Wind power plant non-uniform layout micro-siting optimization method and system

Abstract

The invention belongs to the technical field of wind power generation. The invention provides a wind power plant non-uniform layout micro-siting optimization method and system. The method comprises the following steps: determining a site boundary of a wind power plant according to a sensitive area range and a to-be-arranged position; a parallelogram is used as a grid shape arrangement of a minimum unit, and the maximum generating capacity of the whole wind power plant is used as an optimization target; and performing iterative optimization valuing on the origin coordinate, the long side azimuth angle, the included angle between the long side and the short side, the distance between the starting point and the short side adjacent point, the distance between the starting point and the long side adjacent point, the short side distance diffusion coefficient and the long side distance diffusion coefficient of the coordinate system to obtain an optimized wind turbine generator regular arrangement scheme. According to the method, optimization parameters of eight degrees of freedom are adopted, so that the optimization algorithm has excellent adaptive capacity, the optimization precision is improved, and the method can be suitable for micro-siting optimization of wind power plants on flat terrains and on the sea.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a method for optimizing micro-site selection for non-uniform layout of wind farms, a system for optimizing micro-site selection for non-uniform layout of wind farms, a computer device, a computer-readable storage medium and a computer program product. Background Art

[0002] The statements in this section merely provide background art related to the present invention and do not necessarily constitute prior art.

[0003] As a clean and renewable energy source, wind energy has great development potential and does not pollute the environment, so it has received widespread attention. In the construction of wind farms, micro-site selection is particularly important. Reasonable micro-site selection can reduce unnecessary construction and maintenance costs, and through accurate micro-site selection, the optimal layout of wind turbines in the wind farm can be determined to maximize the capture of wind energy resources.

[0004] The existing micro-site selection optimization algorithms can obtain good results in theoretical calculations, but in actual applications, some optimization methods can only obtain good optimization results under certain specific conditions and cannot be generally applied to all conditions; when performing optimization calculations, although complex algorithms can obtain better results, the amount of calculation is large, and from an economic perspective, they are not suitable for commercial and practical applications; moreover, some optimization methods have poor global search capabilities and are prone to fall into local optimality and cannot obtain correct results. Summary of the invention

[0005] In order to address the shortcomings of the prior art, the present invention provides a method and system for optimizing the micro-site selection of non-uniform layout of a wind farm, which introduce eight parameters, namely, coordinates of the origin of the coordinate system, azimuth of the long side, angle between the long side and the short side, distance between the starting point and the adjacent point of the short side, distance between the starting point and the adjacent point of the long side, diffusion coefficient of the short side distance and diffusion coefficient of the long side distance. By adopting optimization parameters with eight degrees of freedom, the optimization algorithm has excellent adaptability and improves the optimization accuracy, and is suitable for micro-site selection optimization of wind farms on flat terrain and at sea.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for optimizing micro-site selection for non-uniform layout of a wind farm.

[0007] A micro-site selection optimization method for non-uniform layout of wind farms, including the following processes: Determine the site boundary of the wind farm based on the scope of the sensitive area and the location to be laid out; A grid shape arrangement with parallelogram as the smallest unit and the maximum power generation of the wind farm as the optimization goal is adopted. The coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient and the long side distance diffusion coefficient are iteratively optimized to obtain the optimized regular arrangement scheme of wind turbines.

[0008] As a further limitation of the first aspect of the present invention, when the short side distance diffusion coefficient and the long side distance diffusion coefficient are both equal to 1, the grids are arranged evenly in a regular shape.

[0009] As a further limitation of the first aspect of the present invention, when the short side distance diffusion coefficient and the long side distance diffusion coefficient are both not 1, the grid is arranged irregularly. When the starting point is located at the boundary, the grid is arranged only to this side of the venue and will not be arranged outside the boundary. When the starting point is located at the center of the venue, the grid is arranged to both sides.

