Wind power plant layout processing method and device based on double populations, equipment and medium

Abstract

The invention relates to the technical field of wind power plant layout, particularly provides a wind power plant layout processing method and device based on double populations, equipment and a medium, and aims to solve the technical problems of low total output power and high construction cost of a wind power plant caused by the existing wind power plant layout. In order to achieve the purpose, the method comprises the steps that in multiple iterations, according to a first optimization target and a second optimization target, fitness calculation is conducted on a first wind turbine generator set population, a second wind turbine generator set population and a booster station population, and a fitness result is obtained; performing selection processing on the first wind turbine generator group, the second wind turbine generator group and the booster station group according to the fitness result; performing variation processing on the first wind turbine generator set optimization population, the second wind turbine generator set optimization population and the booster station optimization population to obtain a first wind turbine generator set population, a second wind turbine generator set population and a booster station population; and according to the Ith optimization population of the first wind turbine generator and the Ith optimization population of the second wind turbine generator, wind turbine generator arrangement is obtained.

Description

Technical Field

[0001] The present application relates to the technical field of wind farm layout, and specifically provides a wind farm layout processing method, device, equipment and medium based on dual populations. Background Art

[0002] At present, wind energy is an important driving force for the transition to clean energy, and wind farms tend to be large-scale and base-based, which makes the optimization of wind farm layout increasingly important.

[0003] In the prior art, a wind power system mainly includes a wind turbine, a booster station and cables. After the area for installing the wind power system is determined, the layout is carried out according to a regular arrangement, so that more wind turbines can be installed in the wind farm and the layout is beautiful. However, since the wake effect of the wind turbine is not taken into account, the total output power of the wind farm is low and the construction cost is high.

[0004] Accordingly, the art needs a new wind farm layout processing method based on dual populations to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects, the present application is proposed to provide a solution or at least partially solve the technical problem in the prior art that the total output power of the wind farm is low and the construction cost is high due to the failure to consider the wake effect of the wind turbine.

[0006] In a first aspect, the present application provides a wind farm layout processing method based on dual populations, comprising: Get the area of ​​the wind farm; According to the wind farm area, obtaining a first wind turbine generator set initial population and a second wind turbine generator set initial population; In the i-th iteration, the i-th population of the first wind turbine group and the i-th population of the second wind turbine group are obtained; wherein, when i=1, the first population of the first wind turbine group is the initial population of the first wind turbine group, the first population of the second wind turbine group is the initial population of the second wind turbine group, the i-th population of the first wind turbine group and the i-th population of the second wind turbine group both contain multiple individuals, each individual in the i-th population of the first wind turbine group is a regularly arranged shape variable, and each individual in the i-th population of the second wind turbine group is a wind turbine group coordinate vector; According to the i-th population of the first wind turbine generator set and the i-th population of the second wind turbine generator set and the optimization constraint, the i-th population of the booster station is obtained; wherein, when i=1, the first population of the booster station is the initial population of the booster station; According to the first optimization target and the second optimization target, the fitness of the i-th group of the first wind turbines, the i-th group of the second wind turbines and the i-th group of the booster stations is calculated to obtain a fitness result; wherein the first optimization target is to maximize the total output power, and the second optimization target is to minimize the cable cost; According to the fitness result, the i-th population of the first wind turbine generator set, the i-th population of the second wind turbine generator set and the i-th population of the booster station are selected to obtain the i-th optimized population of the first wind turbine generator set, the i-th optimized population of the second wind turbine generator set and the i-th optimized population of the booster station; The i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group, and the i-th optimized population of the booster station are mutated to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group, and the i+1-th population of the booster station; wherein 1≤i≤I, wherein I corresponds to the I-th optimized population of the first wind turbine group, the I-th optimized population of the second wind turbine group, and the I-th optimized population of the booster station obtained after the I-th iteration; According to the first optimized population of the first wind turbines and the first optimized population of the second wind turbines, an arrangement of the wind turbines is obtained.

[0007] In a technical solution of the above-mentioned dual-population-based wind farm layout processing method, obtaining the first wind turbine initial population according to the wind farm area range includes: According to the wind farm area, a global center point is obtained; According to the first preset range, the ratio of the starting points in the line is obtained; According to the preset angle range, the parallel line rotation angle is obtained; According to the preset constraint conditions, the minimum spacing between rows and the minimum spacing within rows are obtained; According to the second preset range, a line spacing gradient coefficient is obtained; According to the third preset range, obtaining the intra-line spacing gradient coefficient; Obtaining the shape variables of the regular arrangement according to the global center point coordinates, the ratio of the starting points within the row, the parallel line rotation angle, the minimum spacing between rows, the minimum spacing within a row, the row spacing gradient coefficient, and the intra-row spacing gradient coefficient; A plurality of the regularly arranged shape variables are combined to obtain the first initial population of wind turbines.

[0008] In a technical solution of the above-mentioned wind farm layout processing method based on dual populations, obtaining the wind turbine arrangement according to the first optimized population of the first wind turbine group and the first optimized population of the second wind turbine group includes: Performing point processing on the regularly arranged shape variables in the first optimized population of the first wind turbine generator set to obtain an available point vector; In the nth cycle, according to the nth coordinate in the first optimized population of the second wind turbine generator set and the available point vector, a distance set between the nth coordinate in the first optimized population of the second wind turbine generator set and the available point vector is obtained; According to the distance of the available points, the coordinates of the nth wind turbine generator set are obtained; Wherein, 1≤n≤N, wherein N is the number of coordinates of the second wind turbine generator set in the first optimized population; The coordinates of the first wind turbine group to the Nth wind turbine group are combined to obtain the arrangement of the wind turbine groups.

[0009] In a technical solution of the above-mentioned wind farm layout processing method based on dual populations, obtaining the initial population of booster stations includes: Within the wind farm area, according to preset booster station position constraints, the booster station coordinates are obtained; The booster station coordinates are combined to obtain the initial population of booster stations.

[0010] In a technical solution of the above-mentioned wind farm layout processing method based on rule arrangement, the ith optimized population of the first wind turbine group, the ith optimized population of the second wind turbine group and the ith optimized population of the booster station are mutated to obtain the i+1th population of the first wind turbine group, the i+1th population of the second wind turbine group and the i+1th population of the booster station, including: Determine whether i is less than the preset number of iterations; If it is determined that i is less than or equal to the preset number of iterations, then for the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group, and the i-th optimized population of the booster station, within the preset large scale and the preset small scale, select the data of each individual to obtain the i+1th population of the first wind turbine group, the i+1th population of the second wind turbine group, and the i+1th population of the booster station; If it is determined that i is greater than the preset number of iterations, then for the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station, the data of each individual is selected within a preset small-scale range to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station.

