Wind power plant layout optimization method and device based on annular rule and medium

Abstract

The invention relates to the technical field of wind power plant micro-siting, and particularly provides a wind power plant layout optimization method and device based on an annular rule and a medium, and the method comprises the steps: obtaining the attribute information of a to-be-optimized wind power plant; randomly generating a shape variable of an annular rule based on the attribute information and establishing an initial population; based on the global center point coordinate, the ring distance starting point proportion and the in-ring starting point ray angle in the shape variable, the arrangement scheme of the wind turbine generator is obtained; optimizing the arrangement scheme based on the initial population and the optimization target; when the optimization target reaches a preset convergence condition, obtaining an optimal arrangement scheme; according to the method, the arrangement scheme of the wind turbine generators is determined by using the global center point coordinates, the ring distance starting point proportion, the in-ring starting point ray angle and other parameters, the in-field space can be fully utilized, arrangement is more regular, and convenience is brought to in-field current collection line planning; traversal calculation is not needed, the number of times of adjustment and optimization is reduced, and the mathematical optimal solution of the wind turbine generator point location is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind farm micro-site selection, and in particular to a wind farm layout optimization method, equipment and medium based on a ring rule. Background Art

[0002] As an important driving force for the transformation to clean energy, wind energy is driving the construction of wind farms towards large-scale and base-based development. In this context, the optimization of wind turbine layout has become the key to improving the overall power generation efficiency and economic benefits of wind farms. Although traditional layout methods, such as manual layout or traversal layout based on the parallelogram rule, can guide the layout of wind farms to a certain extent, manual or traversal calculation methods are inefficient and it is difficult to ensure the true mathematical optimal solution.

[0003] The conventional parallelogram traversal layout often leaves a certain distance from the boundary of the wind farm, making it difficult to fully utilize the space within the farm. At the same time, wind farm planning also involves the design of the collection lines within the farm. In this regard, if the shape of the unit layout is more in line with the mainstream cable layout radiating outward from the booster station, it will bring convenience to the planning of the collection lines within the farm.

[0004] Accordingly, the art needs a new wind farm layout optimization solution based on the ring rule to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects, the present invention is proposed to solve or at least partially solve the technical problems that the existing manual or traversal calculation methods to obtain the layout plan are inefficient, it is difficult to obtain the true mathematical optimal solution for the location of the wind turbines, resulting in poor overall benefits of the wind farm, and it is difficult to fully utilize the space within the field, making the planning of the collection lines within the field complicated.

[0006] In a first aspect, a method for optimizing wind farm layout based on a ring rule is provided, the method comprising: Obtaining attribute information of the wind farm to be optimized; Randomly generate a circular regular shape variable based on the attribute information; An initial population is established based on the shape variables of the circular rule, wherein the initial population includes a plurality of individuals, each of which is a set of shape variables of the circular rule, and the shape variables of the circular rule include the coordinates of the global center point, the ratio of the starting point of the ring spacing, and the ray angle of the starting point within the ring; Obtaining an arrangement scheme of wind turbines in the wind farm to be optimized based on the global center point coordinates, the ring spacing starting point ratio, and the ray angle of the starting point within the ring; Based on the initial population and the preset optimization target, optimizing the arrangement scheme of the wind turbines in the wind farm to be optimized; When the preset optimization target reaches the preset convergence condition, the optimal arrangement scheme of the wind turbines in the wind farm to be optimized is obtained.

[0007] In a technical solution of the above-mentioned wind farm layout optimization method based on the ring rule, the attribute information includes the regional scope of the wind farm to be optimized; the shape variables of the ring rule also include the minimum spacing between rings, the minimum spacing within the ring, the ring spacing gradient coefficient and the inner ring spacing gradient coefficient; The shape variables of the ring rule randomly generated based on the attribute information include: Setting the distance between any two wind turbines in the wind farm to be optimized, wherein the distance between any two wind turbines in the wind farm to be optimized is greater than n times the diameter of the wind rotor, where n is a positive integer greater than 1; Based on the regional scope of the wind farm to be optimized, randomly selecting the coordinates of the global center point; Based on the uniform probability distribution and the distance between any two wind turbines in the wind farm to be optimized, the ring spacing starting point ratio is randomly selected within a preset ratio range, the ray angle of the starting point within the ring is randomly selected within a preset angle range, the minimum spacing between rings and the minimum spacing within the ring are randomly selected within a preset spacing range, and the ring spacing gradient coefficient and the inner ring spacing gradient coefficient are randomly selected within a preset coefficient range; The shape variables of the annular rule are obtained based on the global center point coordinates, the ring spacing starting point ratio, the ray angle of the starting point within the ring, the minimum spacing between rings, the minimum spacing within the ring, the ring spacing gradient coefficient and the inner ring spacing gradient coefficient.

[0008] In a technical solution of the above-mentioned method for optimizing the layout of wind farms based on the ring rule, the attribute information also includes the number of wind turbines in the wind farm to be optimized; The method for obtaining the arrangement scheme of wind turbines in the wind farm to be optimized comprises: Obtaining the line segments between the global center point coordinates and each vertex of the boundary of the wind farm to be optimized and the length of each line segment; Determine the ring spacing starting point of each connecting line segment based on the length of each connecting line segment and the ring spacing starting point ratio; Acquire a plurality of first gradient points on each connecting line segment on both sides of the ring spacing starting point of each connecting line segment, and obtain a plurality of rings similar to the boundary shape of the wind farm to be optimized based on the plurality of first gradient points on each connecting line segment; Based on the global center point coordinates and the ray angle of the starting point in the ring, a ray is obtained with the horizontal line of the regional range of the wind farm to be optimized as a reference; Acquire multiple intersection points where the ray intersects with multiple rings, take the multiple intersection points as the inner starting points corresponding to the multiple rings, and acquire multiple second gradient points on both sides of the inner starting point corresponding to each ring, wherein the second gradient points are coordinate points of the wind turbines in the wind farm to be optimized; An arrangement scheme of the wind turbine sets in the wind farm to be optimized is obtained based on a plurality of coordinate points of the wind turbine sets in the wind farm to be optimized.

