Offshore wind farm arrangement optimization design method considering booster station

Abstract

The invention relates to an offshore wind power plant layout optimization design method considering a booster station, which is suitable for the field of wind power planning design, and comprises the following steps: generating a two-dimensional grid covering a planning field area, the two-dimensional grid being formed by intersecting a plurality of mutually parallel first straight lines and a plurality of mutually parallel second straight lines; determining optimal parameters of a two-dimensional grid by adopting a genetic algorithm by taking maximization of annual energy output of a planning field area as a target; determining a two-dimensional grid based on the optimal parameter of the two-dimensional grid, determining a wind turbine row based on a first straight line on the two-dimensional grid, placing two wind turbines at the two ends of the wind turbine row on two intersection points of the corresponding first straight line and the boundary of the planning field area, and taking the distance between the adjacent wind turbines in the wind turbine row as a first variable, and determining an optimal first variable by adopting a genetic algorithm by taking maximization of annual energy output of a planning field area as a target. By adopting the method, the sea area of the planned field area is fully utilized, and the design scheme of the maximum generating capacity is obtained.

Description

Technical Field

[0001] The present invention relates to the field of wind power planning and design, and particularly to an optimized layout design method for an offshore wind farm considering a booster station. Background Art

[0002] To ensure the navigation safety of offshore ships, in wind power engineering practice, wind turbines are often required to be arranged regularly in a determinant pattern. In coastal provinces such as Zhejiang where fishery resources are rich in China, based on the sea area functional zoning and fishery production requirements, the requirements for the layout of booster stations are further standardized, and it is clearly stipulated that the booster station for voltage boosting and power collection needs to be arranged in the same row as the wind turbines.

[0003] In response to this engineering constraint condition, when carrying out the micro-siting design of an offshore wind farm, the conventional engineering treatment method is to add a booster station site based on the number of wind turbines that meet the planned capacity requirements. Engineers in the planning profession will first give several layout schemes that meet the regular layout requirements according to experience, establish a calculation model in commercial software such as WAsP, and screen out the layout scheme with the largest power generation and submit it to electrical engineers. Subsequently, based on the above recommended layout scheme, electrical engineers determine the specific site for the construction of the booster station. In some cases, electrical engineers directly select a layout site of the layout scheme as the construction site of the booster station.

[0004] Obviously, the above traditional method based on manual comparison has great deficiencies: 1. The number of comparison schemes is limited, and each scheme depends on the personal experience of engineers, which largely determines the quality of the finally recommended layout scheme; 2. The method of determining the location of the booster station in stages is obviously not scientific enough. Specifically, although in the first stage, planning engineers give a recommended layout scheme with the largest power generation as the judgment criterion, after electrical engineers replace the wind turbines in the layout scheme with a booster station, the wake effect between the wind turbines around the booster station changes, resulting in the fact that the power generation of the original scheme with the largest power generation may not be the largest compared with several other alternative schemes (also after replacing the wind turbines with a booster station).

[0005] In addition, in the wind farm layout scheme obtained based on the traditional layout strategy, the wind turbines at both ends of each row of wind turbines are mostly inside the planned field area, and the full utilization of the sea area of the planned field area cannot be achieved, thus limiting its engineering practicability. Summary of the Invention

[0006] The technical problem to be solved by the present invention is: in view of the above problems, to provide an optimized layout design method for an offshore wind farm considering a booster station.

[0007] The technical solution adopted by the present invention is: an optimized layout design method for an offshore wind farm considering a booster station, including: Obtain the boundary information of the planned site area, the number and model parameters of the wind turbines to be assembled in the site area, and the representative annual wind resource dataset at the hub height of the wind turbines; Generate a two-dimensional grid covering the planned site area, which is formed by the intersection of multiple mutually parallel first straight lines and multiple mutually parallel second straight lines; Taking the parameters of the two-dimensional grid as variables, taking the grid points of the two-dimensional grid in the planned site area as the positions of the wind turbines and the booster station to be assembled, and aiming at maximizing the annual power generation of the planned site area, use the genetic algorithm to determine the optimal parameters of the two-dimensional grid; Based on the optimal parameters of the two-dimensional grid, determine the two-dimensional grid. Determine the wind turbine rows based on the first straight lines on the two-dimensional grid. Place the two wind turbines at both ends of the wind turbine row at the two intersection points of the corresponding first straight line and the boundary of the planned site area. Taking the distance between adjacent wind turbines in the wind turbine row as the first variable and aiming at maximizing the annual power generation of the planned site area, use the genetic algorithm to determine the optimal first variable.

