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

Abstract

The invention relates to the technical field of wind power plant micro-siting, and particularly provides a wind power plant layout optimization method and device based on a row arrangement rule and a medium, and the method comprises the steps: obtaining the attribute information of a to-be-optimized wind power plant; randomly generating a shape variable of a row arrangement rule based on the attribute information and establishing an initial population; based on the global center point coordinate, the in-row starting point proportion and the parallel line rotation angle in the shape variable, obtaining an arrangement scheme of the wind turbine generator; optimizing the arrangement scheme based on the initial population and the optimization target; when a preset convergence condition is met, an optimal arrangement scheme is obtained; according to the method, the arrangement scheme of the wind turbine generators is determined by using the global center point coordinates of the row arrangement rule, the in-row starting point proportion, the parallel line rotation angle and other parameters, the degree of freedom is higher, the mathematical optimal solution of the point locations of the wind turbine generators is realized, and the generating capacity of a wind power plant is remarkably improved; and traversal calculation is not needed, so that the machine arrangement efficiency is improved, and the comprehensive benefits of the whole life cycle of the wind power plant are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of micro-site selection for wind farms, and particularly to an optimization method, device, and medium for wind turbine layout based on row arrangement rules. Background Art

[0002] With the continuous growth of the global demand for clean energy, wind power, as one of the important renewable energy sources, has received extensive attention in its development and utilization. The construction scale of wind farms is constantly expanding, and the demand for optimizing the layout of wind turbines is becoming increasingly urgent; a reasonable layout of wind turbines can maximize the utilization of wind energy resources and improve the overall power generation efficiency of wind farms; this makes the importance of research on wind farm layout optimization more prominent.

[0003] Currently, the layout of wind farms often arranges wind turbines based on the parallelogram rule, and often uses a traversal calculation method, which requires a huge amount of time and computing resources, resulting in low efficiency and difficulty in meeting the requirements of rapid response and real-time optimization; at the same time, the parallelogram arrangement lacks flexibility in layout, which may lead to insufficient utilization of wind energy resources in some areas and inability to achieve the optimal layout of wind turbine positions, thus resulting in low power generation.

[0004] Correspondingly, there is a need in the art for a new optimization scheme for wind turbine layout based on row arrangement rules to solve the above problems. Summary of the Invention

[0005] In order to overcome the above defects, the present invention is proposed to solve or at least partially solve the technical problems that the layout method of wind turbines obtained by traversal calculation in existing wind farms is inefficient, it is difficult to obtain the true mathematical optimal solution of wind turbine positions, and the comprehensive benefits of wind farms are poor.

[0006] In a first aspect, an optimization method for wind turbine layout based on row arrangement rules is provided, and the method includes: Obtain the attribute information of the wind farm to be optimized; Randomly generate shape variables of row arrangement rules based on the attribute information; Establish an initial population based on the shape variables of the row arrangement rules, where the initial population includes multiple individuals, each individual is a set of shape variables of row arrangement rules, and the shape variables of the row arrangement rules include global center point coordinates, in-row starting point ratio, and parallel line rotation angle; Obtain the layout scheme of wind turbines in the wind farm to be optimized based on the global center point coordinates, in-row starting point ratio, and parallel line rotation angle; Optimize the layout scheme of wind turbines in the wind farm to be optimized based on the initial population and a preset optimization goal; After the preset optimization objective reaches the preset convergence condition, an optimal layout scheme of the wind turbines in the wind farm to be optimized is obtained.

[0007] In a technical solution of the above wind farm layout optimization method based on row arrangement rules, the attribute information includes the regional scope of the wind farm to be optimized; the shape variables of the row arrangement rules further include the minimum inter-row spacing, the minimum intra-row spacing, the row spacing gradient coefficient, and the intra-row spacing gradient coefficient; Randomly generating the shape variables of the row arrangement rules based on the attribute information includes: Setting the distance between any two wind turbines in the wind farm to be optimized, where the distance between any two wind turbines in the wind farm to be optimized is greater than n times the rotor diameter, and n is a positive integer greater than 1; Based on the regional scope of the wind farm to be optimized, randomly select the global center point coordinates; Based on the uniform probability distribution and the distance between any two wind turbines in the wind farm to be optimized, randomly select the intra-row starting point ratio within a preset ratio range, randomly select the parallel line rotation angle within a preset angle range, randomly select the minimum inter-row spacing and the minimum intra-row spacing within a preset spacing range, and randomly select the row spacing gradient coefficient and the intra-row spacing gradient coefficient within a preset coefficient range; Obtain the shape variables of the row arrangement rules based on the global center point coordinates, the intra-row starting point ratio, the parallel line rotation angle, the minimum inter-row spacing, the minimum intra-row spacing, the row spacing gradient coefficient, and the intra-row spacing gradient coefficient.

