Wind power plant layout method, device, equipment, medium and product

Abstract

The invention relates to the technical field of wind power generation, and discloses a wind power plant layout method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a first parameter and a second parameter of a target wind power plant; constructing a target function by using the first parameter; generating initial fan layout and initial cable wiring based on the second parameter; obtaining an initial function value based on the initial cable wiring and the target function, adjusting the initial fan layout based on the initial function value, obtaining an intermediate fan layout and intermediate cable wiring, obtaining an intermediate function value based on the intermediate cable wiring and the target function, and repeating the steps until the change rate corresponding to the target function value is smaller than a preset value. Stopping adjusting the current fan layout to obtain a target fan layout and target cable wiring; and obtaining a target wind power plant layout based on the target fan layout and the target cable wiring. According to the method, the target function is constructed by using the operation information and the environment information, the target fan layout and the target cable wiring are generated, and the optimal wind power plant layout can be obtained.

Description

Technical Field

[0001] The present disclosure relates to the technical field of wind power generation, and particularly to a wind farm layout method, device, equipment, medium and product. Background Art

[0002] Wind energy is a renewable energy source with huge resource potential and relatively mature technology, and has been widely developed and utilized globally. However, there are still some problems in the layout of wind farms. The layout of a wind farm not only needs to determine the optimal positions of wind turbines according to the given area and wind resource distribution, but also needs to consider many factors such as the annual total power generation, the average annual operating cost, the land use fee, and the layout of the collector line cables.

[0003] When the prior art performs the layout of a wind farm, it only simply considers the annual total power generation or the annual total power generation revenue, without considering factors such as the annual net power generation revenue, the average annual land cost, the average annual operating cost, and the average annual cable investment cost. Therefore, the final layout result of the wind farm may not be the most economical, and it is necessary to find a wind farm layout method that comprehensively considers various costs and has the optimal economy. Summary of the Invention

[0004] In view of this, the present disclosure provides a wind farm layout method, device, equipment, medium and product to solve the problems of wind turbine layout and cable routing in the wind farm layout.

[0005] In a first aspect, the present disclosure provides a wind farm layout method, which includes:

[0006] Obtain a first parameter and a second parameter of a target wind farm, where the first parameter is used to characterize the operation information of the target wind farm, and the second parameter is used to characterize the environmental information of the target wind farm;

[0007] Construct an objective function using the first parameter, where the objective function is used to characterize the first return result of the target wind farm;

[0008] Generate an initial wind turbine layout and an initial cable routing based on the second parameter;

[0009] Obtain an initial function value based on the initial cable routing and the objective function, adjust the initial wind turbine layout based on the initial function value to obtain an intermediate wind turbine layout and an intermediate cable routing, obtain an intermediate function value based on the intermediate cable routing and the objective function, repeat the above steps until the change rate corresponding to the objective function value is less than a preset value, stop adjusting the current wind turbine layout, and obtain a target wind turbine layout and a target cable routing, where the objective function value refers to the optimal solution among each function value in a preset number of iterations, and the function value includes the initial function value and the intermediate function value;

[0010] Obtain a target wind farm layout based on the target wind turbine layout and the target cable routing.

[0011] In the embodiments of the present disclosure, by obtaining the first parameter and the second parameter of the target wind farm; constructing an objective function using the first parameter; generating an initial wind turbine layout and an initial cable routing based on the second parameter; obtaining an initial function value based on the initial cable routing and the objective function, adjusting the initial wind turbine layout based on the initial function value to obtain an intermediate wind turbine layout and an intermediate cable routing, obtaining an intermediate function value based on the intermediate cable routing and the objective function, and repeating the above steps until the change rate corresponding to the objective function value is less than a preset value, stopping adjusting the current wind turbine layout to obtain a target wind turbine layout and a target cable routing; obtaining a target wind farm layout based on the target wind turbine layout and the target cable routing. Since the embodiments of the present disclosure construct an objective function using operation information and environmental information and generate a target wind turbine layout and a target cable routing, an optimal wind farm layout can be obtained.

[0012] In an alternative embodiment, the first parameter includes a third parameter and a fourth parameter. The third parameter is used to characterize the input information of the target wind farm, and the fourth parameter is used to characterize the return information of the target wind farm. Constructing an objective function using the first parameter includes:

[0013] Generating a first function based on the third parameter, where the first function is used to characterize the input result of the target wind farm;

[0014] Generating a second function based on the fourth parameter, where the second function is used to characterize the second return result of the target wind farm;

[0015] Obtaining an objective function based on the first function and the second function.

[0016] In the embodiments of the present disclosure, by constructing an objective function using the input information and return information of the target wind farm, an optimal wind farm layout can be obtained, the power generation efficiency and stability of the target wind farm can be improved, and the stable operation of the target wind farm can be ensured.

[0017] In an alternative embodiment, generating an initial wind turbine layout and an initial cable routing based on the second parameter includes:

[0018] Dividing the target wind farm into regions to obtain a grid matrix, where the grid matrix contains grid points;

[0019] Encoding the grid matrix based on the second parameter to obtain an initial wind turbine layout, where the initial wind turbine layout contains encoded values, and the encoded values are used to characterize whether the grid points are wind turbine points corresponding to wind turbines;

[0020] Constructing a triangulation for the wind turbine points to obtain candidate auxiliary points;

[0021] Obtaining the initial shortest path from the candidate auxiliary points to the wind turbine points;

[0022] Construct a minimum spanning tree based on the fan points, candidate auxiliary points, and the initial shortest path to obtain the target auxiliary points and the target shortest path;

[0023] Based on the fan points, the target auxiliary points, and the target shortest path, obtain the initial cable routing.

[0024] In the embodiments of the present disclosure, by dividing and coding the target wind farm to generate the initial fan layout, and obtaining the initial cable routing by constructing a minimum spanning tree, the initial fan layout and the initial cable routing of the target wind farm can be reasonably determined, improving the effectiveness of wind energy utilization.

