Floating wind turbine mooring positioning method, mooring positioning system and electronic device

Abstract

The application belongs to the technical field of offshore wind power generation, and discloses a floating wind turbine mooring positioning method, a mooring positioning system and electronic equipment. The floating wind turbine mooring positioning method obtains the measurement data of wind speed and wind direction and the position information of wind turbine layout, then constructs a mooring system model of the wind turbine to obtain the maximum length and the minimum length of the mooring line; then the genetic algorithm is used to iteratively process multiple design parameters while keeping other parameters unchanged to obtain the optimized position coordinates of the wind turbine, thereby creating a mooring system design database, and according to the established wake model of the floating offshore wind farm, the power generation capacity of each wind turbine and the position information of the layout are calculated according to the offset of the position of each wind turbine until the position information of the layout with the minimum wake loss of the floating offshore wind farm and the maximum power generation capacity of the wind farm is found, which is beneficial to improve the output power of the wind farm and reduce the fatigue load of the wind turbine.

Description

Technical Field

[0001] This invention relates to the field of offshore wind power generation technology, and in particular to a method, system and electronic equipment for mooring and positioning floating wind turbines. Background Technology

[0002] As offshore wind power expands from nearshore to deep-sea areas, the support structure has shifted from fixed to floating. Although floating and bottom-mounted wind power projects use the same wind turbines, their support foundations differ. Unlike fixed offshore wind turbines, floating platforms allow the turbines to shift and rotate under the influence of wind and waves, adding extra degrees of freedom. This undoubtedly increases the difficulty of controlling floating wind turbines. However, on the other hand, the platform's extra degrees of freedom also provide opportunities for real-time position control of the wind turbines, which is impossible for onshore or fixed-foundation wind turbines.

[0003] Fixed-foundation wind turbines cannot be repositioned after installation. The wake effect reduces the wind farm's output power and increases structural fatigue load. Floating wind turbines, on the other hand, are mobile, allowing the wind farm to track the optimal layout with minimal wake effect during sudden wind changes. Existing technology proposes a method to move floating wind turbines within the wind farm by adjusting the mooring line length. Changing the mooring line length causes tension imbalance, resulting in displacement of the floating wind turbine and ultimately reaching a new equilibrium position. This repositioning mechanism employs a taut mooring line design, with one end connected to the seabed and the other to a winch, enabling rapid and continuous operation during contraction and extension.

[0004] The system consists of an anchor attached to the mooring line, which secures the line to the seabed; a catenary mooring line holds the floating wind turbine in a fixed position and guides it to the winch via a guide cable; and the winch is responsible for pulling in and releasing the mooring cable. By adjusting parameters such as the length, azimuth, and tension of the mooring line, the wind turbine is moved from its original installation position to a new equilibrium position. Once the installation and anchoring positions of the floating wind turbine are determined, the shape of its movable range can be determined. Based on this shape, the coordinates of the wind turbine after displacement via the mooring system can be determined. Currently, one of the problems facing floating offshore wind farms is the lack of effective control methods. This leads to significant wake effects between turbines within the wind farm, limiting the power generation of downstream turbines, and causing high fatigue loads on the turbines, resulting in shorter turbine lifespans and significantly reduced economic benefits.

[0005] Therefore, there is an urgent need to provide a new type of floating wind turbine mooring and positioning method, mooring and positioning system and electronic equipment to solve the above-mentioned technical problems in the prior art. Summary of the Invention

[0006] The purpose of this invention is to provide a mooring and positioning method for floating wind turbines, which can realize the repositioning of floating wind turbines and ultimately achieve rapid generation of a layout scheme for floating wind turbines that meets optimization objectives and constraints, thereby improving the output power of wind farms and reducing wind turbine fatigue loads.