[0008] In a technical solution of the above wind farm layout optimization method based on row arrangement rules, the attribute information further includes the number of wind turbines in the wind farm to be optimized; The method for obtaining the layout scheme of the wind turbines in the wind farm to be optimized includes: Based on the global center point coordinates and the parallel line rotation angle, taking the horizontal line of the regional scope of the wind farm to be optimized as a reference, obtain a straight line intersecting with the regional scope of the wind farm to be optimized, and the length of the intersecting line segment between the two intersection points of the straight line and the regional scope of the wind farm to be optimized; Obtain a plurality of parallel line segments parallel to the intersecting line segment and the lengths of the plurality of parallel line segments within the regional scope of the wind farm to be optimized on both sides of the intersecting line segment; Starting from one end of all the parallel line segments, based on the intra-row starting point ratio and the lengths of all the parallel line segments, obtain a plurality of intra-row starting points corresponding on all the parallel line segments; where all the parallel line segments include the intersecting line segment and a plurality of parallel line segments parallel to the intersecting line segment; Obtain a plurality of gradient points on both sides of the plurality of in-row starting points, where the gradient points are coordinate points of wind turbines in the wind farm to be optimized; Obtain the layout scheme of the wind turbines in the wind farm to be optimized based on the coordinate points of the wind turbines in the plurality of wind farms to be optimized.

[0009] In a technical solution of the above wind farm layout optimization method based on row arrangement rules, the obtaining of a plurality of parallel line segments parallel to the intersecting line segment and the lengths of the plurality of parallel line segments within the area range of the wind farm to be optimized on both sides of the intersecting line segment includes: Obtain all the straight lines passing through the coordinates of the global center point, obtain the lengths of the line segments between the two intersection points of all the straight lines and the boundary of the wind farm to be optimized, and select the longest line segment; Based on the longest line segment and the minimum in-row spacing, obtain the maximum number of parallel line segments within the area range of the wind farm to be optimized; Based on the minimum in-row spacing, the maximum number of parallel line segments, and the in-row spacing gradient coefficient, obtain the in-row gradient interval between the parallel line segments; Generate a plurality of parallel line segments parallel to the intersecting line segment based on the intersecting line segment and the in-row gradient interval.

[0010] In a technical solution of the above wind farm layout optimization method based on row arrangement rules, the obtaining of a plurality of gradient points on both sides of the plurality of in-row starting points includes: Based on the lengths of all the parallel line segments and the minimum in-row spacing, obtain the maximum number of gradient points on each parallel line segment; Based on the minimum in-row spacing, the maximum number of gradient points on each parallel line segment, and the in-row spacing gradient coefficient, obtain the in-row gradient interval of each parallel line segment; Based on the in-row gradient interval of each parallel line segment, obtain a plurality of gradient points on both sides of the in-row starting point of each parallel line segment, and obtain the coordinate points of the plurality of gradient points.

[0011] In a technical solution of the above wind farm layout optimization method based on row arrangement rules, the preset convergence condition is that the target value of the preset optimization target is the largest; The method further includes: Optimize based on the initial population to obtain the shape variables of the row arrangement rules after optimization; Establish an optimized population based on the shape variables of the row arrangement rules after optimization, and obtain the layout scheme of the optimized wind turbines; When the target value of the preset optimization objective reaches the maximum, the optimization process ends, and the optimal shape variables of the row arrangement rule and the optimal layout scheme of the wind turbines in the wind farm to be optimized are obtained.

[0012] In a technical solution of the above wind farm layout optimization method based on the row arrangement rule, the preset optimization objective is the total output power of the wind farm to be optimized under the layout scheme of the wind turbines; The method for obtaining the total output power of the wind farm to be optimized includes: Obtain the wind resource information of the wind farm to be optimized, where the wind resource information includes the environmental incoming flow wind speed of the wind farm to be optimized; Based on the environmental incoming flow wind speed and the layout scheme of the wind farm to be optimized, obtain the total output power of the wind farm to be optimized according to the preset wind turbine wake model.

[0013] In a technical solution of the above wind farm layout optimization method based on the row arrangement rule, the preset wind turbine wake model includes a two-dimensional analytical model of the wind turbine wake and an analytical model of the additional turbulence intensity of the wind turbine wake; The obtaining of the total output power of the wind farm to be optimized according to the preset wake model based on the environmental incoming flow wind speed and the layout scheme of the wind farm to be optimized includes: Obtain the wake flow direction turbulence intensity of each wind turbine in the layout scheme based on the analytical model of the additional turbulence intensity of the wind turbine wake; Obtain the additional incoming flow direction turbulence intensity at multiple points on the wind wheel of each wind turbine based on the wake flow direction turbulence intensity of each wind turbine; Obtain the incoming flow velocity deficit at multiple points on the wind wheel of each wind turbine based on the two-dimensional analytical model of the wind turbine wake and the additional incoming flow direction turbulence intensity at multiple points on the wind wheel of each wind turbine; Obtain the wind speed in front of the hub of each wind turbine based on the incoming flow velocity deficit at multiple points on the wind wheel of each wind turbine and the environmental incoming flow wind speed; Obtain the output power of each wind turbine based on the wind speed in front of the hub of each wind turbine and the preset power curve of each wind turbine; Obtain the total output power of the wind farm to be optimized based on the output power of each wind turbine.

