine array layout;

[0045] Select the analytical wake model, input the actual parameters of the offshore wind farm into the analytical wake model, run the analytical wake model, and obtain the calculation results of the wind farm wake effect;

[0046] Compare the calculation results of large eddy simulation and analytical wake model in wake effect, analyze the differences and reasons between the two, evaluate the accuracy and applicability of analytical wake model, compare the calculation results of the two methods in turbulence intensity, analyze the distribution and variation of turbulence intensity and the simulation effect of different methods on turbulence intensity, compare the calculation results of the two methods in wind speed distribution, analyze the characteristics and laws of wind speed distribution and the simulation accuracy of wind speed distribution by different methods;

[0047] Based on the results of comparative analysis, the layout of the floating wind turbine array is optimized, and a new layout plan is formulated by comprehensively considering the influence of wake effect, turbulence intensity, and wind speed distribution factors;

[0048] The large eddy simulation method is used to carry out numerical simulation verification of the optimized floating wind turbine array layout to ensure that the new layout scheme is superior to the original scheme in terms of wake effect, turbulence intensity, and wind speed distribution. An economic benefit evaluation is also carried out on the optimized floating wind turbine array layout, and the power generation efficiency, operation and maintenance costs, and equipment investment factors are analyzed to comprehensively evaluate the feasibility and economy of the new scheme.

[0049] A further improvement of the technical solution of the present invention is that the formulation process of the new arrangement scheme is:

[0050] The optimization objectives are to minimize the wake effect, reduce the turbulence intensity, and optimize the wind speed distribution. The relative positions of the floating wind turbines are adjusted to reduce the impact of the wake on the downstream floating wind turbines, improve the energy capture efficiency of the entire wind farm, optimize the layout of the floating wind turbines to reduce airflow interference, reduce the turbulence intensity in the wind farm, thereby reducing the fatigue load of the floating wind turbines and extending their service life. The wind speed distribution in the wind farm is ensured to be more uniform, wind speed fluctuations are reduced, and the wind capture efficiency and power generation performance of the floating wind turbines are improved.

[0051] When arranging floating wind turbines, avoid overlapping wakes and ensure that the downstream floating wind turbines are not directly in the wake of the upstream floating wind turbines to reduce energy loss, and utilize the wake energy and optimize the spacing between floating wind turbines. The spacing between floating wind turbines should be large enough to reduce airflow interference and turbulence intensity;

[0052] The floating wind turbines are divided into two rows in a staggered arrangement. The floating wind turbines in each row are staggered relative to the floating wind turbines in the previous or next row. This can reduce wake overlap and improve energy capture efficiency. Based on the results of comparative analysis, the spacing between floating wind turbines is adjusted to ensure a more uniform wind speed distribution while reducing turbulence intensity. The diversity of wind directions is taken into consideration when arranging floating wind turbines. Wind direction changes are tracked by installing wind direction sensors and real-time monitoring systems, and the orientation and layout of floating wind turbines are adjusted as needed.

[0053] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0054] The present invention provides an offshore floating wind turbine array arrangement method based on the wake turbulence operation characteristics. By calculating the wake influence range of each floating wind turbine and optimizing the relative positions between the floating wind turbines, not only the influence of the wake effect on the downstream floating wind turbines is reduced, but also the wind energy utilization rate of the entire wind farm is maximized, the wake is prevented from directly impacting the downstream floating wind turbines, and energy loss is reduced. At the same time, the turbulent energy in the wake is utilized to improve the wind capture ability and power generation efficiency of the floating wind turbines, which not only helps to improve the output power of a single floating wind turbine, but also can achieve more efficient energy conversion within the entire wind farm.