[0011] In a technical solution of the above-mentioned dual-population-based wind farm layout processing method, obtaining the total output power includes: According to the speed loss of the upstream wind turbine at multiple points on the wind rotor of the current wind turbine, the inflow speed loss at multiple points on the wind rotor of the current wind turbine is obtained; According to the additional flow turbulence intensity of the upstream wind turbine at multiple points on the wind rotor of the current wind turbine, the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of the current wind turbine is obtained; Obtaining the wind speed in front of the hub of the current wind turbine generator set according to the inflow velocity losses at multiple points on the wind turbine rotor of the current wind turbine generator set; Obtaining a corresponding relationship between the wind speed in front of the hub of the current wind turbine and the power of the current wind turbine according to the wind conditions, the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of the current wind turbine, and the wind speed in front of the hub of the current wind turbine; The total output power is obtained according to the wind condition, the corresponding relationship, the frequency of occurrence of the wind condition, the number of wind directions, the number of wind speed segments and the number of wind turbine generator sets.

[0012] In a technical solution of the above-mentioned wind farm layout processing method based on dual populations, obtaining the cable cost includes: According to the initial population of the booster station and the preset coastline position, the coast point closest to the booster station is obtained, and the coast point is used as a feeder cable node; Obtaining a path layout according to the wind turbine position and the feeder cable node; According to preset constraint conditions, the path layout is subjected to constraint processing to obtain a constrained path layout; Obtaining a cable cost model according to the constraint path layout, the wind turbine location and the cable information; The cable cost is obtained according to the cable cost model.

[0013] In a second aspect, the present application provides a wind farm layout processing device based on dual populations, comprising: An acquisition module is used to obtain the area range of the wind farm; An analysis module, configured to obtain a first initial population of wind turbines and a second initial population of wind turbines according to the wind farm area; The acquisition module is further used to acquire the i-th population of the first wind turbine group and the i-th population of the second wind turbine group in the i-th iteration; wherein, when i=1, the first population of the first wind turbine group is the initial population of the first wind turbine group, the first population of the second wind turbine group is the initial population of the second wind turbine group, the i-th population of the first wind turbine group and the i-th population of the second wind turbine group both contain multiple individuals, each individual in the i-th population of the first wind turbine group is a regularly arranged shape variable, and each individual in the i-th population of the second wind turbine group is a wind turbine group coordinate vector; The analysis module is further used to obtain the i-th population of booster stations according to the i-th population of the first wind turbine generator set and the i-th population of the second wind turbine generator set and the optimization constraint; wherein, when i=1, the first population of booster stations is the initial population of booster stations; A processing module, configured to calculate the fitness of the i-th population of the first wind turbine generator set, the i-th population of the second wind turbine generator set, and the i-th population of the booster station according to a first optimization objective and a second optimization objective, to obtain a fitness result; wherein the first optimization objective is to maximize the total output power, and the second optimization objective is to minimize the cable cost; A selection module is used to select the i-th population of the first wind turbine generator set, the i-th population of the second wind turbine generator set and the i-th population of the booster station according to the fitness result to obtain the i-th optimized population of the first wind turbine generator set, the i-th optimized population of the second wind turbine generator set and the i-th optimized population of the booster station; a mutation module, used for performing mutation processing on the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station; wherein 1≤i≤I, wherein I corresponds to the I-th optimized population of the first wind turbine group, the I-th optimized population of the second wind turbine group and the I-th optimized population of the booster station obtained after the I-th iteration; A conversion module is used to obtain a wind turbine arrangement according to the first optimized population of the first wind turbines and the first optimized population of the second wind turbines.

[0014] In a third aspect, the present application provides a wind farm layout processing device based on dual populations, comprising a processor and a storage device, wherein the storage device is suitable for storing multiple program codes, and the program codes are suitable for being loaded and run by the processor to execute a method as described in any one of the first aspects.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium having a plurality of program codes stored therein, wherein the program codes are suitable for being loaded and executed by a processor to execute the method as described in any one of the first aspects.

[0016] The present application provides a wind farm layout processing method, device, equipment and medium based on dual populations. The method specifically comprises: obtaining a wind farm area range; obtaining a first wind turbine initial population and a second wind turbine initial population according to the wind farm area range; obtaining an i-th population of the first wind turbine and an i-th population of the second wind turbine in the i-th iteration; wherein, when i=1, the first population of the first wind turbine is the initial population of the first wind turbine, the first population of the second wind turbine is the initial population of the second wind turbine, and the i-th population of the first wind turbine and the i-th population of the second wind turbine are the initial population of the second wind turbine. The second wind turbine group i-th population includes multiple individuals, each individual in the first wind turbine group i-th population is a regularly arranged shape variable, and each individual in the second wind turbine group i-th population is a wind turbine group coordinate vector; according to the first wind turbine group i-th population and the second wind turbine group i-th population and the optimization constraint, the booster station i-th population is obtained; wherein, when i=1, the first booster station population is the initial booster station population; according to the first optimization objective and the second optimization objective, the first wind turbine group i-th population, the second wind turbine group i-th population and the booster station i-th population are optimized. The i-th population is subjected to fitness calculation to obtain a fitness result; wherein the first optimization target is to maximize the total output power, and the second optimization target is to minimize the cable cost; according to the fitness result, the i-th population of the first wind turbines, the i-th population of the second wind turbines, and the i-th population of the booster stations are selected to obtain the i-th optimized population of the first wind turbines, the i-th optimized population of the second wind turbines, and the i-th optimized population of the booster stations; the i-th optimized population of the first wind turbines, the i-th optimized population of the second wind turbines, and the i-th optimized population of the booster stations are selected. The population is mutated to obtain the i+1th population of the first wind turbine group, the i+1th population of the second wind turbine group and the i+1th population of the booster station; wherein 1≤i≤I, wherein I corresponds to the Ith optimized population of the first wind turbine group, the Ith optimized population of the second wind turbine group and the Ith optimized population of the booster station obtained after the Ith iteration; according to the Ith optimized population of the first wind turbine group and the Ith optimized population of the second wind turbine group, the arrangement of the wind turbines is obtained, and then the layout of the wind turbines and the layout of the booster station that simultaneously meet the maximum total output power of the wind farm and the lowest construction cost are obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The disclosure of the present application 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 application. In addition, similar numbers in the drawings are used to represent similar components, among which: Figure 1 A schematic flow chart of a first embodiment of a wind farm layout processing method based on dual populations provided in an embodiment of the present application; Figure 2A schematic flow chart of a second embodiment of a wind farm layout processing method based on dual populations provided in an embodiment of the present application; Figure 3 A schematic flow chart of a third embodiment of a wind farm layout processing method based on dual populations provided in an embodiment of the present application; Figure 4 A schematic flow chart of a fourth embodiment of a wind farm layout processing method based on dual populations provided in an embodiment of the present application; Figure 5 A schematic flow chart of a fifth embodiment of a wind farm layout processing method based on dual populations provided in an embodiment of the present application; Figure 6 A flow chart of a sixth embodiment of a wind farm layout processing method based on dual populations provided in an embodiment of the present application.