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

[0015] In a third aspect, a computer-readable storage medium is provided, which stores multiple program codes. The program codes are adapted to be loaded and run by a processor to execute the method described in any one of the technical solutions of the above technical solution of the wind farm layout optimization method based on row arrangement rules.

[0016] One or more of the above technical solutions of the present invention have at least one or more of the following beneficial effects: In the technical solution of the wind farm layout optimization method based on row arrangement rules provided by the present invention, attribute information of the wind farm to be optimized is obtained; shape variables of the row arrangement rules are randomly generated based on the attribute information, and an initial population is established based on the shape variables; the layout scheme of the wind turbines in the wind farm to be optimized is obtained based on the global center point coordinates, the starting point ratio within the row, and the parallel line rotation angle in the shape variables; the layout scheme is optimized based on the initial population and a preset optimization target; when the optimization target reaches the preset convergence condition, the optimal layout scheme of the wind turbines in the wind farm to be optimized is obtained; the present invention uses parameters such as the global center point coordinates, the starting point ratio within the row, and the parallel line rotation angle of the row arrangement rules to determine the layout scheme of the wind turbines, with a higher degree of freedom, realizes the mathematical optimal solution of the positions of the wind turbines, significantly improves the power generation of the wind farm; and there is no need to perform traversal calculations, improving the layout efficiency, thereby enhancing the comprehensive benefits of the entire life cycle of the wind farm. Description of the Drawings

[0017] Referring to the drawings, the disclosure of the present invention will become more understandable. 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 protection scope of the present invention. Among them: Figure 1 is a schematic main step flow diagram of the wind farm layout optimization method based on row arrangement rules according to an embodiment of the present invention; Figure 2 is a schematic main step flow diagram of randomly generating shape variables of row arrangement rules based on attribute information according to an embodiment of the present invention; Figure 3 is a schematic main step flow diagram of the layout scheme of the wind turbines in the wind farm to be optimized according to an embodiment of the present invention; Figure 4 is a schematic main step flow diagram of the method for obtaining multiple parallel line segments according to an embodiment of the present invention; Figure 5 is a schematic main step flow diagram of the method for obtaining multiple gradient points according to an embodiment of the present invention; Figure 6 is a wind rose diagram according to an embodiment of the present invention; Figure 7 is the unit power curve and thrust coefficient curve according to an embodiment of the present invention; Figure 8 is the original wind turbine positions of the wind farm to be optimized according to an embodiment of the present invention; Figure 9 is a schematic diagram of the wind turbine positions in the wind farm to be optimized under the optimal layout scheme based on the row arrangement rule according to an embodiment of the present invention; Figure 10 is a main structural schematic diagram of an electronic device according to an embodiment of the present invention.

[0018] Reference numerals: 101: Memory; 102: Processor. Specific embodiments

[0019] The following describes some embodiments of the present invention 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 invention and are not intended to limit the protection scope of the present invention.

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

[0021] Refer to the attached Figure 1 , Figure 1 is a main step flow schematic diagram of the wind farm layout optimization method based on the row arrangement rule according to an embodiment of the present invention. As Figure 1 shown, the wind farm layout optimization based on the row arrangement rule in the embodiment of the present invention mainly includes the following steps S101 to step S103.

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

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

[0024] Step S102: Randomly generate shape variables with row arrangement rules based on the attribute information; establish an initial population based on the shape variables with row arrangement rules.

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

[0026] Based on the regional scope of the wind farm to be optimized, the number of wind turbines, and the distance between any two wind turbines in the wind farm to be optimized, randomly generate shape variables with row arrangement rules, and establish an initial population of the genetic algorithm. Among them, the initial population includes multiple individuals, and each individual is a set of shape variables with row arrangement rules. A unique and determined layout scheme of the wind turbines in the wind farm to be optimized with row arrangement rules can be generated based on a specific point-taking program for the shape variables with row arrangement rules.

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

[0028] In this embodiment, the shape variables with row arrangement rules include the global center point coordinates , In-line starting point ratio r , Parallel line rotation angle θ , Minimum inter-line spacing , Minimum in-line spacing , Inter-line spacing gradient coefficient and in-line spacing gradient coefficient .

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

[0030] Step S202: Based on the uniform probability distribution and the distance between any two wind turbines in the wind farm to be optimized, randomly select the in-line starting point ratio within a preset ratio range, randomly select the parallel line rotation angle within a preset angle range, randomly select the minimum inter-line spacing and the minimum in-line spacing within a preset spacing range, and randomly select the inter-line spacing gradient coefficient and the in-line spacing gradient coefficient within a preset coefficient range; Specifically, randomly take out the in-line starting point ratio within the range of [0, 1) r , randomly take out the parallel line rotation angle within the range of [0°, 360°) θ , and randomly take out the minimum inter-line spacing and the minimum in-line spacing for the two parameters, randomly take out the inter-line spacing gradient coefficient and for the two parameters within the range of [0, 1), randomly take out the in-line spacing gradient coefficient and for the two parameters within the range of [0, 1), and for the two parameters; Step S203: Obtain the shape variables of the row arrangement rules based on the global center point coordinates, the in-line starting point ratio, the parallel line rotation angle, the minimum inter-line spacing, the minimum in-line spacing, the inter-line spacing gradient coefficient, and the in-line spacing gradient coefficient.

