A method and system for optimizing the layout of wind turbines considering regional restrictions

Abstract

The present application discloses a method and system for optimizing the arrangement of wind turbines considering regional restrictions, belonging to the field of wind power generation technology. The optimization method includes: analyzing the restricted area, identifying and processing the placement area and the prohibited placement area in the wind resource map; constructing the initial area for placing wind turbines according to the placement area and the prohibited placement area; analyzing the initial position of the machine site, verifying whether the safety distance and the placement area requirements are met, and calculating the initial wake power generation; randomly selecting and updating the position of the wind turbine; using the wake model to calculate the wake power generation under the current wind turbine arrangement; judging whether to update the wind turbine arrangement benchmark according to the wake power generation under the current wind turbine arrangement, and determining whether to continue the cyclic optimization according to the comparison between the number of iterations and the total number of optimizations, and finally outputting the optimal wind turbine arrangement and wake power generation. The optimization of wind turbine arrangement under the constraints of complex real areas is realized.

Description

Technical Field

[0001] The present application belongs to the field of wind power generation technology, and in particular, relates to a method and system for optimizing the arrangement of wind turbines taking into account regional restrictions. Background Art

[0002] Wind power generation has become one of the important means to achieve sustainable development due to its environmental protection and low carbon characteristics. During the planning and construction of wind farms, the layout of wind turbines is directly related to the power generation efficiency, construction cost, environmental impact and other aspects of the entire wind farm. Therefore, how to optimize the layout of wind turbines has become a key issue in wind farm design.

[0003] At present, the development of wind turbine layout optimization is mainly focused on search algorithms. With the development of computing technology and the advancement of optimization algorithms, more and more intelligent optimization algorithms are being applied to wind turbine layout optimization, such as genetic algorithms, particle swarm optimization algorithms, and simulated annealing algorithms. These algorithms can improve the overall benefits of wind farms to a greater extent by simulating real wind farm environments and optimizing calculations. Most of these algorithms are based on ideal conditions, assuming that all areas in the entire wind resource map can be used to deploy wind turbines.

[0004] However, the construction of wind farms needs to be carried out in real space and is affected by various regional restrictions such as topography, land use, environmental protection, noise control and safety distance. These restrictions make the area where wind turbines are arranged often not a regular rectangular space, so the layout problem becomes more complicated. How to reasonably achieve the optimization of wind turbine layout under these regional restrictions, there is still relatively little research on related technologies. Therefore, a wind turbine layout optimization method and system considering regional restrictions is proposed, which can better meet the various complex regional restriction requirements in reality while ensuring the efficiency of wind resource utilization, and has important research significance and application value. Summary of the invention

[0005] The purpose of this application is to provide a method and system for optimizing the layout of wind turbines taking into account regional restrictions, so as to achieve optimization of the layout of wind turbines under realistic and complex regional restriction conditions.

[0006] In order to solve the above technical problems, the technical solution adopted in this application is:

[0007] In a first aspect, the present application provides a method for optimizing the arrangement of wind turbines taking into account regional restrictions, comprising:

[0008] Parse the restricted area file uploaded by the user or read the restricted area range set by the user, identify and process the deployment area and prohibited area in the wind resource map; construct the initial area grid where wind turbines can be deployed based on the deployment area and prohibited area;

[0009] Parse the initial position file of the machine site uploaded by the user to obtain the initial wind turbine arrangement; based on the initial wind turbine arrangement, calculate the initial wake power generation of the wind turbine as the initial wind turbine arrangement benchmark;

[0010] Perform wake power generation calculation iterations: Under regional restrictions, randomly select and update the quasi-new wind turbine arrangement through two rounds of position updates; calculate the quasi-new wake power generation under the quasi-new wind turbine arrangement using the wake model according to the quasi-new wind turbine arrangement; when the quasi-new wake power generation is greater than the initial wake power generation, update the quasi-new wind turbine arrangement to a new baseline wind turbine arrangement, and update the quasi-new wake power generation to a new baseline wake power generation; return and continue the cyclic optimization until the end of the iteration, and output the wind turbine arrangement and wake power generation at the end of the iteration as the optimal wind turbine arrangement plan.

[0011] As a further improvement of the present application, the parsing of the restricted area file uploaded by the user or reading the restricted area range set by the user, identifying and processing the deployment area and the prohibited deployment area in the wind resource map specifically includes:

[0012] The restricted area analysis uploaded by the user includes polygonal area analysis and circular area analysis. The types of restricted areas include deployment areas and prohibited areas.

[0013] Polygonal area analysis is the analysis of a closed polygonal area surrounded by multiple line segments. The coordinates of all the endpoints of the polygon are obtained in the order of arrangement, and each endpoint is connected in sequence according to the order of arrangement to describe the area where the polygon is located.

[0014] Circular area analysis describes the circular area by recording the coordinates of the center of the circle and the radius of the circle.

[0015] As a further improvement of the present application, the initial area grid for deploying wind turbines is constructed according to the deployment area and the prohibited deployment area; including:

[0016] According to the deployment area and the prohibited area, construct the initial deployment area grid, including the large grid variable and small grid variables ;

[0017] Large grid with resolution Divide the wind resource map area into a large grid, and the large grid variable There are three values: -1, 0, and 1. When the area of ​​the large grid that can be deployed is zero, is -1; when the area of ​​the large grid that can be placed is hour, 1; in other cases is 0; =εD / 4, D is the diameter of the wind turbine, ε is the safety spacing factor;

[0018] for The large grid is 0, and the minimum distance accuracy ds is further used as the resolution to segment and construct small grids. The small grid variables It is the ratio of the area that can be laid out in the small grid to the area of ​​the small grid.

[0019] As a further improvement of the present application, the initial position file of the machine site uploaded by the user is parsed to obtain the initial wind turbine arrangement; based on the initial wind turbine arrangement, the initial wake power generation of the wind turbine is calculated as the initial wind turbine arrangement benchmark, including:

[0020] Parse the initial position file of the machine site uploaded by the user to determine whether the wind turbines meet the safety distance constraint ε×D between the wind turbines, where D is the diameter of the wind turbine and ε is the safety spacing coefficient; and determine whether the wind turbine coordinates are located in the layout area of ​​the initial area grid. When both conditions are met, obtain the initial wind turbine coordinates ( , ) as the initial wind turbine arrangement benchmark, and calculate the current wake power generation as the initial wake power generation; in other cases, the initial position of the turbine site is re-analyzed.