[0018] Figure 7 A schematic flow chart of Embodiment 7 of a wind farm layout processing method based on dual populations provided in an embodiment of the present application; Figure 8 A schematic diagram of the structure of a first embodiment of a wind farm layout processing device based on dual populations provided in an embodiment of the present application; Fig. 9 A structural schematic diagram of a first embodiment of a wind farm layout processing device based on dual populations provided in an embodiment of the present application.

[0019] Reference numerals list : 11: acquisition module; 12: analysis module; 13: processing module; 14: selection module; 15: mutation module; 16: conversion module; 21: processor; 22: memory. DETAILED DESCRIPTION

[0020] Some embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not intended to limit the protection scope of the present application.

[0021] In the description of the present application, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, memory, and may also include software parts, such as program code, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware or a combination of the two. Non-temporary computer-readable storage media include any suitable medium that can store program code, such as a 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 A and B. The term "at least one A or B" or "at least one of A and B" has a similar meaning to "A and / or B" and may include only A, only B or A and B. The singular terms "one" and "the" may also include plural forms.

[0022] In the prior art, when laying out wind turbines and booster stations in a wind farm, construction personnel perform layouts based on experience, layouts based on random locations, and layouts based on neat arrangements. Among these three layout methods, the empirical layout cannot obtain the optimal layout, the random layout causes the wind farm to have poor aesthetics, and the neat arrangement causes the overall optimization space to be limited. Therefore, these three methods cannot effectively layout the wind turbines and booster stations in the wind farm, which leads to technical problems such as low total output power of the wind farm and high construction cost of the wind farm.

[0023] Based on this, in order to solve the above technical problems, the present application provides a wind farm layout processing method based on dual populations to achieve maximum total output power and minimum construction cost.

[0024] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0025] Figure 1 The flowchart of the first embodiment of a wind farm layout processing method based on dual populations provided in the present application is shown in FIG. Figure 1 As shown, specifically, the method includes: Step S101: Acquire the area range of the wind farm.

[0026] In this embodiment, the wind farm area range is the coordinates of multiple vertices on the edge of the image in the plane geometric figure composed of the wind farm.

[0027] Step S102: obtaining a first initial population of wind turbines and a second initial population of wind turbines according to the wind farm area.

[0028] In this embodiment, coordinates are randomly selected within the wind farm area to obtain a first initial population of wind turbines and a second initial population of wind turbines.

[0029] Step S103: in the i-th iteration, the i-th population of the first wind turbine generator set and the i-th population of the second wind turbine generator set are obtained.

[0030] In this embodiment, when i=1, the first population of the first wind turbine group is the initial population of the first wind turbine group, the first population of the second wind turbine group is the initial population of the second wind turbine group, the i-th population of the first wind turbine group and the i-th population of the second wind turbine group both contain multiple individuals, each individual in the i-th population of the first wind turbine group is a regularly arranged shape variable, and each individual in the i-th population of the second wind turbine group is a wind turbine group coordinate vector.

[0031] Step S104: obtaining the i-th group of booster stations according to the i-th group of the first wind turbine generator sets and the i-th group of the second wind turbine generator sets and the optimization constraints.

[0032] In this embodiment, when i=1, the first population of booster stations is the initial population of booster stations.

[0033] In this embodiment, the optimization constraints are the installed capacity of the wind turbines and the number of wind turbines. The number of booster stations is obtained based on the optimization constraints, and the position of each booster station in the i-th group of booster stations is determined based on the i-th group of the first wind turbines and the i-th group of the second wind turbines.

[0034] Step S105: according to the first optimization target and the second optimization target, fitness calculation is performed on the i-th group of first wind turbines, the i-th group of second wind turbines and the i-th group of booster stations to obtain a fitness result.

[0035] In this embodiment, the first optimization goal is to maximize the total output power, and the second optimization goal is to minimize the cable cost.

[0036] In this embodiment, if the i-th group of first wind turbines, the i-th group of second wind turbines and the i-th group of booster stations in the current iteration are closer to the first optimization target and the second optimization target, their fitness is higher, otherwise it is smaller.

[0037] Step S106: According to the fitness result, the i-th population of the first wind turbine group, the i-th population of the second wind turbine group and the i-th population of the booster station are selected to obtain the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station.

[0038] In this embodiment, the populations with high fitness among the i-th population of the first wind turbine group, the i-th population of the second wind turbine group and the i-th population of the booster station are screened to obtain the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station.

[0039] Step S107: performing mutation processing on the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station.

[0040] In this embodiment, the i-th optimized population of the first wind turbine generator set, the i-th optimized population of the second wind turbine generator set and the i-th optimized population of the booster station are populations with higher fitness, and by mutating them, a population with higher fitness can be generated.

[0041] In this embodiment, the data in the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station can be randomly changed to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station.

[0042] In this embodiment, 1≤i≤I, where I corresponds to the Ith optimized population of the first wind turbine group, the Ith optimized population of the second wind turbine group, and the Ith optimized population of the booster station obtained after the Ith iteration.

[0043] In this embodiment, steps S103 to S107 are repeated. When it is determined that the first optimization target and the second optimization target have converged, the optimization process is terminated. At this time, the first optimized population of the first wind turbine group, the first optimized population of the second wind turbine group and the first optimized population of the substation are obtained.

[0044] Step S108: obtaining a wind turbine arrangement according to the first optimized population of the first wind turbine and the first optimized population of the second wind turbine.