[0010] As a further limitation of the first aspect of the present invention, during the iterative optimization value-taking process, the distance between any two wind turbines is greater than or equal to the limit safe machine distance, the distance between the starting point and the adjacent point on the short side and the distance between the starting point and the adjacent point on the long side are both greater than the corresponding lower limits of values, and the upper limits of the distance between the starting point and the adjacent point on the short side and the distance between the starting point and the adjacent point on the long side are associated with the area of ​​the wind farm.

[0011] As a further limitation of the first aspect of the present invention, the value range of the azimuth angle of the long side is [0°, 130°); the value range of the angle between the long side and the short side is [80°, 100°].

[0012] As a further limitation of the first aspect of the present invention, the iterative optimization value-taking process includes: Select the origin coordinates of the coordinate system and determine whether the origin coordinates are located at the boundary or the center point; Based on the coordinates of the origin of the coordinate system, the values ​​of the short side distance diffusion coefficient and the long side distance diffusion coefficient are determined; Select different long side azimuth angles, long side and short side angles, the distance between the starting point and the adjacent point on the short side, and the distance between the starting point and the adjacent point on the long side for iterative calculation, and take the maximum power generation as the iterative target to obtain the optimization result; Select different coordinates of the origin of the coordinate system and repeat the calculation until the iteration termination condition is reached, and then get the final values ​​of the origin coordinates of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient and the long side distance diffusion coefficient.

[0013] In a second aspect, the present invention provides a micro-site selection optimization system for the non-uniform layout of a wind farm.

[0014] A wind farm non-uniform layout micro-site selection optimization system, comprising: The boundary determination unit is configured to: determine the site boundary of the wind farm according to the sensitive area range and the location to be laid out; The site selection optimization unit is configured as follows: a grid-shaped arrangement with a parallelogram as the smallest unit, with the maximum power generation of the entire wind farm as the optimization goal, and iterative optimization of the coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient, and the long side distance diffusion coefficient to obtain an optimized regular arrangement plan for wind turbines.

[0015] In a third aspect, the present invention provides a computer device, comprising: a processor and a computer-readable storage medium; a processor adapted to execute a computer program; A computer-readable storage medium having a computer program stored therein, wherein when the computer program is executed by the processor, the method for optimizing the microscopic site selection for the non-uniform layout of a wind farm as described in the first aspect of the present invention is implemented.

[0016] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program is suitable for being loaded by a processor and executing the micro-site selection optimization method for the non-uniform layout of a wind farm as described in the first aspect of the present invention.

[0017] In a fifth aspect, the present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the micro-site selection optimization method for non-uniform layout of wind farms as described in the first aspect of the present invention.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The present invention introduces eight parameters, namely, coordinates of the origin of the coordinate system, azimuth of the long side, angle between the long side and the short side, distance between the starting point and the adjacent point of the short side, distance between the starting point and the adjacent point of the long side, diffusion coefficient of the short side distance and diffusion coefficient of the long side distance, and adopts optimization parameters with eight degrees of freedom. The calculation results and range that can be generated during optimization are wider, so that the optimization algorithm has excellent adaptability and improves the optimization accuracy. The wind energy utilization efficiency and power generation of the wind farm in the optimization results are improved, and the wind farm can be applied to micro-site optimization of wind farms on flat terrain and at sea.

[0019] The present invention innovatively proposes a wind farm non-uniform layout micro-site selection optimization method, which is based on an improved genetic algorithm or enumeration method, enhances the global search capability, and does not fall into the local optimum when performing optimization calculations. This optimization method can save a lot of manpower and material resources, and obtain the optimal layout of the wind farm with the maximum power generation in a short time, which has high commercial value.