[0008] Including: When the number of wind turbines on the wind turbine row is 1, set the distance from the wind turbine position to the intersection point of the first straight line and the boundary of the planned site area as the second variable; When the number of wind turbines on the wind turbine row is 2, place the two wind turbines at the two intersection points of the corresponding first straight line and the boundary of the planned site area; When the number of wind turbines on the wind turbine row is greater than 2, place the two wind turbines at both ends of the wind turbine row at the two intersection points of the corresponding first straight line and the boundary of the planned site area, and take the distance between adjacent wind turbines in the wind turbine row as the first variable; Taking the first variable and the second variable as optimization variables and aiming at maximizing the annual power generation of the planned site area, use the genetic algorithm to determine the optimal first variable and the second variable.

[0009] The step of taking the grid points of the two-dimensional grid in the planned site area as the positions of the wind turbines and the booster station to be assembled includes: Based on the positional relationship between the geometric center of the planned site area and the onshore centralized control center, determine the intersection point M of the outgoing submarine cable and the outer boundary of the planned site area; Calculate the distances from the grid points of the two-dimensional grid in the planned site area to the line between the geometric center and the intersection point M, and select the grid point with the shortest distance as the position of the booster station.

[0010] The calculation of the annual power generation of the planned site area includes: Judge whether the number of grid points of the two-dimensional grid in the planned site area is equal to where is the number of wind turbines to be assembled in the planned site area; If the number of grid points in the planned site area is not equal to , the annual power generation of the planned field area is set as the preset minimum value; otherwise, it is judged whether the distance between adjacent grid points is greater than the preset minimum distance; If the distance between adjacent grid points is less than the preset minimum distance, the annual power generation of the planned field area is set as the preset minimum value; otherwise, based on the positions of the wind turbines in the planned field area, combined with the model parameters and the representative annual wind resource data set, the annual power generation of the planned field area is calculated.

[0011] The calculation of the annual power generation of the planned field area based on the positions of the wind turbines in the planned field area, combined with the model parameters and the representative annual wind resource data set, includes: Set the position of the booster station as a virtual wind turbine, the output power of this virtual wind turbine is constantly 0, and the thrust coefficient is set as 0.001; Based on the wind speed and wind direction, divide the basic wind conditions, and combined with the representative annual wind resource data set, determine the corresponding basic wind conditions for each time period within the representative year, as well as the proportion of each basic wind condition within the representative year, the representative wind speed and representative wind direction of each basic wind condition; Based on the representative wind speed and representative wind direction of each basic wind condition, combined with the positions of the wind turbines in the planned field area, calculate the wind speed loss of each wind turbine in the field area affected by the wake of the upwind wind turbine under each basic wind condition; Based on the representative wind speed under each basic wind condition and the wind speed loss of each wind turbine affected by the wake of the upwind wind turbine, determine the effective wind speed of each wind turbine under each basic wind condition; Based on the effective wind speed of each wind turbine under each basic wind condition, determine the power generation of each wind turbine under each basic wind condition, and then determine the power generation under each basic wind condition; Based on the power generation under each basic wind condition and the proportion of each basic wind condition within the representative year, determine the annual power generation of the planned field area within the representative year.

[0012] The division of the basic wind conditions based on the wind speed and wind direction includes: Take the cut-in wind speed and cut-out wind speed of the wind turbine model to be installed in the planned field area as the maximum value and minimum value, and cut out multiple wind speed intervals between the maximum value and minimum value; Evenly divide the 0-360° wind direction angle and cut out multiple wind direction sectors; Combine the wind speed intervals and wind direction sectors in pairs to form multiple basic wind conditions.

[0013] An offshore wind farm layout optimization design device considering a booster station, including: An information acquisition module, used to acquire the boundary information of the planned field area, the number and model parameters of the wind turbines to be installed in the field area, and the representative annual wind resource data set at the hub height of the wind turbines; A grid generation module, which is used to generate a two-dimensional grid covering the planned field area. The two-dimensional grid is formed by the intersection of multiple mutually parallel first straight lines and multiple mutually parallel second straight lines; A parameter optimization module, which is used to take the parameters of the two-dimensional grid as variables, take the grid points in the two-dimensional grid of the planned field area as the positions for installing wind turbines and booster stations, and take maximizing the annual power generation of the planned field area as the goal, and use the genetic algorithm to determine the optimal parameters of the two-dimensional grid; A position determination module, which is used to determine the two-dimensional grid based on the optimal parameters of the two-dimensional grid, determine the wind turbine rows based on the first straight lines on the two-dimensional grid, place the two wind turbines at both ends of the wind turbine row at the two intersections of the corresponding first straight line and the boundary of the planned field area, and take the distance between adjacent wind turbines in the wind turbine row as the first variable, and use the genetic algorithm to determine the optimal first variable with the goal of maximizing the annual power generation of the planned field area.

[0014] A storage medium, on which a computer program executable by a processor is stored. When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering the booster station are realized.

[0015] An offshore wind farm layout optimization design device, which has a memory and a processor. A computer program executable by the processor is stored on the memory. When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering the booster station are realized.