[0021] As a further improvement of the present application, in the iterative calculation of wake power generation, determining whether to continue the cyclic optimization is performed based on the comparison between the number of iterations and the total number of optimizations, specifically including:

[0022] The calculation iteration is recorded as a large cycle. In the first large cycle, the initial wind turbine arrangement is the baseline wind turbine arrangement and the quasi-new wind turbine arrangement, the initial wake power generation is the baseline wake power generation, and the initial large cycle number is 0;

[0023] When the number of large cycles is greater than the set number of large cycles, the benchmark wind turbine arrangement and benchmark wake power generation are output and the process ends. When the number of large cycles is less than or equal to the set number of large cycles, the large cycle is started for repeated calculation and iteration, and the number of large cycles is increased by 1.

[0024] As a further improvement of the present application, in the iterative calculation of wake power generation, under the regional restriction condition, two rounds of position updates are performed to randomly select and update the arrangement of quasi-new wind turbines, specifically including:

[0025] According to the total number of wind turbines, the number of wind turbines that need to be moved is randomly determined, and the numbers of the wind turbines that need to be moved are randomly determined;

[0026] According to all wind turbines that do not need to be moved, with the location of the wind turbine as the center and the safe distance between wind turbines as the radius, a new temporary no-release area is constructed. Based on the initial deployable area grid, the influence of the no-release area is taken into account, and the deployable area grid at this time is constructed. The deployable area grid at this time is regarded as a dynamic deployable area grid. The large grid variable at this time is T, and the small grid variable is α;

[0027] Perform a small cycle judgment. When the number of small cycles is less than or equal to the number of fans that need to be moved, start the small cycle and increase the number of small cycles by 1.

[0028] Start a round of update. Randomly select the large grid number where the fan needs to be placed from all large grids where T>0. If there is no large grid to place the fan, the small cycle ends abnormally.

[0029] Start the second round of updates. Determine the large grid based on the first round of updates. Randomly generate the small grid number where the fan needs to be placed in all small grids with α≥0.5 to obtain the specific location of the fan. When there is no small grid to place the fan, the small cycle ends abnormally.

[0030] Update the deployable area grid. Based on the current deployable area grid, with the location of the wind turbine as the center and the safe distance between wind turbines as the radius, construct a new temporary prohibited area, generate a new dynamic deployable area grid, and update the values ​​of the large and small grid variables.

[0031] Determine whether to arrange the quasi-new wind turbine group. When the small cycle ends abnormally, the quasi-new wind turbine group arrangement is not updated. When the small cycle ends normally, the wind turbine group arrangement at this time is used as the quasi-new wind turbine group arrangement. The wind turbine group coordinates corresponding to the arrangement at this time are recorded as ( , ).

[0032] As a further improvement of the present application, the method for calculating the wake power generation includes:

[0033] The Park model is used to calculate the wake of each wind turbine in the current wind turbine arrangement. The calculation formula is as follows:

[0034] ;

[0035] ;

[0036] ;

[0037] in is the downstream wind speed of the wind turbine; is the free flow wind speed of the wind turbine, h H is the height; =AΓ(1+1 / k ), It is determined by the Mabel parameters A and K, Γ represents the Gamma function; is the thrust coefficient of the wind turbine; s is the ratio of the distance between the downstream position and the center point of the wind turbine to the diameter of the wind turbine. The distance between the downstream position and the center point of the wind turbine is determined by the diameter D of the wind turbine. k is the wake expansion coefficient, is the surface roughness; represents the wake of the wind turbine;

[0038] The power generation of the current wind turbine arrangement after considering the wake is:

[0039]

[0040]

[0041] in, Indicates the wake power generation of the current wind turbine arrangement, t is the preset time period, specifically one year, v is the wind speed segment value in Weibull fitting, is the number of wind turbines currently arranged. is the number of sectors, is the number of wind speed segments; Indicates wind turbine n In the sector i and wind speed range j The probability density of wind speed at time , k is the wake expansion coefficient; Indicates wind turbine n In wind speed range j The wind turbine power at Wind speed range j With wind speed segment j -1 interval.

[0042] In a second aspect, the present application provides a wind turbine arrangement optimization system considering regional restrictions, including:

[0043] The file parsing unit is used to parse the restricted area file uploaded by the user or read the restricted area range set by the user, identify and process the deployment area and the prohibited area in the wind resource map; construct the initial area grid where the wind turbine can be deployed according to the deployment area and the prohibited area;

[0044] The initial calculation unit is used to parse the initial position file of the machine site uploaded by the user to obtain the initial wind turbine arrangement; based on the initial wind turbine arrangement, the initial wake power generation of the wind turbine is calculated as the initial wind turbine arrangement benchmark;

[0045] The iterative calculation unit is used to perform iterative calculation of wake power generation: under regional restriction conditions, through two rounds of position updates, randomly select and update the quasi-new wind turbine arrangement; according to the quasi-new wind turbine arrangement, use the wake model to calculate the quasi-new wake power generation under the quasi-new wind turbine arrangement; when the quasi-new wake power generation is greater than the initial wake power generation, the quasi-new wind turbine arrangement is updated to a new baseline wind turbine arrangement, and the quasi-new wake power generation is updated to a new baseline wake power generation; return and perform iterative calculation of wake power generation, and output the wind turbine arrangement and wake power generation at the end of the iteration as the optimal wind turbine arrangement plan.

[0046] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for optimizing the arrangement of wind turbines taking into account regional restrictions when executing the computer program.

[0047] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing the arrangement of wind turbines considering regional restrictions is implemented.

[0048] In a fifth aspect, the present application provides a computer program product, wherein the computer program product includes computer instructions, and the computer instructions instruct a computer to execute the wind turbine arrangement optimization method considering regional restrictions.