[0009] In a technical solution of the above-mentioned wind farm layout optimization method based on the ring rule, the step of obtaining a plurality of first gradient points on each connecting line segment on both sides of the ring spacing starting point of each connecting line segment comprises: Obtaining the shortest distance from the global center point coordinates to the boundary of the wind farm to be optimized; Determine the minimum spacing between the first gradient points on each connecting line segment and the maximum number of the first gradient points based on the shortest distance, the length of each connecting line segment and the minimum spacing between the rings; Determine the inter-ring gradient interval on each connecting line segment based on the ring spacing gradient coefficient, the minimum spacing between the first gradient points on each connecting line segment, and the maximum number of the first gradient points; Based on the inter-ring gradient interval on each connecting line segment, a plurality of first gradient points on each connecting line segment are obtained on both sides of the starting point of the inter-ring interval of each connecting line segment.

[0010] In a technical solution of the above-mentioned wind farm layout optimization method based on the ring rule, obtaining multiple intersection points where the ray intersects with multiple rings, taking the multiple intersection points as the inner ring starting points corresponding to the multiple rings, and obtaining multiple second gradient points on both sides of the inner ring starting point corresponding to each ring includes: Get the circumference of each ring; Determine the maximum number of the second gradient points on each ring based on the minimum spacing within the ring and the circumference of each ring; Determine the intra-ring gradient interval on each ring based on the maximum number of the second gradient points on each ring, the minimum spacing within the ring, and the intra-ring spacing gradient coefficient; Based on the gradient interval within each ring, a plurality of second gradient points are acquired on both sides of the starting point within each ring corresponding to each ring, and the coordinate points of the plurality of second gradient points are obtained.

[0011] In a technical solution of the above-mentioned wind farm layout optimization method based on the ring rule, the preset convergence condition is that the target value of the preset optimization target is the maximum; The method further comprises: Optimizing based on the initial population to obtain optimized circular regular shape variables; Establishing an optimized population based on the shape variables of the optimized annular rule, and obtaining an optimized arrangement scheme of the wind turbines; When the target value of the preset optimization target reaches the maximum, the optimization process is terminated to obtain the optimal shape variables of the annular rule and the optimal arrangement scheme of the wind turbines in the wind farm to be optimized.

[0012] In a technical solution of the above-mentioned wind farm layout optimization method based on the ring rule, the preset optimization target is the total output power of the wind farm to be optimized under the arrangement scheme of the wind turbines; The method for obtaining the total output power of the wind farm to be optimized comprises: Acquiring wind resource information of the wind farm to be optimized, wherein the wind resource information includes the ambient incoming wind speed of the wind farm to be optimized; Based on the ambient incoming wind speed and arrangement scheme of the wind farm to be optimized, the total output power of the wind farm to be optimized is obtained according to a preset wind turbine wake model.

[0013] In a technical solution of the above-mentioned wind farm layout optimization method based on the ring rule, the preset wind turbine wake model includes a two-dimensional analytical model of the wind turbine wake and an additional turbulence intensity analytical model of the wind turbine wake; The step of obtaining the total output power of the wind farm to be optimized based on the wind speed and arrangement scheme of the wind farm to be optimized and according to a preset wake model comprises: Based on the analytical model of additional turbulence intensity of the wind turbine wake, the turbulence intensity of the wake of each wind turbine in the arrangement scheme is obtained; Based on the wake flow turbulence intensity of each wind turbine group, obtaining the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of each wind turbine group; Obtaining the inflow velocity loss at multiple points on the wind rotor of each wind turbine based on the two-dimensional analytical model of the wind turbine wake and the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of each wind turbine; Based on the inflow velocity loss at multiple points on the wind rotor of each wind turbine and the ambient incoming wind speed, the wind speed in front of the hub of each wind turbine is obtained; Based on the wind speed in front of the hub of each wind turbine set and a preset power curve of each wind turbine set, the output power of each wind turbine set is obtained; Based on the output power of each wind turbine generator set, the total output power of the wind farm to be optimized is obtained.

[0014] In a second aspect, an electronic device is provided, comprising at least one processor; and a memory communicatively connected to the at least one processor; wherein a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the method described in any one of the technical solutions of the above-mentioned wind farm layout optimization method based on the ring rule is implemented.

[0015] In a third aspect, a computer-readable storage medium is provided, wherein a plurality of program codes are stored therein, wherein the program codes are suitable for being loaded and run by a processor to execute the method described in any one of the technical solutions of the above-mentioned wind farm layout optimization method based on the ring rule.

[0016] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects: In the implementation of the technical solution of the wind farm layout optimization method based on the ring rule provided by the present invention, the attribute information of the wind farm to be optimized is obtained; the shape variables of the ring rule are randomly generated based on the attribute information and an initial population is established based on the shape variables; the layout scheme of the wind turbines in the wind farm to be optimized is obtained based on the global center point coordinates, the ring spacing starting point ratio and the ray angle of the starting point in the ring in the shape variables; the layout scheme is optimized based on the initial population and the preset optimization target; when the optimization target reaches the preset convergence condition, the optimal layout scheme of the wind turbines in the wind farm to be optimized is obtained; the present invention utilizes Using parameters such as the global center point coordinates, the ratio of the ring spacing starting point, and the ray angle of the starting point within the ring to determine the layout of the wind turbines can make full use of the space within the field, making the layout of the wind turbines more orderly and regular. The booster station can be more easily located at or near the center of the wind farm, which is more in line with the mainstream cable layout radiating outward from the booster station, bringing convenience to the planning of the collection lines within the field; there is no need to perform traversal calculations, which reduces the number of adjustments and optimizations and saves computing resources. At the same time, it can achieve the mathematical optimal solution for the location of the wind turbines, thereby improving the comprehensive benefits of the wind farm over its entire life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The disclosure of the present invention will become more easily understood with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention. Among them: Figure 1 It is a schematic flow chart of main steps of a method for optimizing wind farm layout based on a ring rule according to an embodiment of the present invention; Figure 2 is a flowchart of main steps for randomly generating shape variables of a circular rule based on attribute information according to one embodiment of the present invention; Figure 3It is a schematic diagram of the main steps of the layout plan of wind turbines in a wind farm to be optimized according to an embodiment of the present invention; Figure 4 It is a schematic diagram of generating the positions of wind farm units with shape variables based on the circular rule according to an embodiment of the present invention; Figure 5 It is a schematic diagram of the main steps of the method for obtaining multiple first gradient points according to an embodiment of the present invention; Figure 6 It is a schematic diagram of the main steps of the method for obtaining multiple second gradient points according to an embodiment of the present invention; Figure 7 It is a wind rose diagram according to an embodiment of the present invention; Figure 8 It is the power curve and thrust coefficient curve of the unit according to an embodiment of the present invention; Fig. 9 It is the original positions of wind turbines in the wind farm to be optimized according to an embodiment of the present invention; Fig.10 It is the optimization process evolution curve of the wind farm layout optimization method based on the circular rule according to an embodiment of the present invention; Fig.11 It is a schematic diagram of the positions of wind turbines in the wind farm to be optimized under the optimal layout plan based on the circular arrangement rule according to an embodiment of the present invention; Fig.12 It is a schematic diagram of the main structure of an electronic device according to an embodiment of the present invention.