[0025] In an alternative embodiment, obtaining the initial shortest path from the candidate auxiliary points to all fan points includes:

[0026] Obtain the distance value from the candidate auxiliary points to the fan points;

[0027] Obtain the path weight based on the target parameter in the second parameter;

[0028] Weight the distance value using the path weight to obtain the initial shortest path.

[0029] In the embodiments of the present disclosure, by weighting the distance value based on the target parameter, the initial shortest path can be accurately obtained, thereby reasonably determining the initial cable routing of the target wind farm.

[0030] In an alternative embodiment, obtaining the initial function value based on the initial cable routing and the objective function includes:

[0031] Sum the target shortest paths corresponding to the initial cable routing to obtain the total length of the shortest cable;

[0032] Based on the total length of the shortest cable and the objective function, obtain the initial function value.

[0033] In the embodiments of the present disclosure, by using the total length of the shortest cable and the objective function to obtain the initial function value, the return result corresponding to the initial cable routing can be obtained, providing a measurement index for subsequent gradual optimization of the layout of the target wind farm.

[0034] In an alternative embodiment, adjusting the initial fan layout based on the initial function value to obtain the intermediate fan layout and the intermediate cable routing includes:

[0035] Screen the initial fan layout based on the initial function value to obtain the first fan layout;

[0036] Exchange the coding values corresponding to the target fan layout within the first fan layout to obtain the second fan layout;

[0037] Change the encoded values within the second fan layout to obtain an intermediate fan layout;

[0038] Generate an intermediate cable routing based on the intermediate fan layout.

[0039] In the embodiments of the present disclosure, by screening the initial fan layout based on the initial function value, exchanging and changing the encoded values, an intermediate fan layout and an intermediate cable routing are generated, realizing the gradual optimization of the layout of the target wind farm and improving the overall performance of the target wind farm.

[0040] Second, the present disclosure provides a wind farm layout device, which includes:

[0041] An acquisition module, configured to acquire a first parameter and a second parameter of a target wind farm, where the first parameter is used to characterize the operation information of the target wind farm, and the second parameter is used to characterize the environmental information of the target wind farm;

[0042] A construction module, configured to construct an objective function by using the first parameter, where the objective function is used to characterize the first return result of the target wind farm;

[0043] A generation module, configured to generate an initial fan layout and an initial cable routing based on the second parameter;

[0044] A first obtaining module, configured to obtain an initial function value based on the initial cable routing and the objective function, adjust the initial fan layout based on the initial function value to obtain an intermediate fan layout and an intermediate cable routing, obtain an intermediate function value based on the intermediate cable routing and the objective function, and repeat the above steps until the change rate corresponding to the objective function value is less than a preset value, and stop adjusting the current fan layout to obtain a target fan layout and a target cable routing, where the objective function value refers to the optimal solution among each function value in a preset number of iterations, and the function value includes the initial function value and the intermediate function value;

[0045] A second obtaining module, configured to obtain a target wind farm layout based on the target fan layout and the target cable routing.

[0046] Third, the present disclosure provides a computer device, including: a memory and a processor, which are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the wind farm layout method according to the first aspect or any corresponding embodiment thereof.

[0047] Fourth, the present disclosure provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the wind farm layout method according to the first aspect or any corresponding embodiment thereof.

[0048] Fifth aspect, the present disclosure provides a computer program product, including computer instructions for causing a computer to execute the wind farm layout method according to the first aspect or any corresponding embodiment thereof as described above. Description of the Drawings

[0049] In order to more clearly illustrate the specific embodiments of the present disclosure or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0050] Figure 1 is a flowchart of the wind farm layout method according to an embodiment of the present disclosure;

[0051] Figure 2 is an algorithm flowchart of the wind farm layout method according to an embodiment of the present disclosure;

[0052] Figure 3 is a layout diagram of a wind farm according to an embodiment of the present disclosure;

[0053] Figure 4 is a flowchart of another wind farm layout method according to an embodiment of the present disclosure;

[0054] Figure 5 is a flowchart of yet another wind farm layout method according to an embodiment of the present disclosure;

[0055] Figure 6 is a structural block diagram of a wind farm layout device according to an embodiment of the present disclosure;

[0056] Figure 7 is a schematic hardware structure diagram of a computer device according to an embodiment of the present disclosure. Detailed Embodiments

[0057] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present disclosure with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are some, but not all, of the embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present disclosure.

[0058] With the international community's emphasis on energy security, ecological environment, and climate anomalies, reducing the consumption of fossil energy and accelerating the utilization of renewable energy have become a worldwide consensus. Wind power generation converts the kinetic energy of the wind into mechanical kinetic energy and then converts the mechanical energy into electrical kinetic energy. Wind energy is a renewable energy source with huge resource potential and relatively mature technology, and it has been widely developed and utilized globally.

[0059] However, there are still some problems in the layout of wind farms. The layout of wind farms not only needs to determine the optimal positions of wind turbines according to the given area and wind resource distribution, but also needs to consider many factors such as the annual total power generation, annual average operating cost, land use fee, and layout of the collector line cables.

[0060] A reasonable layout of wind turbines can not only increase the power generation of the entire wind farm, but also ensure the reliability of the units. The upstream wind turbines will have a wake effect on the downstream wind turbines during operation, and one wind turbine will be affected by the wakes of multiple wind turbines. The wake not only affects the power output of the entire wind farm, but also increases the load of the units, thereby affecting the service life of the units. By reasonably arranging the wind turbines, the impact of the wake on the wind farm can be minimized. The collector line of the wind farm connects the wind turbines in series, transmits the generated electric energy to the low-voltage side of the on-site booster station, and is incorporated into the main grid after centralized boosting. The path planning of the collector line within the wind farm will directly determine the overall cost of the wind farm project. Therefore, how to select the optimal line path has become a difficult point in the design of the wind farm collector line.

[0061] When the prior art conducts the layout of wind farms, it only simply considers the annual total power generation or the annual total power generation revenue, without considering factors such as the annual net power generation revenue, annual average land cost, annual average operating cost, and annual average cable investment cost. Therefore, the final layout result of the wind farm may not be the most economical, and it is necessary to find a wind farm layout method that comprehensively considers various costs and has the best economy.