[0016] The beneficial effects of the present invention are as follows: Through the two-dimensional grid covering the planned field area, taking the parameters of the two-dimensional grid as variables and the grid points as the positions of wind turbines and booster stations, the layout of the wind farm is optimized. According to the geometric boundary of the planned field area, the model information of the wind turbines to be installed in the field area, and the distribution of wind energy resources, through the iterative optimization of the genetic algorithm, a design scheme corresponding to the maximum power generation that meets the requirements of the regular arrangement of rows and columns of wind turbines and booster stations can be obtained.

[0017] In the optimization calculation of the present invention, facing the engineering constraint that the booster station needs to be arranged in the same row as the wind turbines, according to the principle of the shortest line between the booster station and each wind turbine, or according to the geometric center of gravity of the planned field area and the intersection point of the outgoing submarine cable line and the outer boundary of the planned field area, following the principle of giving priority to the minimum distance, a dynamic booster station position determination method is proposed, realizing the integrated optimization of the booster station and the layout design.

[0018] In the present invention, the preliminary positions of the booster station and each wind turbine are determined through the two-dimensional grid. The two wind turbines at both ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned field area. Taking the distance between adjacent wind turbines in the wind turbine row as a variable, the genetic algorithm is used to re-optimize the distance between adjacent wind turbines in each row, realizing the full utilization of the sea area of the planned field area.

[0019] The present invention overcomes the problems of the traditional manual selection method, which highly relies on the experience of engineers, has a limited number of selection schemes, and determines the booster station site in stages, making it difficult to accurately obtain an excellent engineering solution with a large power generation capacity. Description of the Drawings

[0020] Figure 1 It is a flowchart of the optimization design of the wind turbine layout in an offshore wind farm considering the booster station in the embodiment.

[0021] Figure 2 It is a schematic diagram of the planned field area in different coordinate systems.

[0022] Figure 3 It is a schematic diagram of the optimization of the wind turbine layout based on a two-dimensional grid.

[0023] Figure 4 It is a flowchart of the optimization calculation of the two-dimensional grid parameters.

[0024] Figure 5 It is a schematic diagram of the method for determining the relative position relationship between the grid points and the polygon planned field area.

[0025] Figure 6 It is a schematic diagram of the booster station site under a specified layout scheme.

[0026] Figure 7 It is a flowchart of the annual power generation calculation of the offshore wind farm considering the booster station under a specified layout scheme.

[0027] Figure 8 It is a schematic diagram of the re-optimization of the wind turbine points. Detailed Embodiment

[0028] The embodiments of the present invention are described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are only used to explain the present invention and should not be construed as limiting the present invention. For the step numbers in the following embodiments, they are only set for the convenience of description and explanation, and no limitation is imposed on the order between the steps. The execution order of each step in the embodiments can be adjusted adaptively according to the understanding of those skilled in the art.

[0029] In the description of the present invention, the meaning of "a plurality of" is two or more. If the first and second are described, it is only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence of the indicated technical features. In addition, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0030] Embodiment 1: AsFigure 1 As shown in Figure 1 , this embodiment provides an optimized layout design method for offshore wind farms considering booster stations, which specifically includes: S100. Obtain the boundary information of the planned field area, the number of wind turbines to be assembled in the field area and the model parameters, as well as the representative annual wind resource data set at the hub height of the wind turbine.

[0031] Take any point as the coordinate origin, the due east direction as the positive direction of the x-axis, and the due north direction as the positive direction of the y-axis to establish a rectangular coordinate system, also known as the geodetic coordinate system. According to the obtained boundary information of the planned field area, determine the horizontal and vertical coordinates of each boundary point in the geodetic coordinate system; when the planned field area contains restricted areas where wind turbines cannot be arranged, it is also necessary to determine the horizontal and vertical coordinates of each boundary point enclosing the restricted area.

[0032] Assume that the shapes of the planned field area and its restricted area are as Figure 2 shown, then the coordinates of each outer boundary point in the geodetic coordinate system can be expressed as , and the coordinates of each boundary point of the restricted area can be expressed as .

[0033] In this embodiment, the model parameters include the hub height H, the rotor diameter D, and a list of wind speed-aerodynamic parameters. The list of wind speed-aerodynamic parameters can be obtained from the complete machine manufacturer and covers the thrust coefficient and power at each typical wind speed within the effective wind speed range (cut-in wind speed to cut-out wind speed) for the corresponding model of wind turbine to operate normally and generate electricity.

[0034] In this example, the representative annual wind resource data set at the hub height of the wind turbine refers to a set of representative wind resource data that can reflect the long-term average level of the wind farm after processing the measured wind data. Taking 1 hour as a time period, it includes the wind speed and wind direction at a total of 8760 time periods.