[0018] Reference numerals: 121: Memory; 122: Processor. Detailed implementation manners

[0019] The following describes some implementation manners of the present invention with reference to the accompanying drawings. Those skilled in the art should understand that these implementation manners are only used to explain the technical principle of the present invention and are not intended to limit the protection scope of the present invention.

[0020] In the description of the present invention, a "module" and a "processor" may include hardware, software, or a combination of both. A module may include a hardware circuit, various appropriate sensors, communication ports, a memory, and may also include a software part, such as program code, or may be a combination of software and hardware. A processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other appropriate processor. The processor has data and / or signal processing functions. The processor may be implemented in software, in hardware, or in a combination of both. A computer-readable storage medium includes any appropriate medium that can store program code, such as a magnetic disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, and so on. The term "A and / or B" represents all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one of A or B" or "at least one of A and B" has a meaning similar to "A and / or B" and may include only A, only B, or A and B. The singular terms "a" and "the" may also include the plural form.

[0021] Refer to the attached Figure 1 , Figure 1 is a schematic diagram of the main steps of an optimization method for wind farm layout based on a circular rule according to an embodiment of the present invention. As Figure 1 shown, the optimization method for wind farm layout based on a circular rule in the embodiment of the present invention mainly includes the following steps S101 to S104.

[0022] Step S101: Obtain the attribute information of the wind farm to be optimized.

[0023] In this embodiment, the attribute information includes the regional scope of the wind farm to be optimized and the number of wind turbines. ; In one implementation, an appropriate wind turbine model can be selected according to the regional scope of the wind farm to be optimized, the number of wind turbines, and the installed capacity requirements.

[0024] Step S102: Randomly generate the shape variables of the circular rule based on the attribute information; establish an initial population based on the shape variables of the circular rule.

[0025] In this embodiment, the constraint conditions of the wind turbine coordinates are preset, and the constraint conditions include the regional scope of the wind farm to be optimized and the distance between any two wind turbines in the wind farm to be optimized. Among them, the distance between any two wind turbines in the wind farm to be optimized is greater than the wind wheel diameter D times of n , , n is a positive integer greater than 1; Optionally, the distance between any two wind turbines in the wind farm to be optimized is greater than four times the rotor diameter. It should be noted that the distance between any two wind turbines in the wind farm to be optimized in this embodiment being greater than four times the rotor diameter is only an example of an implementation manner and is not a limitation on this embodiment. In the actual application of the implementation manner of the present invention, the distance between any two wind turbines in the wind farm to be optimized can be set according to actual needs.

[0026] Based on the regional scope of the wind farm to be optimized, the number of wind turbines, and the distance between any two wind turbines in the wind farm to be optimized, randomly generate shape variables of an annular rule, and establish an initial population of a genetic algorithm. Among them, the initial population includes multiple individuals, and each individual is respectively a set of shape variables of an annular rule. The shape variables of the annular rule can be used to generate a corresponding and uniquely determined layout scheme of the wind turbines in the wind farm to be optimized based on a specific point-taking program.

[0027] In one implementation manner, real number coding is adopted to randomly generate shape variables of an annular rule and establish an initial population. The initial population contains multiple individuals, and each individual is a row vector containing 10 variables, that is ; each set of shape variables of the annular rule corresponds to a layout scheme of the wind farm units; among them, real number coding means representing each gene value of each individual with a floating point number within a certain range.

[0028] In this embodiment, the shape variables of the annular rule include the global center point coordinates , the starting point ratio of the ring spacing r , the starting ray angle within the ring θ , the minimum distance between rings , the minimum distance within the ring , the gradient coefficient of the ring spacing , and the gradient coefficient of the distance within the ring .

[0029] In this embodiment, referring to the appendix Figure 2 , Figure 2 is a schematic diagram of the main step flow for randomly generating shape variables of an annular rule according to an embodiment of the present invention. As Figure 2 shown, randomly generating shape variables of an annular rule based on attribute information includes: Step S201: Randomly select the global center point coordinates based on the regional scope of the wind farm to be optimized; Specifically, within the closed polygon of the regional scope of the wind farm to be optimized, randomly take out a point coordinate as the global center point coordinates of the annular rule layout .

[0030] Step S202: Based on the uniform probability distribution and the distance between any two wind turbines in the wind farm to be optimized, randomly select the starting point ratio of the ring spacing within a preset ratio range, randomly select the starting point ray angle of the ring within a preset angle range, randomly select the minimum inter-ring spacing and the minimum intra-ring spacing within a preset spacing range, and randomly select the ring spacing gradual change coefficient and the intra-ring spacing gradual change coefficient within a preset coefficient range; Specifically, according to the uniform probability distribution, randomly take out the starting point ratio of the ring spacing within the range of [0, 1). r , randomly take out the starting point ray angle of the ring within the range of [0°, 360°). θ , within , randomly take out the minimum inter-ring spacing and the minimum intra-ring spacing for the two parameters, randomly take out the ring spacing gradual change coefficient and for the two parameters, randomly take out the intra-ring spacing gradual change coefficient and for the two parameters.