[0062] To solve the above problems, according to an embodiment of the present disclosure, an embodiment of a wind farm layout method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0063] In this embodiment, a wind farm layout method is provided, as Figure 1 shown, Figure 1 is a flowchart of the wind farm layout method according to an embodiment of the present disclosure. This process can be applied to a server and includes the following steps:

[0064] Step S101: Obtain a first parameter and a second parameter of the target wind farm, where the first parameter is used to characterize the operation information of the target wind farm, and the second parameter is used to characterize the environmental information of the target wind farm.

[0065] Optionally, in the embodiments of the present disclosure, the first parameter is used to characterize the operation information of the target wind farm, such as: the number of wind turbines, the output power of the wind turbines, the annual operating hours of the wind turbines, the electricity price, the cost per unit cable length, the cable loss coefficient, the land cost, the fixed operation and maintenance cost per single wind turbine, the variable operation and maintenance cost coefficient, etc. The second parameter is used to characterize the environmental information of the target wind farm, including the annual wind speed and direction of the target wind farm, the terrain, the wind turbine wake, etc.

[0066] Specifically, the server can obtain the operation information of the target wind farm through web crawlers, device collection, etc.; through a geographic information system, obtain the digital elevation model of the target wind farm area (such as a network with a resolution of 10m×10m) to obtain the terrain data of the target wind farm; through historical meteorological station data or computational fluid dynamics, simulate and generate an annual wind speed distribution model to obtain the wind speed v(x,y) at each grid point; calculate the wake effect between wind turbines through a wake model (such as the Jensen wake model) to obtain the downstream wind speed attenuation formula: Where, v downstream represents the wind speed at the downstream wind turbine, v upstream represents the wind speed at the upstream wind turbine, a is the axial induction factor, α is the attenuation coefficient, d is the wind turbine spacing, and D is the wind turbine rotor diameter.

[0067] Step S102: Construct an objective function using the first parameter, where the objective function is used to characterize the first return result of the target wind farm.

[0068] Optionally, in the embodiments of the present disclosure, the first return result may refer to the annual net income of the target wind farm, and the objective function may refer to the annual net income function of the target wind farm.

[0069] Specifically, the server calculates the annual power generation according to the number of wind turbines n, the output power P turbine (v i (representing the output power of the i-th wind turbine at wind speed v i ), and the annual operating hours t operation of the wind turbines: According to the annual power generation E annual (kWh) and the electricity price P tariff (yuan / kWh), the annual total revenue function of the target wind farm is obtained:

[0070] After that, the server calculates according to the total cable length L cable and the cost per unit cable length c cable, the cable loss coefficient r (for example, r = 0.1) is used to obtain the annual cable cost: C cable = L cable ·c cable ·r; According to the fixed operation and maintenance cost C of a single wind turbine fixed (such as labor, insurance, etc.), the variable operation and maintenance cost coefficient C variable (losses related to power generation, spare part replacement, etc.), the number of wind turbines n, and the annual power generation E annual , the annual operation and maintenance cost is obtained: C O&M = n·C fixed + E annual ·C variable (the annual comprehensive cost required for the target wind farm to maintain normal operation of equipment and ensure power generation efficiency during operation).

[0071] Finally, as Figure 2 shown, the server calculates the annual net profit function of the target wind farm based on the annual total revenue function E annual ·P tariff , the annual cable cost C cable , the annual land cost C land , and the annual operation and maintenance cost C O&M : NetProfit = E annual ·P tariff -(C cable + C land + C O&M ).

[0072] Step S103: Generate an initial wind turbine layout and an initial cable routing based on the second parameter.

[0073] Optionally, in the embodiments of the present disclosure, the initial wind turbine layout refers to a preliminary scheme of the positions of the wind turbines determined in the initial stage of the planning of the target wind farm. The initial cable routing refers to a preliminary scheme of the cable laying path connecting each wind turbine based on the initial wind turbine layout.

[0074] Specifically, as Figure 2 shown, the server inputs the second parameter into the genetic algorithm, uses the genetic algorithm to generate an initial population, that is, the initial wind turbine layout, and then uses the geometric Steiner algorithm to construct the minimum Euclidean Steiner tree according to the initial wind turbine layout to obtain the initial cable routing.

[0075] The genetic algorithm is an optimization search algorithm inspired by the biological evolution process. Its core idea is to simulate the natural selection and genetic mechanisms in the biological evolution process. In a population, individuals are selected according to their ability to adapt to the environment (i.e., fitness). Individuals with higher fitness have a greater chance of being selected and reproducing offspring. Through genetic operations such as crossover (exchanging some genes on the chromosome) and mutation (randomly changing a certain gene on the chromosome), new individuals are generated, and continuous iterative evolution is carried out to gradually develop the population towards the optimal solution.

[0076] The geometric Steiner algorithm is an algorithm used to solve the geometric Steiner tree problem. The geometric Steiner tree problem is to given multiple points on a plane, and the goal is to connect these points with line segments of the shortest length so that any two points can be directly or indirectly connected by line segments, and the connecting line segments do not intersect except at the endpoints, and the formed figure is a tree structure. The minimum Euclidean Steiner tree is the shortest network connecting a given set of points.

[0077] In step S104, based on the initial cable routing and the objective function, an initial function value is obtained. Based on the initial function value, the initial fan layout is adjusted to obtain an intermediate fan layout and an intermediate cable routing. Based on the intermediate cable routing and the objective function, an intermediate function value is obtained. The above steps are repeatedly executed until the change rate corresponding to the objective function value is less than a preset value, and the adjustment of the current fan layout is stopped to obtain a target fan layout and a target cable routing, where the objective function value refers to the optimal solution among each function value in a preset number of iterations, and the function value includes the initial function value and the intermediate function value.

[0078] Optionally, in the embodiments of the present disclosure, the initial function value refers to the function value corresponding to the initial cable routing in the objective function. The intermediate fan layout refers to the fan layout scheme obtained by adjusting the initial fan layout, and the intermediate cable routing refers to the cable routing scheme corresponding to the intermediate fan layout. The preset value refers to the convergence value of the change rate corresponding to the objective function value (such as 1%), and the preset number refers to the number of iterations (such as 10 times).