[0045] In this embodiment, the scope of the wind farm area is obtained; according to the scope of the wind farm area, the first initial population of wind turbines and the second initial population of wind turbines are obtained; in the i-th iteration, the i-th population of the first wind turbines and the i-th population of the second wind turbines are obtained; according to the i-th population of the first wind turbines, the i-th population of the second wind turbines and the optimization constraints, the i-th population of the booster stations is obtained; according to the first optimization target and the second optimization target, the fitness of the i-th population of the first wind turbines, the i-th population of the second wind turbines and the i-th population of the booster stations is calculated to obtain the fitness result; according to the fitness result, the i-th population of the first wind turbines, the i-th population of the second wind turbines and the i-th population of the booster stations are calculated. The i-th population of wind turbines and the i-th population of booster stations are selected to obtain the i-th optimized population of the first wind turbine, the i-th optimized population of the second wind turbine and the i-th optimized population of the booster station; the i-th optimized population of the first wind turbine, the i-th optimized population of the second wind turbine and the i-th optimized population of the booster station are mutated to obtain the i+1-th population of the first wind turbine, the i+1-th population of the second wind turbine and the i+1-th population of the booster station; the arrangement of wind turbines is obtained according to the I-th optimized population of the first wind turbine and the I-th optimized population of the second wind turbine. Compared with the prior art, the wind turbines are arranged without considering the wake effect of the wind turbines. In terms of the low total output power and high construction cost of the electric farm, the present application obtains the first initial population of wind turbines and the second initial population of wind turbines according to the regional scope of the wind farm, and in the i-th iteration, obtains the i-th population of booster stations according to the i-th population of the first wind turbines and the i-th population of the second wind turbines and the optimization constraints, and performs fitness calculation on the i-th population of the first wind turbines, the i-th population of the second wind turbines, and the i-th population of booster stations according to the first optimization target and the second optimization target to obtain a fitness result, and then calculates the fitness of the i-th population of the first wind turbines, the i-th population of the second wind turbines, and the i-th population of booster stations according to the fitness result. The i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station are selected and processed, and the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station are mutated to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station. Finally, according to the i-th optimized population of the first wind turbine group and the i-th optimized population of the second wind turbine group, the wind turbine arrangement is obtained, and then the wind turbine layout and booster station layout that simultaneously meet the maximum total output power of the wind farm and the lowest construction cost are obtained.

[0046] Figure 2 The flowchart of the second embodiment of the wind farm layout processing method based on dual populations provided in the present application is shown in FIG. Figure 2 As shown, specifically, in step S102, according to the wind farm area, the first wind turbine initial population is obtained, including: Step S201: Obtain a global center point according to the wind farm area.

[0047] In this embodiment, the wind farm area is a closed polygon. A point is randomly selected in the closed polygon and the point is the global center point.

[0048] Step S202: Obtaining the ratio of starting points within a line according to the first preset range.

[0049] In this embodiment, within the first preset range, any value is taken, and the value is the ratio of the starting points within the line.

[0050] In this embodiment, for example, the first preset range is greater than or equal to 0 and less than 1.

[0051] Step S203: Obtaining the parallel line rotation angle according to a preset angle range.

[0052] In this embodiment, within the preset angle range, any angle value is taken, and the angle value is the parallel line rotation angle.

[0053] In this embodiment, for example, the preset angle range is greater than or equal to 0 degrees and less than 360 degrees.

[0054] Step S204: according to the preset constraint conditions, the minimum spacing between rows and the minimum spacing within a row are obtained.

[0055] In this embodiment, for example, the preset constraint condition is greater than or equal to the diameter of the wind turbine generator set and less than 4 times the diameter of the wind turbine generator set.

[0056] In this embodiment, within the preset constraint conditions, any two values ​​are taken, and the two values ​​are the minimum spacing between rows and the minimum spacing within a row.

[0057] Step S205: Obtaining a line spacing gradient coefficient according to a second preset range.

[0058] In this embodiment, within the second preset range, any two values ​​are taken, and the two values ​​are line spacing gradient coefficients.

[0059] In this embodiment, for example, the second preset range is greater than or equal to 0 and less than 1.

[0060] Step S206: Obtaining a gradient coefficient of the intra-row spacing according to the third preset range.

[0061] In this embodiment, within the third preset range, any two values ​​are taken, and the two values ​​are the intra-line spacing gradient coefficients.

[0062] Step S207: Obtain regularly arranged shape variables according to the global center point coordinates, the ratio of the starting point within the line, the parallel line rotation angle, the minimum spacing between lines, the minimum spacing within a line, the line spacing gradient coefficient and the line spacing gradient coefficient.

[0063] In this embodiment, the global center point coordinates (x0, y0), the ratio of the starting point in the line r, the parallel line rotation angle θ, and the minimum spacing between lines D are lines , minimum spacing within a line D inline , the line spacing gradient coefficient (a1, b1) and the intra-line spacing gradient coefficient (a2, b2) are combined to obtain the regularly arranged shape variables (x0, y0, r, θ, D lines ,D inline ,a1,b1,a2,b2).

[0064] Step S208: combining a plurality of regularly arranged shape variables to obtain a first initial population of wind turbines.

[0065] In this embodiment, step S201 to step S207 are performed multiple times to obtain a plurality of regularly arranged shape variables, and then the plurality of regularly arranged shape variables are combined to obtain a first initial population of wind turbines.

[0066] In this embodiment, the number of executions is the number of wind turbines in the wind farm.

[0067] In this embodiment, a global center point is obtained according to the area range of the wind farm; the proportion of starting points within a row is obtained according to the first preset range; the rotation angle of parallel lines is obtained according to the preset angle range; the minimum spacing between rows and the minimum spacing within a row are obtained according to the preset constraints; the row spacing gradient coefficient is obtained according to the second preset range; the row spacing gradient coefficient is obtained according to the third preset range; regularly arranged shape variables are obtained according to the coordinates of the global center point, the proportion of starting points within a row, the rotation angle of parallel lines, the minimum spacing between rows, the minimum spacing within a row, the row spacing gradient coefficient and the row spacing gradient coefficient; a plurality of regularly arranged shape variables are combined to obtain an initial population of the first wind turbines.

[0068] Figure 3 The following is a flow chart of a third embodiment of a wind farm layout processing method based on dual populations provided in the present application. Figure 3 As shown, specifically, a specific implementation of step S108 is: Step S301: performing point processing on the regularly arranged shape variables in the first optimized population of the first wind turbine generator set to obtain an available point vector.

