Wind farm layout optimization method, device and medium based on ring rule

Abstract

The present application relates to the technical field of wind farm micro-siting, and specifically provides a wind farm machine arrangement optimization method and device based on a ring rule, and a medium, comprising: obtaining attribute information of a wind farm to be optimized; randomly generating shape variables of a ring rule based on the attribute information and establishing an initial population; obtaining an arrangement scheme of wind turbine generators based on global center point coordinates, ring spacing starting point proportions and ring inner starting point ray angles in the shape variables; optimizing the arrangement scheme based on the initial population and an optimization target; and obtaining an optimal arrangement scheme when the optimization target reaches a preset convergence condition; the present application determines the arrangement scheme of wind turbine generators by using parameters such as global center point coordinates, ring spacing starting point proportions and ring inner starting point ray angles, can fully utilize the space in the field, makes the arrangement more regular, and brings convenience to the planning of the field power collection line; without performing traversal calculation, the number of adjustments and optimizations is reduced, and the mathematical optimal solution of the wind turbine generator point position is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wind farm micro-siting, in particular to a wind farm machine layout optimization method based on ring rules, a device and a medium. BACKGROUND

[0002] As an important driving force for clean energy transformation, wind energy is promoting the development of wind farm construction towards large-scale and base. Under this background, the layout optimization of wind turbines has become the key to improving the overall power generation efficiency and economic benefits of wind farms. Traditional machine layout methods, such as manual machine layout or traversal machine layout based on parallelogram rules, can guide the layout of wind farms to a certain extent, but the manual or traversal calculation method is inefficient and it is difficult to ensure that the real mathematical optimal solution is obtained.

[0003] The machine arrangement obtained by the conventional parallelogram traversal machine layout is often a certain distance away from the boundary of the wind farm, and it is difficult to fully utilize the space in the field. At the same time, the planning of the wind farm also involves the design of the collection line in the field. For this purpose, if the machine arrangement shape 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 line in the field.

[0004] Correspondingly, there is a need for a new wind farm machine layout optimization scheme based on ring rules to solve the above problems. SUMMARY

[0005] In order to overcome the above defects, the present application is proposed to solve or at least partially solve the technical problems that the manual or traversal calculation method obtains an arrangement scheme with low efficiency of the machine layout method, it is difficult to obtain the real mathematical optimal solution of the wind turbine point, which leads to poor comprehensive benefits of the wind farm, and it is difficult to fully utilize the space in the field, making the planning of the collection line in the field complicated.

[0006] In a first aspect, a wind farm machine layout optimization method based on ring rules is provided, the method comprising:

[0007] obtaining attribute information of a wind farm to be optimized;

[0008] randomly generating shape variables of ring rules based on the attribute information;

[0009] establishing an initial population based on the shape variables of the ring rules, wherein the initial population includes a plurality of individuals, each individual is a set of shape variables of ring rules, and the shape variables of the ring rules include global center point coordinates, ring spacing starting point proportion and ring inner starting point ray angle;

[0010] 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 proportion and the ring inner starting point ray angle;

[0011] optimizing the arrangement scheme of the wind turbines in the wind farm to be optimized based on the initial population and the preset optimization target;

[0012] When the preset optimization target reaches a preset convergence condition, an optimal arrangement scheme of the wind turbines in the wind farm to be optimized is obtained.

[0013] In one of the technical solutions of the wind farm wind turbine arrangement optimization method based on the ring rule, the attribute information comprises a region range of the wind farm to be optimized; and the shape variable of the ring rule further comprises an inter-ring minimum distance, an intra-ring minimum distance, an inter-ring distance gradual change coefficient, and an intra-ring distance gradual change coefficient.

[0014] The shape variable of the ring rule is randomly generated based on the attribute information, and comprises:

[0015] A distance between any two wind turbines in the wind farm to be optimized is set, where the distance between any two wind turbines in the wind farm to be optimized is greater than n times of a rotor diameter, and n is a positive integer greater than 1.

[0016] The global center point coordinate is randomly selected based on the region range of the wind farm to be optimized.

[0017] The inter-ring distance starting point proportion is randomly selected within a preset proportion range, the intra-ring starting point ray angle is randomly selected within a preset angle range, the inter-ring minimum distance and the intra-ring minimum distance are randomly selected within a preset distance range, and the inter-ring distance gradual change coefficient and the intra-ring distance gradual change coefficient are randomly selected within a preset coefficient range based on the uniform probability distribution and the distance between any two wind turbines in the wind farm to be optimized.

[0018] The shape variable of the ring rule is obtained based on the global center point coordinate, the inter-ring distance starting point proportion, the intra-ring starting point ray angle, the inter-ring minimum distance, the intra-ring minimum distance, the inter-ring distance gradual change coefficient, and the intra-ring distance gradual change coefficient.

[0019] In one of the technical solutions of the wind farm wind turbine arrangement optimization method based on the ring rule, the attribute information further comprises a number of wind turbines in the wind farm to be optimized.

[0020] The arrangement scheme of the wind turbines in the wind farm to be optimized is obtained by:

[0021] The global center point coordinate and a length of each connecting line segment between the global center point coordinate and each vertex of a boundary of the wind farm to be optimized are obtained.

[0022] An inter-ring distance starting point of each connecting line segment is determined based on the length of each connecting line segment and the inter-ring distance starting point proportion.

[0023] a plurality of first gradient points on each connecting line segment are obtained on both sides of the ring interval starting point of each connecting line segment, and a plurality of ring shapes similar to the boundary shape of the wind farm to be optimized are obtained based on the plurality of first gradient points on each connecting line segment;

[0024] a ray is obtained based on the global center point coordinate and the ring inner starting point ray angle, and the ray is taken as a reference of the horizontal line of the area range of the wind farm to be optimized;

[0025] a plurality of intersection points of the ray intersecting with the plurality of ring shapes are obtained, and a plurality of second gradient points are obtained on both sides of the ring inner starting point corresponding to each ring shape, wherein the second gradient points are coordinate points of wind turbines in the wind farm to be optimized;

[0026] a layout scheme of wind turbines in the wind farm to be optimized is obtained based on a plurality of coordinate points of wind turbines in the wind farm to be optimized.