[0007] To achieve this objective, the present invention adopts the following technical solution:

[0008] The method for mooring and positioning floating wind turbines includes the following steps:

[0009] S1. Obtain measurement data of wind speed and direction and location information of wind turbine layout in floating offshore wind farms;

[0010] S2. Construct a mooring system model for the wind turbine to obtain the maximum and minimum lengths of the mooring lines;

[0011] S3. Create a mooring system design database: Use a genetic algorithm to iteratively process multiple design parameters while keeping other parameters constant. The design parameters include fixed and variable parameters. Fixed parameters include: water depth setting h, the number of mooring lines n in each mooring system, mooring line diameter a, anchoring radius R (ranging from 2.5D to 3.5D), initial azimuth angle of the mooring lines (the mooring lines for wind turbines are equilateral triangles with a fixed angle of 120° between adjacent mooring lines), and mooring line length setting b. Variable parameters include: the offset of the wind turbine position relative to the initial layout. Finally, record the optimized wind turbine position coordinates.

[0012] S4. The offset of the wind turbine position relative to the initial layout in step S3 is calculated using an iterative method: gradually adjust the wind turbine position until the mooring system reaches equilibrium, find the steady-state position of each mooring system, and calculate the offset of the wind turbine position relative to the initial layout.

[0013] S5. During the iteration process, a wake model of the floating offshore wind farm is established. Based on the offset of each wind turbine, the power generation and layout location information of each wind turbine are calculated and output until the layout location information of the floating offshore wind farm with the minimum wake loss and the maximum power generation is found.

[0014] Optionally, the mooring system model for the wind turbine is calculated using the following method:

[0015] Where: x0 and y0 are the initial layout coordinates of the wind turbine; xn and y n These are the coordinates of the wind turbine's position after it has been moved; x Fi and y Fi These are the coordinates of the cable guide; x Ai and y Ai These are the anchor coordinates of the mooring line; Δx i and Δy i is the distance from the center point of the wind turbine to the guide wire; i is the mooring line number; Li is the total length of the mooring line from the guide wire to the anchor; Hi(Li) is the horizontal component of the mooring line tension at the guide wire, which is a function of the mooring line length; di is the horizontal distance from the guide wire to the anchor; βi is the direction of the mooring line.

[0016] The horizontal distance from the cable guide to the anchor is: Where, x Fi and y Fi Represented as: Substituting into the above equation, we get:

[0017] The direction of the mooring line is:

[0018] The remaining free variables are the mooring line length Li, which changes the horizontal component of the mooring line tension Hi. Given the horizontal distance di from the guide to the anchor and the vertical distance h from the guide to the seabed, and neglecting environmental loads, the calculated horizontal tension Hi of the catenary mooring line is obtained. The components of the horizontal tension Hi in the x and y directions are expressed as: By calculating the two components of the horizontal tension Hi of the mooring line in the x and y directions, the displacement of each wind turbine is obtained, and the overall system force reaches equilibrium.

[0019] Optionally, in step S2, the maximum length of the mooring line is the length when the mooring line is fully slack, i.e., di+h; the minimum length of the mooring line is the length when the mooring line is taut, i.e.

[0020] Optionally, a quasi-static mooring analysis can be performed with the following constraints: the maximum offset of the mooring system cannot exceed 1D; the maximum allowable pitch angle of the wind turbine is 10°; there is no vertical load on the anchor of the mooring system; and all mooring lines are catenary-shaped to obtain the minimum length of the mooring lines.

[0021] Optionally, an iterative method is used to gradually adjust the position of the wind turbines until a balance is achieved between the external forces and the internal forces of the mooring system, thus finding the steady-state position of each mooring system. The horizontal tension of the guide cable is calculated based on the length of the mooring line, and the two components of the horizontal tension Hi in the x and y directions are obtained. Finally, the displacement of each wind turbine is obtained.

[0022] Optionally, when using a genetic algorithm to iteratively process multiple design parameters, a new generation of individuals is continuously generated through selection, crossover, and mutation operations: the selection operation adopts roulette wheel selection, the crossover operation adopts the exchange of offsets between two parents, and the mutation operation adopts the introduction of random changes.

[0023] Optionally, in step S3, when determining the initial azimuth angle of the mooring lines, one of the mooring lines is aligned directly with the prevailing wind direction, while the other two mooring lines are set at a preset angle, which corresponds to the inflow direction of the prevailing wind direction.