[0049] The beneficial effects of this application compared to the prior art are:

[0050] By proposing deployment areas and prohibited areas, this application allows users to define "deployment areas", that is, areas where wind turbines are allowed to be deployed, and "prohibited areas", that is, areas where wind turbines are not allowed to be deployed, thereby realizing regional restrictions when optimizing the layout of wind turbines and ensuring that the layout of wind turbines meets actual geographical and environmental protection requirements; by setting a safety spacing coefficient, a safe distance between wind turbines is ensured to avoid mutual interference and accident risks; the power generation generated by the layout of wind turbines is evaluated using the wake power generation calculation formula; by iteratively updating the positions of wind turbines for multiple times, it is realized to find a layout scheme with the maximum wake power generation under given constraints, in which the wind turbine placement position is calculated by two rounds of position updates, which effectively ensures that the space of the deployable area is fully considered while ensuring calculation efficiency; ultimately, a complete technical route for optimizing the layout of wind turbines considering regional restrictions is formed, and ultimately the optimization of the layout of wind turbines under realistic complex regional restrictions is realized, with the advantages of improving power generation efficiency, reducing costs, enhancing safety, environmental benefits, flexibility and intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following introduction is made to the drawings of the embodiments of the present application or the related technical solutions in the prior art. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 A schematic diagram of a method for optimizing the arrangement of wind turbines taking into account regional restrictions provided by an embodiment of the present invention;

[0053] Figure 2 A schematic diagram of the initial deployable area grid structure according to an embodiment of the present invention;

[0054] Figure 3 A schematic diagram of two rounds of position updates provided by an embodiment of the present invention;

[0055] Figure 4 This is a flow chart of step S7 in an embodiment of the present invention;

[0056] Figure 5 Schematic diagram of the wind turbine layout optimization system architecture considering regional restrictions according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and are not to be construed as limitations on the present application. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0058] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present application have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0059] It should be noted that the terms used here are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof. It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The embodiments will be described in detail below in conjunction with the accompanying drawings.

[0060] The following are explanations of the relevant terms involved in this application:

[0061] RSF file: "RSF" is the abbreviation of "Resource Summary File", which is used to describe the distribution and summary information of wind resources.

[0062] WTG file, Wind Turbine Generator, is the model data of the wind turbine generator.

[0063] The shp format is a vector data format used to store geographic information system (GIS) data. It is used to represent features such as points, lines, and polygons, and record their coordinates and attribute information. The shp format is commonly used to store and share various types of GIS data, such as maps, terrain, population data, etc.

[0064] Gamma function, also known as Euler's second integral, is a type of function that extends the factorial function on real and complex numbers. This function has important applications in analysis, probability theory, partial differential equations, and combinatorial mathematics.

[0065] Wind turbine thrust coefficient CT, a wind turbine is a device that converts wind energy into electrical energy, in which the rotor blades are the core components of power generation. During the rotation process, each blade will bear the impact of the wind and generate a thrust.

[0066] Weibull parameters are shape parameter and scale parameter. The shape parameter determines the shape of the Weibull distribution, while the scale parameter determines the scale of the Weibull distribution, that is, the scale of the time or life span of the event.

[0067] The Park model is a mathematical model used to describe the dynamic behavior of three-phase motors (especially separately excited synchronous motors and asynchronous motors).

[0068] The first purpose of this application is to propose a wind turbine layout optimization method considering regional restrictions, such as Figure 1As shown, the following steps are included.

[0069] Step 1: parse the restricted area file uploaded by the user or read the restricted area range set by the user, identify and process the deployment area and prohibited area in the wind resource map; construct the initial area grid where the wind turbine can be deployed according to the deployment area and prohibited area;

[0070] Step 2: parse the initial position file of the machine site uploaded by the user to obtain the initial wind turbine arrangement; based on the initial wind turbine arrangement, calculate the initial wake power generation of the wind turbine as the initial wind turbine arrangement benchmark;

[0071] Step 3, perform iterative calculation of wake power generation: under regional restriction conditions, randomly select and update the quasi-new wind turbine arrangement through two rounds of position updates; according to the quasi-new wind turbine arrangement, use the wake model to calculate the quasi-new wake power generation under the quasi-new wind turbine arrangement; when the quasi-new wake power generation is greater than the initial wake power generation, update the quasi-new wind turbine arrangement to a new baseline wind turbine arrangement, and update the quasi-new wake power generation to a new baseline wake power generation; return and continue the cyclic optimization until the end of the iteration, and take the wind turbine arrangement and wake power generation at the end of the iteration as the optimal wind turbine arrangement plan and output them.

[0072] The following is a detailed description of each step of this application:

[0073] Step S1: wind resource map analysis: parse the wind resource map file to obtain the height H, coordinates and altitude (X, Y, Z), Weibull parameters (A, K), sector frequency F, and sector number N of the grid points in the wind resource map. d Information, where X, Y, can determine the spatial range of the wind resource map, used in steps S4, S5, S7 and S8; Z and wind turbine hub height h H , used in steps S5 and S8 to determine the vertical coordinates of each wind turbine, so as to determine whether the downstream wind turbine is located in the wake area of ​​the upstream wind turbine; the height H is used in step S2 to determine whether it is consistent with the wind turbine hub height; the Weibull parameters (A, K) include the total A of all sectors A , K A Also includes the A corresponding to each sector i , K i , A A , K A For the calculation of free flow wind speed u0 in steps S5 and S8, A i , K i , F and N d Used for power generation calculation in steps S5 and S8.

[0074] Step S2: Analyze basic model information: Analyze the wind turbine power curve WTG file uploaded by the user, read the parameters set by the user, and obtain the wind turbine characteristic parameters and model parameters. The wind turbine characteristic parameters include wind turbine thrust coefficient CT, wind turbine power P, wind turbine diameter D and hub height h H , are used for the wake power generation calculation in steps S5 and S8. The thrust coefficient CT and wind turbine power P are both functions of the wind speed segment v. P contains the total number of wind speed segments, i.e., the number of wind speed segments N. s ; In addition, only when the hub height h H The calculation result is accurate only when it is consistent with the height H of the grid point in the map in step S1. In other cases, the user needs to re-upload the wind resource map or reset the wind turbine model. The model parameters include the safety spacing coefficient ε, the minimum distance accuracy ds, the surface roughness z0, the wake expansion coefficient k, and the total number of optimizations m, where the safety spacing coefficient ε and the minimum distance accuracy ds are used for the large and small grid resolution calculations in step S4; the surface roughness z0 and the wake expansion coefficient k are used for the wake calculations in steps S5 and S8; the total number of optimizations m is used for the judgment of the start of the large cycle in step S6.