[0069] In this embodiment, by performing point processing on the regularly arranged shape variables in the first optimized population of the first wind turbine generator set, an available point vector (x1 reg ,…,x NT reg ,y1 reg ,…,yNT reg ).

[0070] Step S302: In the nth cycle, according to the nth coordinate and the available point vector in the Ith optimized population of the second wind turbine generator set, a distance set between the nth coordinate and the available point vector in the Ith optimized population of the second wind turbine generator set is obtained.

[0071] In this embodiment, in the nth cycle, the nth coordinate (x n rand ,y n rand ) and the distance between each point in the available point vector, and obtain the distance set between the nth coordinate in the I-th optimized population of the second wind turbine generator set and the available point vector.

[0072] Step S303: Obtain the coordinates of the nth wind turbine generator set according to the distance set of available points.

[0073] In this embodiment, the available point corresponding to the minimum value in the distance set of the available points is used as the coordinate of the nth wind turbine generator set.

[0074] Step S304: combining the coordinates of the first wind turbine group to the coordinates of the Nth wind turbine group to obtain a wind turbine group arrangement.

[0075] In this embodiment, 1≤n≤N, where N is the number of coordinates in the first optimized population of the second wind turbine generator set.

[0076] In this embodiment, the coordinates of the first wind turbine group to the Nth wind turbine group are combined to obtain the arrangement of all wind turbine groups in the current wind farm.

[0077] In this embodiment, the regularly arranged shape variables in the first optimized population of the first wind turbine are processed by point selection to obtain an available point vector; in the nth cycle, according to the nth coordinates and the available point vectors in the first optimized population of the second wind turbine, a distance set between the nth coordinates and the available point vectors in the first optimized population of the second wind turbine is obtained; according to the distance set of the available points, the coordinates of the nth wind turbine are obtained; the coordinates of the 1st wind turbine to the Nth wind turbine are combined to obtain the arrangement of the wind turbines.

[0078] Figure 4 The flowchart of the fourth embodiment of the wind farm layout processing method based on dual populations provided in the present application is as follows. Figure 4 As shown, specifically, obtaining the initial population of booster stations in step S104 includes: Step S401: within the wind farm area, according to preset booster station position constraints, the booster station coordinates are obtained.

[0079] In this embodiment, the booster station location constraint is that the booster station location is within the wind farm area and the distance to the wind turbine is greater than n times the diameter of the wind turbine rotor.

[0080] In this embodiment, coordinate points are randomly selected within the wind farm area to obtain the coordinates of the booster station.

[0081] Step S402: Combining the booster station coordinates to obtain the initial population of booster stations.

[0082] In this embodiment, the booster station coordinates are regarded as an individual, and the coordinates of multiple booster stations are combined to obtain an initial population of booster stations.

[0083] In this embodiment, within the wind farm area, the booster station coordinates are obtained according to preset booster station position constraints; the booster station coordinates are combined to obtain the booster station initial population.

[0084] Figure 5 The flowchart of the fifth embodiment of the wind farm layout processing method based on dual populations provided in the present application is shown in FIG. Figure 5 Specifically, a specific implementation of step S107 includes: Step S501: Determine whether i is less than a preset number of iterations.

[0085] In this embodiment, less than the preset number of iterations is the early stage of optimization, and greater than the preset number of iterations is the late stage of optimization.

[0086] Step S502: If it is determined that i is less than or equal to the preset number of iterations, then for the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station, within the preset large scale and the preset small scale, select the data of each individual to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station.

[0087] In this embodiment, when it is determined that i is less than or equal to the preset number of iterations, for each individual in the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station, the data of each individual is randomly selected within a preset large scale and a preset small scale, and the set data is used as the i+1th population of the first wind turbine group, the i+1th population of the second wind turbine group and the i+1th population of the booster station.

[0088] Optionally, when it is determined that i is less than or equal to a preset number of iterations, for each individual in the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station, the data of each individual is selected within a preset large scale with a preset first probability and within a preset small scale with a preset second probability, and the set data is used as the i+1th population of the first wind turbine group, the i+1th population of the second wind turbine group and the i+1th population of the booster station.

[0089] In this embodiment, a preset large scale and a preset small scale are used to mutate each individual in the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station to prevent the occurrence of local optimality.

[0090] Step S503: If it is determined that i is greater than the preset number of iterations, for the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station, the data of each individual is selected within a preset small-scale range to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station.

[0091] In this embodiment, it is determined whether i is less than a preset number of iterations; if it is determined that i is less than or equal to the preset number of iterations, then for the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station, within a preset large scale and a preset small scale, the data of each individual is selected to obtain the i+1th population of the first wind turbine group, the i+1th population of the second wind turbine group and the i+1th population of the booster station; if it is determined that i is greater than the preset number of iterations, then for the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station, within a preset small scale, the data of each individual is selected to obtain the i+1th population of the first wind turbine group, the i+1th population of the second wind turbine group and the i+1th population of the booster station, so as to generate a new population.

[0092] Figure 6 The flowchart of the sixth embodiment of the wind farm layout processing method based on dual populations provided in the present application is as follows. Figure 6 As shown, specifically, obtaining the total output power in step S105 includes: Step S601: obtaining the inflow velocity losses at multiple points on the wind rotor of the current wind turbine generator set according to the velocity losses of the upstream wind turbine generator set at multiple points on the wind rotor of the current wind turbine generator set.

[0093] In this embodiment, according to Formula 1: (1) Get the inflow velocity loss ΔU at multiple points on the wind turbine rotor i(x,y,z). When the i-th wind turbine is downstream of the j-th wind turbine, q ij is 1, in other cases, q ij is 0; N is the number of wind turbines; ΔU i (x, y, z) is the speed loss of the jth upstream wind turbine at the point (x, y, z) on the rotor of the i-th wind turbine.

[0094] In this embodiment, the average speed loss of the wind turbine can be obtained according to the two-dimensional analytical model of the wind turbine wake of Formula 2: (2) Among them C T is the thrust coefficient; k=2*(0.3837*Iu+0.003678) is the wake expansion rate; 𝑅 is the rotor radius; σ=(kx+R) / 2 is the standard deviation of the spanwise distribution of velocity loss.

[0095] According to formula (1), the inflow velocity loss of multiple points on the wind rotor of the current wind turbine can be calculated for each point on the wind rotor of the current wind turbine.