[0024] Optionally, in step S5, a wake model of the floating offshore wind farm is established. The wake model used includes analytical wake models and computational wake models. The analytical wake model includes any one of the Jensen wake model, Frandsen wake model, Bastankhah wake model, and Larsen wake model. Different wake models are selected for iteration until the location information of the layout with the minimum wake loss and the maximum power generation of the floating offshore wind farm is found.

[0025] Another object of the present invention is to provide a floating wind turbine mooring and positioning system for performing the floating wind turbine mooring and positioning method as described in any of the above embodiments, comprising:

[0026] The acquisition module is used to acquire measurement data of wind speed and direction and location information of wind turbine layout in floating offshore wind farms;

[0027] The mooring system modeling module is used to build mooring system models;

[0028] The database module is used to iteratively process any one of multiple design parameters using a genetic algorithm, while keeping other design parameters unchanged, and finally record the optimized wind turbine location coordinates to form a database of wind turbine location coordinates.

[0029] The offset calculation module is used to gradually adjust the position of the wind turbine until the mooring system reaches a balanced state, find the steady-state position of each mooring system, and calculate the offset of the wind turbine position relative to the initial layout.

[0030] The output module is used to establish the wake model of the floating offshore wind farm, and calculates the power generation and layout location information of each wind turbine based on the offset of each wind turbine's position. After comparison, the final output is the layout location information of the floating offshore wind farm with the minimum wake loss and the maximum power generation.

[0031] Another object of the present invention is to provide an electronic device comprising a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, the processor executing the instructions, the instructions including the floating wind turbine mooring and positioning method as described in any of the above embodiments.

[0032] Beneficial effects:

[0033] This floating wind turbine mooring and positioning method acquires wind speed and direction measurements and wind turbine layout information within a floating offshore wind farm. It then constructs a mooring system model to determine the maximum and minimum mooring line lengths. A genetic algorithm iteratively processes multiple design parameters while keeping other parameters constant, optimizing the wind turbine position coordinates and creating a mooring system design database. Based on the established wake model of the floating offshore wind farm, and considering the offset of each wind turbine's position, it calculates and outputs the power generation and layout information for each turbine until it finds the layout that minimizes wake loss and maximizes power generation. This method helps improve wind farm output power and reduce turbine fatigue load. This floating wind turbine mooring and positioning method, based on a genetic algorithm, optimizes the layout and finds the optimal wind turbine arrangement under multiple parameter constraints, significantly improving layout efficiency and power output. It can quickly adapt to different layout requirements, reducing air resistance and wake effects by rationally arranging the position and spacing of wind turbines, thus optimizing the overall grid's energy storage and dispatch capabilities. It can not only improve the power generation efficiency of wind farms, but also reduce construction costs and maintenance expenses during operation. It can also dynamically adjust the layout plan based on real-time meteorological data and marine environmental information to keep the wind turbines in the best working condition, thereby improving the reliability and stability of power generation and promoting more efficient construction and operation of offshore wind power projects. Attached Figure Description

[0034] Figure 1 This is a flowchart of the floating wind turbine mooring and positioning method provided in a specific embodiment of the present invention;

[0035] Figure 2 This is a schematic diagram of the mooring system after movement in the mooring system model of the wind turbine provided in a specific embodiment of the present invention;

[0036] Figure 3 This is a schematic diagram of the mooring system of a wind turbine generator provided in a specific embodiment of the present invention when the mooring system is in a static state.

[0037] Figure 4 This is a schematic diagram of the method for determining the initial azimuth angle of the mooring line of a wind turbine provided in a specific embodiment of the present invention. Detailed Implementation

[0038] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0039] In the description of this invention, unless otherwise explicitly specified and limited, the terms "connected," "linked," and "fixed" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0040] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0041] In the description of this embodiment, the terms "upper," "lower," "right," etc., refer to the orientation or positional relationship shown in the accompanying drawings. They are used only for ease of description and simplification of operation, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention. In addition, the terms "first" and "second" are used only for distinction in description and have no special meaning.

[0042] Please refer to Figures 1 to 4 In this embodiment, the mooring and positioning method for the floating wind turbine includes the following steps:

[0043] S1. Obtain measurement data of wind speed and direction in floating offshore wind farms and location information of wind turbine layout; S2. Construct a mooring system model for wind turbines to obtain the maximum and minimum lengths of mooring lines.