[0031] Specifically, based on the global center point coordinates , the in-line starting point ratio r , the parallel line rotation angle θ , the minimum inter-line spacing , minimum in-line spacing , line spacing gradient coefficient and in-line spacing gradient coefficient to obtain the shape variables of the row arrangement rule .

[0032] Step S103: Based on the global center point coordinates, in-line starting point ratio, and parallel line rotation angle, obtain the layout plan of the wind turbines in the wind farm to be optimized.

[0033] In this embodiment, referring to the attached Figure 3 , Figure 3 is the main step flow diagram of the layout plan of the wind turbines in the wind farm to be optimized according to an embodiment of the present invention. As Figure 3 shown, the method for obtaining the layout plan of the wind turbines in the wind farm to be optimized includes: Step S301: Based on the global center point coordinates and the parallel line rotation angle, taking the horizontal line of the area range of the wind farm to be optimized as a reference, obtain the straight line intersecting with the area range of the wind farm to be optimized, and the length of the intersecting line segment between the two intersection points of the straight line and the area range of the wind farm to be optimized; Specifically, taking the global center point coordinates as the center, taking the horizontal line of the area range of the wind farm to be optimized as a reference, make a straight line with an angle of the parallel line rotation angle θ with the horizontal line. The two intersection points of the straight line and the closed polygon boundary of the area range of the wind farm to be optimized are respectively A 1 , B 1 , forming the intersecting line segment , and determining the length of the intersecting line segment .

[0034] Step S302: Obtain multiple parallel line segments parallel to the intersecting line segment within the area range of the wind farm to be optimized on both sides of the intersecting line segment and the lengths of the multiple parallel line segments; Specifically, based on the intersecting line segment , take multiple parallel lines on both sides to obtain multiple parallel line segments within the closed polygon of the area range of the wind farm to be optimized, and determine the lengths of the multiple parallel line segments, and make a set of gradually changing parallel line segments, where is the total number of parallel line segments existing in the wind farm to be optimized, and each parallel line segment is a row .

[0035] Referring to the attached Figure 4 , Figure 4It is a schematic flowchart of the main steps of a method for obtaining multiple parallel line segments according to an embodiment of the present invention. As Figure 4 shown, obtaining multiple parallel line segments parallel to the intersecting line segment within the area range of the wind farm to be optimized on both sides of the intersecting line segment and the lengths of the multiple parallel line segments include: Step S401: Obtain all the straight lines passing through the global center point coordinates, obtain the lengths of the line segments between the two intersection points of all the straight lines and the boundary of the wind farm to be optimized, and select the longest line segment; Specifically, based on the global center point coordinates , obtain all the straight lines passing through the global center point coordinates . At this time, all the straight lines intersect with the boundary of the wind farm to be optimized; obtain the lengths of the line segments between the two intersection points of each straight line and the boundary of the wind farm to be optimized, select the longest line segment, and determine the length of the longest line segment as .

[0036] Step S402: Based on the longest line segment and the minimum inter-row spacing, obtain the maximum number of parallel line segments within the area range of the wind farm to be optimized; Specifically, based on the length of the longest line segment and the minimum inter-row spacing , determine that the maximum number of parallel line segments within the area range of the wind farm to be optimized is at most , where is the largest integer not exceeding z.

[0037] Step S403: Based on the minimum inter-row spacing, the maximum number of parallel line segments, and the row spacing gradient coefficient, obtain the inter-row gradient interval between the parallel line segments; specifically, consider the Gaussian distribution function with an average value of 0 , uniformly extract numbers in the range of [-1,1], then the gradient interval sets not less than can be obtained according to the Gaussian distribution function , where and are the row spacing gradient coefficients, is the maximum number of parallel line segments within the area range of the wind farm to be optimized.

[0038] Step S404: Generate multiple parallel line segments parallel to the intersecting line segment based on the intersecting line segment and the inter-row gradient interval.

[0039] Specifically, within the area range of the wind farm to be optimized, with the straight line as the center, take points on both sides according to the gradient interval set based on the Gaussian distribution, that is, take out inter-row gradient points on both sides of respectively; Judge

[0040] Whether the inter - row gradient points are within the wind farm range, remove the points beyond the range, and retain the set of parallel line segments composed of all passing gradient points 。

[0041] Step S303: Starting from one end of all parallel line segments, based on the in - row starting point ratio and the lengths of all parallel line segments, obtain multiple in - row starting points corresponding on all parallel line segments; among them, all parallel line segments include intersecting line segments and multiple parallel line segments parallel to the intersecting line segments; Specifically, starting from the starting point of the parallel line segment A i and based on the in - row starting point ratio r , at a position A i from the starting point with a distance , take a point as the in - row starting point of this row; similarly, repeat this process on other rows to obtain the in - row starting points of all rows.