[0075] In the above embodiment, steps S1 and S2 mainly parse the wind resource map file to obtain key parameters in the wind resource map; parse the basic information of the wind turbine arrangement model, and read the user setting parameters to obtain characteristic parameters and model parameters. Key parameters include the height, coordinates, altitude, Weibull parameters, frequency and number of sectors of the grid points; characteristic parameters include wind turbine thrust coefficient, wind turbine power, wind turbine diameter, and hub height; model parameters include safety spacing coefficient, minimum distance accuracy and total number of optimizations.

[0076] Step S3: parsing the restricted area; parsing the restricted area file uploaded by the user or reading the restricted area range set by the user, identifying and processing the deployment area and the prohibited area in the wind resource map; both methods require the user to input the type of the restricted area, namely "deployment area" and "prohibited area"; the area range set by the user supports two methods: polygonal area setting and circular area setting. The polygonal area setting is set by setting multiple points, each of which is numbered as ip and has coordinates ( , ), connect the points in order to describe the polygonal area; set the circular area by setting the coordinates of the center of the circle and the radius of the circle , which can represent the scope of the circular area; it supports users to upload restricted area files and set restricted area scopes multiple times, and form the final restricted area settings through superposition. If the same area involves multiple restricted area type settings, the final setting shall prevail.

[0077] Restricted area analysis aims to clarify the "deployment area" and "prohibited area" in the wind farm to ensure the reasonable layout of wind turbines while avoiding interference with the ecological environment, important facilities or sensitive areas. In the absence of a clear "deployment area", it is generally considered that the entire wind resource map, except for the clearly marked "prohibited area", is a deployment area.

[0078] As an example, the polygon area setting can flexibly adapt to various complex terrains and boundary conditions, such as rivers, mountains, forests, residential areas, etc., to ensure the accuracy of the deployment area division. By adjusting the coordinates and arrangement order of the endpoints, the shape and size of the polygon can be easily modified to meet the specific needs of different projects.

[0079] As an example, the circular area setting is relatively simple and direct, mainly by recording the coordinates of the center of the circle and the radius of the circle To describe the scope of the circular area. This method is suitable for restricted areas with regular shapes and clear boundaries, such as lakes, protection areas of large facilities, etc.

[0080] As a further example, polygonal area analysis and circular area analysis each have their own unique advantages and applicable scenarios. In practical applications, the appropriate analysis method should be selected according to the specific needs and constraints of the project. At the same time, in order to ensure the accuracy and reliability of the analysis results.

[0081] Step S4: Initial deployable area grid construction: construct the initial area grid where wind turbines can be deployed according to the restricted area range analyzed in step S3; solve the large grid variable The value and small grid variable This step depends on the wind turbine diameter D, safety spacing factor ε and minimum distance accuracy ds obtained in step S2.

[0082] The initial area grid where wind turbines can be placed is a nested grid, including large grids and small grids; the resolution of the large grid is =ε×D / 4. Where D is the diameter of the wind turbine and ε is the safety spacing factor;

[0083] like Figure 2 As shown, the large grid variable There are only three values: -1, 0, and 1. When the area of ​​the deployable area in the large grid is zero, is -1; when the area of ​​the large grid that can be placed is hour, 1, the rest is 0. The large grid is 0, and the small grid is constructed with the minimum distance accuracy ds as the resolution. It is the ratio of the area that can be laid out in the small grid to the area of ​​the small grid.

[0084] Step S5: Initialize the position of the machine site; parse the initial position file of the machine site uploaded by the user, determine whether the wind turbines meet the safety distance constraint (ε×D) between the wind turbines, and determine whether the coordinates of the wind turbines are located in the "deployment area". If they meet the requirements, obtain the initial coordinates of the wind turbines ( , ), calculate the initial wake power generation of the wind turbine under the arrangement of the wind turbine at this time (The calculation of wake power generation is the same as step S8, see this step for details) as the initial wind turbine arrangement benchmark, and proceed to the next step. If it is not satisfied, the user is asked to re-enter; if it is satisfied, the number of initial wind turbines is the number of wind turbines in the current wind turbine arrangement in step S8 ; It depends on the wind resource map coordinate information (X, Y, Z) obtained in step S1, the safety spacing factor ε obtained in step S2, the diameter D of the wind turbine, and the restricted area information obtained in step S3, including the coordinates of the arrangement order ip of all the endpoints of the polygon ( , ), the coordinates of the center of the circular area and the radius of the circle .

[0085] As an example, strict safety distance constraint verification ensures the safe distance between wind turbines, avoiding potential safety hazards caused by too close spacing between turbines. Verification of deployment areas and prohibited deployment areas ensures that wind farm planning complies with relevant laws and regulations and environmental protection requirements, reducing legal risks that may arise from illegal construction. The estimation of wake power generation provides an important basis for the economic benefit evaluation of wind farms, helping project decision makers to more accurately evaluate the feasibility and profitability of projects.

[0086] Step S6: Iteration start judgment, record this cycle as a large cycle, in the first large cycle, the initial wind turbine arrangement is the benchmark wind turbine arrangement and the quasi-new wind turbine arrangement, the initial wake power generation is the benchmark wake power generation, the initial large cycle number is 0, and the total number of optimizations m obtained in step S2 is the number of large cycles in this step. When the number of large cycles is greater than the set number of large cycles, the benchmark wind turbine arrangement and the benchmark wake power generation are output and the cycle ends. When the number of large cycles is less than or equal to the set number of large cycles, the large cycle is started, and the number of large cycles is +1.

[0087] As an example, the arrangement of wind turbines can be dynamically adjusted by continuously iterating the algorithm to pursue higher power generation efficiency. Setting the total number of optimizations m as the iteration termination condition ensures that the algorithm stops after reaching the predetermined number of iterations, avoiding the possibility of an infinite loop. The following is the specific implementation process of this step and its advantages analysis:

[0088] As a further example, it is allowed to find a relatively good solution within a limited number of iterations, which not only ensures the optimization effect, but also controls the computational cost and time. The wind turbine arrangement and wake power generation output finally output are the results of multiple iterations of optimization, with high reliability and practicality. The total number of optimizations m can be adjusted according to actual needs to adapt to wind farm planning problems of different scales and complexities. The iteration process and result output are clear and concise, which is convenient for users to understand and analyze the optimization effect.