[0035] According to the coordinates of each boundary point of the outer boundary of the planned field area, determine the coordinate values of the geometric centroid of the planned field area in the geodetic coordinate system. The process is as follows: 1. Calculate the area of the planned field area: ; 2. Determine the geometric centroid of the planned field area: ; ; In the formula, and successively represent the abscissa and ordinate of the geometric centroid of the planned field area. Specifically, for the planned field area polygon shown in Figure 2 , n = 5, respectively take , respectively take .

[0036] For the convenience of subsequent processing, the coordinate origin of the geodetic coordinate system is adjusted to the geometric centroid of the planned field area obtained above, and thus the reference coordinate system is obtained , as Figure 2 shown. Further, determine the coordinates of each boundary point of the planned field area in the reference coordinate system. Taking the boundary point A in Figure 2 as an example, the calculation formula is: ; ; In the formula, and respectively represent the abscissa and ordinate of the boundary point A in the reference coordinate system.

[0037] S200. Generate a two-dimensional grid covering the planned field area ( Figure 3 ), which is formed by the intersection of mutually parallel first straight lines and mutually parallel second straight lines.

[0038] In this embodiment, it is assumed that the distance between adjacent first straight lines is ; the distance between adjacent second straight lines is ; the angle between the first straight line and the preset first direction (the positive direction of the X-axis of the reference coordinate system in this example) is ; the angle between the second straight line and the first straight line is . By adjusting the values of the parameters of the two-dimensional grid, different forms of two-dimensional grids can be generated.

[0039] To ensure that the constructed two-dimensional grid can completely cover the planned field area, it is recommended to take and as relatively large odd numbers, such as 1001. Further, the intersection positioning coordinates ( , ) of the middlemost straight line among the first straight lines and the middlemost straight line among the second straight lines are located at the position where and respectively represent the minimum values of the abscissa and ordinate of the outer boundary points of the planned field area in the reference coordinate system. This design not only ensures that the constructed two-dimensional grid completely covers the planned field area, but also guarantees the flexibility of the grid nodes located within the planned field area.

[0040] S300. Taking the parameters of the two-dimensional grid as variables, taking the grid points of the two-dimensional grid within the planned field area as the positions for installing wind turbines and booster stations, and aiming to maximize the annual power generation of the planned field area, use the genetic algorithm to determine the optimal parameters of the two-dimensional grid.

[0041] S310. Use the parameters of the two-dimensional grid as design variables, and take maximizing the annual power generation of the planned field area as the objective function to construct an optimization calculation model for loom layout based on the genetic algorithm. According to the set population size Q, randomly generate the initial population, where each individual represents a parameter scheme of the two-dimensional grid.

[0042] In this embodiment, the grid points of the two-dimensional grid in the planned field area are used as the points for installing wind turbines and booster stations. For example, the coordinates of the wind turbine are determined by the intersection of the i-th first straight line and the j-th second straight line : ; ; Among them, ; S320. As Figure 4 shown, for the parameter scheme of the two-dimensional grid corresponding to any individual in the population, it is necessary to check the constraint conditions before calculating the annual power generation.

[0043] S321. Judge whether the number of grid points of the two-dimensional grid in the planned field area under the parameter scheme corresponding to the target individual is equal to , where is the number of wind turbines to be installed in the planned field area, and 1 corresponds to the point for building the booster station.

[0044] In this embodiment, the "ray intersection method" is used to judge the relative position relationship between each grid node and the polygon of the planned field area. The core idea is: taking the target grid node as the end point, draw a horizontal ray to the right (parallel to the X-axis of the reference coordinate system), and calculate the number of intersections of the ray and the polygon of the planned field area. When the number of intersections is odd, it can be determined that the grid node is inside the polygon of the planned field area, and when it is even, the grid node is outside the planned field area.

[0045] Specifically, as Figure 5 shown, because the rightward ray with the grid node as the vertex intersects the polygon of the planned field area at only 1 point (odd number), so it is inside the planned field area, while the number of intersections of the rightward ray with the grid node as the vertex and the polygon of the planned field area is 2 (even number), so it is outside the planned field area.

[0046] For the case where there are restricted areas in the planned field area, the "ray intersection method" can also be referred to judge the relative position relationship between each grid node and the restricted area.

[0047] When the number of grid nodes located inside the planned field area and outside the restricted area is equal to When it is equal to, it can be determined that the parameter scheme corresponding to the target individual meets the quantity constraint; if it is not equal to , it is determined that the parameter scheme corresponding to the target individual does not meet the quantity constraint, and a penalty value, such as 0.001 (preset minimum value), is assigned to the annual power generation of the target individual.

[0048] S322. Determine whether the distance between adjacent grid points under the parameter scheme corresponding to the target individual is greater than the preset minimum distance .

[0049] In this embodiment, the minimum value of the distance between adjacent grid nodes is determined , and the calculation formula is: ; Judge and . If the minimum value of the distance between adjacent grid points is greater than or equal to the preset minimum distance, it is determined that the parameter scheme corresponding to the target individual meets the distance constraint; if the minimum value of the distance between adjacent grid points is less than the preset minimum distance, it is determined that the parameter scheme corresponding to the target individual does not meet the distance constraint, and a penalty value, such as 0.001, is assigned to the annual power generation of the target individual.