[0031] Step S203: Obtain the shape variables of the circular rule based on the global center point coordinates, the starting point ratio of the ring spacing, the starting point ray angle of the ring, the minimum inter-ring spacing, the minimum intra-ring spacing, the ring spacing gradual change coefficient, and the intra-ring spacing gradual change coefficient.

[0032] Specifically, based on the global center point coordinates , the starting point ratio of the ring spacing r , the starting point ray angle of the ring θ , the minimum inter-ring spacing , the minimum intra-ring spacing , and the intra-ring spacing gradual change coefficient to obtain the shape variables of the circular rule .

[0033] Step S103: Obtain the layout scheme of the wind turbines in the wind farm to be optimized based on the global center point coordinates, the starting point ratio of the ring spacing, and the starting point ray angle of the ring.

[0034] In this embodiment, refer to the appendix Figure 3 , Figure 3 is the main step flow schematic diagram of the layout scheme of the wind turbines in the wind farm to be optimized according to an embodiment of the present invention. As Figure 3 shown, the method for obtaining the layout scheme of the wind turbines in the wind farm to be optimized includes: Step S301: Obtain the line segments connecting the global center point coordinates with the vertices of the boundary of the wind farm to be optimized and the length of each connecting line segment.

[0035] Specifically, referring to the attached Figure 4 , Figure 4 is a schematic diagram of generating the positions of wind farm turbines based on a circular rule for shape variables according to an embodiment of the present invention. As Figure 4 shown, the global center point coordinates and the vertices of the closed polygon boundary of the area range of the wind farm to be optimized are connected. The connection equation of the line segments is: , and the length of each connection line segment is determined to be , where is a vertex of a boundary of the area range of the wind farm to be optimized, is the total number of vertices of the closed polygon of the area range of the wind farm to be optimized; Step S302: Determine the starting points of the ring intervals for each connection line segment based on the length of each connection line segment and the starting point ratio of the ring interval.

[0036] Specifically, on the connection line segment between the global center point coordinates and the boundary point , based on the starting point ratio r of the ring interval, the starting point C of the ring interval on with a distance of from the global center point is taken; similarly, this process is repeated on other connection line segments to obtain the starting points of the ring interval on each connection line segment .

[0037] Step S303: Obtain multiple first gradient points on each connection line segment on both sides of the starting point of the ring interval for each connection line segment, and obtain multiple rings similar to the boundary shape of the wind farm to be optimized based on the multiple first gradient points on each connection line segment.

[0038] Specifically, as Figure 4 shown, on the connection line segment , starting from the starting point of the ring interval, a set of multiple first gradient points is taken on both sides towards the starting point of the ring interval according to the linear gradient point-taking method, where is the total number of gradient points (i.e., the total number of rings within the wind farm to be optimized); Based on the gradient points on the connection line segment , similarly, this process is repeated on other connection line segments, and other connection line segments The set of multiple first gradient points on is , where a certain first gradient point to the global center point coordinates the distance satisfies ; Based on the global center point coordinates and the wind farm boundary vertex the connecting line segment the set of first gradient points on , sorting to obtain multiple rings similar to the closed polygon boundary of the area range of the wind farm to be optimized, and the vertex set of each ring .

[0039] Refer to the appendix Figure 5 , Figure 5 is the main step flow schematic diagram of the method for obtaining multiple first gradient points according to an embodiment of the present invention. As Figure 5 shown, obtaining multiple first gradient points on each connecting line segment on both sides of the starting point of the ring spacing of each connecting line segment includes: Step S501: Obtain the shortest distance from the global center point coordinates to the boundary of the wind farm to be optimized; Specifically, obtain the global center point coordinates C to the shortest distance of the closed polygon boundary of the area range of the wind farm to be optimized.

[0040] Step S502: Based on the shortest distance, the length of each connecting line segment, and the minimum inter-ring spacing, determine the minimum spacing between the first gradient points on each connecting line segment and the maximum number of first gradient points; Specifically, for the connecting line segment , based on the current connecting line segment length , the minimum inter-ring spacing and the global center point C to the shortest distance of the wind farm boundary, determine that the minimum spacing between the first gradient points on the connecting line segment is , and the maximum number of first gradient points on the connecting line segment is at most , where is the largest integer not exceeding z; Similarly, repeat this process on each connecting line segment to determine the minimum spacing between the first gradient points on each connecting line segment and the maximum number of first gradient points.

[0041] Step S503: Determine the inter-ring gradient interval on each connection line segment based on the ring spacing gradient coefficient, the minimum spacing between the first gradient points on each connection line segment, and the maximum number of first gradient points. Specifically, for the connection line segment , consider the Gaussian distribution function with an average value of 0 , and uniformly extract numbers within the range of [-1, 1]. Then, according to the Gaussian distribution function, a set of inter-ring gradient intervals not less than on the connection line segment can be obtained as , where and are the ring spacing gradient coefficients; Similarly, repeat this process on each connection line segment to determine the inter-ring gradient interval on each connection line segment.

[0042] Step S504: Based on the inter-ring gradient interval on each connection line segment, obtain multiple first gradient points on both sides of the ring spacing starting point of each connection line segment.

[0043] Specifically, for the connection line segment , on the connection line segment , with the ring spacing starting point as the center, take points on both sides according to the set of inter-ring gradient intervals based on the Gaussian distribution, that is, take out first gradient points on both sides of ; Judge whether the first gradient points are within the range of the connection line segment , and remove the first gradient points that exceed the range. Then, the remaining first gradient points form the set ; Similarly, repeat this process on each connection line segment to determine multiple first gradient points obtained on each connection line segment.

[0044] Step S304: Based on the global center point coordinates and the in-ring starting point ray angle, obtain a ray with the horizontal line of the area range of the wind farm to be optimized as the reference.

[0045] Specifically, as Figure 4 shown, starting from the global center point coordinates , with the horizontal line of the area range of the wind farm to be optimized as the reference, make a ray θ with an emission angle of the in-ring starting point ray angle S .

[0046] Step S305: Obtain multiple intersection points where the ray intersects multiple rings. Using the multiple intersection points as the starting points inside the rings corresponding to the multiple rings, obtain multiple second gradient points on both sides of the starting points inside the rings corresponding to each ring, where the second gradient points are the coordinate points of the wind turbines in the wind farm to be optimized.