[0044] Steps S1 and S2 first utilize wind speed and direction measurements from the offshore wind farm, along with the layout and location information of the wind turbines, to calculate the maximum and minimum lengths of the mooring lines using a mooring system model. It is assumed that the original location and foundation type of the wind turbines are known in advance; the original location and anchoring location determine the shape of the movable range. To optimize the layout of floating wind turbines, the motion pattern of the mooring system must first be determined. It is necessary to investigate whether the assumed movable range of the wind turbines is the actual movable range, and to study different locations within this range to determine whether force balance can be achieved at these desired locations by adjusting the mooring line length. From this, the maximum and minimum lengths of the mooring lines can be obtained, allowing calculations to determine whether the wind turbines can be moved to these different locations via location mooring.

[0045] In addition, the wind farm parameters also include the set wind farm boundaries to prevent wind turbines from drifting outside the set boundaries; they also include sensitive areas of the wind farm to prevent wind turbines from entering sensitive areas (such as reef areas, protected areas, etc.) to avoid the risk of accidents; furthermore, they also include wind turbine power curves to calculate the power generation of wind turbines at different wind speeds and wind directions, which will not be elaborated here.

[0046] Figure 2 This is a schematic diagram of the mooring system after it has moved in the model of the wind turbine mooring system. The position of the wind turbine is represented by a circle, the left side shows the movement of the mooring system, and the right side shows the direction of the force on the mooring line.

[0047] Optionally, the mooring system model of the wind turbine is calculated using the following method, where: x0 and y0 are the initial layout coordinates of the wind turbine; x n and y n These are the coordinates of the wind turbine's position after it has been moved; x Fi and y Fi These are the coordinates of the cable guide; x Ai and y Ai These are the anchor coordinates of the mooring line; Δx i and Δy i is the distance from the center point of the wind turbine to the guide wire; i is the mooring line number; Li is the total length of the mooring line from the guide wire to the anchor; Hi(Li) is the horizontal component of the mooring line tension at the guide wire, which is a function of the mooring line length; di is the horizontal distance from the guide wire to the anchor; βi is the direction of the mooring line.

[0048] The horizontal distance from the cable guide to the anchor is: Where, x Fi and y Fi Represented as: Substituting into the above equation, we get:

[0049] The direction of the mooring line is:

[0050] The remaining free variables are the mooring line length Li, which changes the horizontal component of the mooring line tension Hi. Given the horizontal distance di from the guide to the anchor and the vertical distance h from the guide to the seabed, and neglecting environmental loads, the calculated horizontal tension Hi of the catenary mooring line is obtained. The components of the horizontal tension Hi in the x and y directions are expressed as: By calculating the two components of the horizontal tension Hi of the mooring line in the x and y directions, the displacement of each wind turbine is obtained, and the overall system force reaches equilibrium.

[0051] Furthermore, the horizontal distance from the guide to the anchor determines the minimum and maximum mooring line length. For example... Figure 3 As shown, the lower left corner is the anchor point on the seabed, and the upper right corner is the location of the wind turbine's guide cable. The curve connecting the two is the mooring line. In step S2, the maximum length of the mooring line is the length when the mooring line is fully slack, i.e., di+h; the minimum length of the mooring line is the length when the mooring line is taut, i.e., This allows us to determine the range of values ​​for the mooring line length, which facilitates reducing the data range for subsequent iterative calculations and improving computational efficiency.

[0052] In a preferred embodiment, the minimum length of the mooring line is the length of the taut mooring line. In such cases, vertical loads are generated at the anchorage points, which does not meet practical requirements. Therefore, the minimum length of the mooring line needs to be redefined. This embodiment addresses this by adding constraints during the optimization process. Static mooring analysis can be used to find the wind turbine location that provides force balance. Static mooring analysis can perform quasi-static mooring analysis on the mooring system, including any arrangement of the mooring line and platform. It can calculate the average offset of the wind turbine, the mooring balance force and the mooring line stiffness matrix, the tension of each mooring line, and the Jacobian determinant of the mooring line tension relative to the platform's degrees of freedom.