[0079] Specifically, as Figure 2 shown, the server inputs the total cable length corresponding to the initial cable routing into the objective function to obtain the initial function value, and then uses the initial function value as the fitness in the genetic algorithm. According to the fitness, the initial fan layout is selected, crossed, and mutated to obtain an intermediate fan layout. According to the intermediate fan layout, an intermediate cable routing is obtained. The above steps are repeatedly executed until the change rate corresponding to the optimal solution among each function value in a preset number of (such as 10 times) iterations is less than a preset value (such as 1%), and the adjustment of the current fan layout is stopped to obtain a target fan layout and a target cable routing.

[0080] As Figure 3 shown, Figure 3It is a schematic diagram of a wind farm layout according to an embodiment of the present disclosure. Among them, the solid dots are the fan points, the hollow dots are the target auxiliary points, the line segments connecting these points are the cables, the set of solid dots is the target fan layout, and the set of line segments is the target cable routing.

[0081] Step S105, based on the target fan layout and the target cable routing, obtain the target wind farm layout.

[0082] Optionally, in the embodiment of the present disclosure, the target wind farm layout includes the target fan layout and the target cable routing. After the server obtains the target fan layout and the target cable routing, it outputs the target fan layout and the target cable routing together to obtain the target wind farm layout.

[0083] In addition, the server can also output a final economic report, including parameters such as annual net income, cable cost, power generation, etc., for subsequent analysis and optimization of the power generation situation of the target wind farm.

[0084] In the embodiment of the present disclosure, by obtaining the first parameter and the second parameter of the target wind farm; using the first parameter to construct an objective function; generating an initial fan layout and an initial cable routing based on the second parameter; obtaining an initial function value based on the initial cable routing and the objective function, adjusting the initial fan layout based on the initial function value to obtain an intermediate fan layout and an intermediate cable routing, obtaining an intermediate function value based on the intermediate cable routing and the objective function, repeating the above steps until the change rate corresponding to the objective function value is less than a preset value, stopping adjusting the current fan layout, obtaining the target fan layout and the target cable routing; based on the target fan layout and the target cable routing, obtaining the target wind farm layout. Since the embodiment of the present disclosure constructs an objective function using operation information and environmental information to generate the target fan layout and the target cable routing, an optimal wind farm layout can be obtained.

[0085] In this embodiment, a method for wind farm layout is provided, as Figure 4 shown Figure 4 is a schematic flowchart of another method for wind farm layout according to an embodiment of the present disclosure. This process can be applied to a server and includes the following steps:

[0086] Step S401, obtain the first parameter and the second parameter of the target wind farm, where the first parameter is used to characterize the operation information of the target wind farm, and the second parameter is used to characterize the environmental information of the target wind farm. For details, please refer to Figure 1 Step S101 of the embodiment shown, which will not be elaborated here.

[0087] Step S402, use the first parameter to construct an objective function, where the objective function is used to characterize the first return result of the target wind farm.

[0088] Specifically, the above step S402 includes:

[0089] Step S4021: Generate a first function based on a third parameter, where the first function is used to characterize the input result of the target wind farm.

[0090] Optionally, in the embodiments of the present disclosure, the third parameter is used to characterize the input information of the target wind farm, such as: cost per unit cable length, cable loss coefficient, land cost, fixed operation and maintenance cost per single wind turbine, variable operation and maintenance cost coefficient, etc. The first function is used to characterize the input result of the target wind farm, such as: annual cable cost C cable of the target wind farm, annual land cost C land and annual operation and maintenance cost C O&M etc.

[0091] Specifically, the server obtains the annual cable cost according to the total cable length L cable , cost per unit cable length c cable , and cable loss coefficient r (for example, r = 0.1): C cable = L cable · c cable · r; according to the fixed operation and maintenance cost C fixed (such as labor, insurance, etc.) per single wind turbine, variable operation and maintenance cost coefficient C variable (loss related to power generation, spare part replacement, etc.), number of wind turbines n, and annual power generation E annual , obtains the annual operation and maintenance cost: C O&M = n · C fixed + E annual · C variable (the annual comprehensive cost required for the target wind farm to maintain normal operation of equipment and ensure power generation efficiency during operation).

[0092] Step S4022: Generate a second function based on a fourth parameter, where the second function is used to characterize the second return result of the target wind farm.

[0093] Optionally, in the embodiments of the present disclosure, the fourth parameter is used to characterize the return information of the target wind farm, such as: number of wind turbines, output power of wind turbines, annual operation hours of wind turbines, electricity price, etc. The second function is used to characterize the second return result of the target wind farm, such as: annual total revenue function E annual · P tariff .

[0094] Specifically, the server obtains the annual power generation according to the number of wind turbines n, output power P turbine (v i ) (representing the output power of the i-th wind turbine at wind speed v i ) and annual operation hours t operation of the wind turbines. Based on the annual power generation Eannual (kWh) and electricity price P tariff (yuan / kWh) to obtain the annual total revenue function of the target wind farm: That is, the second function.

[0095] Step S4023, obtain the objective function based on the first function and the second function.

[0096] Optionally, in the embodiments of the present disclosure, the server obtains the annual net revenue function of the target wind farm according to the annual total revenue function E annual ·P tariff , annual cable cost C cable , annual land cost C land and annual operation and maintenance cost C O&M , and obtains the annual net revenue function of the target wind farm: NetProfit = E annual ·P tariff -(C cable +C land +C O&M ).

[0097] Step S403, generate an initial wind turbine layout and an initial cable routing based on the second parameter. For details, please refer to Figure 1 Step S103 of the illustrated embodiment, which will not be elaborated here.