[0027] In one of the above technical solutions of the wind farm layout optimization method based on the ring rule, the plurality of first gradient points on each connecting line segment are obtained on both sides of the ring interval starting point of each connecting line segment, comprising:

[0028] the shortest distance from the global center point coordinate to the boundary of the wind farm to be optimized is obtained;

[0029] the minimum distance between the first gradient points on each connecting line segment and the maximum number of the first gradient points are determined based on the shortest distance, the length of each connecting line segment and the minimum ring interval;

[0030] the ring interval gradient interval on each connecting line segment is determined based on the ring interval gradient coefficient, the minimum distance between the first gradient points on each connecting line segment and the maximum number of the first gradient points;

[0031] the plurality of first gradient points on each connecting line segment are obtained on both sides of the ring interval starting point of each connecting line segment based on the ring interval gradient interval on each connecting line segment.

[0032] In one of the above technical solutions of the wind farm layout optimization method based on the ring rule, the plurality of intersection points of the ray intersecting with the plurality of ring shapes are obtained, and the plurality of second gradient points are obtained on both sides of the ring inner starting point corresponding to each ring shape, comprising:

[0033] the circumference of each ring is obtained;

[0034] the maximum number of the second gradient points on each ring is determined based on the ring inner minimum distance and the circumference of each ring.

[0035] determining an intra-ring gradient interval on each ring shape based on the maximum number of the second gradient points on the ring shape, the minimum distance within the ring shape, and the intra-ring distance gradient coefficient;

[0036] obtaining a plurality of second gradient points on both sides of the corresponding intra-ring starting point of each ring shape based on the intra-ring gradient interval on each ring shape, and obtaining coordinate points of the plurality of second gradient points.

[0037] In one of the technical solutions of the wind farm layout optimization method based on the ring shape rule, the preset convergence condition is that a target value of the preset optimization target is maximum.

[0038] The method further includes:

[0039] optimizing the initial population as a benchmark to obtain a shape variable of the optimized ring shape rule;

[0040] establishing an optimized population based on the shape variable of the optimized ring shape rule, and obtaining an optimized layout scheme of the wind turbine generator;

[0041] until the target value of the preset optimization target reaches the maximum, the optimization process is ended, and an optimal shape variable of the ring shape rule and an optimal layout scheme of the wind turbine generator in the wind farm to be optimized are obtained.

[0042] In one of the technical solutions of the wind farm layout optimization method based on the ring shape rule, the preset optimization target is a total output power of the wind farm to be optimized under the layout scheme of the wind turbine generator.

[0043] The method for obtaining the total output power of the wind farm to be optimized includes:

[0044] obtaining wind resource information of the wind farm to be optimized, wherein the wind resource information includes an ambient inflow wind speed of the wind farm to be optimized;

[0045] obtaining the total output power of the wind farm to be optimized according to a preset wind turbine generator wake model based on the ambient inflow wind speed and the layout scheme of the wind farm to be optimized.

[0046] In one of the technical solutions of the wind farm layout optimization method based on the ring shape rule, the preset wind turbine generator wake model includes a wind turbine generator wake two-dimensional analytical model and a wind turbine generator wake additional turbulence intensity analytical model.

[0047] The method for obtaining the total output power of the wind farm to be optimized according to a preset wind turbine generator wake model based on the ambient inflow wind speed and the layout scheme of the wind farm to be optimized includes:

[0048] obtaining the inflow additional flow direction turbulence intensity of a plurality of point positions on the wind wheel of each wind turbine based on the flow direction turbulence intensity of the wake of each wind turbine;

[0049] obtaining the inflow additional flow direction turbulence intensity of a plurality of point positions on the wind wheel of each wind turbine based on the flow direction turbulence intensity of the wake of each wind turbine;

[0050] obtaining the inflow velocity deficit of a plurality of point positions on the wind wheel of each wind turbine based on the two-dimensional analytical model of the wake of the wind turbine and the inflow additional flow direction turbulence intensity of the plurality of point positions on the wind wheel of each wind turbine;

[0051] obtaining the hub front wind speed of each wind turbine based on the inflow velocity deficit of a plurality of point positions on the wind wheel of each wind turbine and the ambient inflow wind speed;

[0052] obtaining the output power of each wind turbine based on the hub front wind speed of each wind turbine and the preset power curve of each wind turbine;

[0053] obtaining the total output power of the wind farm to be optimized based on the output power of each wind turbine.

[0054] In a second aspect, an electronic device is provided, which includes at least one processor; and a memory connected with the at least one processor in communication; wherein the memory has stored therein a computer program, and the computer program is executed by the at least one processor to implement the method of any one of the technical solutions of the wind farm layout optimization method based on the ring rule.

[0055] In a third aspect, a computer readable storage medium is provided, which has stored therein a plurality of program codes, and the program codes are adapted to be loaded and run by a processor to execute the method of any one of the technical solutions of the wind farm layout optimization method based on the ring rule.

[0056] The one or more technical solutions of the present application have at least one or more of the following beneficial effects:

[0057] In the implementation of the wind farm layout optimization method based on the ring rule provided by the application, the attribute information of the wind farm to be optimized is obtained; the shape variable of the ring rule is randomly generated based on the attribute information, and the initial population is established based on the shape variable; the arrangement scheme of the wind turbine generator in the wind farm to be optimized is obtained based on the global center point coordinate, the ring spacing starting point proportion and the ring inner starting point ray angle in the shape variable; the arrangement scheme is optimized based on the initial population and the preset optimization target; when the optimization target reaches the preset convergence condition, the optimal arrangement scheme of the wind turbine generator in the wind farm to be optimized is obtained; the arrangement scheme of the wind turbine generator is determined by using the global center point coordinate, the ring spacing starting point proportion and the ring inner starting point ray angle and other parameters, the space in the field can be fully utilized, the arrangement of the wind turbine generator is more orderly and regular, the booster station can be more easily positioned at the center or near the wind farm, and the cable layout from the booster station outward is more compliant, which brings convenience for the field power collection line planning; without traversal calculation, the number of adjustment and optimization is reduced, the calculation resources are saved, and the mathematical optimal solution of the wind turbine generator point position can be realized, so that the comprehensive benefit of the whole life cycle of the wind farm is improved. BRIEF DESCRIPTION OF DRAWINGS