[0089] Step S7: Position update, a method for updating the wind turbine layout position under regional restriction conditions.

[0090] The implementation of this step depends on the wind resource map coordinate information (X, Y, Z) obtained in step S1, the safety spacing factor ε obtained in step S2, the wind turbine diameter D, and the large grid variable obtained in step S4. and small grid variables , the initial wind turbine coordinates obtained in step S5 ( , ), initial wake power generation E W0 .

[0091] like Figure 3 and Figure 4 As shown, the above step S7: position update, considering the wind turbine arrangement position update method under the regional restriction condition, the specific steps are as follows:

[0092] S7-1, randomly calculate the number of wind turbines that need to be moved according to the total number of wind turbines, and randomly calculate the numbers of the wind turbines that need to be moved based on the number of wind turbines that need to be moved.

[0093] S7-2: Based on all the wind turbines that do not need to be moved, with the location of the wind turbine as the center and the safe distance between the wind turbines as the radius, a new temporary "forbidden area" is constructed. Based on the initial deployable area grid, the influence of the "forbidden area" is taken into account, and the deployable area grid at this time is constructed. The deployable area grid at this time is regarded as a "dynamic deployable area grid". The large grid variable at this time is T, and the small grid variable is α.

[0094] S7-3, small cycle judgment, when the number of small cycles is less than or equal to the number of fans that need to be moved, the small cycle is started, and the number of small cycles is increased by 1.

[0095] S7-4, starts a round of updating. Among all the large grids with T>0, randomly selects the large grid number where the fan needs to be placed. When there is no large grid to place the fan, the small cycle ends abnormally.

[0096] S7-5, start the second round of updates, determine the large grid based on the first round of updates, randomly select the small grid number where the fan needs to be placed from all the small grids with α≥0.5, and obtain the specific location of the fan. When there is no small grid to place the fan, the small cycle ends abnormally.

[0097] S7-6, update the grid of the deployable area. Based on the current grid of the deployable area, with the location of the wind turbine as the center and the safe distance between wind turbines as the radius, construct a new temporary "no-placement area", generate a new "dynamic deployable area grid", update the values ​​of the large and small grid variables, and continue to step S7-3. (The wind turbine that moves randomly at the end skips this step)

[0098] S7-7, quasi-fresh wind turbine arrangement. When the small cycle ends abnormally, the quasi-fresh wind turbine arrangement is not updated. When the small cycle ends normally, the wind turbine arrangement at this time is used as the quasi-fresh wind turbine arrangement. The wind turbine coordinates corresponding to the arrangement are recorded as ( , ).

[0099] Therefore, by iteratively updating the location of wind turbines, taking into account safety distance constraints and deployment area restrictions, it helps to improve the overall layout efficiency and power generation of wind farms. The introduction of randomness and a multi-layer grid system makes the search process more flexible and can explore more layout solutions. By setting the maximum number of attempts and a multi-layer update mechanism, the algorithm tries to find an optimal solution that meets the conditions while maintaining search efficiency.

[0100] S8: Calculate wake power generation. Use the wake model and power generation calculation formula to calculate wake power generation. This step requires the height H, coordinates and altitude (X, Y, Z), Weibull parameters (A, K), sector frequency F, and number of sectors of the grid point in the map of step S1. Information, wind turbine thrust coefficient CT, wind turbine power P, wind turbine diameter D, hub height h in step S2 H , step S5 wind turbine coordinates ( , ) or step S7 wind turbine coordinates ( , ).

[0101] The Park model is used to calculate the wake of each wind turbine in the current wind turbine arrangement. The calculation formula is as follows.

[0102] ;

[0103] ;

[0104] ;

[0105] Where u is the downstream wind speed of the wind turbine; u0 is the free flow wind speed of the wind turbine, h H is the height; by the Weibull parameter A A and K A Determine, determined by step S1, u0=A A Γ(1+1 / K A ), Γ represents the Gamma function; CT is the thrust coefficient of the wind turbine, which is determined by step S2; s is the ratio of the distance between the downstream position and the center point of the wind turbine to the diameter D of the wind turbine, the distance between the downstream position and the center point of the wind turbine is determined by the wind turbine coordinates of step S5 or S7, and D is determined by step S2; k is the wake expansion coefficient, which is usually 0.075 and is determined by step S2; z0 is the surface roughness, which is determined by step S2; C w Represents the wake of a wind turbine.

[0106] The power generation of the current wind turbine arrangement after considering the wake is:

[0107]

[0108]

[0109] in, It represents the power generation of the current wind turbine arrangement after considering the wake, that is, the wake power generation; t is the preset time period, specifically one year, and v is the wind speed segment value in the Weibull fitting; The number of wind turbines currently arranged in the wind turbine group is determined in step S5; is the number of sectors, determined by step S1; is the number of wind speed segments, determined by step S2; represents the wind speed probability density of wind turbine n in sector i and wind speed segment j, where A i , K i Determined by step S1; represents the wind turbine power of wind turbine n in wind speed range j, is the interval between wind speed segment j and wind speed segment j-1, determined by step S2. The wake power generation calculated based on the quasi-new wind turbine arrangement is the quasi-new wake power generation, and the wake power generation calculated based on the reference wind turbine arrangement is the reference wake power generation.

[0110] S9: Update judgment. According to the relationship between the quasi-new wake power generation obtained in step S8 and the benchmark wake power generation obtained in step S7, determine whether to update the benchmark wind turbine arrangement. If the quasi-new wake power generation is greater than the benchmark wake power generation, the quasi-new wind turbine arrangement is updated to the benchmark wind turbine arrangement. In other cases, the benchmark wind turbine arrangement is not updated. After the judgment is completed, enter step S6.

[0111] As an example, determining whether to update the baseline wind turbine arrangement and the baseline wake power generation includes:

[0112] Compare the quasi-new wake power generation with the benchmark wake power generation. If the quasi-new wake power generation is greater than the benchmark wake power generation, the quasi-new wind turbine arrangement is updated to the benchmark wind turbine arrangement, and the quasi-new wake power generation is updated to the benchmark wake power generation. In other cases, the benchmark wind turbine arrangement is not updated.