[0042] Step S304: Obtain multiple gradient points on both sides of multiple in - row starting points, where the gradient points are the coordinate points of the wind turbines in the wind farm to be optimized; Specifically, starting from the in - row starting point R i of the row and according to the gradient point - taking method, take out the set of all gradient points on both sides of the in - row starting point R i on the row , where is the total number of gradient points on the row ; similarly, repeat this process on other rows to obtain the gradient points of all rows, and the gradient points are the coordinate points of the wind turbines in the wind farm to be optimized.

[0043] Refer to the appendix Figure 5 , Figure 5 is a schematic diagram of the main step flow for obtaining multiple gradient points according to an embodiment of the present invention. As Figure 5 shown, obtaining multiple gradient points on both sides of multiple in - row starting points includes: Step S501: Based on the lengths of all parallel line segments and the minimum in - row spacing, obtain the maximum number of gradient points on each parallel line segment; Specifically, based on the length of the current row (line segment ) and the minimum in - row spacing , determine the current row (line segment The maximum number of upper gradient points is , where is the largest integer not exceeding z.

[0044] Step S502: Obtain the in-line gradient interval of each parallel line segment based on the minimum in-line spacing, the maximum number of gradient points on each parallel line segment, and the in-line spacing gradient coefficient; Specifically, consider the Gaussian distribution function with an average of 0 , and uniformly extract numbers in the range of [-1, 1], then according to the Gaussian distribution function, in the current row (line segment ), gradient interval sets not less than can be obtained, where and are the in-line spacing gradient coefficients.

[0045] Step S503: Based on the in-line gradient interval of each parallel line segment, obtain multiple gradient points on both sides of the starting point of each parallel line segment in the line, and obtain the coordinate points of the multiple gradient points.

[0046] Specifically, on the current row (line segment ), centered on , based on the gradient interval set of the Gaussian distribution of each line segment, take points on both sides, that is, take points on both sides of the point ; Judge whether gradient points are within the range of the current row (line segment ), and remove the points that exceed the range of the current row (line segment ), then retain the coordinate point set of the multiple gradient points composed of all gradient points .

[0047] Step S305: Obtain the layout plan of the wind turbines in the wind farm to be optimized based on the coordinate points of the wind turbines in the multiple wind farms to be optimized.

[0048] Specifically, merge the coordinate points of the multiple gradient points of all rows into a coordinate point set , as the uniquely determined wind farm unit layout plan corresponding to the shape variable of the current row layout rule.

[0049] Step S104: Optimize the layout plan of the wind turbines in the wind farm to be optimized based on the initial population and the preset optimization goal; when the preset optimization goal reaches the preset convergence condition, obtain the optimal layout plan of the wind turbines in the wind farm to be optimized.

[0050] In this embodiment, the preset convergence condition is that the target value of the preset optimization objective is the largest; A method for optimizing the layout scheme of wind turbines in a wind farm to be optimized includes: Optimizing based on the initial population to obtain the shape variables of the row arrangement rule after optimization; Establishing an optimized population based on the shape variables of the row arrangement rule after optimization and obtaining the layout scheme of the wind turbines in the wind farm to be optimized; Until the target value of the preset optimization objective reaches the maximum, end the optimization process, and obtain the optimal shape variables of the row arrangement rule and the optimal layout scheme of the wind turbines in the wind farm to be optimized.

[0051] In one embodiment, the layout scheme of wind turbines in a wind farm to be optimized is optimized based on the genetic algorithm as the optimization algorithm, and the genetic algorithm can be the NSGA-II algorithm.

[0052] In one embodiment, the shape variables of the row arrangement rule can be obtained through crossover and mutation based on the constraint conditions of the coordinates of the wind turbines to obtain new shape variables of the row arrangement rule.

[0053] In one embodiment, the method for optimizing the initial population can be: setting the optimization target value, passing through the layout optimization process based on the optimization algorithm, and combining other frameworks to calculate the preset optimization objective, and iteratively obtaining a series of layout schemes of the wind turbines in the wind farm to be optimized that meet the requirements and have a globally better or optimal optimization target value. The specific optimization process of the initial population is as follows: (1) Population initialization. Randomly generate optimization variables (including the shape variables of the row arrangement rule) to form an initial population containing N individuals. Each individual is a definite layout scheme, containing the coordinates of N units. The optimization variables are encoded using real numbers, and the unit coordinates are randomly generated within the optimization constraints. If the available points of the generated row arrangement rule do not fully meet the optimization constraints, or the number of points is less than the required number of units, then regenerate this individual until it meets the requirements.

[0054] (2) Crossover and mutation. The present invention uses the simulated binary crossover method for crossover operations and performs mutation operations by adding Gaussian random numbers to the optimization variables (if the row arrangement rule layout form is used, crossover and mutation are performed on the shape variables). In the mutation operation, there is a chance to add random numbers of two scales, large and small, to the variables. The Gaussian standard deviation of the large-scale mutation is set to , and the Gaussian standard deviation of the small-scale mutation is set to , and the mutation probabilities and are respectively set.