[0058] The disclosure of the application will become more apparent with reference to the 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 application. Among them:

[0059] Figure 1 It is the main step flow diagram of the wind farm layout optimization method based on the ring rule according to an embodiment of the application;

[0060] Figure 2 It is the main step flow diagram of the ring rule shape variable randomly generated based on the attribute information according to an embodiment of the application;

[0061] Figure 3 It is the main step flow diagram of the arrangement scheme of the wind turbine generator in the wind farm to be optimized according to an embodiment of the application;

[0062] Figure 4 It is the diagram of the wind farm generator point position generated based on the ring rule shape variable according to an embodiment of the application;

[0063] Figure 5 It is the main step flow diagram of the acquisition method of the plurality of first gradual change points according to an embodiment of the application;

[0064] Figure 6 It is the main step flow diagram of the acquisition method of the plurality of second gradual change points according to an embodiment of the application;

[0065] Figure 7 is a wind rose diagram according to an embodiment of the present application;

[0066] Figure 8 is a power curve and a thrust coefficient curve of an engine according to an embodiment of the present application;

[0067] Figure 9 is a raw wind turbine site to be optimized in a wind farm according to an embodiment of the present application;

[0068] Figure 10 is an optimization process evolution curve of a wind farm layout optimization method based on a ring arrangement rule according to an embodiment of the present application;

[0069] Figure 11 is a wind turbine site to be optimized in a wind farm under an optimal arrangement scheme based on a ring arrangement rule according to an embodiment of the present application;

[0070] Figure 12 is a main structure diagram of an electronic device according to an embodiment of the present application.

[0071] Reference Signs:

[0072] 121: memory; 122: processor. DETAILED DESCRIPTION

[0073] Some embodiments of the present application will be described below with reference to the accompanying drawings. It will be understood by those skilled in the art that these embodiments are merely for the purpose of explaining the technical principles of the present application, and are not intended to limit the scope of protection of the present application.

[0074] In the description of the present application, "module" and "processor" can include hardware, software or a combination of both. A module can include a hardware circuit, various suitable sensors, communication ports, memories, and can also include a software part such as program codes, and can be a combination of software and hardware. The processor can be a central processing unit, a microprocessor, a graphic processing unit, a digital signal processor or any other suitable processor. The processor has data and / or signal processing functions. The processor can be implemented in software, hardware or a combination of both. The computer readable storage medium includes any suitable medium that can store program codes, such as a magnetic disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B or both A and B. The term "at least one of A or B" or "at least one of A and B" has a similar meaning as "A and / or B", and can include only A, only B or both A and B. The singular form of the term "one", "this" can also include the plural form.

[0075] Reference will now be made toFigure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a wind farm turbine deployment optimization method based on ring rules, according to an embodiment of the present invention. Figure 1 As shown, the wind farm deployment optimization method based on ring rules in this embodiment of the invention mainly includes the following steps S101 to S104.

[0076] Step S101: Obtain the attribute information of the wind farm to be optimized.

[0077] In this embodiment, the attribute information includes the area of ​​the wind farm to be optimized and the number of wind turbines. ;

[0078] In one implementation, a suitable wind turbine model can be selected based on the area of ​​the wind farm to be optimized, the number of wind turbines, and the installed capacity requirements.

[0079] Step S102: Randomly generate shape variables with ring rules based on attribute information; establish an initial population based on the shape variables with ring rules.

[0080] In this embodiment, pre-set constraints on the wind turbine coordinates include the area of ​​the wind farm to be optimized and the distance between any two wind turbines in the wind farm to be optimized. Larger than the diameter of the wind turbine D of n times, , n It is a positive integer greater than 1;

[0081] Optionally, the distance between any two wind turbines in the wind farm to be optimized. Greater than four times the diameter of the wind turbine rotor. It should be noted that this embodiment optimizes the distance between any two wind turbines in the wind farm. The statement that the distance is greater than four times the rotor diameter is merely an example of one implementation method and is not a limitation of this embodiment. In practical applications, the embodiment of this invention addresses the distance between any two wind turbines in the wind farm to be optimized. It can be set according to actual needs.

[0082] Based on the area 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, a ring-shaped variable is randomly generated to establish the initial population of the genetic algorithm. The initial population includes multiple individuals, each of which is a set of ring-shaped variables. Based on a specific point selection procedure, the ring-shaped variables can generate a unique ring-shaped arrangement scheme of wind turbines in the wind farm to be optimized.

[0083] In an embodiment, real number coding is adopted to randomly generate the shape variables of the ring rule, and an initial population is established. The initial population contains multiple individuals, each of which is a row vector containing 10 variables, i.e. ; each set of shape variables of the ring rule corresponds to a wind farm unit arrangement scheme; wherein the real number coding means that each gene value of each individual is represented by a floating point number in a certain range.

[0084] In the embodiment, the shape variables of the ring rule include global center point coordinates , ring interval starting point proportion r , ring inner starting point radial angle θ , ring interval minimum distance , ring inner minimum distance , ring interval gradient coefficient , and ring inner interval gradient coefficient .

[0085] In the embodiment, refer to the accompanying Figure 2 , Figure 2 is a main step flowchart diagram of randomly generating shape variables of a ring rule based on attribute information according to an embodiment of the present application. As shown in Figure 2 , randomly generating shape variables of a ring rule based on attribute information includes:

[0086] Step S201: randomly selecting global center point coordinates based on the area range of the wind farm to be optimized;

[0087] Specifically, within the closed polygon range of the area range of the wind farm to be optimized, a point coordinate is randomly taken out as the global center point coordinates of the ring rule arrangement.