[0055] The present invention provides an offshore floating wind turbine array arrangement method based on the wake turbulence operation characteristics. By optimizing the floating wind turbine layout, the turbulence intensity in the wind farm can be effectively reduced, the airflow interference between the floating wind turbines can be reduced, and the possibility of turbulence generation can be reduced. At the same time, the turbulence energy in the wake is used to balance the turbulence distribution of the entire wind farm, reduce the situation where the local turbulence intensity is too high, help reduce the fatigue load of the floating wind turbine, improve its structural safety and operation stability, and thus extend the service life of the floating wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0057] Figure 1 is a flow chart of the method of the present invention;

[0058] Figure 2 The following is a flow chart for analyzing the aerodynamic performance of the floating fan of the present invention;

[0059] Figure 3 This is a flowchart for correcting and optimizing the wake model of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] Embodiment 1, as Figure 1 , Figure 2 As shown, the present invention provides a method for arranging an offshore floating wind turbine array based on wake turbulence operating characteristics, comprising the following steps:

[0062] Step 1: Analyze the various environmental loads on offshore floating wind turbines, and establish a dynamic wind turbine array model for offshore floating wind turbines based on the coupling of large eddy simulation and FAST, simulate the dynamic response of floating wind turbines in actual operation, including the aerodynamic characteristics of blades, the dynamic characteristics of structures and wake effects, and analyze the various environmental loads on offshore floating wind turbines, including wind loads, wave loads and flow loads. The size and direction of wind loads will change with the changes in wind speed and wind direction, and have a dynamic impact on the blades, towers and other structures of floating wind turbines. The fluctuation of waves has a large impact on the floating platform, causing the platform to shake and displace, thereby affecting the stable operation of the floating wind turbine. The ocean current will have a negative impact on the floating platform. A certain force will be generated, which will affect the stability of the floating wind turbine under long-term action. The large eddy simulation is coupled with the FAST software to fully simulate the dynamic response of the offshore floating wind turbine. The large eddy simulation is used to capture the large-scale vortex structure in the fluid. In the simulation of the offshore floating wind turbine, the large eddy simulation is used to simulate the flow field distribution around the floating wind turbine, including the changes in wind speed and wind direction and the influence of the wake effect. The FAST software is used to simulate the aerodynamic characteristics, structural dynamic characteristics and fatigue life of the floating wind turbine. In the simulation of the offshore floating wind turbine, FAST establishes a mathematical model of the floating wind turbine, including the dynamic equations of the blades, towers, and floating platform structures, as well as the calculation models of wind loads, wave loads and environmental loads. The simulation is used to simulate the flow field distribution around the floating wind turbine, and the spatial distribution and temporal variation of wind speed and wind direction parameters are obtained. The wind speed and wind direction parameters obtained by the large eddy simulation are used as input conditions and input into the FAST software to calculate the aerodynamic characteristics and structural dynamic characteristics of the floating wind turbine, analyze the influence of wave loads and flow loads, and perform dynamic analysis on the floating platform to obtain the displacement and shaking response of the platform. The aerodynamic characteristics, structural dynamic characteristics and response of the floating wind turbine are coupled with the response of the floating platform to obtain the dynamic response of the floating wind turbine during actual operation, simulate the deformation and vibration response of the blades under wind loads, and the influence of the changes in the angle of attack and curvature parameters of the blades on the aerodynamic characteristics, analyze the influence of the wake effect, and simulate the downstream The operation status of floating wind turbine blades in the wake area of ​​the upstream floating wind turbine, including the phenomenon of wind speed drop and turbulence intensity increase, simulate the displacement and shaking response of the tower and floating platform structure under the action of wind load, wave load and environmental load, analyze the nonlinear effect and coupling effect of the structure, such as the interaction between the tower and the blades, the interaction between the floating platform and the mooring system, etc., use large eddy simulation to capture the flow characteristics of the wake area, including the phenomenon of wind speed drop and turbulence intensity increase, analyze the impact of the wake effect on the operation status of the downstream floating wind turbine, including the reduction of input wind speed and the reduction of power generation, based on the optimization problem of wind farm layout, by adjusting the distance and arrangement between floating wind turbines, reduce the impact of the wake effect and improve the overall power generation efficiency of the wind farm;