[0050] S330. For the two-dimensional grid parameter scheme corresponding to each individual, based on the positional relationship between the geometric center of gravity of the planned field area and the onshore centralized control center, determine the intersection point M of the outgoing submarine cable and the outer boundary of the planned field area; calculate the distances from each grid point in the two-dimensional grid within the planned field area to the line between the geometric center of gravity and the intersection point M, and select the grid point with the shortest distance as the location of the booster station ( Figure 6 ).

[0051] In some embodiments, for the two-dimensional grid parameter scheme corresponding to each individual, each grid point in the two-dimensional grid within the planned field area is used as an alternative location of the booster station, and with the goal of the shortest line between the booster station and each wind turbine within the planned field area, determine the location of the booster station within the planned field area.

[0052] S340. For the individuals that meet the constraints in step S320, obtain the coordinates of each grid node within the planned field area in the reference coordinate system to form a set WF_set, and then combine with S330 to determine the construction location of the booster station, and calculate the annual power generation of all wind turbines in the planned field area under the corresponding parameter scheme ( Figure 7 ).

[0053] S341. Based on the wind speed and wind direction, divide the basic wind conditions, and combine with the representative annual wind resource data set to determine the basic wind conditions corresponding to each time period within the representative year, as well as the proportion of each basic wind condition within the representative year and the representative wind speed and representative wind direction of each basic wind condition.

[0054] S341a. Using the cut-in wind speed of the planned installed model within the planned field area and the cut-out wind speed As the lower and upper limits, combined with the preset wind speed calculation interval , multiple distinct wind speed intervals are divided.

[0055] According to the definition, the total number is , and the central value of the m-th wind speed interval is .

[0056] S341b. According to the preset number of wind direction sectors , the 0 - 360° wind direction angle is evenly cut to obtain multiple distinct wind direction sectors.

[0057] According to the definition, the size of the wind direction sector is . Assuming the central value of the first wind direction interval is 0, the central value of the n-th wind direction interval is .

[0058] S341c. Combining the above - divided wind direction sectors and wind speed intervals pairwise, multiple distinct basic wind conditions can be obtained. According to the definition, the total number of basic wind conditions is .

[0059] For each basic wind condition, its representative wind speed and representative wind direction respectively take the central values of the wind direction sector and wind speed interval that constitute the basic wind condition. Assuming the r-th basic wind condition is composed of the m-th wind speed interval and the n-th wind direction sector, the representative wind speed and representative wind direction of this basic wind condition are respectively and .

[0060] S341d. Process the representative annual wind resource data set obtained at the hub height of the wind turbine in step S100. According to the wind direction and wind speed in each time period, assign this time period to the corresponding basic wind condition.

[0061] Statistical ratio of the number of time periods under each basic wind condition to the number of time periods in the wind resource data set can obtain the proportion of each basic wind condition. The corresponding set can be expressed as , where represents the proportion of the r-th basic wind condition.

[0062] S342. Based on the representative wind speed and representative wind direction of each basic wind condition, combined with the positions of each wind turbine in the planned area, calculate the wind speed loss of each wind turbine in the area affected by the wake of the upwind wind turbine under each basic wind condition.

[0063] According to the relative front - back positions along the representative wind direction under the target basic wind condition , sort the grid nodes in WF_set starting from serial number 1, and then use the analytical model to quantify the wind speed loss of the wind turbines to be installed at each grid node in sequence.

[0064] Let the serial number of the target grid node be . When , the serial number of the upwind grid node is . Taking the calculation of the wind speed loss and power generation of the wind turbine at the serial number as an example, the detailed process is as follows: When , since there is no other wind turbine upwind of the wind turbine at this grid node, the wind speed loss is ; When , the wind turbine rotor disk at the target node is discretized, and the average value of the wind speed loss at each discrete point is calculated. Thus, the wind speed loss of the wind turbine at the target grid node p can be obtained: ; In the formula, is the total number of discrete points in the wind turbine rotor disk at node p, refers to the wind speed loss at the o-th discrete point. In this embodiment, the superposition of the square sums method is used to handle the overlapping influence of the wakes of multiple upwind wind turbines. It is calculated by the following formula : ; In the formula, represents the wind speed loss of the isolated wake of the wind turbine at the grid node with serial number at the o-th discrete point in the wind turbine rotor disk at node p with serial number p. The calculation formula is: ; ; ; ; ; In the formula, , and are the flow direction, spanwise direction, and vertical distance between the discrete point o and the center point of the wind turbine rotor disk at the node with serial number in turn. and respectively refer to the thrust coefficient and wake expansion coefficient of the wind turbine at the grid node with serial number . According to existing research, is closely related to the effective turbulence intensity of the wind turbine at node , and satisfies the following relational formula: ; In the formula, and are adjustable parameters, and the recommended values are 0.38 and 0.004 respectively. When q = 1, it means that there are no other wind turbines upwind of the wind turbine at node q. Therefore, the effective turbulence intensity is approximately equal to the turbulence intensity at the representative height, that is: ; When , in addition to the inflow turbulence intensity, the effective turbulence intensity sensed by the wind turbine at this node also includes the additional turbulence intensity generated by the operation of the upstream wind turbine. The calculation formula is: ; ; In the formula, and represent the shielding area of the isolated wake of the wind turbine at node k on the wind turbine rotor at node q, and the magnitude of the additional turbulence intensity at the wind turbine at node q, respectively. The calculation formula is: ; ; In the formula, is the effective turbulence intensity of the wind turbine at node k, is the flow direction spacing of the wind turbines at node k and node q along the representative wind direction.