[0088] Step S202: randomly selecting ring interval starting point proportion within a preset proportion range, randomly selecting ring inner starting point radial angle within a preset angle range, randomly selecting ring interval minimum distance and ring inner minimum distance within a preset interval range, and randomly selecting ring interval gradient coefficient and ring inner interval gradient coefficient within a preset coefficient range based on uniform probability distribution and the distance between any two wind power units in the wind farm to be optimized;

[0089] Specifically, the ring interval starting point proportion r is randomly taken out within the range of [0, 1) according to uniform probability distribution, the ring inner starting point radial angle θ is randomly taken out within the range of [0°, 360°), the ring interval minimum distance and the ring inner minimum distance two parameters are randomly taken out within the range of [0, 1), and the ring interval gradient coefficient is randomly taken out within the range of [0, 1). and Two parameters, ring interval gradual change coefficient in [0, 1) range is randomly taken out and Two parameters.

[0090] Step S203: Obtain the shape variable of the ring rule based on the global center point coordinate, the ring interval starting point proportion, the ring inner starting point ray angle, the ring interval minimum distance, the ring inner minimum distance, the ring interval gradual change coefficient and the ring inner interval gradual change coefficient.

[0091] Specifically, the shape variable of the ring rule is obtained based on the global center point coordinate , the ring interval starting point proportion r , the ring inner starting point ray angle θ , the ring interval minimum distance , the ring inner minimum distance , and the ring inner interval gradual change coefficient . .

[0092] Step S103: Obtain the arrangement scheme of the wind turbine generator in the wind farm to be optimized based on the global center point coordinate, the ring interval starting point proportion and the ring inner starting point ray angle.

[0093] In this embodiment, refer to the accompanying Figure 3 , Figure 3 is the main step flow schematic diagram of the arrangement scheme of the wind turbine generator in the wind farm to be optimized according to an embodiment of the present application. As Figure 3 shown, the method for obtaining the arrangement scheme of the wind turbine generator in the wind farm to be optimized includes:

[0094] Step S301: Obtain the line segment between the global center point coordinate and each vertex of the boundary of the wind farm to be optimized and the length of each line segment.

[0095] Specifically, refer to the accompanying Figure 4 , Figure 4 is the schematic diagram of generating the wind farm generator point based on the shape variable of the ring rule according to an embodiment of the present application. As Figure 4 shown, the line equation of the line segment between the global center point coordinate and each vertex of the boundary of the region range of the wind farm to be optimized is: , and the length of each line segment is determined as , wherein, is a certain boundary vertex of the region range of the wind farm to be optimized, is the total number of vertices of the closed polygon of the region range of the wind farm to be optimized;

[0096] Step S302: determining the ring distance starting point of each connecting line segment based on the length of each connecting line segment and the ring distance starting point proportion.

[0097] Specifically, the global center point coordinate is determined based on the global center point coordinate of the wind farm boundary vertex . r On the connecting line segment C from the global center point , the ring distance starting point is taken out based on the ring distance starting point proportion ; similarly, this process is repeated on other connecting line segments to obtain the ring distance starting point on each connecting line segment .

[0098] Step S303: obtaining a plurality of first gradient points on each connecting line segment on both sides of the ring distance starting point of each connecting line segment, and obtaining 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.

[0099] Specifically, as shown in Figure 4 , on the connecting line segment , starting from the ring distance starting point , a plurality of first gradient point sets are taken out on both sides of the ring distance starting point according to the straight line gradient point taking method, where is the total number of gradient points (i.e. the total number of rings in the wind farm to be optimized) ;

[0100] Based on the gradient points on the connecting line segment , similarly, this process is repeated on other connecting line segments to recursively take out the plurality of first gradient point sets on other connecting line segments , where the distance of a certain first gradient point from the global center point coordinate satisfies ;

[0101] Based on the global center point coordinate and the first gradient point set on the connecting line segment between the wind farm boundary vertex , a plurality of rings similar to the closed polygon boundary of the area range of the wind farm to be optimized are obtained, as well as the vertex set of each ring.

[0102] Referring to the accompanying Figure 5 ,Figure 5 is the main flow chart of the method for acquiring a plurality of first gradient points according to an embodiment of the present application. As shown in Figure 5 , acquiring a plurality of first gradient points on each connecting line segment at both sides of the ring spacing starting point of each connecting line segment comprises:

[0103] Step S501: Acquire the shortest distance from the global center point coordinate to the boundary of the wind farm to be optimized;

[0104] Specifically, the shortest distance from the global center point coordinate C to the boundary of the closed polygon range of the region of the wind farm to be optimized is acquired.

[0105] Step S502: Determine the minimum spacing between the first gradient points on each connecting line segment and the maximum number of first gradient points based on the shortest distance, the length of each connecting line segment, and the minimum ring spacing;

[0106] Specifically, for the connecting line segment , based on the length of the current connecting line segment , the minimum ring spacing , and the shortest distance C from the global center point to the boundary of the wind farm, the minimum spacing between the first gradient points on the connecting line segment is determined to be , and the maximum number of first gradient points on the connecting line segment is , where is the maximum integer not exceeding z;

[0107] Similarly, this process is repeated 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.

[0108] Step S503: Determine the ring spacing 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 first gradient points;

[0109] Specifically, for the connecting line segment , a Gaussian distribution function with an average of 0 is considered, and numbers are uniformly taken in the range [-1, 1], then the set of ring spacing gradient intervals on the connecting line segment that are not less than can be obtained according to the Gaussian distribution function, which is , where and is a ring interval gradient coefficient;

[0110] Similarly, repeat the process on each line segment to determine the ring interval gradient interval on each line segment.

[0111] Step S504: Based on the ring interval gradient interval on each line segment, obtain a plurality of first gradient points on each line segment on both sides of the ring interval starting point of each line segment.

[0112] Specifically, for the line segment , take points on both sides of the ring interval starting point based on the set of ring interval gradient intervals based on Gaussian distribution, that is, take first gradient points on both sides ;

[0113] Determine whether the first gradient points are within the range of the line segment , remove the first gradient points that are out of range, and then the remaining first gradient points constitute the set .

[0114] Similarly, repeat the process on each line segment to determine the plurality of first gradient points obtained on each line segment.

[0115] Step S304: Based on the global center point coordinate and the ring inside starting point radial angle, obtain a radial line based on the horizontal line of the area range of the wind farm to be optimized.