[0055] (3) Combine the parent and offspring generations. Combine the parent generation with the offspring population generated by crossover and mutation to form a population of 2N individuals in total.

[0056] (4) Fast non-dominated sorting and crowding degree calculation. Calculate the optimization objective values of each individual in the merged population. According to the optimization objective values, find the non-dominated individuals in the merged population of parent and offspring in turn to divide them into ranks. In the same rank, sort the individuals in ascending order according to one objective to obtain the serial numbers i , and then calculate the crowding degree of the individuals .

[0057] (5) Screen to obtain the dominant population. Select N individuals in the merged population of parent and offspring using the obtained ranks. If adding a certain rank exactly exceeds the population size, then randomly select two individuals using the elite strategy in this rank , , and select the one with a larger crowding degree until the required number of individuals is taken.

[0058] (6) Convergence judgment. Return to (2) and repeat the steps until the number of iterations meets the requirements to obtain a convergent solution set. At this time, the convergent solution set is the optimized population.

[0059] In this embodiment, the preset optimization objective is the total output power of the wind farm to be optimized under the layout scheme of the wind turbines; The method for obtaining the total output power of the wind farm to be optimized includes: Obtain the wind resource information of the wind farm to be optimized, where the wind resource information includes the environmental incoming flow wind speed of the wind farm to be optimized; Based on the environmental incoming flow wind speed of the wind farm to be optimized and the layout scheme of the wind turbines in the wind farm to be optimized, obtain the total output power of the wind farm to be optimized according to the preset wind turbine wake model.

[0060] In this embodiment, the preset wind turbine wake model includes a two-dimensional analytical model of the wind turbine wake and an analytical model of the additional turbulence intensity of the wind turbine wake; Based on the environmental incoming flow wind speed of the wind farm to be optimized and the layout scheme of the wind turbines in the wind farm to be optimized, obtaining the total output power of the wind farm to be optimized according to the preset wake model includes: Obtain the wake flow direction turbulence intensity of each wind turbine in the layout scheme based on the analytical model of the additional turbulence intensity of the wind turbine wake; Obtain the additional incoming flow direction turbulence intensity at multiple points on the wind wheel of each wind turbine based on the wake flow direction turbulence intensity of each wind turbine; Obtain the incoming flow velocity deficit at multiple points on the wind wheel of each wind turbine based on the two-dimensional analytical model of the wind turbine wake and the additional incoming flow direction turbulence intensity at multiple points on the wind wheel of each wind turbine; Obtain the wind speed in front of the hub of each wind turbine based on the incoming flow velocity deficit at multiple points on the wind wheel of each wind turbine and the environmental incoming flow wind speed. Obtain the output power of each wind turbine based on the wind speed in front of the hub of each wind turbine and the preset power curve of each wind turbine; Obtain the total output power of the wind farm to be optimized based on the output power of each wind turbine.

[0061] In one embodiment, the method for obtaining the total output power of the wind farm to be optimized includes: Calculate the wake flow direction turbulence intensity of each wind turbine in the layout scheme. The wake flow direction turbulence intensity of the wind turbine can be obtained from the wake additional turbulence intensity analysis model of the wind turbine in the following formulas (1)-(6): (1) Where, is the thrust coefficient; is the atmospheric environmental turbulence intensity; D is the wind turbine rotor diameter; r is the lateral distance of the rotor axis; is the standard deviation of the Gaussian curve the same as the velocity deficit model; z is the vertical height.

[0062] Flow direction function is the maximum additional turbulence intensity of the wake cross-section at each flow direction position: (2) Where, ; ; is the correction value considering the near wake region.

[0063] Spanwise function of formula (1) is: (3) Where, and take values: (4) (5) is the vertical correction function: (6) For each wind turbine in the wind farm, obtain the additional inflow direction turbulence intensity at multiple points on the wind turbine rotor of the current wind turbine according to the wake flow direction turbulence intensity at multiple points on the wind turbine rotor of the upstream wind turbine of the current wind turbine: (7) Where, is the current i th unit on the wind turbine rotor point The inflow additional flow direction turbulence intensity at is the j th unit at the i point on the wind turbine rotor of the is a binary variable, when and only when the current i th unit is at the j downstream of the th unit ; N is the number of wind turbines in the wind farm to be optimized.

[0064] Obtain the average velocity deficit of the wind turbine according to the two-dimensional analytical model of the wind turbine wake and the inflow additional flow direction turbulence intensity at multiple points on the wind turbine rotor of each wind turbine: (8) Where is the thrust coefficient; is the actual expansion rate of the wake boundary; is the rotor radius; is the standard deviation of the spanwise distribution of the velocity deficit, taken as half of the wake width, which is also used as the wake radius, is the wake width.