[0047] Specifically, as Figure 4 shown, the ray S intersects a certain ring at the intersection point . This point is called the starting point inside the ring on the ring ; On a certain ring , starting from the starting point inside the ring , according to the method of taking points by circular gradient, obtain the coordinate set of the second gradient points on this ring , where is the total number of second gradient points on the ring . Similarly, repeat this process on other rings to obtain the second gradient points on all rings. The second gradient points are the coordinate points of the wind turbines in the wind farm to be optimized.

[0048] Refer to Appendix Figure 6 , Figure 6 which is a schematic flow chart of the main steps of the method for obtaining multiple second gradient points according to an embodiment of the present invention. As Figure 6 shown, the method for obtaining multiple second gradient points includes: Step S601: Obtain the perimeter of each ring; Specifically, multiple first gradient points are connected correspondingly to form multiple rings, and obtain the perimeter of each ring .

[0049] Step S602: Based on the minimum distance inside the ring and the perimeter of each ring, determine the maximum number of second gradient points on each ring; Specifically, based on the perimeter of each ring , the minimum distance inside the ring , determine that the maximum number of second gradient points on each ring is at most , where is the largest integer not exceeding z.

[0050] Step S603: Based on the maximum number of second gradient points on each ring, the minimum distance inside the ring, and the gradient coefficient of the distance inside the ring, determine the gradient interval inside each ring; Specifically, for each ring , consider a Gaussian distribution function with a mean of 0 , uniformly extract within the range [-1, 1] numbers , then according to the Gaussian distribution function, for each ring on a set of ring inner gradient intervals not less than can be obtained, where and and are the ring inner spacing gradient coefficients.

[0051] Step S604: Based on the ring inner gradient intervals on each ring, obtain multiple second gradient points on both sides of the ring inner starting point corresponding to each ring, and obtain the coordinate points of the multiple second gradient points.

[0052] Specifically, as Figure 4 shown, on the ring , with the ring inner starting point as the center, and with the gradient intervals and as the radii, draw arcs in both the clockwise and counterclockwise directions, and respectively take the intersection points of the arcs and the ring and as the second gradient points. If there are multiple intersection points between the arc and the ring , then select the point whose connection slope with is closest to the slope of the side where is located as one second gradient point; Using the intersection point (or ) of the clockwise (or counterclockwise) arc obtained in the previous step as the center, and with the gradient intervals and as the radii, continue to draw arcs in the clockwise and counterclockwise directions, and take the intersection points of the arcs and the ring (or ) as the second gradient points, and repeat the above steps; If the distance and between the clockwise and counterclockwise intersection points obtained in a certain step of the circular gradient point selection satisfies , then stop taking points. If , then take the intersection point of the perpendicular bisector of the line connecting and and the ring as the last second gradient point within this ring; Organize all the second gradient points to form a set of the coordinates of the second gradient points .

[0053] Step S306: Obtain the layout plan of the wind turbines in the wind farm to be optimized based on the coordinate points of the wind turbines in multiple wind farms to be optimized.

[0054] Specifically, the set of the second gradient points on all the rings , as the shape variable of the current ring rule The uniquely determined layout plan of the wind farm units corresponding to it.

[0055] Step S104: Optimize the layout plan of the wind turbines in the wind farm to be optimized based on the initial population and the preset optimization goal; when the preset optimization goal reaches the preset convergence condition, obtain the optimal layout plan of the wind turbines in the wind farm to be optimized.

[0056] In this embodiment, the preset convergence condition is that the target value of the preset optimization goal is the largest; The method for optimizing the layout plan of the wind turbines in the wind farm to be optimized includes: Optimize based on the initial population to obtain the shape variable of the optimized ring arrangement rule; Establish an optimized population based on the shape variable of the optimized ring arrangement rule and obtain the optimized layout plan of the wind turbines; Until the target value of the preset optimization goal reaches the maximum, end the optimization process, and obtain the optimal shape variable of the ring arrangement rule and the optimal layout plan of the wind turbines in the wind farm to be optimized.

[0057] In one implementation, the layout plan of the wind turbines in the wind farm to be optimized is optimized based on the genetic algorithm as the optimization algorithm, and the genetic algorithm can be the NSGA-II algorithm.

[0058] In one implementation, the shape variable of the ring arrangement rule can be obtained by crossover and mutation based on the constraint conditions of the wind turbine coordinates to obtain a new shape variable of the ring arrangement rule.

[0059] In one implementation, the method for optimizing the initial population can be: set the optimization target value, and through the layout optimization process based on the optimization algorithm, and combine other frameworks to calculate the preset optimization goal, and iteratively obtain a series of layout plans of the wind turbines in the wind farm to be optimized that meet the requirements and have a globally better or optimal optimization target value. The specific optimization process of the initial population is as follows: (1) Population initialization. Optimized variables (including shape variables with circular arrangement rules) are randomly generated to form an initial population consisting of N individuals. Each individual is a definite layout plan, including the coordinates of N units. The optimized variables are encoded using real numbers, and the unit coordinates are randomly generated within the optimization constraints. If the available points of the generated circular arrangement rules do not fully meet the optimization constraints, or the number of points is less than the required number of units, the individual is regenerated until it meets the requirements.

[0060] (2) Crossover and mutation. In the present invention, the simulated binary crossover method is used for the crossover operation, and the mutation operation is carried out by adding Gaussian random numbers to the optimized variables (if the circular arrangement rule layout form is adopted, the shape variables are crossover-mutated). In the mutation operation, there is a probability of adding random numbers of two scales, large and small, to the variables. The Gaussian standard deviation of the large-scale mutation is set to and the Gaussian standard deviation of the small-scale mutation is set to , and the mutation probabilities and are set respectively.

[0061] (3) Combining parents and offspring. The parent population is combined with the offspring population generated by crossover and mutation to form a population of 2N individuals.

[0062] (4) Fast non-dominated sorting and crowding degree calculation. Calculate the optimized objective values of each individual in the combined population. According to the optimized objective values, non-dominated individuals in the combined population of parents and offspring are found in turn to divide the levels. In the same level, the individuals are sorted from small to large according to one objective to obtain the serial number i , and then calculate the crowding degree of the individual.