[0116] Specifically, as shown in the figure, starting from the global center point coordinate Figure 4 , a radial line with a radial angle of the ring inside starting point radial angle is made based on the horizontal line of the area range of the wind farm to be optimized. θ S

[0117] Step S305: Obtain a plurality of intersection points of the radial line and a plurality of ring shapes, and obtain a plurality of second gradient points on both sides of the ring inside starting point corresponding to the plurality of ring shapes with the plurality of intersection points as the ring inside starting point corresponding to the plurality of ring shapes, wherein the second gradient point is a coordinate point of a wind turbine in the wind farm to be optimized.

[0118] Specifically, as shown in the figure, the intersection point of the radial line Figure 4 and a certain ring shape S is , which is called the ring inside starting point on the ring shape ;

[0119] the intersection point of the radial line​​​​ the second gradient point on the ring , the second gradient point on the ring is obtained according to the circle gradient point taking method , wherein is the total number of the second gradient points on the ring , and the process is repeated on other rings to obtain the second gradient points on all rings, and the second gradient points are the coordinate points of the wind turbines in the wind farm to be optimized.

[0120] Referring to the accompanying Figure 6 , Figure 6 is a main step flow diagram of a method for obtaining a plurality of second gradient points according to an embodiment of the present application. As shown in Figure 6 , the method for obtaining a plurality of second gradient points comprises:

[0121] Step S601: obtaining the circumference of each ring;

[0122] Specifically, the plurality of first gradient points correspond to the connection to form a plurality of rings, and the circumference of each ring is obtained. .

[0123] Step S602: determining the maximum number of second gradient points on each ring based on the minimum distance within the ring and the circumference of each ring;

[0124] Specifically, based on the circumference of each ring , the minimum distance within the ring , the number of second gradient points on each ring is determined to be at most , wherein is the maximum integer not exceeding z.

[0125] Step S603: determining the ring gradient interval on each ring based on the maximum number of second gradient points on each ring, the minimum distance within the ring and the ring distance gradient coefficient;

[0126] Specifically, for each ring , a Gaussian distribution function with an average value of 0 is considered , and numbers are uniformly taken in the range of [-1, 1] , then a set of ring gradient intervals not less than on each ring can be obtained according to the Gaussian distribution function, wherein and are the ring distance gradient coefficients. ​

[0127] Step S604: Based on the in-ring gradient interval on each ring, obtain multiple second gradient points on both sides of the starting point in the ring corresponding to each ring, and obtain the coordinates of the multiple second gradient points.

[0128] Specifically, such as Figure 4 As shown, in the ring Above, starting from the inner ring. Centered on, with gradually changing intervals and Using a radius of , draw arcs in both clockwise and counterclockwise directions, and extract the arcs and the ring shape respectively. intersection and As the second transition point, if the arc and the ring... If there are multiple intersection points, choose the one with... The slope of the connecting line is closest The point on the slope of the side is used as a second gradient point;

[0129] The intersection point of the clockwise (or counterclockwise) arcs obtained in the previous step (or Centered on ) with gradually changing intervals and Using the radius as the starting point, continue drawing arcs in both clockwise and counterclockwise directions, and extract the arcs that intersect with the ring. intersection (or Repeat the above steps, using this as the second gradient point.

[0130] If we take a point at a certain step of a circular gradient, the intersection of the clockwise and counterclockwise directions is obtained. and Spacing between satisfy If, then stop taking points, if Then and The perpendicular bisector of the line connecting the two points and the circle The intersection point serves as the last second transition point within this ring;

[0131] Organize all the second gradient points to form a set of coordinates for the second gradient points. .

[0132] Step S306: Obtain the layout scheme of 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.

[0133] Specifically, the set of all the second gradient points on the ring. As the shape variable of the current ring rule The corresponding unique and definite wind farm turbine layout scheme.

[0134] Step S104: based on the initial population and the preset optimization target, the arrangement scheme of the wind turbines in the wind farm to be optimized is 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.

[0135] In this embodiment, the preset convergence condition is that the target value of the preset optimization target is maximum;

[0136] The method for optimizing the arrangement scheme of the wind turbines in the wind farm to be optimized comprises:

[0137] The initial population is taken as a benchmark to perform optimization, and the shape variable of the optimized circular arrangement rule is obtained;

[0138] The optimized population is established based on the shape variable of the optimized circular arrangement rule, and the arrangement scheme of the wind turbines after optimization is obtained;

[0139] Until the target value of the preset optimization target reaches the maximum, the optimization process is ended, and the optimal shape variable of the circular arrangement rule and the optimal arrangement scheme of the wind turbines in the wind farm to be optimized are obtained.

[0140] In one embodiment, the arrangement scheme of the wind turbines in the wind farm to be optimized is optimized based on a genetic algorithm as an optimization algorithm, and the genetic algorithm can be an NSGA-II algorithm.

[0141] In one embodiment, the shape variable of the circular arrangement rule can be obtained through crossover and mutation based on the constraint condition of the wind turbine coordinates to obtain a new shape variable of the circular arrangement rule.

[0142] In one embodiment, the method for optimizing the initial population can be: setting an optimization target value, calculating the preset optimization target through the optimization algorithm-based machine arrangement optimization process, and combining other frameworks to iteratively obtain a series of arrangement schemes of the wind turbines in the wind farm to be optimized that meet the requirements, have a globally optimal or optimal optimization target value. The optimization process of the initial population is as follows:

[0143] (1) Population initialization. Randomly generate optimization variables (including the shape variable of the circular arrangement rule) to form an initial population containing N individuals. Each individual is a certain arrangement scheme, including N turbine coordinates. The optimization variable is encoded by a real number, and the turbine coordinates are randomly generated within the optimization constraint. If the available point positions of the circular arrangement rule do not completely satisfy the optimization constraint, or the number of point positions is less than the required number of turbines, the individual is re-generated until it meets the requirements.

[0144] (2) Crossover mutation. The application adopts a simulated binary crossover method to perform a crossover operation, and a method of adding a Gaussian random number to an optimization variable to perform a mutation operation (if a ring arrangement rule is adopted, a shape variable is subjected to a crossover mutation). In the mutation operation, there is a probability of adding a random number of two scales to the variable, a Gaussian standard deviation of large-scale mutation is set to , a Gaussian standard deviation of small-scale mutation is set to , and mutation probabilities and are set respectively.