[0098] Step S404, obtain an initial function value based on the initial cable routing and the objective function, adjust the initial wind turbine layout based on the initial function value to obtain an intermediate wind turbine layout and an intermediate cable routing, obtain an intermediate function value based on the intermediate cable routing and the objective function, and repeat the above steps until the change rate corresponding to the objective function value is less than a preset value, stop adjusting the current wind turbine layout, and obtain a target wind turbine layout and a target cable routing, where the objective function value refers to the optimal solution among each function value in a preset number of iterations, and the function value includes the initial function value and the intermediate function value. For details, please refer to Figure 1 Step S104 of the illustrated embodiment, which will not be elaborated here.

[0099] Step S405, obtain the target wind farm layout based on the target wind turbine layout and the target cable routing. For details, please refer to Figure 1 Step S105 of the illustrated embodiment, which will not be elaborated here.

[0100] In the embodiments of the present disclosure, by constructing an objective function using the input information and return information of the target wind farm, an optimal wind farm layout can be obtained, the power generation efficiency and stability of the target wind farm can be improved, and the stable operation of the target wind farm can be ensured.

[0101] In this embodiment, a method for wind farm layout is provided, as shown in Figure 5 shown, Figure 5It is a schematic flowchart of another wind farm layout method according to an embodiment of the present disclosure. This process can be applied to a server and includes the following steps:

[0102] Step S501, obtain the first parameter and the second parameter of the target wind farm, where the first parameter is used to characterize the operation information of the target wind farm, and the second parameter is used to characterize the environmental information of the target wind farm. For details, please refer to Figure 4 Step S401 of the embodiment shown, which will not be elaborated here.

[0103] Step S502, construct an objective function using the first parameter, where the objective function is used to characterize the first return result of the target wind farm. For details, please refer to Figure 4 Step S402 of the embodiment shown, which will not be elaborated here.

[0104] Step S503, generate an initial wind turbine layout and an initial cable routing based on the second parameter.

[0105] Specifically, the above step S503 includes:

[0106] Step S5031, divide the target wind farm into regions to obtain a grid matrix, where the grid matrix contains grid points.

[0107] Optionally, in the embodiment of the present disclosure, as Figure 3 shown, the server divides the target wind farm into an M×N grid matrix. The grid matrix contains multiple grid points. Each grid contains coordinates (x i , y i ), terrain height h(x i , y i ), average wind speed v(x i , y i ), slope and other parameters. The constraint condition is to eliminate the infeasible regions where the slope > 15% or the height difference > 50m.

[0108] Step S5032, encode the grid matrix based on the second parameter to obtain an initial wind turbine layout, where the initial wind turbine layout contains encoded values, and the encoded values are used to characterize whether the grid point is a wind turbine point corresponding to a wind turbine.

[0109] Optionally, in the embodiment of the present disclosure, the encoded value is used to characterize whether the grid point is a wind turbine point corresponding to a wind turbine. For example, an encoded value of 1 represents that a wind turbine is placed at this grid point, and an encoded value of 0 represents that no wind turbine is placed at this grid point.

[0110] Specifically, the server can construct an evaluation function based on the second parameter to evaluate whether a grid point is suitable for arranging a wind turbine. For example, the server will give priority to areas with higher and stable wind speeds, less wake influence, and relatively flat terrain as wind turbine points. The server can also set an evaluation threshold. When the score of the evaluation function of a grid point is greater than or equal to this evaluation threshold, it is determined that the grid point is suitable for arranging a wind turbine; when the score of the evaluation function of a grid point is less than this evaluation threshold, it is determined that the grid point is not suitable for arranging a wind turbine.

[0111] The server inputs the second parameter into the genetic algorithm, traverses each grid point in the grid matrix, calculates the evaluation function value corresponding to each grid point, compares it with the evaluation threshold, determines the coding value corresponding to each grid point. After completing the coding assignment for all grid points, these coding values are integrated into a matrix, and this matrix is the coding representation of the initial wind turbine layout. Among them, each element in the matrix corresponds to the coding value of a grid point, intuitively showing the initial distribution of wind turbines in the target wind farm.

[0112] Step S5033: Perform triangulation on the wind turbine points to obtain candidate auxiliary points.

[0113] Optionally, in the embodiment of the present disclosure, the server obtains the coordinate set V turbine ={(x1,y1),(x2,y2),...,(x n ,y n )} of the wind turbine points (i.e., the points with a coding value of 1) in the initial wind turbine layout, and uses the geometric Steiner algorithm to perform triangulation (such as Delaunay triangulation) on these wind turbine points to obtain a set of candidate Steiner points, that is, a set of candidate auxiliary points S.

[0114] Specifically, the server first selects any three non-collinear points from the wind turbine points in the initial wind turbine layout to form an initial triangle. For the other points in the wind turbine points except those that form the initial triangle, they are inserted into the existing triangulation in turn.

[0115] After inserting a new point to form a new triangle, the server needs to check whether the newly formed triangle satisfies the property that there are no other points inside the circumcircle of any triangle, that is, the empty circumcircle property. If there are pairs of triangles that do not satisfy the empty circumcircle property (that is, the circumcircles of two adjacent triangles contain the vertices of each other), then through an edge flip operation (reconnecting the two endpoints of the common edge of two adjacent triangles to form two other triangles) for adjustment, so that the final triangulation result satisfies the empty circumcircle property.

[0116] The server repeats the above steps of point-by-point insertion and optimization adjustment until all points in the fan points are inserted into the triangulation, and the fan points are divided into multiple triangles, obtaining a triangulation result that conforms to the empty circumcircle property, that is, the candidate auxiliary point set S.

[0117] Step S5034, obtain the initial shortest path from the candidate auxiliary points to the fan points.

[0118] Optionally, in the embodiment of the present disclosure, for each candidate auxiliary point s ∈ S, the server calculates its initial shortest path to all fan points.

[0119] In some alternative embodiments, the above step S5034 includes:

[0120] Step a1, obtain the distance value from the candidate auxiliary points to the fan points.

[0121] Step a2, obtain the path weight based on the target parameter in the second parameter.

[0122] Step a3, weight the distance value with the path weight to obtain the initial shortest path.