[0020] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0022] Figure 1 One of the flow charts of the micro-site selection optimization method for non-uniform layout of wind farms provided in Example 1 of the present invention; Figure 2 Flow chart 2 of the micro-site selection optimization method for non-uniform layout of wind farms provided in Example 1 of the present invention; Figure 3 The grid distribution of different starting points when the short side distance diffusion coefficient Sx and the long side distance diffusion coefficient Sy provided in Example 1 of the present invention are both 1; Figure 4 The grid distribution of different starting points when the short side distance diffusion coefficient Sx and the long side distance diffusion coefficient Sy provided in Example 1 of the present invention are both greater than 1; Figure 5 The grid distribution of different starting points when the short side distance diffusion coefficient Sx and the long side distance diffusion coefficient Sy provided in Example 1 of the present invention are both less than 1; Figure 6 A schematic diagram of a wind farm non-uniform layout micro-site selection optimization system provided in Example 2 of the present invention; Figure 7 A schematic diagram of a computer device provided in Example 3 of the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0024] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0025] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0026] Embodiment 1: This implementation proposes a micro-site selection optimization method for non-uniform layout of wind farms, such as Figure 1 and Figure 2 As shown, eight parameters are introduced, including the coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point of the short side, the distance between the starting point and the adjacent point of the long side, the short side distance diffusion coefficient, and the long side distance diffusion coefficient, so as to improve the optimization accuracy; based on the improved genetic algorithm or enumeration method, the global search capability is realized, and the parameters of eight degrees of freedom make the optimization algorithm have excellent adaptability, which can be applied to the micro-site selection optimization of wind farms on flat terrain and offshore.

[0027] Before formulating the wind turbine layout plan, it is necessary to clarify the site boundaries and sensitive area scope of the wind farm, and use white solid line polygons to indicate the wind farm boundaries and sensitive areas; the wind farm boundaries and sensitive area data are extracted from the map data file or directly obtained from the Excel file.

[0028] In the optimal layout of wind turbines in a wind farm, a grid shape with a parallelogram as the smallest unit is set, and the following assumptions are made for the model: the coordinates of the origin of the coordinate system are (Cx, Cy), the azimuth of the long side is θx, the angle between the long side and the short side is θy, the distance between the starting point and the adjacent point on the short side is Lx1, the distance between the starting point and the adjacent point on the long side is Ly1, the short side distance diffusion coefficient is Sx, and the long side distance diffusion coefficient is Sy.

[0029] like Figure 3 As shown in , when the short side distance diffusion coefficient Sx and the long side distance diffusion coefficient Sy are both equal to 1, the grid is arranged evenly in a regular shape; Figure 4 and Figure 5 As shown in the figure, when Sx and Sy are not 1, the grid is arranged irregularly. When the starting point is at the boundary, the grid is arranged only to this side of the field, and not to the outside of the boundary; when the starting point is at the center of the field, the grid is arranged to both sides. Specifically, the eight-variable variable spacing layout method general model adopted in this implementation method: Cx, Cy, θx, θy, Lx1, Ly1, Sx, Sy. In the regular arrangement optimization process of wind turbines, the maximum power generation of the whole wind farm is taken as the optimization goal, and the above eight parameters are iteratively selected to finally obtain a regular arrangement scheme of wind turbines that meets the above requirements, including the following process: S1: During the optimization process, the fan position must meet the following restrictions: (1) The distance between each wind turbine is not less than the maximum safe distance dmin (generally 4 times the diameter of the wind turbine rotor), and the actual number of wind turbines installed within the wind farm boundary is consistent with the number of pre-installed units; (2) Further restricting the distance between the starting point and the adjacent point on the short side to Lx1 and the distance between the starting point and the adjacent point on the long side to Ly1, the lower limit of the value is dmin, and the upper limit is determined by the area of ​​the wind farm.

[0030] (3) The range of the azimuth angle of the long side θx is further restricted to [0°, 130°), that is, an angle value greater than or equal to 0° and less than 130° can be selected; the range of the angle between the long side and the short side θy is generally [80°, 100°], that is, an angle value greater than or equal to 80° and less than or equal to 100° can be selected.

[0031] S2: Establishing the maximum power generation of the wind farm as the optimization goal.

[0032] S3: Determine the iterative algorithm, using an improved genetic algorithm or an enumeration method to iterate.