[0065] In this embodiment, a "virtual wind turbine" is arranged at the step-up station site. Different from the real wind turbines to be installed in the planned wind farm area, the "virtual wind turbine" is always in a shutdown state, that is, no matter how the inflow wind condition changes, its output power is always 0, and theoretically the thrust coefficient is also 0, indicating that its existence does not cause any obstruction to the inflow wind field. However, in the subsequent steps of evaluating the wake effect of the wind farm using the analytical model, a thrust coefficient of 0 will cause a calculation overflow error. Therefore, in this embodiment, the thrust coefficient of the "virtual wind turbine" is set to 0.001 to ensure stable calculation.

[0066] S343. Based on the representative wind speeds under each basic wind condition and the wind speed losses of each wind turbine affected by the wake of the upstream wind turbine, determine the effective wind speeds of each wind turbine under each basic wind condition.

[0067] Based on the wind speed loss calculated in step S342, combined with the representative wind speed under the target basic wind condition , the effective wind speed of the wind turbine at the grid node with serial number p can be obtained: .

[0068] S344. Determine the power generation of each wind turbine under each basic wind condition based on the effective wind speed of each wind turbine under each basic wind condition, and then determine the power generation under each basic wind condition.

[0069] When the grid node with the serial number is the step-up station site represented by the "virtual wind turbine", take its thrust coefficient = 0.001, and the power generation ; while when the real model wind turbine is installed at the grid node with the serial number , based on the effective wind speed obtained above , combined with the wind speed-aerodynamic parameter list obtained in step S100, the thrust coefficient of the wind turbine can be obtained with reference to the following formula and the power generation : ; ; In the formula, and are respectively the two typical wind speeds in the list that are closest to , satisfying , , and is the thrust coefficient and power corresponding to and in the list.

[0070] ; In the formula, represents the power generation under the rth basic wind condition ; is the power generation of the wind turbine at the grid node numbered p in the layout plan under the target basic wind condition .

[0071] S345. Determine the annual power generation of the planned field area in the representative year based on the power generation under each basic wind condition and the proportion of each basic wind condition in the representative year.

[0072] ; In the formula, is the annual power generation of the planned field area; respectively represent the proportion of the rth basic wind condition and the power generation under this basic wind condition.

[0073] S400. Determine the two-dimensional grid based on the optimal parameters of the two-dimensional grid, and then determine the positions of the wind turbines and step-up stations to be assembled in the planned field area based on the grid points of the two-dimensional grid.

[0074] S410. Determine wind turbine rows based on each first straight line on the two-dimensional grid determined by the optimal parameters. The wind turbines (including virtual wind turbines) on the first straight line form a row. Determine the number of wind turbines on each wind turbine row that are located within the planned site (regard the booster station as a "virtual wind turbine", that is, in the row where it is located, the wind turbine count is the number of real wind turbines + 1).

[0075] S420. Based on the number of wind turbines on each wind turbine row located within the planned area, adjust the locations of wind turbines within the planned area according to different situations.

[0076] When the number of wind turbines on the wind turbine row is 1, the distance from the wind turbine point to the intersection of the first straight line and the planned site boundary is set as the second variable.

[0077] When the number of wind turbines on the wind turbine row is 2, place the two wind turbines at the two intersections of the corresponding first straight line and the planned site boundary. Figure 8 In the case shown in "Typical Row 1", at this time, it is only necessary to adjust the two wind turbines to the two intersection points of the row of straight lines and the geometric boundary of the planned site (the blue squares and purple diamonds in the figure respectively represent the wind turbines before and after the adjustment), and there are no design variables that need to be optimized.

[0078] When the number of wind turbines on a wind turbine row is greater than 2, the two wind turbines at both ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned site, and the spacing between adjacent wind turbines in the wind turbine row is used as the first variable. Figure 8 In the case of "Typical Row 3" in Figure 1, after adjusting the wind turbines at both ends of the row to the intersection of the row and the planned site, it is necessary to further optimize the spacing between any two wind turbines in the row (the blue squares and orange diamonds in the figure represent the wind turbines before and after the adjustment, respectively). The set of corresponding design variables is ,in, It indicates the distance between the first and second wind turbines in the third row. The meanings of other variables are similar.