[0123] Optionally, the target parameter refers to the terrain slope

[0124] Specifically, the server first obtains the distance value from the candidate auxiliary points to the fan points Then, based on the terrain slope s(x i , y i ), obtain the average slope s from point i to point j i,j , and then, based on the average slope s i,j obtain the path weight (1 + k · s i,j ), where k is the terrain correction coefficient (such as 0.2).

[0125] After that, the server weights the distance value i,j with the path weight (1 + k · s to obtain the initial shortest path

[0126] In the above embodiment, by weighting the distance value based on the target parameter, the initial shortest path can be accurately obtained, so as to reasonably determine the initial cable routing of the target wind farm.

[0127] Step S5035, construct a minimum spanning tree based on the fan points, candidate auxiliary points, and the initial shortest path to obtain the target auxiliary points and the target shortest path.

[0128] Optionally, in the embodiments of the present disclosure, the target auxiliary points are included in the candidate auxiliary points, and the target shortest path is included in the initial shortest path. The server can use Prim's algorithm to construct a minimum spanning tree. Prim's algorithm is a greedy algorithm that starts from an initial vertex and gradually expands the spanning tree. Each time, it selects the edge with the smallest weight among the edges connected to the current spanning tree until all vertices are included in the spanning tree.

[0129] Specifically, the server first combines the fan points and the candidate auxiliary points to obtain a vertex set, and constructs an edge set based on the vertex set and the initial shortest path. Each edge includes two vertices and the weight corresponding to the edge (i.e., the initial shortest path).

[0130] Then, the server randomly selects a point from the vertex set as the starting point. Starting from the starting point, it checks all the paths connecting the starting point and other points not yet included in the tree, and selects the path with the smallest weight (i.e., the smallest initial shortest path) from these paths. The new point connected by this path is included in the constructed tree. Repeat the above steps until all the fan points and related candidate auxiliary points are included in the tree. The constructed tree is the minimum spanning tree. The candidate auxiliary points in the minimum spanning tree are the target auxiliary points, and the paths connecting each point in the tree are the target shortest paths.

[0131] Step S5036, obtain the initial cable routing based on the fan points, the target auxiliary points, and the target shortest path.

[0132] Optionally, in the embodiments of the present disclosure, the server constructs a network with the fan points and the target auxiliary points as nodes and the target shortest path as edges, and the obtained network is the initial cable routing.

[0133] Step S504, obtain an initial function value based on the initial cable routing and the objective function, adjust the initial fan layout based on the initial function value to obtain an intermediate fan layout and an intermediate cable routing, obtain an intermediate function value based on the intermediate cable routing and the objective function, and repeat the above steps until the change rate corresponding to the objective function value is less than a preset value, and stop adjusting the current fan layout to obtain a target fan layout and a target cable routing. The objective function value refers to the optimal solution among each function value in a preset number of iterations, and the function value includes the initial function value and the intermediate function value.

[0134] In some alternative embodiments, obtaining the initial function value based on the initial cable routing and the objective function in the above step S504 includes:

[0135] Step b1, sum the target shortest paths corresponding to the initial cable routing to obtain the total length of the shortest cable.

[0136] Step b2: Obtain the initial function value based on the shortest total cable length and the objective function.

[0137] Optionally, in the embodiments of the present disclosure, as Figure 2 shown, the server sums the target shortest paths corresponding to the edge set E in the initial cable routing to obtain the shortest total cable length EMST Then, the server takes the shortest total cable length L as the total cable length and inputs it into the objective function to calculate the function value corresponding to the initial cable routing in the objective function. cable In the above embodiments, by using the shortest total cable length and the objective function to obtain the initial function value, the return result corresponding to the initial cable routing can be obtained, providing a measurement index for gradually optimizing the layout of the target wind farm in the subsequent process.

[0138] In some optional embodiments, adjusting the initial wind turbine layout based on the initial function value in step S504 to obtain the intermediate wind turbine layout and the intermediate cable routing includes:

[0139] Step c1: Screen the initial wind turbine layout based on the initial function value to obtain the first wind turbine layout.

[0140] Step c2: Exchange the coding values corresponding to the target wind turbine layout in the first wind turbine layout to obtain the second wind turbine layout.

[0141] Step c3: Modify the coding values in the second wind turbine layout to obtain the intermediate wind turbine layout.

[0142] Step c4: Generate the intermediate cable routing based on the intermediate wind turbine layout.

[0143] Step c4: Generate the intermediate cable routing based on the intermediate wind turbine layout.

[0144] Optionally, in the embodiments of the present disclosure, as Figure 2 shown, the server uses the genetic algorithm, takes the initial wind turbine layout as the initial population, takes each wind turbine layout scheme in the initial wind turbine layout as a chromosome, and takes the initial function value as the fitness value.

[0145] First, the server screens the initial wind turbine layout using the roulette wheel selection method. The selection probability of the roulette wheel selection method is proportional to the fitness, that is, the higher the initial function value of the wind turbine layout scheme, the greater the probability of being selected. In this way, the server selects some better wind turbine layout schemes from the initial population and forms the first wind turbine layout with these wind turbine layout schemes.

[0146] Then, the server uses the genetic operation of two-point crossover to randomly select two parental chromosomes from the first wind turbine layout (i.e., the coding matrices corresponding to two wind turbine layout schemes, and these two wind turbine layout schemes are the target wind turbine layouts), and exchanges some segments of these two parental chromosomes (i.e., exchanges the coding values of some segments corresponding to the target wind turbine layout), so as to obtain two new chromosomes, and the wind turbine layout schemes corresponding to these two new chromosomes are the second wind turbine layout.

[0147] After that, the server uses the mutation operation to randomly flip a certain gene of the chromosome in the second wind turbine layout, that is, if the coding value corresponding to a certain grid point was originally 1 (indicating that a wind turbine is placed at this grid point), it may become 0 after mutation (indicating that no wind turbine is placed at this grid point), realizing the removal of the wind turbine at this grid point; if the coding value corresponding to a certain grid point was originally 0 (indicating that no wind turbine is placed at this grid point), it may become 1 after mutation (indicating that a wind turbine is placed at this grid point), realizing the addition of a wind turbine at this grid point.