[0053] Specifically, the constraints for quasi-static mooring analysis are as follows: the maximum offset of the mooring system cannot exceed 1D (where D is the diameter of the wind turbine rotor); the maximum allowable pitch angle of the wind turbine is 10°; there is no vertical load on the anchor of the mooring system; and all mooring lines are catenary-shaped to obtain the minimum length of the mooring lines. This minimum length of the mooring lines ensures that there is no vertical load on the anchor, preventing the anchor from being pulled up and improving the reliability of the wind turbine.

[0054] In this embodiment, the floating wind turbines are passively rearranged according to wind direction and speed. Therefore, the layout of each wind turbine in the wind farm will be slightly different for each wind direction and speed. To achieve this layout, this embodiment creates a mooring system design database. The dynamic optimization of the floating wind turbines takes into account the impact of wind direction and mooring system displacement. Based on the original layout, a quasi-static mooring model is introduced to calculate the offset of each turbine, thereby repositioning the floating wind turbines and calculating their power generation. Ultimately, this achieves the rapid generation of a database of floating wind turbine layout schemes that meet the optimization objectives and constraints.

[0055] Optionally, an iterative method is used to gradually adjust the positions of the wind turbines until a balance is achieved between external forces and the internal forces of the mooring system, thus finding the steady-state position of each mooring system. The horizontal tension of the guide wire is calculated based on the mooring line length, and the two components of the horizontal tension Hi in the x and y directions are obtained, ultimately yielding the displacement of each wind turbine. This ensures that the wind turbines are positioned in balance between external forces (incoming wind direction and speed) and internal forces (stress on the mooring line), enabling the rapid generation of a database of floating wind turbine layout schemes that meet optimization objectives and constraints, and ultimately obtaining the minimum mooring line length that satisfies the constraints.

[0056] Specifically, in step S3, a mooring system design database is created: a genetic algorithm is used to iteratively process multiple design parameters while keeping other parameters constant. These design parameters include fixed and variable parameters. Fixed parameters include: a water depth setting h, the number of mooring lines n in each mooring system, a mooring line diameter a, an anchoring radius R (ranging from 2.5D to 3.5D), the initial azimuth angle of the mooring lines (with the wind turbine mooring lines forming equilateral triangles and the angle between adjacent mooring lines fixed at 120°), and a mooring line length setting b. Variable parameters include: the offset of the wind turbine position relative to the initial layout. Finally, the optimized wind turbine position coordinates are recorded. Here, the units for water depth, mooring line diameter, anchoring radius, and mooring line length are all meters. The genetic algorithm, as an intelligent optimization technique, iteratively calculates and continuously approaches the optimal solution by simulating the biological genetic evolution process. Specifically, the genetic algorithm first randomly generates a set of possible wind turbine layout schemes. Then, it evaluates the merits of each scheme through a fitness function, selecting the better solution for "breeding" (i.e., combination and crossover). A mutation mechanism is introduced to ensure the diversity of the search space. This method shows superiority in handling high-dimensional, multi-objective problems, and can quickly adapt to different layout requirements, thereby promoting more efficient construction and operation of offshore wind power projects.

[0057] Optionally, when using a genetic algorithm to iteratively process multiple design parameters, a new generation of individuals is continuously generated through selection, crossover, and mutation operations: the selection operation uses roulette wheel selection, the crossover operation involves exchanging offsets between two parents, and the mutation operation introduces random variations. During optimization, the improved genetic algorithm continuously generates a new generation of individuals through selection, crossover, and mutation operations. The selection operation uses roulette wheel selection to ensure that individuals are more likely to enter the next generation; the crossover operation can exchange offsets between two parents to generate new layout schemes, while the mutation operation introduces small random variations to generate different optimization schemes. After multiple generations of iteration, the algorithm will converge to the solution corresponding to the fitness, ultimately finding the optimal offset.