[0096] Step S602: according to the additional flow turbulence intensity of the upstream wind turbine at multiple points on the wind rotor of the current wind turbine, the inflow additional flow turbulence intensity at multiple points on the wind rotor of the current wind turbine is obtained, which is used to solve the wake expansion rate of the wake model.

[0097] In this embodiment, according to Formula 3: (3) Get the additional flow turbulence intensity ΔIu of the inflow at multiple points on the wind turbine rotor ij (x,y,z). Among them, ΔIu ij is the additional flow turbulence intensity of the j-th wind turbine at the point (x, y, z) on the rotor of the i-th wind turbine; when the i-th wind turbine is downstream of the j-th wind turbine, q ij is 1, otherwise, q ij is 0; N is the number of wind turbines.

[0098] In this embodiment, according to Formula 4: (4) The additional turbulence intensity ΔIu is obtained. Where σ is the standard deviation of the Gaussian curve that is the same as the velocity loss model, z is the vertical height, and the flow function G(C T ,I0,x / D) is the maximum additional turbulence intensity of the wake interface at each flow direction, and δ(z) is the vertical correction function. According to Formula 5: (5) Get the flow function G(C T ,I0,x / D). Where d=2.3C T -1.2 ,e=I0 0.1 , q=0.7*C T -3.2 *I0 -0.45 *(1+x / D) -2 .

[0099] In this embodiment, according to Formula 6: (6) The spanwise function φ(r / σ) is obtained. The values ​​of k1 and k2 are:

[0100]

[0101] The vertical correction function δ(z) is:

[0102] Step S603: Obtain the wind speed in front of the hub of the current wind turbine according to the inflow velocity losses at multiple points on the wind rotor of the current wind turbine.

[0103] In this embodiment, according to Formula 7: (7) Get the wind speed U in front of the hub of the current i-th wind turbine i . Among them, U0 is the ambient wind speed; It is the average inflow velocity loss at multiple points on the wind turbine rotor.

[0104] Step S604: Obtain the corresponding relationship between the wind speed in front of the hub of the current wind turbine and the power of the current wind turbine according to the wind conditions, the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of the current wind turbine, and the wind speed in front of the hub of the current wind turbine.

[0105] Step S605: Obtain the total output power according to the wind conditions, the corresponding relationship, the frequency of occurrence of the wind conditions, the number of wind directions, the number of wind speed ranges and the number of wind turbines.

[0106] In this embodiment, according to Formula 8: (8) The total output power P is obtained total Among them, u j is the wind speed; θ k W is the wind direction; jk For the wind speed u jand wind direction θ k Wind conditions under P i is the wind turbine i in wind condition W jk Output power under jk ) is the wind condition W jk Occurrence frequency; N θ is the number of wind directions, N u is the number of wind speed segments taken in a single wind direction; N is the number of wind turbines.

[0107] In this embodiment, the inflow velocity loss at multiple points on the wind rotor of the current wind turbine is obtained based on the velocity loss of the upstream wind turbine at multiple points on the wind rotor of the current wind turbine; the inflow additional flow turbulence intensity at multiple points on the wind rotor of the current wind turbine is obtained based on the additional flow turbulence intensity of the upstream wind turbine at multiple points on the wind rotor of the current wind turbine; the wind speed in front of the hub of the current wind turbine is obtained based on the inflow velocity loss at multiple points on the wind rotor of the current wind turbine; the correspondence between the wind speed in front of the hub of the current wind turbine and the power of the current wind turbine is obtained based on the wind conditions, the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of the current wind turbine, and the wind speed in front of the hub of the current wind turbine; the total output power is obtained based on the wind conditions, the corresponding relationship, the frequency of occurrence of wind conditions, the number of wind directions, the number of wind speed segments and the number of wind turbines, and then the total output power is obtained.

[0108] Figure 7 The flowchart of the seventh embodiment of a wind farm layout processing method based on rule arrangement provided in the present application is shown in FIG. Figure 7 As shown, specifically, obtaining the cable cost in step S105 includes: Step S701: According to the initial population of the booster station and the preset coastline position, the coast point closest to the booster station is obtained, and the coast point is used as the feeder cable node.

[0109] In this embodiment, the booster station positions in the initial population of booster stations are connected to the preset coastline positions to obtain multiple lines, and the point on the coastline corresponding to the shortest line among the multiple lines is used as the coast point, and the coast point is used as the feeder cable node.

[0110] Step S702: Obtaining a path layout according to the wind turbine position and the feeder cable nodes.

[0111] Step S703: According to preset constraint conditions, the path layout is constrained to obtain a constrained path layout.

[0112] In this embodiment, for example, the preset constraint conditions are the safety distance between wind turbines and the area of ​​the wind farm.

[0113] Step S704: Obtain a cable cost model according to the constraint path layout, wind turbine location and cable information.

[0114] Step S705: Obtain the cable cost according to the cable cost model.

[0115] In this embodiment, according to Formula 9: (9) Get the cable cost Cost. Among them, C unit is the cable unit price; d(i,j) is the Euclidean distance between point i and point j; sf is the safety factor; when type C cable is used between point i and point j, then x c (i,j) is 1, otherwise it is 0.

[0116] In this embodiment, based on the initial population of the substation and the preset coastline position, the coast point closest to the substation is obtained, and the coast point is used as the feeder cable node; based on the wind turbine position and the feeder cable node, a path layout is obtained; based on the preset constraints, the path layout is constrained to obtain a constrained path layout; based on the constrained path layout, the wind turbine position and the cable information, a cable cost model is obtained; based on the cable cost model, the cable cost is obtained, and then the wind turbine layout and the substation layout can be optimized according to the cable cost.

[0117] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art can understand that in order to achieve the effect of the present application, different steps do not have to be performed in such an order. They can be performed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present application.

[0118] Furthermore, the present application also provides a wind farm layout processing device based on dual populations.