[0063] Step 2, using the vortex filament method and blade element momentum theory under the framework of large eddy simulation, simulate the wake field under the interaction of multiple wind turbine wakes, analyze the aerodynamic performance of floating wind turbines, and establish a three-dimensional floating wind turbine model based on the layout and parameters of multiple wind turbines (including floating wind turbine diameter, speed, and number of blades) using the modeling function of fluid dynamics (CFD) software. The floating wind turbine model includes key components such as blades, hubs, and towers to ensure the accuracy of the simulation. In the framework of large eddy simulation, set the calculation domain, mesh division, and boundary conditions to prepare for the simulation process. Mesh the calculation domain and generate discrete points for simulation. The density and resolution of the grid should be determined according to the accuracy requirements of the simulation. In the vicinity of the floating wind turbine and in the wake area, a denser grid should be used to capture details. Set the boundary conditions of the calculation domain, including the boundary conditions of the inlet, outlet, side, and top. The inlet boundary conditions are set to the incoming wind speed, wind direction parameters, and turbulence characteristics (such as turbulence intensity and turbulence scale). The outlet boundary conditions are set to free flow conditions or pressure outlet conditions. The side and top boundary conditions are set to symmetric boundary conditions or far-field boundary conditions. Before the simulation, the flow field is initialized, including setting the incoming wind speed, wind direction parameters, turbulence intensity and turbulence scale. The vortex filament method and blade element momentum theory are used to run the large eddy simulation program. During the simulation, the vortex structure, wind speed distribution and force parameters of the floating wind turbine in the fluid are calculated. The vortex filament method represents the vortex in the fluid as discrete vortex filaments to capture the dynamic characteristics of the vortex. The blade element momentum theory divides the blades of the floating wind turbine into multiple blade elements along the span direction and calculates the force and torque on each blade element. The flow field state is updated in real time to reflect the wake and turbulence of the floating wind turbine. After the simulation, relevant data are extracted from the simulation results, and the simulation results are post-processed and analyzed. By analyzing the simulation results, the wake field characteristics under the interaction of multiple wind turbine wakes are obtained, including the wind speed distribution in the wake area, the turbulence intensity variation parameters, and the influence of the wake on the downstream floating wind turbines. According to the simulation results, the aerodynamic performance parameters of the power output and thrust of each floating wind turbine are calculated. By comparing the performance differences between different floating wind turbines, the performance difference evaluation index is calculated to evaluate the impact of the interaction of multiple wind turbine wakes on the performance of floating wind turbines.

[0064] Furthermore, the calculation formula of the performance difference evaluation index is:

[0065] ;

[0066] Among them, PEI is the performance difference evaluation index, is the performance parameter (power output or thrust) of the ith floating wind turbine under actual wake interaction, is the benchmark performance parameter of the ith floating wind turbine without wake interaction, is the time of the i-th floating wind turbine under the actual wake interaction, is the benchmark time of the i-th floating wind turbine without wake interaction, n is the total number of floating wind turbines, when the actual performance parameters of all floating wind turbines are equal to the benchmark performance parameters, PEI tends to 1, indicating that wake interaction has no effect on performance, when the actual performance parameters are significantly lower than the benchmark performance parameters, the PEI value will increase significantly, indicating that wake interaction has a negative impact on the performance of floating wind turbines;

[0067] Step 3: Based on the changes in the wake expansion coefficient, turbulence intensity, and the rotation effect of the floating wind turbine blades, the wake model is modified and optimized to more accurately simulate the speed loss in the wake area, thereby avoiding the problem of overestimating the speed loss in the wake area;

[0068] Step 4: Based on the optimized wake model, the layout of the floating wind turbine array in the wind farm in the designated area is optimized by using an optimization algorithm to improve the power generation efficiency and economic benefits of the entire wind farm;

[0069] Step 5: Use the large eddy simulation method to perform numerical simulation of the offshore wind farm, compare and analyze the calculation results with the analytical wake model, and verify the optimized floating wind turbine array layout.

[0070] Embodiment 2, as Figure 3 As shown, based on Example 1, the present invention provides a technical solution: Preferably, in step 3, the process of correcting and optimizing the wake model is:

[0071] The diameter, rotation speed, and number of blades of floating wind turbines are collected, and the operating data of the wind farm wake expansion coefficient and turbulence intensity are analyzed. The wake expansion coefficient is an important indicator to measure the width of the wake area and the degree of velocity reduction. By analyzing the operating data of the wind farm, the wake expansion coefficient under different wind speeds, wind directions, and floating wind turbine layouts can be obtained. The turbulence intensity reflects the degree of velocity fluctuation in the flow field. In the wind farm, the turbulence intensity is affected by many factors. By analyzing the operating data, the influence of turbulence intensity on the wake effect can be understood. Based on the simulation results, combined with the roughness and turbulence intensity conditions in the flow field, the wind farm is numerically simulated using computational fluid dynamics software to obtain the wake expansion coefficient under different roughness and turbulence intensity conditions. Through regression analysis Fit the relationship between the wake expansion coefficient and the roughness and turbulence intensity, dynamically adjust the wake expansion coefficient to more accurately reflect the actual flow field conditions, introduce the rotation effect of the floating wind turbine blades into the wake model, capture the vortex and wake structure changes caused by the blade rotation, capture the changes in turbulence intensity in the wake area through numerical simulation results, and analyze the impact of the floating wind turbine blade rotation on the turbulence intensity. According to the analysis results of the blade rotation model and the change of turbulence intensity, optimize the wake model to improve the accuracy of the simulation results. Use the modified and optimized wake model to perform numerical simulation of the wake area in the wind farm, adjust the input parameters (such as wind speed, wind direction, floating wind turbine layout, etc.), and simulate the speed loss in the wake area under different conditions;

[0072] Furthermore, the relationship between the wake expansion coefficient, roughness and turbulence intensity is fitted through regression analysis, and the wake expansion coefficient is dynamically adjusted. The expression is:

[0073] ;

[0074] Where k is the wake expansion coefficient, which indicates the rate at which the wind speed in the wake area recovers. is the turbulence intensity at the jth calculation point, is the baseline turbulence intensity, measured in the free stream region, is the height of the jth calculation point from the ground, As the reference height, take the hub height, is the surface roughness correlation coefficient, which is inversely proportional to the surface roughness, m is the total number of calculation points, and the value of k is between 0 and 0.1, depending on the layout of the wind farm and atmospheric conditions. near and near When k approaches 0, it means that the wake expansion effect is weak. Significantly higher than or Significantly higher than When , k increases, indicating that the wake expansion effect is stronger;

[0075] In step 4, the process of optimizing the layout of the floating wind turbine array in the wind farm in the specified area is as follows:

[0076] Collect topographic and meteorological data of the wind farm area, analyze the operating data of the wind farm wake expansion coefficient and turbulence intensity, and obtain the technical parameters of the floating wind turbine, including rated power, rotor diameter, speed, number of blades, and tower height. Use the optimized wake model, combined with topographic and meteorological conditions, to re-establish the three-dimensional flow field model of the wind farm. Use the optimization algorithm to optimize the layout of the floating wind turbines in the wind farm, define the objective function of the layout optimization, set constraints, divide the wind farm area into multiple potential floating wind turbine locations, and use the genetic algorithm to optimize the layout. Search for the optimal floating wind turbine layout scheme under constraints. In each iteration, use the three-dimensional flow field model to evaluate the power generation of the current layout scheme. Adjust the position of the floating wind turbine according to the evaluation results until the convergence condition is reached. Compare the floating wind turbine layout schemes before and after optimization, analyze the improvements in power generation, wind speed distribution, and wake effect, evaluate the impact of the optimization scheme on the economic benefits of the wind farm, verify the optimization results with actual data to ensure the feasibility and accuracy of the optimization scheme, and fine-tune the optimization scheme according to the verification results to further improve power generation efficiency and economic benefits.

[0077] In step 5, the process of verifying the optimized floating wind turbine array layout is as follows:

[0078] Based on the large eddy simulation method, a numerical simulation model of an offshore wind farm is established. According to the actual situation of the offshore wind farm, the simulation parameters are set, and then the large eddy simulation model is run to perform numerical simulation of the offshore wind farm. The simulation results are analyzed, and key information such as the wake expansion coefficient, turbulence intensity, and wind speed distribution are extracted for subsequent comparative analysis with the analytical wake model and verification of the floating wind turbine array layout. The analytical wake model is selected, and the actual parameters of the offshore wind farm are input into the analytical wake model. The analytical wake model is run to obtain the calculation results of the wind farm's wake effect. The calculation results of the large eddy simulation and analytical wake models in terms of wake effects are compared, the differences and reasons between the two are analyzed, the accuracy and applicability of the analytical wake model are evaluated, and the two methods are compared in terms of turbulence intensity. The calculation results of the two methods are used to analyze the distribution and variation of turbulence intensity and the simulation effects of turbulence intensity by different methods. The calculation results of the two methods in terms of wind speed distribution are compared. The characteristics and laws of wind speed distribution and the simulation accuracy of wind speed distribution by different methods are analyzed. According to the results of the comparative analysis, the layout of the floating wind turbine array is optimized. A new layout plan is formulated by comprehensively considering the influence of wake effect, turbulence intensity and wind speed distribution factors. The large eddy simulation method is used to perform numerical simulation verification on the optimized floating wind turbine array layout to ensure that the new layout plan is superior to the original plan in terms of wake effect, turbulence intensity and wind speed distribution. The economic benefit evaluation of the optimized floating wind turbine array layout is also carried out. The power generation efficiency, operation and maintenance cost and equipment investment factors are analyzed to comprehensively evaluate the feasibility and economy of the new plan.