[0063] (5) Screening to obtain the dominant population. N individuals are selected from the combined population of parents and offspring using the obtained levels. If adding a certain level exactly exceeds the population size, then two individuals , are randomly selected using the elite strategy in this level, and the one with the larger crowding degree is selected until the required number of individuals is obtained.

[0064] (6) Convergence judgment. Return to (2) and repeat the steps until the number of iterations meets the requirements to obtain a convergent solution set. At this time, the convergent solution set is the optimized population.

[0065] In this embodiment, the preset optimized objective is the total output power of the wind farm to be optimized under the layout plan of the wind turbines; The method for obtaining the total output power of the wind farm to be optimized includes: Obtain the wind resource information of the wind farm to be optimized, where the wind resource information includes the ambient incoming wind speed of the wind farm to be optimized; Based on the ambient incoming wind speed of the wind farm to be optimized and the layout scheme of the wind turbines in the wind farm to be optimized, the total output power of the wind farm to be optimized is obtained according to a preset wind turbine wake model.

[0066] In this embodiment, the preset wind turbine wake model includes a two-dimensional analytical model of the wind turbine wake and an analytical model of the additional turbulence intensity of the wind turbine wake; Based on the ambient incoming wind speed of the wind farm to be optimized and the layout scheme of the wind turbines in the wind farm to be optimized, obtaining the total output power of the wind farm to be optimized according to the preset wake model includes: Obtaining the wake flow direction turbulence intensity of each wind turbine in the layout scheme based on the analytical model of the additional turbulence intensity of the wind turbine wake; Obtaining the additional incoming flow direction turbulence intensity at multiple points on the wind wheel of each wind turbine based on the wake flow direction turbulence intensity of each wind turbine; Obtaining the incoming flow velocity deficit at multiple points on the wind wheel of each wind turbine based on the two-dimensional analytical model of the wind turbine wake and the additional incoming flow direction turbulence intensity at multiple points on the wind wheel of each wind turbine; Obtaining the wind speed in front of the hub of each wind turbine based on the incoming flow velocity deficit at multiple points on the wind wheel of each wind turbine and the ambient incoming wind speed; Obtaining the output power of each wind turbine based on the wind speed in front of the hub of each wind turbine and the preset power curve of each wind turbine; Obtaining the total output power of the wind farm to be optimized based on the output power of each wind turbine.

[0067] In one embodiment, the method for obtaining the total output power of the wind farm to be optimized includes: Calculating the wake flow direction turbulence intensity of each wind turbine in the layout scheme, and the wake flow direction turbulence intensity of the wind turbine can be obtained according to the analytical model of the additional turbulence intensity of the wind turbine wake in the following formulas (1)-(6): (1) Where, is the thrust coefficient; is the atmospheric environmental turbulence intensity; D is the diameter of the wind turbine rotor; r is the lateral distance of the rotor axis; is the standard deviation of the Gaussian curve the same as the velocity deficit model; z is the vertical height.

[0068] Flow direction function is the maximum additional turbulence intensity of the wake cross-section at each flow direction position: (2) Where, ; ; For considering the correction value in the near wake region.

[0069] The spanwise function of formula (1) is: (3) Wherein, and take values as: (4) (5) is the vertical correction function: (6) For each wind turbine in the wind farm, according to the wake flow direction turbulence intensity at multiple points on the wind turbine rotor of the upstream wind turbine of the current wind turbine, the additional inflow direction turbulence intensity at multiple points on the wind turbine rotor of the current wind turbine is obtained: (7) Wherein, is the additional inflow direction turbulence intensity at point i on the rotor of the th unit of the current unit; is the wake flow direction turbulence intensity at point i on the rotor of the i th unit of the th unit; is a binary variable, when and only when the current i th unit is downstream of the j th unit , in other cases ; N is the number of wind turbines in the wind farm to be optimized.

[0070] According to the two-dimensional analytical model of the wind turbine wake and the additional inflow direction turbulence intensity at multiple points on the rotor of each wind turbine, the average velocity deficit of the wind turbine is obtained: (8) Wherein, is the thrust coefficient; is the actual expansion rate of the wake boundary; is the rotor radius; is the standard deviation of the spanwise distribution of the velocity deficit, taken as half of the wake width, and is also used as the wake radius, is the wake width.

[0071] Obtain the inflow velocity deficit at multiple points on the rotor of the current wind turbine based on the average velocity deficit at multiple points on the rotor of the upstream wind turbine of the current wind turbine: (9) Wherein, is the inflow velocity deficit at point i on the rotor of the current th wind turbine; is the average velocity deficit at point j on the rotor of the i th wind turbine by the th wind turbine; is a binary variable, which is i when and only when the current j th wind turbine is downstream of the th wind turbine, and in other cases; N is the number of wind turbines in the wind farm to be optimized.

[0072] Based on the inflow velocity deficits at multiple points on the rotor of the current wind turbine, take the average value to obtain the wind speed in front of the hub of the current wind turbine under the preset wind conditions: (10) Wherein, is the wind speed in front of the hub of the current i rd wind turbine; is the ambient incoming flow wind speed; At a wind speed of , and a wind direction angle of , obtain the wind speed in front of the hub of the current wind turbine and the power curve of the current wind turbine, and obtain the output power of the current wind turbine under the above wind conditions; wherein, the power curve of the wind turbine includes the corresponding relationship between the wind speed in front of the hub and the output power of the wind turbine.

[0073] Based on the output power corresponding to the above wind conditions, obtain the total output power of the wind farm to be optimized under the current layout plan: (11) Wherein, is the total output power of the wind farm to be optimized under the current layout plan; is the wind condition with a wind speed of and a wind direction of ; is the output power of the i th unit under the wind condition of ; is the frequency of the wind condition appearing; is the number of wind directions; is the number of wind speed segments taken under a single wind direction; N is the number of wind turbines.