[0113] like Figure 5 As shown, this embodiment also provides a wind turbine layout optimization system that takes regional restrictions into consideration. The system is divided into a front-end part and a back-end part. The front-end mainly includes three modules: an instruction parsing module, a data transmission module, and a visualization module. The modules are responsible for parsing user instructions, transferring user data to the back-end for parsing, and completing data visualization, including visualization of wind resource maps, visualization of wind turbine locations, and visualization of restricted areas. For example, the "layout area" can be normal bright color, the "prohibited area" can be shaded dark color, and the circular area within the wind turbine safety spacing can be a circular border filled with a light gray transparent band.

[0114] The backend mainly consists of nine modules: data analysis module, area analysis module, area judgment module, constraint judgment module, wake calculation module, power generation calculation module, first round random search module, second round random search module, and update module. Among them, the data analysis module is responsible for analyzing the data uploaded by the user, and is mainly used to implement steps S1, S2, S3 and S5 in the method of this application;

[0115] The area parsing module is responsible for parsing the restricted area range and supports two methods of parsing restricted areas, one is a circular area and the other is a polygonal area. It allows users to set restricted areas in three ways: 1) input the center and radius of the circular area. This method will be parsed by parsing the circular restricted area method; 2) upload the shp file, the system will automatically parse the shp file and extract the area information. This method will use the polygonal area parsing method for parsing; 3) input the coordinates of multiple endpoints, the last point must coincide with the first point, the system will connect multiple endpoints in sequence, if all line segments can form a polygon without self-intersection, all line segments do not cross, and the number of endpoints needs to be greater than 3, this method will also use the polygonal area parsing method for parsing; this module is mainly used to implement steps S3 and S7 in the method of this application;

[0116] The area judgment module is responsible for judging the positional relationship between the target point and the restricted area, and constructing a deployable area grid, and is mainly used in steps S4, S5 and S7 of the method of this application.

[0117] The constraint judgment module is responsible for judging whether the wind turbines meet the safety distance constraints, mainly using steps S5 and S7.

[0118] The wake calculation module is responsible for calculating the wake loss under the current wind turbine arrangement and is mainly used in steps S5 and S8.

[0119] The power generation calculation module is responsible for calculating the wake power generation under the current wind turbine arrangement, and is mainly used in steps S5 and S8.

[0120] A round of random search module is responsible for a round of update, randomly moving the wind turbines with a coarse resolution to determine the approximate location of the wind turbine layout, and is mainly used in step S7.

[0121] The second round random search module is responsible for the second round of updating, randomly moving the wind turbines with fine resolution to determine the fine position of the wind turbine layout, and is mainly used in step S7.

[0122] The update module is responsible for determining whether the baseline wind turbine arrangement needs to be updated and whether to continue to iterate on the position update, and is mainly used in steps S6 and S9.

[0123] The wind turbine arrangement optimization system considering regional restrictions provided in the embodiment of the present application specifically includes: three front-end modules and nine back-end modules to implement various links of a wind turbine arrangement optimization method considering regional restrictions.

[0124] The three front-end modules are the instruction parsing module, the data transmission module and the visualization module. The instruction parsing module is responsible for parsing the user instructions; the data transmission module is responsible for transferring the data uploaded by the user on the front-end to the back-end for parsing, and transferring the back-end data to the front-end for visualization; the visualization module is responsible for performing data visualization, including visualization of wind resource maps, visualization of wind turbine locations, and visualization of restricted areas.

[0125] The nine modules of the backend are data analysis module, area analysis module, area judgment module, constraint judgment module, wake calculation module, power generation calculation module, first-round random search module, second-round random search module and update module. The data analysis module is responsible for parsing the data uploaded by users; the area analysis module is responsible for parsing the scope of the restricted area; the constraint judgment module is responsible for judging whether the wind turbines meet the constraints of the safe distance; the area judgment module is responsible for judging the positional relationship between the target point and the restricted area, and constructing the deployable area grid; the wake calculation module is responsible for calculating the wake loss under the current wind turbine arrangement; the power generation calculation module is responsible for calculating the wake power generation under the current wind turbine arrangement; the first-round random search module is responsible for realizing the first round of position update; the first-round random search module is responsible for realizing the second round of position update; the update module is responsible for judging whether the baseline wind turbine arrangement needs to be updated, and whether to continue to start the iteration of position update.

[0126] The wind resource map file parsing stage and the model basic information parsing stage are both implemented by the instruction parsing module, data transmission module, visualization module and data parsing module.

[0127] The restricted area analysis link is implemented by the instruction analysis module, data transmission module, visualization module, data analysis module and area analysis module.

[0128] The initial deployable area grid construction process is implemented by the area judgment module, wake calculation module and power generation calculation module.

[0129] The initialization of the machine site position is implemented by the analysis module, data transmission module, visualization module, data analysis module, area judgment module and constraint judgment module.

[0130] The iteration start judgment phase is implemented by the update module.

[0131] The position update link is implemented by a first-round random search module, a second-round random search module, a region analysis module, a region judgment module and a constraint judgment module.

[0132] The wake power generation calculation link is implemented by the wake calculation module and the power generation calculation module.

[0133] The update judgment link is implemented by the data transmission module, visualization module and update module.

[0134] Combination Figure 5 The second purpose of the embodiment of the present application is to provide a wind turbine arrangement optimization system considering regional restrictions, including the following modules:

[0135] The instruction parsing module is responsible for parsing user instructions;

[0136] Data transmission module, responsible for transmitting user data to the backend for analysis;

[0137] Visualization module, responsible for completing data visualization;

[0138] The data analysis module is responsible for analyzing the data uploaded by the user, and is used to implement the wind resource map analysis, model basic information analysis, restricted area analysis, and machine site location initialization in the method of this application;

[0139] The area resolution module is responsible for resolving the restricted area range, and is mainly used to implement the restricted area resolution and location update in the method of this application;

[0140] The area judgment module is responsible for judging the positional relationship between the target point and the restricted area, and constructing a deployable area grid. It is mainly used to implement the initial deployable area grid construction, machine site location initialization and location update in the method of this application.