[0145] (3) Merging of parents and offspring. The parent and offspring populations generated by the crossover mutation are merged to form a population of 2N individuals.

[0146] (4) Fast non-dominated sorting and calculation of crowding degree. The optimization target value of each individual in the merged population is calculated, and according to the optimization target value, non-dominated individuals in the population are sequentially found in the merged parent-offspring population to divide levels. The individuals are sorted from small to large according to one target to obtain a serial number i , and the crowding degree of the individual is calculated .

[0147] (5) Screening to obtain a superior population. In the merged parent-offspring population, N individuals are selected by using the obtained levels. If a certain level is just increased and exceeds the population size, the elite strategy is used to randomly select two individuals , , and the individual with a larger crowding degree is selected until the required number of individuals is obtained.

[0148] (6) Convergence judgment. Return to (2) and repeat the steps until the iteration number meets the requirements to obtain a converged solution set, and at this time, the converged solution set is the optimized population.

[0149] In this embodiment, the preset optimization target is the total output power of the wind farm under the arrangement scheme of the wind turbine generator;

[0150] The method for obtaining the total output power of the wind farm to be optimized includes:

[0151] obtaining wind resource information of the wind farm to be optimized, wherein the wind resource information includes an environmental inflow wind speed of the wind farm to be optimized;

[0152] based on the environmental inflow wind speed of the wind farm to be optimized and the arrangement scheme of the wind turbine generator in the wind farm to be optimized, obtaining the total output power of the wind farm to be optimized according to a preset wind turbine generator wake model.

[0153] In this embodiment, the preset wind turbine generator wake model includes a wind turbine generator wake two-dimensional analytical model and a wind turbine generator wake additional turbulence intensity analytical model;

[0154] obtaining the total output power of the wind farm to be optimized according to a preset wake model based on the ambient flow wind speed and the arrangement scheme of the wind turbines in the wind farm to be optimized comprises:

[0155] obtaining the wake flow direction turbulence intensity of each wind turbine in the arrangement scheme based on the wind turbine wake additional turbulence intensity analytical model;

[0156] obtaining the inflow additional flow direction turbulence intensity of multiple points on the wind wheel of each wind turbine based on the wake flow direction turbulence intensity of each wind turbine;

[0157] obtaining the inflow velocity deficit of multiple points on the wind wheel of each wind turbine based on the wind turbine wake two-dimensional analytical model and the inflow additional flow direction turbulence intensity of multiple points on the wind wheel of each wind turbine;

[0158] obtaining the wind speed in front of the hub of each wind turbine based on the inflow velocity deficit of multiple points on the wind wheel of each wind turbine and the ambient flow wind speed;

[0159] obtaining the output power of each wind turbine based on the wind speed in front of the hub of each wind turbine and a preset power curve of each wind turbine;

[0160] obtaining the total output power of the wind farm to be optimized based on the output power of each wind turbine.

[0161] In one embodiment, the method for obtaining the total output power of the wind farm to be optimized comprises:

[0162] calculating the wake flow direction turbulence intensity of each wind turbine in the arrangement scheme, and the wake flow direction turbulence intensity of the wind turbine can be obtained according to the wind turbine wake additional turbulence intensity analytical model in the following formulas (1)-(6):

[0163] (1)

[0164] wherein, is the thrust coefficient; is the atmospheric ambient turbulence intensity; D is the wind wheel diameter of the wind turbine; r is the lateral distance of the wind wheel axis; is the same Gaussian curve standard deviation as the velocity deficit model; z is the vertical height.

[0165] the flow direction function is the maximum additional turbulence intensity of the wake section at each flow direction position:

[0166] (2)

[0167] wherein, ; ; Correction values ​​are taken into account for the near-wake region.

[0168] Formula (1) expansion function for:

[0169] (3)

[0170] in, and The value can be:

[0171] (4)

[0172] (5)

[0173] For vertical correction functions:

[0174] (6)

[0175] For each wind turbine in the wind farm, based on the wake turbulence intensity at multiple points on the rotor of the current wind turbine, the inflow additional turbulence intensity at multiple points on the rotor of the current wind turbine is obtained:

[0176] (7)

[0177] in, For the current number i Taiwan wind turbine rotor top point Additional inflow turbulence intensity at the point; For the first i Taiwanese unit in i Taiwan wind turbine rotor top point The turbulence intensity in the wake direction at that location; It is a binary variable if and only if the current number is... i The Taiwanese unit is in the first j Downstream of the Taiwanese unit In other cases ; N The number of wind turbines in the wind farm needs to be optimized.

[0178] The average velocity deficit of the wind turbine is obtained based on the two-dimensional analytical model of the wind turbine wake and the inflow additional turbulence intensity at multiple points on the rotor of each wind turbine:

[0179] (8)

[0180] in, This is the thrust coefficient; This represents the actual expansion rate of the wake boundary; The radius of the wind turbine; The standard deviation of the velocity deficit spanwise distribution is taken as half the wake width and is also used as the wake radius. This refers to the wake width.

[0181] Based on the average velocity loss of upstream wind turbines at multiple points on the rotor of the current wind turbine, the inflow velocity loss at multiple points on the rotor of the current wind turbine is obtained:

[0182] (9)

[0183] in, For the current number i Taiwan wind turbine rotor top point The inflow rate at the location is at a loss; For the first j Taiwanese unit in i Taiwan wind turbine rotor top point Average speed loss at the location; It is a binary variable if and only if the current number is... i The Taiwanese unit is in the first j Downstream of the Taiwanese unit In other cases ; N The number of wind turbines in the wind farm needs to be optimized.

[0184] Based on the inflow velocity deficit at multiple points on the wind turbine rotor, the average value is taken to obtain the wind speed in front of the wind turbine hub under preset wind conditions:

[0185] (10)

[0186] in, For the current number i Wind speed in front of the turbine hub of the typhoon generator; For the incoming airflow velocity;

[0187] At a wind speed of The wind direction angle is Under the given wind conditions, obtain the wind speed in front of the hub 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 wind turbine power curve includes the correspondence between the wind speed in front of the hub and the output power of the wind turbine.