[0074] In an application scenario according to an embodiment of the present invention, the regional vertices of the wind farm to be optimized can be , , and , the coordinate dimension is meters (m), the turbine model is Vestas-V80 turbine (Vestas-V80 turbine), the number of turbines is , the wind rose diagram is as shown in Figure 7 , the turbine power curve and the thrust coefficient curve are as shown in Figure 8 , the original turbine positions of the wind farm to be optimized are as shown in Fig. 9 . The available form of the available positions of the turbines in the wind farm to be optimized is the circular arrangement rule. It should be noted that the regional scope of the wind farm to be optimized, the coordinates of the regional vertices, the available form of the available positions of the turbines in the wind farm to be optimized, the turbine model, the number of turbines, etc. are only for illustrative purposes, and in actual applications, they can be set as needed.

[0075] The basic parameters of the wind farm to be optimized are shown in Table 1; Table 1 Wind farm parameters

[0076] Select the wind conditions of multiple wind directions and multiple wind speeds, and refer to Appendix Figure 7 for the probability values under each wind direction and wind speed. Figure 7 is the wind rose diagram according to an embodiment of the present invention. In Appendix Figure 7 , the central angle of the polar coordinate histogram represents the wind direction angle, and the height of the histogram represents the wind frequency. Figure 8 is the turbine power curve and the thrust coefficient curve according to an embodiment of the present invention. The ordinate Thrust Coefficient is the thrust coefficient, Power is the power (kw), and the abscissa Wind Speed is the wind speed (m / s). The optimization constraint conditions are the regional scope of the wind farm to be optimized, and the distance between any two wind turbines must be greater than 4 times the rotor diameter D . In this application scenario, flat terrain is selected, and the influence of complex terrain is not considered. It should be noted that the distance between any two wind turbines must be greater than 4 times the rotor diameter D , and the selection of flat terrain are both for illustrative purposes in this application scenario, and can be selected as needed in practice.

[0077] When performing the layout optimization of the wind farm to be optimized, the evolution curve of the optimization process is as shown in Appendix Fig.10 . Fig.10 It is the optimization process evolution curve of the wind farm layout optimization method based on the circular rule according to an embodiment of the present invention. The abscissa is the optimization iteration number (iteration), and the ordinate represents the maximum value of the annual power generation of the whole field under different layout schemes of the wind farm to be optimized (Annual Power / MWh). It can be seen from the appendix Fig.10 that as the number of iterations increases, the maximum value of the annual power generation of the whole field gradually rises and finally tends to converge. Fig. 9 It is the original wind turbine positions of the wind farm to be optimized according to an embodiment of the present invention, Fig.11 It is a schematic diagram of the wind turbine positions in the wind farm to be optimized under the optimal layout scheme based on the circular arrangement rule according to an embodiment of the present invention. It can be seen from Fig.11 that the optimal wind turbine positions in the wind farm have obvious characteristics of circular arrangement rule. The annual power generation corresponding to the wind turbine positions in the wind farm to be optimized under this optimal layout scheme is 266508.40 MWh. Compared with Fig. 9 the annual power generation of 261616.18 MWh corresponding to the original wind turbine positions of the wind farm to be optimized in

[0078] It should be noted that although the above steps are described in a specific order in the above embodiments, those skilled in the art can understand that in order to achieve the effects of the present invention, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders. These adjusted schemes are equivalent technical schemes to the technical schemes described in the present invention, and thus will also fall within the protection scope of the present invention.

[0079] Those skilled in the art can understand that all or part of the processes in the method of the above embodiment of the present invention can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above method embodiments can be realized. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable storage medium can include: any entity or device, medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc., that can carry the computer program code.

[0080] Another aspect of the present invention also provides a computer-readable storage medium.

[0081] In an embodiment of a computer-readable storage medium according to the present invention, the computer-readable storage medium may be configured to store a program for executing the method embodiment of the wind farm layout optimization method based on the ring rule described above. This program can be loaded and run by a processor to implement the above-mentioned wind farm layout optimization method based on the ring rule. For the sake of convenience of description, only the parts related to the embodiments of the present invention are shown. For the specific technical details not disclosed, please refer to the method part of the embodiments of the present invention. The computer-readable storage medium may be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiments of the present invention is a non-transitory computer-readable storage medium.

[0082] Another aspect of the present invention also provides an electronic device.

[0083] In an embodiment of an electronic device according to the present invention, the electronic device may include at least one processor; and a memory communicatively connected to the at least one processor; wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the method described in any of the above embodiments is implemented. Refer to the appended Fig.12 , Fig.12 It is exemplarily shown in the figure that the memory 121 and the processor 122 are communicatively connected through a bus.

[0084] In some embodiments of the present invention, the electronic device described in the present invention may be, but is not limited to, a mobile phone, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, a vehicle-mounted device, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), an augmented reality (AR) / virtual reality (VR) device, etc. The embodiments of the present invention do not make any limitations in this regard.

[0085] So far, the technical solution of the present invention has been described in conjunction with an embodiment shown in the drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A wind farm layout optimization method based on the ring rule, characterized in that: include: Obtaining attribute information of the wind farm to be optimized; Randomly generate a circular regular shape variable based on the attribute information; An initial population is established based on the shape variables of the circular rule, wherein the initial population includes a plurality of individuals, each of which is a set of shape variables of the circular rule, and the shape variables of the circular rule include the coordinates of the global center point, the ratio of the starting point of the ring spacing, and the ray angle of the starting point within the ring; Obtaining an arrangement scheme of wind turbines in the wind farm to be optimized based on the global center point coordinates, the ring spacing starting point ratio, and the ray angle of the starting point within the ring; Based on the initial population and the preset optimization target, optimizing the arrangement scheme of the wind turbines in the wind farm to be optimized; When the preset optimization target reaches the preset convergence condition, the optimal arrangement scheme of the wind turbines in the wind farm to be optimized is obtained.