[0119] Figure 8 The schematic diagram of the structure of a wind farm layout processing device based on dual populations provided in the embodiment of the present application. Figure 8As shown, the device in the embodiment of the present application mainly includes an acquisition module 11, an analysis module 12, a processing module 13, a selection module 14, a variation module 15 and a conversion module 16. In some embodiments, one or more of the acquisition module 11, the analysis module 12, the processing module 13, the selection module 14, the variation module 15 and the conversion module 16 can be combined into one module. In some embodiments, the acquisition module 11 can be configured to obtain the wind farm area range. The analysis module 12 can be configured to obtain the first wind turbine initial population and the second wind turbine initial population according to the wind farm area range. The acquisition module 11 can also be configured to acquire the i-th population of the first wind turbine group and the i-th population of the second wind turbine group in the i-th iteration; wherein, when i=1, the first population of the first wind turbine group is the initial population of the first wind turbine group, the first population of the second wind turbine group is the initial population of the second wind turbine group, the i-th population of the first wind turbine group and the i-th population of the second wind turbine group both contain multiple individuals, each individual in the i-th population of the first wind turbine group is a regularly arranged shape variable, and each individual in the i-th population of the second wind turbine group is a wind turbine group coordinate vector. The analysis module 12 can be configured to obtain the i-th population of the booster station according to the i-th population of the first wind turbine group and the i-th population of the second wind turbine group and the optimization constraints; wherein, when i=1, the first population of the booster station is the initial population of the booster station. The processing module 13 can be configured to perform fitness calculation on the i-th population of the first wind turbine group, the i-th population of the second wind turbine group, and the i-th population of the booster station according to the first optimization target and the second optimization target, and obtain the fitness result; wherein the first optimization target is to maximize the total output power, and the second optimization target is to minimize the cable cost. The selection module 14 can be configured to perform selection processing on the i-th population of the first wind turbine group, the i-th population of the second wind turbine group, and the i-th population of the booster station according to the fitness result, and obtain the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group, and the i-th optimized population of the booster station. The mutation module 15 can be configured to perform mutation processing on the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group, and the i-th optimized population of the booster station to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group, and the i+1-th population of the booster station; wherein 1≤i≤I, wherein I corresponds to the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group, and the i-th optimized population of the booster station obtained after the i-th iteration. The conversion module 16 can be configured to obtain a wind turbine arrangement according to the i-th optimized population of the first wind turbine group and the i-th optimized population of the second wind turbine group.

[0120] The above-mentioned wind farm layout processing device based on dual population is used to execute Figure 1The embodiment of the wind farm layout processing method based on dual populations shown in the figure has similar technical principles, technical problems solved and technical effects produced. Technicians in this technical field can clearly understand that for the convenience and conciseness of description, the specific working process and related instructions of the wind farm layout processing device based on dual populations can refer to the contents described in the embodiment of the wind farm layout processing method based on dual populations, and will not be repeated here.

[0121] It is understood by those skilled in the art that all or part of the processes in the method for implementing the above-mentioned embodiments of the present application can also be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device, medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium, etc. that can carry the computer program code. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electric carrier signals and telecommunication signals.

[0122] Furthermore, the present application also provides a wind farm layout processing device based on dual populations.

[0123] Fig. 9 This is a schematic diagram of the structure of a wind farm layout processing device based on dual populations provided in the present application. Fig. 9 As shown, the wind farm layout processing device based on dual populations includes at least one processor 21 and a memory 22, and the memory 22 can be configured to store and execute the above Figures 1 to 7 The program of the wind farm layout processing method based on dual populations in the illustrated embodiment, the processor 21 can be configured to execute the program in the memory 22, which includes but is not limited to executing a program of a wind farm layout processing method based on dual populations in the above method embodiment. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The wind farm layout processing device based on dual populations can be a control device device formed by various electronic devices.

[0124] Furthermore, the present application also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present application, the computer-readable storage medium can be configured to store a program for executing the wind farm layout processing method based on dual populations of the above-mentioned method embodiment, and the program can be loaded and run by the processor to implement the above-mentioned wind farm layout processing method based on dual populations. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment 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 embodiment of the present application is a non-temporary computer-readable storage medium.

[0125] Further, it should be understood that since the setting of each module is only for illustrating the functional units of the device of the present application, the physical devices corresponding to these modules may be the processor itself, or a part of the software in the processor, a part of the hardware, or a part of the combination of software and hardware. Therefore, the number of each module in the figure is only schematic.

[0126] It is understood by those skilled in the art that each module in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principle of the present application, and therefore, the technical solutions after splitting or merging will fall within the protection scope of the present application.

[0127] So far, the technical solutions of the present application have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, 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. Without departing from the principles of the present application, 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 application.

Claims

1. A wind farm layout processing method based on dual populations, characterized in that: include: Get the area of ​​the wind farm; According to the wind farm area, obtaining a first wind turbine generator set initial population and a second wind turbine generator set initial population; In the i-th iteration, the i-th population of the first wind turbine group and the i-th population of the second wind turbine group are obtained; wherein, when i=1, the first population of the first wind turbine group is the initial population of the first wind turbine group, the first population of the second wind turbine group is the initial population of the second wind turbine group, the i-th population of the first wind turbine group and the i-th population of the second wind turbine group both contain multiple individuals, each individual in the i-th population of the first wind turbine group is a regularly arranged shape variable, and each individual in the i-th population of the second wind turbine group is a wind turbine group coordinate vector; According to the i-th population of the first wind turbine generator set and the i-th population of the second wind turbine generator set and the optimization constraint, the i-th population of the booster station is obtained; wherein, when i=1, the first population of the booster station is the initial population of the booster station; According to the first optimization target and the second optimization target, the fitness of the i-th group of the first wind turbines, the i-th group of the second wind turbines and the i-th group of the booster stations is calculated to obtain a fitness result; wherein the first optimization target is to maximize the total output power, and the second optimization target is to minimize the cable cost; According to the fitness result, the i-th population of the first wind turbine generator set, the i-th population of the second wind turbine generator set and the i-th population of the booster station are selected to obtain the i-th optimized population of the first wind turbine generator set, the i-th optimized population of the second wind turbine generator set and the i-th optimized population of the booster station; The i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group, and the i-th optimized population of the booster station are mutated to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group, and the i+1-th population of the booster station; wherein 1≤i≤I, wherein I corresponds to the I-th optimized population of the first wind turbine group, the I-th optimized population of the second wind turbine group, and the I-th optimized population of the booster station obtained after the I-th iteration; According to the first optimized population of the first wind turbines and the first optimized population of the second wind turbines, an arrangement of the wind turbines is obtained.