[0079] Furthermore, the process of formulating the new layout plan is as follows:

[0080] The optimization objectives are clearly defined, namely minimizing the wake effect, reducing turbulence intensity, and optimizing wind speed distribution. Among them, by adjusting the relative positions between floating wind turbines, reducing the impact of wake on downstream floating wind turbines, improving the energy capture efficiency of the entire wind farm, optimizing the layout of floating wind turbines to reduce airflow interference, reducing the turbulence intensity in the wind farm, thereby reducing the fatigue load of floating wind turbines, extending their service life, ensuring a more uniform wind speed distribution in the wind farm, reducing wind speed fluctuations, and improving the wind capture efficiency and power generation performance of floating wind turbines. When arranging floating wind turbines, avoid overlapping wakes to ensure that the downstream floating wind turbines are not directly in the wake of the upstream floating wind turbines to reduce Energy loss, and utilize wake energy and optimize the spacing of floating wind turbines. The spacing between floating wind turbines should be large enough to reduce airflow interference and turbulence intensity. The floating wind turbines are divided into two rows in a staggered arrangement. The floating wind turbines in each row are staggered relative to the floating wind turbines in the previous or next row. This can reduce wake overlap and improve energy capture efficiency. According to the results of comparative analysis, the spacing between floating wind turbines is adjusted to ensure a more uniform wind speed distribution while reducing turbulence intensity. The diversity of wind directions is considered when arranging floating wind turbines. Wind direction changes are tracked by installing wind direction sensors and real-time monitoring systems, and the orientation and layout of floating wind turbines are adjusted as needed.

[0081] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for arranging an offshore floating wind turbine array based on wake turbulence operating characteristics, characterized in that: The following steps are involved: Step 1: Analyze various environmental loads on offshore floating wind turbines, and establish a dynamic wind turbine array model of offshore floating wind turbines based on the coupling of large eddy simulation and FAST; Step 2, using the vortex filament method and blade element momentum theory under the large eddy simulation framework, simulate the wake field under the interaction of multiple wind turbine wakes and analyze the aerodynamic performance of the floating wind turbine; Step 3, based on the change of the wake expansion coefficient, the turbulence intensity and the rotation effect of the floating wind turbine blades, the wake model is corrected and optimized. In step 3, the process of correcting and optimizing the wake model is: Collect the diameter, speed, and number of blades of floating wind turbines, and analyze the operating data of the wind farm wake expansion coefficient and turbulence intensity; Based on the simulation results, combined with the roughness and turbulence intensity conditions in the flow field, the wind farm was numerically simulated using computational fluid dynamics software to obtain the wake expansion coefficient under different roughness and turbulence intensity conditions. The relationship between the wake expansion coefficient and the roughness and turbulence intensity was fitted through regression analysis to dynamically adjust the wake expansion coefficient. The rotation effect of floating wind turbine blades is introduced into the wake model to capture the changes in vortices and wake structure caused by blade rotation. The changes in turbulence intensity in the wake area are captured through numerical simulation results, and the impact of floating wind turbine blade rotation on turbulence intensity is analyzed. The wake model is optimized based on the analysis results of the blade rotation model and turbulence intensity changes. The modified and optimized wake model is used to numerically simulate the wake area in the wind farm, and the input parameters are adjusted to simulate the speed loss in the wake area under different conditions. Step 4, based on the optimized wake model, the layout of the floating wind turbine array of the wind farm in the designated area is optimized by an optimization algorithm. In step 4, the process of optimizing the layout of the floating wind turbine array of the wind farm in the designated area is as follows: Collect data on topography and meteorological conditions in the wind farm area, analyze the operating data of the wind farm wake expansion coefficient and turbulence intensity, and obtain the technical parameters of floating wind turbines; Using the optimized wake model, combined with topography and meteorological conditions, the three-dimensional flow field model of the wind farm is re-established; Use an optimization algorithm to optimize the layout of the floating wind turbines in the wind farm, define the objective function of the layout optimization, set constraints, divide the wind farm area into multiple potential floating wind turbine locations, and use a genetic algorithm to search for the optimal floating wind turbine layout solution under the constraints. In each iteration, use a three-dimensional flow field model to evaluate the power generation of the current layout solution, and adjust the floating wind turbine location according to the evaluation results until the convergence condition is reached. Compare the floating wind turbine layout schemes before and after optimization, analyze the improvements in power generation, wind speed distribution, and wake effect, evaluate the impact of the optimization scheme on the economic benefits of the wind farm, verify the optimization results with actual data, and fine-tune the optimization scheme based on the verification results; Step 5: Use the large eddy simulation method to perform numerical simulation of the offshore wind farm, compare and analyze the calculation results with the analytical wake model, and verify the optimized floating wind turbine array layout.