[0058] Furthermore, in step S3, when determining the initial azimuth of the mooring lines, one mooring line is aligned directly with the prevailing wind direction, while the other two mooring lines are set at a preset angle, corresponding to the inflow direction of the prevailing wind. Existing floating wind farms such as Hywind, WindFloat Atlantic 2, and Kincardine, as well as relevant definitions in regulations, have adopted the above method when determining the initial azimuth of the mooring lines. Figure 4 As shown, this ensures that in the mooring system, one mooring line is directly aligned with the prevailing wind direction, while the other two mooring lines are arranged at an angle that precisely corresponds to the inflow direction of the prevailing wind. This embodiment adopts the above method to design the initial azimuth angle of the mooring lines. Once the initial azimuth angle is determined, the specific location of the anchoring point is also determined, ensuring the scientific and practical nature of the mooring system design.

[0059] S4. The offset of the wind turbine position relative to the initial layout in step S3 is calculated using an iterative method: the wind turbine position is gradually adjusted until the mooring system reaches equilibrium, the steady-state position of each mooring system is found, and the offset of the wind turbine position relative to the initial layout is calculated. As mentioned above, this ensures that the wind turbine position is in balance between external forces (incoming wind direction and speed) and internal forces (stress of the mooring line), achieving the goal of quickly generating a database of floating wind turbine layout schemes that meet the optimization objectives and constraints in step S3.

[0060] S5. During the iteration process, a wake model of the floating offshore wind farm is established. Based on the offset of each wind turbine's position, the power generation and layout information of each wind turbine are calculated and output until the layout with the minimum wake loss and maximum power generation of the floating offshore wind farm is found. Considering the offset of each wind turbine caused by the mooring system, the process is iterated and optimized multiple times until the layout with the minimum wake loss and maximum annual net power generation of the floating wind farm is found. The optimization ends at this point. Finally, the impact of different wake models on the annual power generation of the floating wind turbines is compared, as well as the impact of dynamic layout optimization and static layout optimization on the annual power generation, to evaluate the difference in power generation efficiency between floating and stationary wind turbines.

[0061] Optionally, in step S5, a wake model of the floating offshore wind farm is established. The wake model used includes analytical wake models and computational wake models. The analytical wake model includes any one of the Jensen wake model, Frandsen wake model, Bastankhah wake model, and Larsen wake model. Different wake models are selected and iterated until the location information of the layout of the floating offshore wind farm with the minimum wake loss and the maximum power generation is found. Since different wake models have different effects on the power generation calculation output of floating wind turbines, it is necessary to consider different wake models to output the optimal result of the optimal wind turbine location layout. Under the constraints of multiple parameters, the optimal wind turbine arrangement scheme is found, which greatly improves the layout efficiency and power output of the wind farm.

[0062] This floating wind turbine mooring and positioning method acquires wind speed and direction measurements and wind turbine layout information within a floating offshore wind farm. It then constructs a mooring system model to determine the maximum and minimum mooring line lengths. A genetic algorithm iteratively processes multiple design parameters while keeping other parameters constant, optimizing the wind turbine position coordinates and creating a mooring system design database. Based on the established wake model of the floating offshore wind farm, and considering the offset of each wind turbine's position, it calculates and outputs the power generation and layout information for each turbine until it finds the layout that minimizes wake loss and maximizes power generation. This method helps improve wind farm output power and reduce turbine fatigue load. This floating wind turbine mooring and positioning method, based on a genetic algorithm, optimizes the layout and finds the optimal wind turbine arrangement under multiple parameter constraints, significantly improving layout efficiency and power output. It can quickly adapt to different layout requirements, reducing air resistance and wake effects by rationally arranging the position and spacing of wind turbines, thus optimizing the overall grid's energy storage and dispatch capabilities. It can not only improve the power generation efficiency of wind farms, but also reduce construction costs and maintenance expenses during operation. It can also dynamically adjust the layout plan based on real-time meteorological data and marine environmental information to keep the wind turbines in the best working condition, thereby improving the reliability and stability of power generation and promoting more efficient construction and operation of offshore wind power projects.