2. The method according to claim 1, characterized in that The step of obtaining a first initial population of wind turbines according to the wind farm area range includes: According to the wind farm area, a global center point is obtained; According to the first preset range, the ratio of the starting points in the line is obtained; According to the preset angle range, the parallel line rotation angle is obtained; According to the preset constraint conditions, the minimum spacing between rows and the minimum spacing within rows are obtained; According to the second preset range, a line spacing gradient coefficient is obtained; According to the third preset range, obtaining the intra-line spacing gradient coefficient; Obtaining the shape variables of the regular arrangement according to the global center point coordinates, the ratio of the starting points within the row, the parallel line rotation angle, the minimum spacing between rows, the minimum spacing within a row, the row spacing gradient coefficient, and the intra-row spacing gradient coefficient; A plurality of the regularly arranged shape variables are combined to obtain the first initial population of wind turbines.

3. The method according to claim 1, characterized in that The step of obtaining a wind turbine arrangement according to the first optimized population of the first wind turbines and the first optimized population of the second wind turbines comprises: Performing point processing on the regularly arranged shape variables in the first optimized population of the first wind turbine generator set to obtain an available point vector; In the nth cycle, according to the nth coordinate in the first optimized population of the second wind turbine generator set and the available point vector, a distance set between the nth coordinate in the first optimized population of the second wind turbine generator set and the available point vector is obtained; Obtaining the coordinates of the nth wind turbine generator set according to the distance set of the available points; Combining the coordinates of the first wind turbine group to the coordinates of the Nth wind turbine group to obtain the arrangement of the wind turbine groups; Wherein, 1≤n≤N, wherein N is the number of coordinates in the first optimized population of the second wind turbine generator set.

4. The method according to claim 1, characterized in that: The initial population of the booster station is obtained, including: Within the wind farm area, according to preset booster station position constraints, the booster station coordinates are obtained; The booster station coordinates are combined to obtain the initial population of booster stations.

5. The method according to claim 1, characterized in that The step of performing mutation processing on the i-th optimized population of the first wind turbine generator set, the i-th optimized population of the second wind turbine generator set, and the i-th optimized population of the booster station to obtain the i+1-th population of the first wind turbine generator set, the i+1-th population of the second wind turbine generator set, and the i+1-th population of the booster station includes: Determine whether i is less than the preset number of iterations; If it is determined that i is less than or equal to the preset number of iterations, then for the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group, and the i-th optimized population of the booster station, within the preset large scale and the preset small scale, select the data of each individual to obtain the i+1th population of the first wind turbine group, the i+1th population of the second wind turbine group, and the i+1th population of the booster station; If it is determined that i is greater than the preset number of iterations, then for the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station, the data of each individual is selected within a preset small-scale range to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station.

6. The method according to claim 1, characterized in that The total output power is obtained, comprising: According to the speed loss of the upstream wind turbine at multiple points on the wind rotor of the current wind turbine, the inflow speed loss at multiple points on the wind rotor of the current wind turbine is obtained; According to the additional flow turbulence intensity of the upstream wind turbine at multiple points on the wind rotor of the current wind turbine, the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of the current wind turbine is obtained; Obtaining the wind speed in front of the hub of the current wind turbine generator set according to the inflow velocity losses at multiple points on the wind turbine rotor of the current wind turbine generator set; Obtaining a corresponding relationship between the wind speed in front of the hub of the current wind turbine and the power of the current wind turbine according to the wind conditions, the additional flow turbulence intensity of the inflow at multiple points on the wind rotor of the current wind turbine, and the wind speed in front of the hub of the current wind turbine; The total output power is obtained according to the wind condition, the corresponding relationship, the frequency of occurrence of the wind condition, the number of wind directions, the number of wind speed segments and the number of wind turbine generator sets.

7. The method according to claim 1, characterized in that Get the cable cost, including: According to the initial population of the booster station and the preset coastline position, the coast point closest to the booster station is obtained, and the coast point is used as a feeder cable node; Obtaining a path layout according to the wind turbine position and the feeder cable node; According to preset constraint conditions, the path layout is subjected to constraint processing to obtain a constrained path layout; Obtaining a cable cost model according to the constraint path layout, the wind turbine location and the cable information; The cable cost is obtained according to the cable cost model.

8. A wind farm layout processing device based on dual populations, characterized in that: include: An acquisition module is used to obtain the area range of the wind farm; An analysis module, configured to obtain a first initial population of wind turbines and a second initial population of wind turbines according to the wind farm area; The acquisition module is further used to acquire the i-th population of the first wind turbine group and the i-th population of the second wind turbine group in the i-th iteration; wherein, when i=1, the first population of the first wind turbine group is the initial population of the first wind turbine group, the first population of the second wind turbine group is the initial population of the second wind turbine group, the i-th population of the first wind turbine group and the i-th population of the second wind turbine group both contain multiple individuals, each individual in the i-th population of the first wind turbine group is a regularly arranged shape variable, and each individual in the i-th population of the second wind turbine group is a wind turbine group coordinate vector; The analysis module is further used to obtain the i-th population of booster stations according to the i-th population of the first wind turbine generator set and the i-th population of the second wind turbine generator set and the optimization constraint; wherein, when i=1, the first population of booster stations is the initial population of booster stations; A processing module, configured to calculate the fitness of the i-th population of the first wind turbine generator set, the i-th population of the second wind turbine generator set, and the i-th population of the booster station according to a first optimization objective and a second optimization objective, to obtain a fitness result; wherein the first optimization objective is to maximize the total output power, and the second optimization objective is to minimize the cable cost; A selection module is used to select the i-th population of the first wind turbine generator set, the i-th population of the second wind turbine generator set and the i-th population of the booster station according to the fitness result to obtain the i-th optimized population of the first wind turbine generator set, the i-th optimized population of the second wind turbine generator set and the i-th optimized population of the booster station; a mutation module, used for performing mutation processing on the i-th optimized population of the first wind turbine group, the i-th optimized population of the second wind turbine group and the i-th optimized population of the booster station to obtain the i+1-th population of the first wind turbine group, the i+1-th population of the second wind turbine group and the i+1-th population of the booster station; wherein 1≤i≤I, wherein I corresponds to the I-th optimized population of the first wind turbine group, the I-th optimized population of the second wind turbine group and the I-th optimized population of the booster station obtained after the I-th iteration; A conversion module is used to obtain a wind turbine arrangement according to the first optimized population of the first wind turbines and the first optimized population of the second wind turbines.

9. A wind farm layout processing device based on dual populations, comprising a processor and a storage device, wherein the storage device is suitable for storing multiple program codes, characterized in that: The program code is suitable for being loaded and executed by the processor to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and executed by a processor to execute the method according to any one of claims 1 to 7.

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