2. The method for arranging an offshore floating wind turbine array based on wake turbulence operating characteristics according to claim 1, characterized in that: In step 1, the construction process of the offshore floating wind turbine dynamic array model is as follows: Analyze various environmental loads on offshore floating wind turbines, including wind loads, wave loads, and flow loads; The large eddy simulation is coupled with FAST software to fully simulate the dynamic response of offshore floating wind turbines. Large eddy simulation is used to capture the large-scale vortex structure in the fluid, and FAST software is used to simulate the aerodynamic characteristics, structural dynamic characteristics and fatigue life of floating wind turbines. Large eddy simulation is used to simulate the flow field distribution around the floating wind turbine to obtain the spatial distribution and temporal variation of wind speed and wind direction parameters. The wind speed and wind direction parameters obtained by large eddy simulation are used as input conditions and input into the FAST software to calculate the aerodynamic characteristics and structural dynamic characteristics of the floating wind turbine, analyze the influence of wave loads and flow loads, conduct dynamic analysis on the floating platform, obtain the displacement and shaking response of the platform, and couple the aerodynamic characteristics, structural dynamic characteristics and response of the floating wind turbine with the floating platform to obtain the dynamic response of the floating wind turbine during actual operation. Simulate the deformation and vibration response of blades under wind loads, as well as the impact of changes in blade angle of attack and camber parameters on aerodynamic characteristics, analyze the impact of wake effects, and simulate the operating conditions of downstream floating wind turbine blades in the wake area of ​​upstream floating wind turbines, including the phenomenon of wind speed drop and turbulence intensity increase; Simulate the displacement and sway response of tower and floating platform structures under wind load, wave load and environmental load, and analyze the nonlinear effect and coupling effect of the structure; Large eddy simulation is used to capture the flow characteristics of the wake zone, including the decrease in wind speed and the increase in turbulence intensity, and to analyze the impact of the wake effect on the operating conditions of the downstream floating wind turbines, including the reduction in input wind speed and the decrease in power generation.

3. The method for arranging an offshore floating wind turbine array based on wake turbulence operating characteristics according to claim 2, characterized in that: In step 2, the analysis process of the aerodynamic performance of the floating wind turbine is as follows: According to the layout and parameters of multiple wind turbines, a three-dimensional floating wind turbine model is established using the modeling function of fluid dynamics software; In the framework of large eddy simulation, the computational domain, meshing, and boundary conditions are set. The computational domain is meshed, discrete points for simulation are generated, and boundary conditions of the computational domain are set, including the inlet, outlet, side, and top boundary conditions. Before simulation, the flow field is initialized, including setting the incoming wind speed, wind direction parameters, turbulence intensity and turbulence scale; Using the vortex filament method and blade element momentum theory, the large eddy simulation program is run. During the simulation, the vortex structure in the fluid, wind speed distribution, and force parameters of the floating wind turbine are calculated; After the simulation is completed, relevant data is extracted from the simulation results, and the simulation results are post-processed and analyzed. By analyzing the simulation results, the wake field characteristics under the interaction of multiple wind turbine wakes are obtained, including the wind speed distribution in the wake area, the turbulence intensity variation parameters, and the influence of the wake on the downstream floating wind turbines. Based on the simulation results, the power output and thrust aerodynamic performance parameters of each floating wind turbine are calculated; By comparing the performance differences between different floating wind turbines, the performance difference evaluation index is calculated, and the impact of multi-wind turbine wake interaction on the performance of floating wind turbines is evaluated.