[0063] This embodiment also provides a floating wind turbine mooring and positioning system. This system is used to execute the floating wind turbine mooring and positioning method described in any of the above schemes. It includes an acquisition module, a mooring system modeling module, a database module, an offset calculation module, and an output module. The acquisition module acquires measurement data of wind speed and direction in the floating offshore wind farm and the location information of the wind turbine layout. The mooring system modeling module constructs a mooring system model. The database module iteratively processes any one of multiple design parameters using a genetic algorithm while keeping other design parameters constant, ultimately recording... The system records the optimized wind turbine location coordinates to form a database of wind turbine location coordinates. The offset calculation module is used to gradually adjust the wind turbine positions until the mooring system reaches a balanced state, find the steady-state position of each mooring system, and calculate the offset of the wind turbine position relative to the initial layout. The output module is used to establish a wake model of the floating offshore wind farm, and calculate and output the power generation and layout location information of each wind turbine based on the offset of each wind turbine position. After comparison, the final output is the location information of the layout of the floating offshore wind farm with the minimum wake loss and the maximum power generation.

[0064] Regarding the floating wind turbine mooring and positioning system in the above embodiments, the specific methods by which each module performs its operation have been described in detail in the embodiments concerning the floating wind turbine mooring and positioning method, and will not be repeated here.

[0065] For this floating wind turbine mooring and positioning system, since it basically corresponds to the floating wind turbine mooring and positioning method, the relevant parts can be found in the description of the method embodiment. The floating wind turbine mooring and positioning system described above is merely illustrative; the modules may or may not be physically separated, and each module may or may not be a physical unit. That is, each module may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without any inventive effort.

[0066] This embodiment also provides an electronic device, which includes a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, and the processor executes the instructions, the instructions including the floating wind turbine mooring and positioning method as described in any of the above embodiments.

[0067] In particular, according to embodiments of this disclosure, the appendix referenced above... Figure 1 The process described in the flowchart can be implemented as a computer software program, i.e., instructions executed by a processor. Specifically, the electronic device in the embodiments of this disclosure is a computer device that executes a computer program. The computer device includes a computer program carried on a computer-readable medium, which contains program code for executing the floating wind turbine mooring and positioning method as described in any of the above embodiments. In such embodiments, the computer program can be downloaded and installed into a memory from a network via a communication module, or installed from a memory. When the computer program is executed by a processor, it can implement the floating wind turbine mooring and positioning method as described in any of the above embodiments, thereby enabling the rapid generation of a floating wind turbine layout scheme that meets the optimization objectives and constraints.

[0068] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0069] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art will be able to make various obvious changes, readjustments, and substitutions without departing from the scope of protection of the present invention. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for mooring and positioning floating wind turbine units, characterized in that, include: S1. Obtain measurement data of wind speed and direction and location information of wind turbine layout in floating offshore wind farms; S2. Construct a mooring system model for the wind turbine to obtain the maximum and minimum lengths of the mooring lines; S3. Create a mooring system design database: Use a genetic algorithm to iteratively process multiple design parameters while keeping other parameters constant. The design parameters include fixed and variable parameters. Fixed parameters include: water depth setting h, the number of mooring lines n in each mooring system, mooring line diameter a, anchoring radius R (ranging from 2.5D to 3.5D), initial azimuth angle of the mooring lines (the mooring lines for wind turbines are equilateral triangles with a fixed angle of 120° between adjacent mooring lines), and mooring line length setting b. Variable parameters include: the offset of the wind turbine position relative to the initial layout. Finally, record the optimized wind turbine position coordinates. S4. The offset of the wind turbine position relative to the initial layout in step S3 is calculated using an iterative method: gradually adjust the wind turbine position until the mooring system reaches equilibrium, find the steady-state position of each mooring system, and calculate the offset of the wind turbine position relative to the initial layout. S5. During the iteration process, establish a wake model of the floating offshore wind farm. Based on the offset of each wind turbine, calculate and output the power generation and layout location information of each wind turbine until the layout location information of the floating offshore wind farm with the minimum wake loss and the maximum power generation is found. When using a genetic algorithm to iteratively process multiple design parameters, a new generation of individuals is continuously generated through selection, crossover, and mutation operations: the selection operation uses roulette wheel selection, the crossover operation uses the exchange of offsets between two parents, and the mutation operation introduces random changes.