[0188] Based on the output power under the above wind conditions, obtain the total output power of the wind farm to be optimized under the current layout:

[0189] (11)

[0190] wherein, P is the total output power of the wind farm to be optimized under the current arrangement scheme; is the wind condition with the wind speed being and the wind direction being ; P is the output power of the unit i under the wind condition ; is the frequency of the wind condition ; is the number of wind directions; is the number of wind speed segments taken under a single wind direction; N is the number of units.

[0191] In one application scenario according to an embodiment of the present application, the area vertex of the wind farm to be optimized can be , , and , the coordinate dimension is meter (m), the unit type is Vestas-V80 unit, the number of units is , the wind rose diagram is shown in Figure 7 , the unit power curve and the thrust coefficient curve are shown in Figure 8 , the original unit position of the wind farm to be optimized is shown in Figure 9 , and the rule form of the available unit position of the wind farm to be optimized is a circular arrangement rule. It should be noted that the area range of the wind farm to be optimized, the coordinates of the area vertex, the available form of the available unit position of the wind farm to be optimized, the unit type and the number of units, etc. are only exemplary descriptions, and in actual application, they can be set as needed.

[0192] The basic parameters of the wind farm to be optimized are shown in Table 1.

[0193] Table 1: Wind farm parameters

[0194]

[0195] The wind conditions of multiple wind directions and multiple wind speeds are selected, and the probability values under each wind direction and wind speed are referred to the attached Figure 7 . Figure 7 is a wind rose diagram according to an embodiment of the present application, and the central angle of the polar column chart in the attached Figure 7 represents the wind direction angle, and the height of the column chart represents the wind frequency. Figure 8is a machine group power curve and a thrust coefficient curve according to an embodiment of the application, the vertical coordinate Thrust Coefficient is the thrust coefficient, Power is the power (kw), the horizontal coordinate Wind Speed is the wind speed (m / s). The optimization constraint condition is the area range 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 The selection of flat terrain is also an exemplary description of the application scenario, and can be selected as needed in practice.

[0196] When optimizing the wind turbine arrangement of the wind farm to be optimized, the evolution curve of the optimization process is as shown in the accompanying Figure 10 . Figure 10 is the optimization process evolution curve of the wind farm arrangement optimization method based on the ring rule according to an embodiment of the application. The horizontal coordinate is the number of optimization iterations, and the vertical coordinate represents the maximum value of the annual power of the wind farm under different arrangement schemes of the wind farm to be optimized (Annual Power / MWh). It can be seen from the accompanying Figure 10 that as the number of iterations increases, the maximum value of the annual power of the wind farm gradually increases and eventually converges. Figure 9 is the original wind turbine point of the wind farm to be optimized according to an embodiment of the application, Figure 11 is a schematic diagram of the wind turbine point of the wind farm to be optimized under the optimal arrangement scheme based on the ring arrangement rule according to an embodiment of the application. It can be seen from the accompanying Figure 11 that the optimal wind turbine point of the wind farm has obvious ring arrangement rule arrangement characteristics, and the annual power corresponding to the wind turbine point of the wind farm to be optimized under this optimal arrangement scheme is 266508.40 MWh. Compared with the annual power 261616.18 MWh corresponding to the original wind turbine point of the wind farm to be optimized in Figure 9 , the arrangement scheme based on the ring arrangement rule after optimization has an annual power improvement of about 1.87%, which can significantly improve the power generation of the wind farm in the whole life cycle while ensuring that the wind turbine points of the wind farm to be optimized are arranged in a ring arrangement rule.

[0197] It should be noted that although the above embodiments describe the steps in a specific order, those skilled in the art can understand that, in order to achieve the effect of the present application, the different steps do not have to be executed in such an order, they can be executed simultaneously (in parallel) or in other orders, and these adjusted schemes are equivalent to the technical schemes described in the present application, and therefore will also fall within the protection scope of the present application.

[0198] Those skilled in the art can understand that all or part of the processes in the method of the above embodiment of the present application can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable storage medium can include any entity or device, medium, U disk, 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.

[0199] Another aspect of the present application also provides a computer readable storage medium.

[0200] In an embodiment of the computer readable storage medium according to the present application, the computer readable storage medium can be configured to store a program for implementing the wind farm layout optimization method based on the ring rule described above. The program can be loaded and run by the processor to implement the wind farm layout optimization method based on the ring rule described above. For the sake of illustration, only the parts related to the embodiments of the present application are shown, and the specific technical details that are not disclosed are referred to the method part of the embodiments of the present application. The computer readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer readable storage medium in the embodiments of the present application is a non-transitory computer readable storage medium.

[0201] Another aspect of the present application also provides an electronic device.

[0202] In an embodiment of the electronic device according to the present application, the electronic device can include at least one processor; and a memory in communication connection with the at least one processor; wherein the memory stores a computer program, and the computer program is executed by the at least one processor to implement the method described in any of the above embodiments. Refer to the Figure 12 , Figure 12 The memory 121 and the processor 122 are communicatively connected through a bus, as shown exemplarily in the figure.

[0203] In some embodiments of the present application, the electronic device described in the present application can 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., and the embodiments of the present application do not limit this.

[0204] So far, the technical solutions of the present application have been described in combination with one embodiment shown in the drawings, but it is easy for those skilled in the art to understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will all fall within the protection scope of the present application.