[0033] S4: Iterate under the above constraints, the steps include: S4.1: Select the origin coordinates of the coordinate system as (Cx, Cy), and determine whether the origin coordinates are located at the boundary or the center point; S4.2: Based on S4.1, determine the values ​​of the short side distance diffusion coefficient Sx and the long side distance diffusion coefficient Sy; S4.3: Select different long side azimuth angles θx, long side and short side angles θy, the distance between the starting point and the adjacent point on the short side Lx1, and the distance between the starting point and the adjacent point on the long side Ly1 for iterative calculation, take the maximum power generation as the iterative target, and obtain the optimization result; S4.4: Return to step S4.1 and select different origin coordinates for calculation until the maximum number of iterations is reached.

[0034] S5: Derive the optimal wind turbine layout diagram.

[0035] By introducing eight parameters, namely Cx, Cy, θx, θy, Lx1, Ly1, Sx and Sy, the present invention can generate calculation results with a wider range during optimization, with higher optimization accuracy, and the wind energy utilization efficiency and power generation of the wind farm in the optimization result are improved; the present invention is based on an improved genetic algorithm or enumeration method, which enhances the global search capability and will not fall into the local optimum when performing optimization calculations. The optimization method can save a lot of manpower and material resources, and obtain the optimized arrangement of the wind farm with the maximum power generation in a short time, which has high commercial value.

[0036] Embodiment 2: like Figure 6 As shown, this implementation provides a wind farm non-uniform layout micro-site selection optimization system, including: The boundary determination unit is configured to: determine the site boundary of the wind farm according to the sensitive area range and the location to be laid out; The site selection optimization unit is configured as follows: a grid-shaped arrangement with a parallelogram as the smallest unit, with the maximum power generation of the entire wind farm as the optimization goal, and iterative optimization of the coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient, and the long side distance diffusion coefficient to obtain an optimized regular arrangement plan for wind turbines.

[0037] The specific working methods of the above-mentioned units are described in Example 1 and will not be repeated here.

[0038] It is understandable that the above-mentioned units can be separately or completely combined into one or several other units to constitute, or one (some) of the units can be further divided into multiple functionally smaller units to constitute, which can achieve the same operation without affecting the realization of the technical effects of the embodiments of the present application. The above-mentioned units are divided based on logical functions. In practical applications, the function of one unit can also be implemented by multiple units, or the functions of multiple units can be implemented by one unit. In other embodiments of the present application, the wind farm non-uniform layout micro-site selection optimization system can also include other units. In practical applications, these functions can also be implemented with the assistance of other units, and can be implemented by the collaboration of multiple units.

[0039] According to another embodiment of the present application, the system described in this embodiment can be constructed, and the micro-site selection optimization method for the non-uniform layout of a wind farm according to an embodiment of the present application can be implemented by running a computer program (including program code) capable of executing the steps involved in the corresponding method described in Example 1 on a general-purpose computing device such as a computer, which includes processing elements and storage elements such as a central processing unit (CPU), random access memory (RAM), and read-only memory (ROM). The computer program can be recorded on, for example, a computer-readable recording medium, and loaded into the above-mentioned computing device through the computer-readable recording medium, and run therein.

[0040] Embodiment 3: like Figure 7 As shown, this implementation provides an electronic device, which includes a processor 1001, a communication interface 1002, and a computer-readable storage medium 1003. The processor 1001, the communication interface 1002, and the computer-readable storage medium 1003 may be connected via a bus or other means.

[0041] Among them, the communication interface 1002 is used to receive and send data, the computer-readable storage medium 1003 can be stored in the memory of the electronic device, the computer-readable storage medium 1003 is used to store a computer program, the computer program includes program instructions, and the processor 1001 is used to execute the program instructions stored in the computer-readable storage medium 1003.

[0042] The processor 1001 (or CPU (Central Processing Unit)) is the computing core and control core of the electronic device, which is suitable for implementing one or more instructions, and specifically suitable for loading and executing one or more instructions to implement corresponding method processes or corresponding functions.