[0079] Taking the first variable and the second variable as optimization variables, with the goal of maximizing the annual power generation of the planned area, combined with the row optimization constraints, a genetic algorithm is used to determine the optimal first variable and second variable, and based on the first variable and the second variable, the position of each wind turbine on each wind turbine row in the planned area is determined.

[0080] In this embodiment, the optimization constraints include the following two: 1) the distance between any two wind turbines is greater than a preset minimum distance threshold; 2) when there is a restricted area in the planned site, each wind turbine must be outside the restricted area.

[0081] In this embodiment, a genetic algorithm is used to generate an initial population. Each individual in the population is a set of values of the first variable and the second variable set. In the corresponding loom arrangement scheme, it is necessary to first determine whether the above two constraint conditions are satisfied. Further, for the individuals that satisfy the constraint conditions, the annual power generation of the wind farm is calculated using the calculation methods in steps S341 - S345 (still assuming that there is a "virtual wind turbine" at the booster station location), while for those that do not satisfy, their power generation is taken as a minimum value, such as 0.001.

[0082] Embodiment 2: This embodiment is an offshore wind farm layout optimization design device considering a booster station, including: An information acquisition module, configured to acquire the boundary information of the planned field area, the number and model parameters of the wind turbines to be assembled in the field area, and the representative annual wind resource data set at the hub height of the wind turbines; A grid generation module, configured to generate a two-dimensional grid covering the planned field area, which is formed by the intersection of multiple mutually parallel first straight lines and multiple mutually parallel second straight lines; A parameter optimization module, configured to use the parameters of the two-dimensional grid as variables, use the grid points of the two-dimensional grid in the planned field area as the positions of the wind turbines and the booster station to be assembled, and take maximizing the annual power generation of the planned field area as the goal, and use a genetic algorithm to determine the optimal parameters of the two-dimensional grid; A position determination module, configured to determine the two-dimensional grid based on the optimal parameters of the two-dimensional grid, determine the wind turbine rows based on the first straight lines on the two-dimensional grid, place the two wind turbines at both ends of the wind turbine row at the two intersections of the corresponding first straight line and the boundary of the planned field area, and use the distance between adjacent wind turbines in the wind turbine row as the first variable, and take maximizing the annual power generation of the planned field area as the goal, and use a genetic algorithm to determine the optimal first variable.

[0083] Embodiment 3: This embodiment is a storage medium, on which a computer program executable by a processor is stored. When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering a booster station described in Embodiment 1 are implemented.

[0084] Embodiment 4: This embodiment is an offshore wind farm layout optimization design device, having a memory and a processor. A computer program executable by the processor is stored on the memory. When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering a booster station described in Embodiment 1 are implemented.

[0085] In addition, although the present invention has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the above-described functions and / or features may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It should also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. Rather, considering the attributes, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the modules will be understood within the ordinary skills of an engineer. Thus, those skilled in the art can implement the present invention as set forth in the claims without undue experimentation. It should also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0086] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the above methods in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0087] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a predefined sequence of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0088] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable media can even be paper or other suitable media on which the above programs can be printed, because the above programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, deciphering or, when necessary, otherwise processing in a suitable manner, and then storing them in a computer memory.

[0089] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0090] In the above description of this specification, the descriptions referring to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0091] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the claims and their equivalents.

[0092] The above is a specific description of the preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present invention, and these equivalent deformations or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for optimizing the layout of offshore wind farms considering booster stations, characterized in that: include: Obtain the boundary information of the planned site, the number and model parameters of wind turbines to be installed in the site, and the representative annual wind resource data set at the hub height of the wind turbine; Generate a two-dimensional grid covering the planned site, the two-dimensional grid being formed by the intersection of a plurality of mutually parallel first straight lines and a plurality of mutually parallel second straight lines; The parameters of the two-dimensional grid are used as variables, the grid points of the two-dimensional grid in the planned area are used as the locations where wind turbines and booster stations are to be installed, and the goal is to maximize the annual power generation of the planned area. The genetic algorithm is used to determine the optimal parameters of the two-dimensional grid. Based on the optimal parameters of the two-dimensional grid, the two-dimensional grid is determined, and the wind turbine row is determined based on the first straight line on the two-dimensional grid. The two wind turbines at both ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned site. The spacing between adjacent wind turbines in the wind turbine row is used as the first variable. With the goal of maximizing the annual power generation of the planned site, a genetic algorithm is used to determine the optimal first variable.