[0065] Obtain the inflow velocity deficit at multiple points on the wind turbine rotor of the current wind turbine according to the average velocity deficit at multiple points on the wind turbine rotor of the upstream wind turbine of the current wind turbine: (9) Where is the inflow velocity deficit at the i point on the wind turbine rotor of the current th unit; j is the i th unit at the point on the wind turbine rotor of the i th unit; j is a binary variable, when and only when the current th unit is at the downstream of the N th unit

[0066] Obtain the wind speed in front of the hub of the current wind turbine under the preset wind conditions by taking the average value of the inflow velocity deficits at multiple points on the wind turbine rotor of the current wind turbine: (10) Where is the wind speed in front of the hub of the current typhoon wind turbine; i is the ambient oncoming wind speed; At a wind speed of and a wind direction angle of obtain the wind speed in front of the hub of the current wind turbine and the power curve of the current wind turbine, and obtain the output power of the current wind turbine under the above wind conditions; wherein, the wind turbine power curve includes the corresponding relationship between the wind speed in front of the hub and the output power of the wind turbine.

[0067] According to the output power corresponding to the above wind conditions, obtain the total output power of the wind farm to be optimized under the current layout plan: (11) Wherein, is the total output power of the wind farm to be optimized under the current layout plan; is the wind condition with a wind speed of and a wind direction of ; is the output power of the unit i under the wind condition of ; is the frequency of occurrence 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.

[0068] In an application scenario according to an embodiment of the present invention, the regional vertices of the wind farm to be optimized can be , , and , the coordinate dimension is meters (m), the unit model is Vestas-V80 unit (Vestas-V80 unit), the number of units is , the wind rose diagram is as Figure 6 shown, the unit power curve and the thrust coefficient curve are as Figure 7 shown, the original unit positions of the wind farm to be optimized are as Figure 8 shown, and the available form of the available positions of the units in the wind farm to be optimized is the row arrangement rule. It should be noted that the regional scope of the wind farm to be optimized, the coordinates of the regional vertices, the available form of the available positions of the units in the wind farm to be optimized, the unit model and the number of units, etc. are only for illustrative purposes, and can be set as needed in actual applications.

[0069] The basic parameters of the wind farm to be optimized are shown in Table 1; Table 1 Wind farm parameters

[0070] Select wind conditions with multiple wind directions and wind speeds. For the probability values at each wind direction and speed, refer to the appendix Figure 6 . Figure 6 is a wind rose diagram according to an embodiment of the present invention. In the appendix Figure 6 the central angle of the polar coordinate histogram represents the wind direction angle, and the height of the histogram represents the wind frequency. Figure 7 is the unit power curve and thrust coefficient curve according to an embodiment of the present invention. The ordinate Thrust Coefficient is the thrust coefficient, Power is the power (kW), and the abscissa Wind Speed is the wind speed (m / s). The optimization constraint conditions are the regional scope of the wind farm to be optimized and the distance between any two wind turbines must be greater than 4 times the rotor diameter D . In this application scenario, flat terrain is selected without considering the influence of complex terrain. It should be noted that the distance between any two wind turbines must be greater than 4 times the rotor diameter D , and the selection of flat terrain are all exemplary descriptions of this application scenario, and can be selected according to needs in practice.

[0071] Figure 8 is the original wind turbine positions of the wind farm to be optimized according to an embodiment of the present invention, Figure 9 is a schematic diagram of the wind turbine positions in the wind farm to be optimized under the optimal layout scheme based on the row arrangement rule according to an embodiment of the present invention. It can be seen from Figure 9 that the optimal wind turbine positions in the wind farm have obvious characteristics of row arrangement. The annual power generation corresponding to the wind turbine positions in the wind farm to be optimized under this optimal layout scheme is 269331.59 MWh. Compared with Figure 8 the annual power generation of 261616.18 MWh corresponding to the original wind turbine positions of the wind farm to be optimized in it, the optimized layout scheme based on the row arrangement rule has an annual power generation increase of about 2.949%, which can significantly improve the power generation of the entire life cycle of the wind farm while ensuring that the wind turbine positions in the wind farm to be optimized are arranged in a row arrangement rule.

[0072] It should be noted that although the above embodiments describe each step in a specific order, those skilled in the art can understand that in order to achieve the effects of the present invention, different steps do not necessarily have to be executed in such an order, and they can be executed simultaneously (in parallel) or in other orders. These adjusted schemes are equivalent technical schemes to the technical schemes described in the present invention, and therefore will also fall within the protection scope of the present invention.

[0073] Those skilled in the art can understand that all or part of the processes in the methods of the above-mentioned embodiments of the present invention can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable storage medium can include: any entity or device, medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, 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.

[0074] Another aspect of the present invention also provides a computer-readable storage medium.

[0075] In an embodiment of a computer-readable storage medium according to the present invention, the computer-readable storage medium can be configured to store a program for executing the row arrangement rule-based wind farm layout optimization method of the above-mentioned method embodiment. This program can be loaded and run by a processor to implement the above-mentioned row arrangement rule-based wind farm layout optimization method. For the sake of convenience of description, only the parts related to the embodiments of the present invention are shown. For the specific technical details not disclosed, please refer to the method part of the embodiments of the present invention. The computer-readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiments of the present invention is a non-transitory computer-readable storage medium.

[0076] Another aspect of the present invention also provides an electronic device.