Claims

1. A method for wind farm layout optimization based on ring rule, characterized in that, The method comprises the following steps: obtaining attribute information of a wind farm to be optimized; randomly generating shape variables of ring rules based on the attribute information; establishing an initial population based on the shape variables of the ring rules, wherein the initial population comprises a plurality of individuals, each individual being a set of shape variables of ring rules, and the shape variables of the ring rules comprising a global center point coordinate, a ring spacing starting point proportion, and a ring inner starting point ray angle; obtaining an arrangement scheme of wind turbines in the wind farm to be optimized based on the global center point coordinate, the ring spacing starting point proportion, and the ring inner starting point ray angle; optimizing the arrangement scheme of wind turbines in the wind farm to be optimized based on the initial population and a preset optimization target; obtaining an optimal arrangement scheme of wind turbines in the wind farm to be optimized when the preset optimization target reaches a preset convergence condition; the attribute information comprises a region range of the wind farm to be optimized and a 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 the following steps: obtaining a line segment between the global center point coordinate and each vertex of the boundary of the wind farm to be optimized and a length of each line segment; determining a ring spacing starting point of each line segment based on the length of each line segment and the ring spacing starting point proportion; obtaining a plurality of first gradual points on each line segment on both sides of the ring spacing starting point of each line segment, and obtaining a plurality of rings similar to the boundary shape of the wind farm to be optimized based on the plurality of first gradual points on each line segment; obtaining a ray based on the global center point coordinate and the ring inner starting point ray angle, with a horizontal line of the region range of the wind farm to be optimized as a reference; obtaining a plurality of intersection points of the ray and the plurality of rings, taking the plurality of intersection points as ring inner starting points corresponding to the plurality of rings, and obtaining a plurality of second gradual points on both sides of each ring inner starting point, wherein the second gradual points are coordinate points of wind turbines in the wind farm to be optimized; obtaining the arrangement scheme of wind turbines in the wind farm to be optimized based on the plurality of coordinate points of wind turbines in the wind farm to be optimized.

2. The ring-based rule based wind farm layout optimization method according to claim 1, characterized in that, The shape variables of the ring rules further comprise a ring interval minimum distance, a ring inner minimum distance, a ring interval gradual coefficient, and a ring inner interval gradual coefficient; randomly generating the shape variables of the ring rules based on the attribute information comprises the following steps: a 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 a rotor diameter of the wind turbine times, is a positive integer greater than 1; randomly selecting the global center point coordinate based on the region range of the wind farm to be optimized; randomly selecting the ring spacing starting point proportion within a preset proportion range, the ring inner starting point ray angle within a preset angle range, the ring interval minimum distance and the ring inner minimum distance within a preset interval range, and the ring interval gradual coefficient and the ring inner interval gradual coefficient within a preset coefficient range based on a uniform probability distribution and a distance between any two wind turbines in the wind farm to be optimized; obtaining the shape variables of the ring rules based on the global center point coordinate, the ring spacing starting point proportion, the ring inner starting point ray angle, the ring interval minimum distance, the ring inner minimum distance, the ring interval gradual coefficient, and the ring inner interval gradual coefficient.

3. The ring-based layout optimization method for wind farm according to claim 2, characterized in that, The method further comprises: acquiring a plurality of first gradient points on each connecting line segment based on the ring spacing starting point of each connecting line segment; acquiring the shortest distance from the global center point coordinate to the boundary of the wind farm to be optimized; determining 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 ring spacing; determining the ring spacing 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; 4. The ring-based layout optimization method for wind farm according to claim 2, characterized in that, acquiring a plurality of first gradient points on each connecting line segment based on the ring spacing gradient interval on each connecting line segment. The method further comprises: acquiring the length of each ring; determining the maximum number of the second gradient points on each ring based on the minimum ring spacing and the length of each ring; determining the ring spacing gradient interval on each ring based on the maximum number of the second gradient points on each ring, the minimum ring spacing, and the ring spacing gradient coefficient; 5. The ring-based rule based wind farm layout optimization method according to claim 1, wherein, acquiring a plurality of second gradient points on each ring based on the ring spacing gradient interval on each ring, and obtaining the coordinate points of the plurality of second gradient points. The preset convergence condition is that the target value of the preset optimization target is maximum; The method further comprises: optimizing the initial population to obtain the shape variable of the optimized ring rule; establishing an optimized population based on the shape variable of the optimized ring rule, and obtaining the arrangement scheme of the wind turbine generator; 6. The ring-based layout optimization method for wind farm according to claim 5, characterized in that, until the target value of the preset optimization target reaches the maximum, the optimization process is ended, and the optimal shape variable of the ring rule and the optimal arrangement scheme of the wind turbine generator in the wind farm to be optimized are obtained. The preset optimization target is the total output power of the wind farm to be optimized under the arrangement scheme of the wind turbine generator. The method for obtaining the total output power of the wind farm to be optimized comprises: acquiring the wind resource information of the wind farm to be optimized, wherein the wind resource information comprises the environmental inflow wind speed of the wind farm to be optimized; 7. The ring-based layout optimization method for wind farm according to claim 6, characterized in that, obtaining the total output power of the wind farm to be optimized according to the preset wind turbine generator wake model based on the environmental inflow wind speed and the arrangement scheme of the wind farm to be optimized. The preset wind turbine generator wake model comprises a wind turbine generator wake two-dimensional analytical model and a wind turbine generator wake additional turbulence intensity analytical model. The method for obtaining the total output power of the wind farm to be optimized according to the preset wake model based on the environmental inflow wind speed and the arrangement scheme of the wind farm to be optimized comprises: obtaining the wake flow direction turbulence intensity of each wind turbine generator in the arrangement scheme based on the wind turbine generator wake additional turbulence intensity analytical model; obtaining, based on the wake flow direction turbulence intensity of each wind turbine, inflow additional flow direction turbulence intensity of multiple points on the wind wheel of each wind turbine; obtaining, based on the two-dimensional analytical model of the wind turbine wake and the inflow additional flow direction turbulence intensity of multiple points on the wind wheel of each wind turbine, inflow velocity deficit of multiple points on the wind wheel of each wind turbine; obtaining, based on the inflow velocity deficit of multiple points on the wind wheel of each wind turbine and the ambient inflow wind speed, wind speed in front of the hub of each wind turbine; obtaining, based on the wind speed in front of the hub of each wind turbine and a preset power curve of each wind turbine, output power of each wind turbine; obtaining, based on the output power of each wind turbine, total output power of the wind farm to be optimized.

8. An electronic device, comprising: comprise: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory has stored therein a computer program, and the computer program is executed by the at least one processor to implement the wind farm layout optimization method based on the ring rule according to any one of claims 1 to 7.

9. A computer readable storage medium having stored therein a plurality of program codes, characterized in that, The program code is adapted to be loaded and run by the processor to execute the wind farm layout optimization method based on the ring rule according to any one of claims 1 to 7. The program code is adapted to be loaded and run by the processor to execute the wind farm layout optimization method based on the ring rule according to any one of claims 1 to 7.

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