[0141] The constraint judgment module is responsible for judging whether the wind turbines meet the safety distance constraints, and is mainly used for initializing and updating the position of the wind turbine site.

[0142] The wake calculation module is responsible for calculating the wake loss under the current wind turbine arrangement, and is mainly used for initializing the position of the step generator site and calculating the wake power generation.

[0143] The power generation calculation module is responsible for calculating the wake power generation under the current wind turbine arrangement, and is mainly used for stepping the machine site location initialization and wake power generation calculation.

[0144] A round of random search module is responsible for one round of update, randomly moving the wind turbines with a coarse resolution to determine the approximate location of the wind turbine layout, which is mainly used for position update.

[0145] The second round random search module is responsible for the second round of updates, randomly moving the wind turbines with fine resolution to determine the fine location of the wind turbine layout, and is mainly used for position updates.

[0146] The update module is responsible for determining whether the baseline wind turbine arrangement needs to be updated and whether to continue the iteration of starting the position update. It is mainly used for step iteration start judgment and update judgment.

[0147] The system requires users to input wind resource map RSF file, wind turbine WTG file and initial machine location, and set parameters and restricted area. Through the above modules, the system can effectively perform wind turbine layout optimization considering regional restrictions, output wind turbine layout, wake power generation, and calculate iteration time.

[0148] Based on the above embodiment, the use of the system requires the user to input the wind resource map RSF file, the wind turbine WTG file and the initial machine location, and perform parameter settings and restricted area settings. Through the above modules, the system can effectively perform wind turbine layout optimization considering regional restrictions, output wind turbine layout, wake power generation, and calculate iteration time.

[0149] The second purpose of the embodiment of the present application is to provide a wind turbine arrangement optimization system considering regional restrictions, based on the above-mentioned wind turbine arrangement optimization method considering regional restrictions, specifically including:

[0150] The file parsing unit is used to parse the restricted area file uploaded by the user or read the restricted area range set by the user, identify and process the deployment area and the prohibited area in the wind resource map; construct the initial area grid where the wind turbine can be deployed according to the deployment area and the prohibited area;

[0151] The initial calculation unit is used to parse the initial position file of the machine site uploaded by the user to obtain the initial wind turbine arrangement; based on the initial wind turbine arrangement, the initial wake power generation of the wind turbine is calculated as the initial wind turbine arrangement benchmark;

[0152] The iterative calculation unit is used to perform iterative calculation of wake power generation: under regional restriction conditions, through two rounds of position updates, randomly select and update the quasi-new wind turbine arrangement; according to the quasi-new wind turbine arrangement, use the wake model to calculate the quasi-new wake power generation under the quasi-new wind turbine arrangement; when the quasi-new wake power generation is greater than the initial wake power generation, the quasi-new wind turbine arrangement is updated to a new baseline wind turbine arrangement, and the quasi-new wake power generation is updated to a new baseline wake power generation; return and perform iterative calculation of wake power generation, and output the wind turbine arrangement and wake power generation at the end of the iteration as the optimal wind turbine arrangement plan.

[0153] The third object of an embodiment of the present application is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the wind turbine layout optimization method considering regional restrictions when executing the computer program.

[0154] A fourth objective of an embodiment of the present application is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing the arrangement of wind turbines taking into account regional restrictions is implemented.

[0155] A fifth objective of an embodiment of the present application is to provide a computer program product, wherein the computer program product includes computer instructions, and the computer instructions instruct a computer to execute the method for optimizing the arrangement of wind turbines considering regional restrictions.

[0156] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0157] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0158] The present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, readable storage medium, optical storage, etc.) containing computer-usable program codes.

[0159] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0160] Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application rather than to limit it. Although the present application has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present application can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present application should be included in the protection scope of the present application.

Claims

1. A method for optimizing the layout of wind turbines considering regional restrictions, characterized in that: include: Parse the restricted area file uploaded by the user or read the restricted area range set by the user, identify and process the deployment area and prohibited area in the wind resource map; According to the deployment area and the prohibited area, construct the initial area grid where the wind turbines can be deployed; Parse the initial position file of the machine site uploaded by the user to obtain the initial wind turbine arrangement; Based on the initial wind turbine arrangement, the initial wake power generation of the wind turbine is calculated as a benchmark for the initial wind turbine arrangement; Perform wake power generation calculation iterations: Under regional restrictions, randomly select and update the quasi-new wind turbine arrangement through two rounds of position updates; calculate the quasi-new wake power generation under the quasi-new wind turbine arrangement using the wake model according to the quasi-new wind turbine arrangement; When the quasi-new wake power generation is greater than the initial wake power generation, the quasi-new wind turbine arrangement is updated to a new reference wind turbine arrangement, and the quasi-new wake power generation is updated to a new reference wake power generation; Return and continue the optimization cycle until the iteration ends, and take the wind turbine arrangement and wake power generation at the end of the iteration as the optimal wind turbine arrangement plan and output it; According to the deployment area and the prohibited area, an initial area grid for deploying wind turbines is constructed; include: According to the deployment area and the prohibited area, construct the initial deployment area grid, including the large grid variable and small grid variables ; Large grid with resolution Divide the wind resource map area into a large grid, and the large grid variable There are three values: -1, 0, and 1. When the area of ​​the large grid that can be deployed is zero, is -1; when the area of ​​the large grid that can be placed is hour, 1; in other cases is 0; =εD / 4, D is the diameter of the wind turbine, ε is the safety spacing factor; for The large grid is 0, and the minimum distance accuracy ds is further used as the resolution to segment and construct small grids. The small grid variables It is the ratio of the area that can be laid out in the small grid to the area of ​​the small grid; In the iterative calculation of wake power generation, determining whether to continue the cyclic optimization is performed based on the comparison between the number of iterations and the total number of optimizations, specifically including: The calculation iteration is recorded as a large cycle. In the first large cycle, the initial wind turbine arrangement is the baseline wind turbine arrangement and the quasi-new wind turbine arrangement, the initial wake power generation is the baseline wake power generation, and the initial large cycle number is 0; When the number of large cycles is greater than the set number of large cycles, the benchmark wind turbine arrangement and benchmark wake power generation are output and the process ends. When the number of large cycles is less than or equal to the set number of large cycles, the large cycle is started for repeated calculation and iteration, and the number of large cycles is increased by 1. In the iterative calculation of wake power generation, under the regional restriction condition, two rounds of position updates are performed to randomly select and update the arrangement of quasi-new wind turbines, specifically including: According to the total number of wind turbines, the number of wind turbines that need to be moved is randomly determined, and the numbers of the wind turbines that need to be moved are randomly determined; According to all wind turbines that do not need to be moved, with the location of the wind turbine as the center and the safe distance between wind turbines as the radius, a new temporary no-release area is constructed. Based on the initial deployable area grid, the influence of the no-release area is taken into account, and the deployable area grid at this time is constructed. The deployable area grid at this time is regarded as a dynamic deployable area grid. The large grid variable at this time is T, and the small grid variable is α; Perform a small cycle judgment. When the number of small cycles is less than or equal to the number of fans that need to be moved, start the small cycle and increase the number of small cycles by 1. Start a round of update. Randomly select the large grid number where the fan needs to be placed from all large grids where T>0. If there is no large grid to place the fan, the small cycle ends abnormally. Start the second round of updates. Determine the large grid based on the first round of updates. Randomly generate the small grid number where the fan needs to be placed in all small grids with α≥0.5 to obtain the specific location of the fan. When there is no small grid to place the fan, the small cycle ends abnormally. Update the deployable area grid. Based on the current deployable area grid, with the location of the wind turbine as the center and the safe distance between wind turbines as the radius, construct a new temporary prohibited area, generate a new dynamic deployable area grid, and update the values ​​of the large and small grid variables. Determine whether to arrange the quasi-new wind turbine group. When the small cycle ends abnormally, the quasi-new wind turbine group arrangement is not updated. When the small cycle ends normally, the wind turbine group arrangement at this time is used as the quasi-new wind turbine group arrangement. The wind turbine group coordinates corresponding to the arrangement at this time are recorded as ( , ).