[0148] Finally, the server uses the geometric Steiner algorithm to construct the minimum Euclidean Steiner tree according to the intermediate wind turbine layout to obtain the intermediate cable routing.

[0149] In the above embodiments, by screening the initial wind turbine layout, exchanging and changing the coding values based on the initial function value, the intermediate wind turbine layout and the intermediate cable routing are generated, realizing the gradual optimization of the layout of the target wind farm and improving the overall performance of the target wind farm.

[0150] Step S505, based on the target wind turbine layout and the target cable routing, obtain the target wind farm layout. For details, please refer to Figure 4 Step S405 of the embodiment shown, which will not be elaborated here.

[0151] In the embodiments of the present disclosure, by dividing the target wind farm into regions and encoding to generate the initial wind turbine layout, and by constructing the minimum spanning tree to obtain the initial cable routing, the initial wind turbine layout and the initial cable routing of the target wind farm can be reasonably determined, improving the effectiveness of wind energy utilization.

[0152] In this embodiment, a wind farm layout device is also provided. This device is used to implement the above embodiments and preferred implementation manners, and those that have been described will not be elaborated again. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0153] This embodiment provides a wind farm layout device, as Figure 6 shown, including:

[0154] An acquisition module 601, configured to acquire a first parameter and a second parameter of a target wind farm, where the first parameter is used to characterize the operation information of the target wind farm, and the second parameter is used to characterize the environmental information of the target wind farm;

[0155] A construction module 602, configured to construct an objective function by using the first parameter, where the objective function is used to characterize the first return result of the target wind farm;

[0156] A generation module 603, configured to generate an initial wind turbine layout and an initial cable routing based on the second parameter;

[0157] A first obtaining module 604, configured to obtain an initial function value based on the initial cable routing and the objective function, adjust the initial wind turbine layout based on the initial function value to obtain an intermediate wind turbine layout and an intermediate cable routing, obtain an intermediate function value based on the intermediate cable routing and the objective function, and repeat the above steps until the change rate corresponding to the objective function value is less than a preset value, stop adjusting the current wind turbine layout, and obtain a target wind turbine layout and a target cable routing, where the objective function value refers to the optimal solution among each function value in a preset number of iterations, and the function value includes the initial function value and the intermediate function value;

[0158] A second obtaining module 605, configured to obtain a target wind farm layout based on the target wind turbine layout and the target cable routing.

[0159] In the embodiments of the present disclosure, by acquiring the first parameter and the second parameter of the target wind farm; constructing an objective function by using the first parameter; generating an initial wind turbine layout and an initial cable routing based on the second parameter; obtaining an initial function value based on the initial cable routing and the objective function, adjusting the initial wind turbine layout based on the initial function value to obtain an intermediate wind turbine layout and an intermediate cable routing, obtaining an intermediate function value based on the intermediate cable routing and the objective function, and repeating the above steps until the change rate corresponding to the objective function value is less than a preset value, stop adjusting the current wind turbine layout, and obtain a target wind turbine layout and a target cable routing; obtaining a target wind farm layout based on the target wind turbine layout and the target cable routing. Since the embodiments of the present disclosure construct an objective function by using operation information and environmental information, and generate a target wind turbine layout and a target cable routing, an optimal wind farm layout can be obtained.

[0160] In some alternative embodiments, the construction module 602 includes:

[0161] A first generation sub-module, configured to generate a first function based on a third parameter, where the first function is used to characterize the input result of the target wind farm;

[0162] A second generation sub-module, configured to generate a second function based on a fourth parameter, where the second function is used to characterize the second return result of the target wind farm;

[0163] The first obtaining sub-module is used to obtain a target function based on a first function and a second function.

[0164] In some optional embodiments, the generating module 603 includes:

[0165] The dividing sub-module is used to divide a target wind farm into regions to obtain a grid matrix, where the grid matrix contains grid points;

[0166] The encoding sub-module is used to encode the grid matrix based on a second parameter to obtain an initial wind turbine layout, where the initial wind turbine layout contains encoded values, and the encoded values are used to indicate whether a grid point is a wind turbine point corresponding to a wind turbine;

[0167] The triangulating sub-module is used to perform triangulation on the wind turbine points to obtain candidate auxiliary points;

[0168] The obtaining sub-module is used to obtain an initial shortest path from the candidate auxiliary points to the wind turbine points;

[0169] The second obtaining sub-module is used to construct a minimum spanning tree based on the wind turbine points, the candidate auxiliary points, and the initial shortest path to obtain target auxiliary points and a target shortest path;

[0170] The third obtaining sub-module is used to obtain an initial cable routing based on the wind turbine points, the target auxiliary points, and the target shortest path.

[0171] In some optional embodiments, the obtaining sub-module includes:

[0172] The first obtaining unit is used to obtain distance values from the candidate auxiliary points to the wind turbine points;

[0173] The second obtaining unit is used to obtain path weights based on a target parameter in the second parameter;

[0174] The weighting unit is used to weight the distance values with the path weights to obtain an initial shortest path.

[0175] In some optional embodiments, the first obtaining module 604 includes:

[0176] The summing sub-module is used to sum the target shortest paths corresponding to the initial cable routing to obtain the total shortest cable length;

[0177] The fourth obtaining sub-module is used to obtain an initial function value based on the total shortest cable length and the target function.

[0178] In some optional embodiments, the first obtaining module 604 includes:

[0179] The screening sub-module is used to screen the initial wind turbine layout based on the initial function value to obtain a first wind turbine layout;

[0180] A commutator module is configured to exchange the encoding values corresponding to the target fan layout within the first fan layout to obtain a second fan layout.

[0181] An alteration module is configured to alter the encoding values within the second fan layout to obtain an intermediate fan layout.

[0182] A third generation sub-module is configured to generate an intermediate cable routing based on the intermediate fan layout.

[0183] The further function descriptions of the above-mentioned various modules and units are the same as those in the corresponding foregoing embodiments, and will not be elaborated herein.

[0184] The wind farm layout device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0185] This disclosure embodiment also provides a computer device having the above-mentioned Figure 6 shown wind farm layout device.