2. The wind farm layout optimization method based on the ring rule according to claim 1 is characterized in that: The attribute information includes the regional scope of the wind farm to be optimized; the shape variables of the ring rule also include the minimum spacing between rings, the minimum spacing within a ring, the ring spacing gradient coefficient and the ring spacing gradient coefficient; The shape variables of the ring rule randomly generated based on the attribute information include: The distance between any two wind turbines in the wind farm to be optimized is set, wherein the distance between any two wind turbines in the wind farm to be optimized is greater than the diameter of the wind rotor. times, is a positive integer greater than 1; Based on the regional scope of the wind farm to be optimized, randomly selecting the coordinates of the global center point; Based on the uniform probability distribution and the distance between any two wind turbines in the wind farm to be optimized, the ring spacing starting point ratio is randomly selected within a preset ratio range, the ray angle of the starting point within the ring is randomly selected within a preset angle range, the minimum spacing between rings and the minimum spacing within the ring are randomly selected within a preset spacing range, and the ring spacing gradient coefficient and the inner ring spacing gradient coefficient are randomly selected within a preset coefficient range; The shape variables of the annular rule are obtained based on the global center point coordinates, the ring spacing starting point ratio, the ray angle of the starting point within the ring, the minimum spacing between rings, the minimum spacing within the ring, the ring spacing gradient coefficient and the inner ring spacing gradient coefficient.

3. The wind farm layout optimization method based on the ring rule according to claim 2 is characterized in that: The attribute information also includes the number of wind turbines in the wind farm to be optimized; The method for obtaining the arrangement scheme of wind turbines in the wind farm to be optimized comprises: Obtaining the line segments between the global center point coordinates and each vertex of the boundary of the wind farm to be optimized and the length of each line segment; Determine the ring spacing starting point of each connecting line segment based on the length of each connecting line segment and the ring spacing starting point ratio; Acquire a plurality of first gradient points on each connecting line segment on both sides of the ring spacing starting point of each connecting line segment, and obtain a plurality of rings similar to the boundary shape of the wind farm to be optimized based on the plurality of first gradient points on each connecting line segment; Based on the global center point coordinates and the ray angle of the starting point in the ring, a ray is obtained with the horizontal line of the regional range of the wind farm to be optimized as a reference; Acquire multiple intersection points where the ray intersects with multiple rings, take the multiple intersection points as the inner starting points corresponding to the multiple rings, and acquire multiple second gradient points on both sides of the inner starting point corresponding to each ring, wherein the second gradient points are coordinate points of the wind turbines in the wind farm to be optimized; An arrangement scheme of the wind turbine sets in the wind farm to be optimized is obtained based on a plurality of coordinate points of the wind turbine sets in the wind farm to be optimized.

4. The wind farm layout optimization method based on the ring rule according to claim 3 is characterized in that: The step of obtaining a plurality of first gradient points on each connecting line segment on both sides of the ring spacing starting point of each connecting line segment comprises: Obtaining the shortest distance from the global center point coordinates to the boundary of the wind farm to be optimized; Determine the minimum spacing between the first gradient points on each connecting line segment and the maximum number of the first gradient points based on the shortest distance, the length of each connecting line segment and the minimum spacing between the rings; Determine the inter-ring gradient interval on each connecting line segment based on the ring spacing gradient coefficient, the minimum spacing between the first gradient points on each connecting line segment, and the maximum number of the first gradient points; Based on the inter-ring gradient interval on each connecting line segment, a plurality of first gradient points on each connecting line segment are obtained on both sides of the starting point of the inter-ring interval of each connecting line segment.

5. The wind farm layout optimization method based on the ring rule according to claim 3 is characterized in that: The step of obtaining a plurality of intersection points where the ray intersects with the plurality of rings, taking the plurality of intersection points as the inner ring starting points corresponding to the plurality of rings, and obtaining a plurality of second gradient points on both sides of the inner ring starting point corresponding to each ring comprises: Get the circumference of each ring; Determine the maximum number of the second gradient points on each ring based on the minimum spacing within the ring and the circumference of each ring; Determine the intra-ring gradient interval on each ring based on the maximum number of the second gradient points on each ring, the minimum spacing within the ring, and the intra-ring spacing gradient coefficient; Based on the gradient interval within each ring, a plurality of second gradient points are acquired on both sides of the starting point within each ring corresponding to each ring, and the coordinate points of the plurality of second gradient points are obtained.

6. The wind farm layout optimization method based on the ring rule according to claim 1 is characterized in that: The preset convergence condition is that the target value of the preset optimization target is maximum; The method further comprises: Optimizing based on the initial population to obtain optimized circular regular shape variables; Establishing an optimized population based on the shape variables of the optimized annular rule, and obtaining an optimized arrangement scheme of the wind turbines; When the target value of the preset optimization target reaches the maximum, the optimization process is terminated to obtain the optimal shape variables of the annular rule and the optimal arrangement scheme of the wind turbines in the wind farm to be optimized.

7. The method for optimizing wind farm layout based on the ring rule according to claim 6 is characterized in that: The preset optimization target is the total output power of the wind farm to be optimized under the arrangement scheme of the wind turbines; The method for obtaining the total output power of the wind farm to be optimized comprises: Acquiring wind resource information of the wind farm to be optimized, wherein the wind resource information includes the ambient incoming wind speed of the wind farm to be optimized; Based on the ambient incoming wind speed and arrangement scheme of the wind farm to be optimized, the total output power of the wind farm to be optimized is obtained according to a preset wind turbine wake model.

8. The method for optimizing wind farm layout based on the ring rule according to claim 7 is characterized in that: The preset wind turbine wake model includes a two-dimensional analytical model of the wind turbine wake and an additional turbulence intensity analytical model of the wind turbine wake; The step of obtaining the total output power of the wind farm to be optimized based on the wind speed and arrangement scheme of the wind farm to be optimized and according to a preset wake model comprises: Based on the analytical model of additional turbulence intensity of the wind turbine wake, the turbulence intensity of the wake of each wind turbine in the arrangement scheme is obtained; Based on the wake flow turbulence intensity of each wind turbine group, obtaining the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of each wind turbine group; Obtaining the inflow velocity loss at multiple points on the wind rotor of each wind turbine based on the two-dimensional analytical model of the wind turbine wake and the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of each wind turbine; Based on the inflow velocity loss at multiple points on the wind rotor of each wind turbine and the ambient incoming wind speed, the wind speed in front of the hub of each wind turbine is obtained; Based on the wind speed in front of the hub of each wind turbine set and a preset power curve of each wind turbine set, the output power of each wind turbine set is obtained; Based on the output power of each wind turbine generator set, the total output power of the wind farm to be optimized is obtained.

9. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; Wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the wind farm layout optimization method based on the ring rule described in any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by a processor to execute the wind farm layout optimization method based on the ring rule according to any one of claims 1 to 8.

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