4. The method for arranging an offshore floating wind turbine array based on wake turbulence operating characteristics according to claim 3, characterized in that: The calculation formula of the performance difference evaluation index is: Among them, PEI is the performance difference evaluation index, P i，ac is the performance parameter of the ith floating wind turbine under actual wake interaction, P i，base is the benchmark performance parameter of the ith floating wind turbine without wake interaction, T i，ac is the time of the i-th floating wind turbine under the actual wake interaction, T i，base is the reference time of the i-th floating wind turbine without wake interaction, and n is the total number of floating wind turbines.

5. The offshore floating wind turbine array arrangement method based on wake turbulence operation characteristics according to claim 1, characterized in that: The relationship between the wake expansion coefficient, roughness and turbulence intensity is fitted through regression analysis to dynamically adjust the wake expansion coefficient, and its expression is: Where k is the wake expansion coefficient, which indicates the rate at which the wind speed in the wake area recovers, TI j is the turbulence intensity at the jth calculation point, TI base is the baseline turbulence intensity, z j is the height of the jth calculation point from the ground, z base As the reference height, take the hub height, C μ is the surface roughness correlation coefficient, which is inversely proportional to the surface roughness, m is the total number of calculation points, and the value of k is between 0 and 0.

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6. The method for arranging an offshore floating wind turbine array based on wake turbulence operating characteristics according to claim 5, characterized in that: In step 5, the process of verifying the optimized floating wind turbine array arrangement is as follows: Based on the large eddy simulation method, a numerical simulation model of the offshore wind farm is established, and the simulation parameters are set according to the actual situation of the offshore wind farm, and then the large eddy simulation model is run to perform numerical simulation of the offshore wind farm; Analyze the simulation results and extract key information on wake expansion coefficient, turbulence intensity, and wind speed distribution; Select the analytical wake model, input the actual parameters of the offshore wind farm into the analytical wake model, run the analytical wake model, and obtain the calculation results of the wind farm wake effect; Compare the calculation results of large eddy simulation and analytical wake model in wake effect, analyze the differences and reasons between the two, compare the calculation results of the two methods in turbulence intensity, analyze the distribution and variation of turbulence intensity and the simulation effect of different methods on turbulence intensity, compare the calculation results of the two methods in wind speed distribution, analyze the characteristics and laws of wind speed distribution and the simulation accuracy of wind speed distribution by different methods; Based on the results of comparative analysis, the layout of the floating wind turbine array is optimized, and a new layout plan is formulated by comprehensively considering the influence of wake effect, turbulence intensity, and wind speed distribution factors; The large eddy simulation method is used to carry out numerical simulation verification of the optimized floating wind turbine array layout to ensure that the new layout scheme is superior to the original scheme in terms of wake effect, turbulence intensity, and wind speed distribution. An economic benefit evaluation is also carried out on the optimized floating wind turbine array layout, and the power generation efficiency, operation and maintenance costs, and equipment investment factors are analyzed to comprehensively evaluate the feasibility and economy of the new scheme.

7. The method for arranging an offshore floating wind turbine array based on wake turbulence operating characteristics according to claim 6, characterized in that: The formulation process of the new arrangement scheme is as follows: The optimization objectives are to minimize the wake effect, reduce the turbulence intensity, and optimize the wind speed distribution. When arranging floating wind turbines, avoid wake overlap, utilize wake energy and optimize floating wind turbine spacing; The floating wind turbines are divided into two rows in a staggered arrangement. The floating wind turbines in each row are staggered relative to the floating wind turbines in the previous or next row. The spacing between the floating wind turbines is adjusted based on the results of comparative analysis. When arranging the floating wind turbines, wind direction changes are tracked by installing wind direction sensors and a real-time monitoring system, and the orientation and layout of the floating wind turbines are adjusted as needed.

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