[0043] The processor 1001 is configured to execute the following process: Determine the site boundary of the wind farm based on the scope of the sensitive area and the location to be laid out; The grid shape arrangement is based on a parallelogram as the smallest unit, and the optimization goal is to maximize the power generation of the entire wind farm. The coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient, and the long side distance diffusion coefficient are iteratively optimized to obtain the optimized regular arrangement scheme of wind turbines. Iterative optimization value selection, specifically, including: Select the origin coordinates of the coordinate system and determine whether the origin coordinates are located at the boundary or the center point; Based on the coordinates of the origin of the coordinate system, the values ​​of the short side distance diffusion coefficient and the long side distance diffusion coefficient are determined; Select different long side azimuth angles, long side and short side angles, the distance between the starting point and the adjacent point on the short side, and the distance between the starting point and the adjacent point on the long side for iterative calculation, and take the maximum power generation as the iterative target to obtain the optimization result; Select different coordinates of the origin of the coordinate system and repeat the calculation until the iteration termination condition is reached, and then get the final values ​​of the origin coordinates of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient and the long side distance diffusion coefficient.

[0044] The more specific working method is described in Example 1 and will not be repeated here.

[0045] Embodiment 4: This implementation provides a computer-readable storage medium (Memory), which is a memory device in an electronic device for storing programs and data. It is understandable that the computer-readable storage medium here can include both built-in storage media in the electronic device and, of course, extended storage media supported by the electronic device. The computer-readable storage medium provides a storage space that stores the processing system of the electronic device.

[0046] In addition, the storage space also stores one or more instructions suitable for being loaded and executed by the processor, and these instructions may be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here may be a high-speed RAM memory, or a non-volatile memory, such as at least one disk memory; optionally, it may also be at least one computer-readable storage medium located away from the aforementioned processor.

[0047] In one embodiment, the computer-readable storage medium stores one or more instructions; the processor loads and executes the one or more instructions stored in the computer-readable storage medium to implement the following process: Determine the site boundary of the wind farm based on the scope of the sensitive area and the location to be laid out; The grid shape arrangement is based on a parallelogram as the smallest unit, and the optimization goal is to maximize the power generation of the entire wind farm. The coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient, and the long side distance diffusion coefficient are iteratively optimized to obtain the optimized regular arrangement scheme of wind turbines. Iterative optimization value selection, specifically, including: Select the origin coordinates of the coordinate system and determine whether the origin coordinates are located at the boundary or the center point; Based on the coordinates of the origin of the coordinate system, the values ​​of the short side distance diffusion coefficient and the long side distance diffusion coefficient are determined; Select different long side azimuth angles, long side and short side angles, the distance between the starting point and the adjacent point on the short side, and the distance between the starting point and the adjacent point on the long side for iterative calculation, and take the maximum power generation as the iterative target to obtain the optimization result; Select different coordinates of the origin of the coordinate system and repeat the calculation until the iteration termination condition is reached, and then get the final values ​​of the origin coordinates of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient and the long side distance diffusion coefficient.

[0048] The more specific working method is described in Example 1 and will not be repeated here.

[0049] Embodiment 5: The present implementation provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device performs the following process: Determine the site boundary of the wind farm based on the scope of the sensitive area and the location to be laid out; The grid shape arrangement is based on a parallelogram as the smallest unit, and the optimization goal is to maximize the power generation of the entire wind farm. The coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient, and the long side distance diffusion coefficient are iteratively optimized to obtain the optimized regular arrangement scheme of wind turbines. Iterative optimization value selection, specifically, including: Select the origin coordinates of the coordinate system and determine whether the origin coordinates are located at the boundary or the center point; Based on the coordinates of the origin of the coordinate system, the values ​​of the short side distance diffusion coefficient and the long side distance diffusion coefficient are determined; Select different long side azimuth angles, long side and short side angles, the distance between the starting point and the adjacent point on the short side, and the distance between the starting point and the adjacent point on the long side for iterative calculation, and take the maximum power generation as the iterative target to obtain the optimization result; Select different coordinates of the origin of the coordinate system and repeat the calculation until the iteration termination condition is reached, and then get the final values ​​of the origin coordinates of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient and the long side distance diffusion coefficient.