2. A method for optimizing the layout of wind turbines considering regional restrictions according to claim 1, characterized in that: The parsing of the restricted area file uploaded by the user or reading the restricted area range set by the user, identifying and processing the deployment area and the prohibited deployment area in the wind resource map specifically includes: The restricted area analysis uploaded by the user includes polygonal area analysis and circular area analysis. The types of restricted areas include deployment areas and prohibited areas. Polygonal area analysis is the analysis of a closed polygonal area surrounded by multiple line segments. The coordinates of all the endpoints of the polygon are obtained in the order of arrangement, and each endpoint is connected in sequence according to the order of arrangement to describe the area where the polygon is located. Circular area analysis describes the circular area by recording the coordinates of the center of the circle and the radius of the circle.

3. The method for optimizing the layout of wind turbines considering regional restrictions according to claim 1, characterized in that: The initial position file of the machine site uploaded by the user is parsed to obtain the initial arrangement of the wind turbine sets; Based on the initial wind turbine arrangement, the initial wind turbine wake power generation is calculated as the initial wind turbine arrangement benchmark, including: Parse the initial position file of the machine site uploaded by the user to determine whether the wind turbines meet the safety distance constraint ε×D between the wind turbines, where D is the diameter of the wind turbine and ε is the safety spacing coefficient; and determine whether the wind turbine coordinates are located in the layout area of ​​the initial area grid. When both conditions are met, obtain the initial wind turbine coordinates ( , ) as the initial wind turbine arrangement benchmark, and calculate the current wake power generation as the initial wake power generation; in other cases, the initial position of the turbine site is re-analyzed.

4. The method for optimizing the layout of wind turbines considering regional restrictions according to claim 1, characterized in that: The method for calculating the wake power generation comprises: The Park model is used to calculate the wake of each wind turbine in the current wind turbine arrangement. The calculation formula is as follows: ； ; ； in, is the downstream wind speed of the wind turbine; is the free flow wind speed of the wind turbine, h H is the height; =AΓ(1+1 / k ), Determined by the Weibull parameters A and K, Γ represents the Gamma function; is the thrust coefficient of the wind turbine; s is the ratio of the distance between the downstream position and the center point of the wind turbine to the diameter of the wind turbine. The distance between the downstream position and the center point of the wind turbine is determined by the diameter D of the wind turbine. k is the wake expansion coefficient, is the surface roughness; represents the wake of the wind turbine; The power generation of the current wind turbine arrangement after considering the wake is: in, Indicates the wake power generation of the current wind turbine arrangement, t is the preset time period, specifically one year, v is the wind speed segment value in Weibull fitting, is the number of wind turbines currently arranged. is the number of sectors, is the number of wind speed segments; Indicates wind turbine n In the sector i and wind speed range j The probability density of wind speed at time ; Indicates wind turbine n In the wind speed range j The wind turbine power at Wind speed range j With wind speed segment j -1 interval.

5. A wind turbine arrangement optimization system considering regional restrictions, based on the wind turbine arrangement optimization method considering regional restrictions as claimed in any one of claims 1 to 4, characterized in that: include: The file parsing unit is used to parse the restricted area file uploaded by the user or read the restricted area range set by the user, identify and process the deployment area and the prohibited area in the wind resource map; construct the initial area grid where the wind turbine can be deployed according to the deployment area and the prohibited area; An initial calculation unit is used to parse the initial position file of the machine site uploaded by the user to obtain the initial wind turbine arrangement; Based on the initial wind turbine arrangement, the initial wake power generation of the wind turbine is calculated as a benchmark for the initial wind turbine arrangement; Iterative calculation unit, used for iterative calculation of wake power generation: under regional restriction conditions, through two rounds of position updates, randomly select and update the arrangement of quasi-new wind turbines; According to the arrangement of quasi-new wind turbines, the wake model is used to calculate the quasi-new wake power generation under the arrangement of quasi-new wind turbines; When the quasi-new wake power generation is greater than the initial wake power generation, the quasi-new wind turbine arrangement is updated to a new reference wind turbine arrangement, and the quasi-new wake power generation is updated to a new reference wake power generation; Return and iterate the wake power generation calculation, and output the wind turbine arrangement and wake power generation at the end of the iteration as the optimal wind turbine arrangement plan.

6. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for optimizing the arrangement of wind turbines taking into account regional restrictions as described in any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing the arrangement of wind turbines considering regional restrictions as described in any one of claims 1 to 4 is implemented.

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