2. The method for mooring and positioning a floating wind turbine according to claim 1, characterized in that, The mooring system model for wind turbines is calculated using the following method: Where: x0 and y0 are the initial layout coordinates of the wind turbine; x n and y n These are the coordinates of the wind turbine's position after it has been moved; x Fi and y Fi These are the coordinates of the cable guide; x Ai and y Ai These are the anchor coordinates of the mooring line; Δx i and Δy i is the distance from the center point of the wind turbine to the guide wire; i is the mooring line number; Li is the total length of the mooring line from the guide wire to the anchor; Hi(Li) is the horizontal component of the mooring line tension at the guide wire, which is a function of the mooring line length; di is the horizontal distance from the guide wire to the anchor; βi is the direction of the mooring line. The horizontal distance from the cable guide to the anchor is: ; where x Fi and y Fi Represented as: Substituting into the above equation, we get: ; The direction of the mooring line is: ; The remaining free variables are the mooring line length Li, which changes the horizontal component of the mooring line tension Hi. Given the horizontal distance di from the guide to the anchor and the vertical distance h from the guide to the seabed, and neglecting environmental loads, the calculated horizontal tension Hi of the catenary mooring line is obtained. The components of the horizontal tension Hi in the x and y directions are expressed as: By calculating the two components of the horizontal tension Hi of the mooring line in the x and y directions, the displacement of each wind turbine is obtained, and the overall system force reaches equilibrium.

3. The method for mooring and positioning floating wind turbine units according to claim 2, characterized in that, In step S2, the maximum length of the mooring line is the length when the mooring line is fully slack, that is... The minimum length of the mooring line is the length of the mooring line when it is taut, that is... .

4. The mooring and positioning method for floating wind turbine units according to claim 3, characterized in that, Quasi-static mooring analysis was conducted with the following constraints: the maximum offset of the mooring system cannot exceed 1D; the maximum allowable pitch angle of the wind turbine is 10°; there is no vertical load on the anchor of the mooring system; and all mooring lines are catenary-shaped to obtain the minimum length of the mooring lines.

5. The method for mooring and positioning a floating wind turbine according to claim 2, characterized in that, An iterative method is used to gradually adjust the position of the wind turbines until a balance is achieved between the external forces and the internal forces of the mooring system, thus finding the steady-state position of each mooring system. The horizontal tension of the guide wire is calculated based on the length of the mooring line, and the two components of the horizontal tension Hi in the x and y directions are obtained. Finally, the displacement of each wind turbine is obtained.

6. The mooring and positioning method for floating wind turbine units according to claim 1, characterized in that, In step S3, when determining the initial azimuth of the mooring lines, one of the mooring lines is aligned directly with the prevailing wind direction, while the other two mooring lines are set at a preset angle, which corresponds to the inflow direction of the prevailing wind direction.

7. The method for mooring and positioning a floating wind turbine according to claim 1, characterized in that, In step S5, a wake model of the floating offshore wind farm is established. The wake model used includes analytical wake models and computational wake models. The analytical wake model includes any one of the Jensen wake model, Frandsen wake model, Bastankhah wake model, and Larsen wake model. Different wake models are selected for iteration until the location information of the layout with the minimum wake loss and the maximum power generation of the floating offshore wind farm is found.

8. A floating wind turbine mooring and positioning system, characterized in that, A method for performing the mooring and positioning of a floating wind turbine as described in any one of claims 1-7, comprising: The acquisition module is used to acquire measurement data of wind speed and direction and location information of wind turbine layout in floating offshore wind farms; The mooring system modeling module is used to build mooring system models; The database module is used to iteratively process any one of multiple design parameters using a genetic algorithm, while keeping other design parameters unchanged, and finally record the optimized wind turbine location coordinates to form a database of wind turbine location coordinates. The offset calculation module is used to gradually adjust the position of the wind turbine until the mooring system reaches a balanced state, find the steady-state position of each mooring system, and calculate the offset of the wind turbine position relative to the initial layout. The output module is used to establish the wake model of the floating offshore wind farm. Based on the offset of each wind turbine, it calculates and outputs the power generation and layout location information of each wind turbine. After comparison, it finally outputs the layout location information of the floating offshore wind farm with the minimum wake loss and the maximum power generation.

9. An electronic device, characterized in that, The system includes a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, the processor executing the instructions, the instructions including a floating wind turbine mooring and positioning method as described in any one of claims 1-7.

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