[0186] Please refer to Figure 7 , Figure 7 which is a schematic structural diagram of a computer device provided by an optional embodiment of this disclosure. As shown in Figure 7 , the computer device includes: one or more processors 10, a memory 20, and an interface for connecting each component, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional implementation manners, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 7 In

[0187] The processor 10 may be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 may further include a hardware chip. The above-mentioned hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The above-mentioned programmable logic device may be a complex programmable logic device, a field-programmable gate array, a generic array logic, or any combination thereof.

[0188] Among them, the memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.

[0189] The memory 20 may include a program storage area and a data storage area. Among them, the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may further include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 may optionally include a memory remotely provided with respect to the processor 10, and these remote memories may be connected to the computer device through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0190] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state drive; the memory 20 may further include a combination of the above-mentioned types of memories.

[0191] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or communication networks.

[0192] The embodiments of the present disclosure also provide a computer-readable storage medium. The method according to the embodiments of the present disclosure may be implemented in hardware, firmware, or may be implemented as computer code recorded on a storage medium, or may be implemented as computer code originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium may further include a combination of the above-mentioned types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is implemented.

[0193] Part of the present disclosure can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the present disclosure through the operations of the computer. Those skilled in the art should understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Herein, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0194] Although the embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A wind farm layout method, characterized in that, The method includes: Obtaining a first parameter and a second parameter of a target wind farm, where the first parameter is used to characterize the operation information of the target wind farm, and the second parameter is used to characterize the environmental information of the target wind farm; Constructing an objective function using the first parameter, where the objective function is used to characterize the first return result of the target wind farm; Generating an initial wind turbine layout and an initial cable routing based on the second parameter; Obtaining an initial function value based on the initial cable routing and the objective function, adjusting the initial wind turbine layout based on the initial function value to obtain an intermediate wind turbine layout and an intermediate cable routing, obtaining an intermediate function value based on the intermediate cable routing and the objective function, and repeating the above steps until the change rate corresponding to the objective function value is less than a preset value, stopping adjusting the current wind turbine layout, and obtaining a target wind turbine layout and a target cable routing, where the objective function value refers to the optimal solution among each function value in a preset number of iterations, and the function values include the initial function value and the intermediate function value; Obtaining a target wind farm layout based on the target wind turbine layout and the target cable routing.

2. The method according to claim 1, wherein The first parameter includes a third parameter and a fourth parameter, the third parameter is used to characterize the input information of the target wind farm, the fourth parameter is used to characterize the return information of the target wind farm, and constructing the objective function using the first parameter includes: Generating a first function based on the third parameter, where the first function is used to characterize the input result of the target wind farm; Generating a second function based on the fourth parameter, where the second function is used to characterize the second return result of the target wind farm; Obtaining the objective function based on the first function and the second function.

3. The method according to claim 1, characterized in that Generating the initial wind turbine layout and the initial cable routing based on the second parameter includes: Dividing the target wind farm into regions to obtain a grid matrix, where the grid matrix contains grid points; Encoding the grid matrix based on the second parameter to obtain the initial wind turbine layout, where the initial wind turbine layout contains encoded values, and the encoded values are used to characterize whether the grid points are wind turbine points corresponding to wind turbines; Constructing a triangulation for the wind turbine points to obtain candidate auxiliary points; Obtaining an initial shortest path from the candidate auxiliary points to the wind turbine points; Constructing a minimum spanning tree based on the wind turbine points, the candidate auxiliary points, and the initial shortest path to obtain target auxiliary points and a target shortest path; Obtaining the initial cable routing based on the wind turbine points, the target auxiliary points, and the target shortest path.

4. The method according to claim 3, wherein Obtaining the initial shortest path from the candidate auxiliary points to all the wind turbine points includes: Obtaining the distance values from the candidate auxiliary points to the wind turbine points; Obtaining path weights based on the target parameter in the second parameter; Weighting the distance values using the path weights to obtain the initial shortest path.

5. The method according to claim 3, wherein Obtaining the initial function value based on the initial cable routing and the objective function includes: Summing the target shortest paths corresponding to the initial cable routing to obtain the total length of the shortest cable; Based on the total shortest cable length and the objective function, the initial function value is obtained.

6. The method according to claim 3, characterized in that, Adjusting the initial wind turbine layout based on the initial function value to obtain an intermediate wind turbine layout and an intermediate cable routing includes: Screening the initial wind turbine layout based on the initial function value to obtain a first wind turbine layout; Exchanging the coding values corresponding to the target wind turbine layout within the first wind turbine layout to obtain a second wind turbine layout; Changing the coding values within the second wind turbine layout to obtain the intermediate wind turbine layout; Generating the intermediate cable routing based on the intermediate wind turbine layout.

7. A wind farm layout device, characterized in that, The device includes: An acquisition module, configured to acquire a first parameter and a second parameter of a target wind farm, where the first parameter is used to characterize the operation information of the target wind farm, and the second parameter is used to characterize the environmental information of the target wind farm; A construction module, configured to construct an objective function by using the first parameter, where the objective function is used to characterize the first return result of the target wind farm; A generation module, configured to generate an initial wind turbine layout and an initial cable routing based on the second parameter; A first obtaining module, configured to obtain an initial function value based on the initial cable routing and the objective function, adjust the initial wind turbine layout based on the initial function value to obtain an intermediate wind turbine layout and an intermediate cable routing, obtain an intermediate function value based on the intermediate cable routing and the objective function, repeat the above steps until the change rate corresponding to the objective function value is less than a preset value, stop adjusting the current wind turbine layout, and obtain a target wind turbine layout and a target cable routing, where the objective function value refers to the optimal solution among each function value in a preset number of iterations, and the function values include the initial function value and the intermediate function value; A second obtaining module, configured to obtain a target wind farm layout based on the target wind turbine layout and the target cable routing.

8. A computer device, characterized in that, Includes: A memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the wind farm layout method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, A computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the wind farm layout method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer instructions, and the computer instructions are used to cause a computer to execute the wind farm layout method according to any one of claims 1 to 6.

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