[0050] The more specific working method is described in Example 1 and will not be repeated here.

[0051] A person skilled in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0052] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server, a data center, etc. that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0053] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing the micro-site selection of non-uniform layout of wind farms, characterized in that: The process includes: Determine the site boundary of the wind farm based on the scope of the sensitive area and the location to be laid out; A grid shape arrangement with parallelogram as the smallest unit and the maximum power generation of the wind farm as the optimization goal is adopted. The coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient and the long side distance diffusion coefficient are iteratively optimized to obtain the optimized regular arrangement scheme of wind turbines.

2. The method for optimizing the micro-site selection of non-uniform layout of a wind farm according to claim 1, characterized in that: When the short side distance diffusion coefficient and the long side distance diffusion coefficient are both equal to 1, the grid is arranged evenly in a regular shape.

3. The method for optimizing the micro-site selection of non-uniform layout of wind farms according to claim 1, characterized in that: When the short side distance diffusion coefficient and the long side distance diffusion coefficient are not 1, the grid is arranged irregularly. When the starting point is at the boundary, the grid is only arranged to this side of the site and will not be arranged outside the boundary. When the starting point is at the center of the site, the grid is arranged to both sides.

4. The method for optimizing the micro-site selection of non-uniform layout of a wind farm according to claim 1, characterized in that: During the iterative optimization value-taking process, the distance between any two wind turbines is greater than or equal to the limit safe machine distance, the distance between the starting point and the adjacent point on the short side and the distance between the starting point and the adjacent point on the long side are both greater than the corresponding lower limits of values, and the upper limits of the distance between the starting point and the adjacent point on the short side and the distance between the starting point and the adjacent point on the long side are associated with the area of ​​the wind farm.

5. The method for optimizing the micro-site selection of non-uniform layout of wind farms according to claim 1, characterized in that: The value range of the long side azimuth is [0°, 130°); the value range of the angle between the long side and the short side is [80°, 100°].

6. The method for optimizing the micro-site selection of a non-uniform layout of a wind farm according to any one of claims 1 to 5, characterized in that: The iterative optimization value selection process includes: Select the origin coordinates of the coordinate system and determine whether the origin coordinates are located at the boundary or the center point; Based on the coordinates of the origin of the coordinate system, the values ​​of the short side distance diffusion coefficient and the long side distance diffusion coefficient are determined; Select different long side azimuth angles, long side and short side angles, the distance between the starting point and the adjacent point on the short side, and the distance between the starting point and the adjacent point on the long side for iterative calculation, and take the maximum power generation as the iterative target to obtain the optimization result; Select different coordinates of the origin of the coordinate system and repeat the calculation until the iteration termination condition is reached, and then get the final values ​​of the origin coordinates of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient and the long side distance diffusion coefficient.

7. A wind farm non-uniform layout micro-site selection optimization system, characterized in that: include: The boundary determination unit is configured to: determine the site boundary of the wind farm according to the sensitive area range and the location to be laid out; The site selection optimization unit is configured as follows: a grid-shaped arrangement with a parallelogram as the smallest unit, with the maximum power generation of the entire wind farm as the optimization goal, and iterative optimization of the coordinates of the origin of the coordinate system, the azimuth of the long side, the angle between the long side and the short side, the distance between the starting point and the adjacent point on the short side, the distance between the starting point and the adjacent point on the long side, the short side distance diffusion coefficient, and the long side distance diffusion coefficient to obtain an optimized regular arrangement plan for wind turbines.

8. A computer device, characterized in that: include: a processor and a computer readable storage medium; a processor adapted to execute a computer program; A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the method for optimizing the micro-site selection for the non-uniform layout of a wind farm according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor and executing the micro-site selection optimization method for non-uniform layout of a wind farm according to any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method for optimizing micro-site selection for non-uniform layout of a wind farm as claimed in any one of claims 1 to 6 is implemented.

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