[0077] In an embodiment of an electronic device according to the present invention, the electronic device can include at least one processor; and a memory communicatively connected to at least one processor; wherein, a computer program is stored in the memory, and when the computer program is executed by at least one processor, the method described in any of the above-mentioned embodiments is implemented. Refer to the appendix Figure 10 , Figure 10 in which the memory 101 and the processor 102 are communicatively connected through a bus is exemplarily shown.

[0078] In some embodiments of the present invention, the electronic device described in the present invention may be, but is not limited to, a mobile phone, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, a vehicle-mounted device, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), an augmented reality (AR) / virtual reality (VR) device, etc., and the embodiments of the present invention do not limit this.

[0079] So far, the technical solution of the present invention has been described in conjunction with one embodiment shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

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

2. The wind farm layout optimization method based on row arrangement rules according to claim 1 is characterized in that: The attribute information includes the area range of the wind farm to be optimized; the shape variables of the row arrangement rule also include the minimum spacing between rows, the minimum spacing within a row, the row spacing gradient coefficient and the intra-row spacing gradient coefficient; The shape variables for randomly generating row arrangement rules based on the attribute information include: The distance between any two wind turbines in the wind farm to be optimized is set, wherein the distance between any two wind turbines in the wind farm to be optimized is greater than the diameter of the wind rotor. times, is a positive integer greater than 1; Based on the regional scope of the wind farm to be optimized, randomly selecting the coordinates of the global center point; Based on the uniform probability distribution and the distance between any two wind turbines in the wind farm to be optimized, the ratio of the starting points in the row is randomly selected within a preset ratio range, the parallel line rotation angle is randomly selected within a preset angle range, the minimum spacing between rows and the minimum spacing within a row are randomly selected within a preset spacing range, and the row spacing gradient coefficient and the intra-row spacing gradient coefficient are randomly selected within a preset coefficient range; The shape variables of the row arrangement rule are obtained based on 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 row spacing gradient coefficient.

3. The wind farm layout optimization method based on row arrangement rules according to claim 2 is characterized in that: The attribute information also includes the number of wind turbines in the wind farm to be optimized; The method for obtaining the arrangement scheme of wind turbines in the wind farm to be optimized comprises: Based on the global center point coordinates and the parallel line rotation angle, taking the horizontal line of the regional range of the wind farm to be optimized as a reference, obtaining a straight line intersecting with the regional range of the wind farm to be optimized, and the length of the intersecting line segment between two points where the straight line intersects with the regional range of the wind farm to be optimized; Acquire, on both sides of the intersecting line segment, a plurality of parallel line segments parallel to the intersecting line segment within the region of the wind farm to be optimized and the lengths of the plurality of parallel line segments; Starting from one end of all parallel line segments, based on the ratio of in-line starting points and the lengths of all parallel line segments, a plurality of in-line starting points are correspondingly obtained on all parallel line segments; wherein all parallel line segments include the intersecting line segments and a plurality of parallel line segments parallel to the intersecting line segments; Acquire multiple gradient points on both sides of the multiple in-row starting points, wherein the gradient points are coordinate points of wind turbines in the wind farm to be optimized; An arrangement scheme of the wind turbine sets in the wind farm to be optimized is obtained based on a plurality of coordinate points of the wind turbine sets in the wind farm to be optimized.

4. The wind farm layout optimization method based on row arrangement rules according to claim 3 is characterized in that: The step of obtaining a plurality of parallel line segments parallel to the intersecting line segment within the region of the wind farm to be optimized on both sides of the intersecting line segment and the lengths of the plurality of parallel line segments comprises: Obtain all straight lines passing through the coordinates of the global center point, obtain the lengths of line segments between two points where all straight lines intersect the boundary of the wind farm to be optimized, and select the longest line segment; Based on the longest line segment and the minimum spacing between rows, obtaining the maximum number of parallel line segments within the regional range of the wind farm to be optimized; Based on the minimum inter-row spacing, the maximum number of the parallel line segments and the inter-row spacing gradient coefficient, obtaining an inter-row gradient interval between the parallel line segments; Based on the intersecting line segments and the inter-row gradient interval, a plurality of parallel line segments parallel to the intersecting line segments are generated.

5. The wind farm layout optimization method based on row arrangement rules according to claim 3 is characterized in that: The step of obtaining a plurality of gradient points on both sides of the starting points in the plurality of lines comprises: Based on the lengths of all the parallel line segments and the minimum spacing within the line, obtaining the maximum number of gradient points on each parallel line segment; Based on the minimum spacing within the line, the maximum number of gradient points on each parallel line segment and the gradient coefficient of the spacing within the line, obtaining the gradient spacing within the line of each parallel line segment; Based on the gradient interval within each parallel line segment, multiple gradient points are acquired on both sides of the starting point within each parallel line segment, and coordinate points of the multiple gradient points are obtained.

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

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

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

9. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores a computer program, and when the computer program is executed by the at least one processor, the method for optimizing wind farm layout based on row arrangement rules according to any one of claims 1 to 8 is implemented.

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

Images