2. The offshore wind farm layout optimization design method considering the booster station according to claim 1 is characterized in that: include: When the number of wind turbines on the wind turbine row is 1, the distance from the wind turbine point to the intersection of the first straight line and the planned site boundary is set as the second variable; When the number of wind turbines on the wind turbine row is 2, two wind turbines are placed at the two intersections of the corresponding first straight line and the boundary of the planned site; When the number of wind turbines on the wind turbine row is greater than 2, the two wind turbines at both ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned site, and the spacing between adjacent wind turbines in the wind turbine row is used as the first variable; Taking the first variable and the second variable as optimization variables and maximizing the annual power generation of the planned site as the goal, a genetic algorithm is used to determine the optimal first variable and the second variable.

3. The offshore wind farm layout optimization design method considering the booster station according to claim 1 is characterized in that: The grid points of the two-dimensional grid in the planned site are used as the locations where wind turbines and booster stations are to be installed, including: Based on the geometric center of gravity of the planned site and the positional relationship between the onshore centralized control center, determine the intersection point M of the outgoing submarine cable and the outer boundary of the planned site; Calculate the distance from each grid point of the two-dimensional grid in the planning area to the line between the geometric center of gravity and the intersection point M, and select the grid point with the shortest distance as the location of the booster station.

4. The offshore wind farm layout optimization design method considering booster stations according to claim 1 is characterized in that: The calculation of the annual power generation of the planned site includes: Determine whether the number of grid points in the two-dimensional grid in the planning area is equal to ,in The number of wind turbines to be installed in the planned area; If the number of grid points in the planned area is not equal to , the preset minimum value is used as the annual power generation of the planned site; otherwise, it is determined whether the spacing between adjacent grid points is greater than the preset minimum spacing; If the spacing between adjacent grid points is less than the preset minimum spacing, the preset minimum value is used as the annual power generation of the planned site; otherwise, the annual power generation of the planned site is calculated based on the location of each wind turbine in the planned site, combined with the model parameters and the representative annual wind resource data set.

5. The offshore wind farm layout optimization design method considering booster stations according to claim 4 is characterized in that: The annual power generation of the planned area is calculated based on the location of each wind turbine in the planned area, combined with the model parameters and the representative annual wind resource data set, including: Assume that the boost station is located at a virtual wind turbine, the output power of the virtual wind turbine is always 0, and the thrust coefficient is set to 0.001; Divide the basic wind conditions based on wind speed and wind direction, and combine with the representative annual wind resource data set to determine the basic wind conditions corresponding to each period of the year, as well as the proportion of each basic wind condition in the year and the representative wind speed and representative wind direction of each basic wind condition; Based on the representative wind speed and representative wind direction of each basic wind condition, combined with the location of each wind turbine in the planned site, calculate the wind speed loss of each wind turbine in the site affected by the wake of the upwind wind turbine under each basic wind condition; Based on the representative wind speed under each basic wind condition and the wind speed loss of each wind turbine affected by the wake of the upwind wind turbine, the effective wind speed of each wind turbine under each basic wind condition is determined; Based on the effective wind speed of each wind turbine under each basic wind condition, determine the power generation of each wind turbine under each basic wind condition, and then determine the power generation under each basic wind condition; Based on the power generation under each basic wind condition and the proportion of each basic wind condition in a representative year, the annual power generation of the planned site in the representative year is determined.

6. The offshore wind farm layout optimization design method considering booster stations according to claim 5 is characterized in that: The basic wind conditions divided based on wind speed and wind direction include: The cut-in wind speed of the wind turbine model to be installed in the planning area Cut-out wind speed As the maximum value and the minimum value, multiple wind speed intervals are divided between the maximum value and the minimum value; Evenly divide the wind direction angle from 0 to 360° and divide it into multiple wind direction sectors; The wind speed ranges and wind direction sectors are combined in pairs to form multiple basic wind conditions.

7. An offshore wind farm layout optimization design device considering booster stations, characterized in that: include: An information acquisition module is used to obtain the boundary information of the planned site, the number and model parameters of wind turbines to be installed in the site, and a representative annual wind resource data set at the height of the wind turbine hub; A grid generation module, used to generate a two-dimensional grid covering the planned area, the two-dimensional grid being formed by the intersection of a plurality of mutually parallel first straight lines and a plurality of mutually parallel second straight lines; The parameter optimization module is used to use the parameters of the two-dimensional grid as variables, the grid points of the two-dimensional grid in the planning area as the locations where wind turbines and booster stations are to be installed, and the goal is to maximize the annual power generation of the planning area, and use genetic algorithms to determine the optimal parameters of the two-dimensional grid; The point determination module is used to determine the two-dimensional grid based on the optimal parameters of the two-dimensional grid, determine the wind turbine row based on the first straight line on the two-dimensional grid, place the two wind turbines at both ends of the wind turbine row at the two intersections of the corresponding first straight line and the boundary of the planned site, and use the spacing between adjacent wind turbines in the wind turbine row as the first variable, with the goal of maximizing the annual power generation of the planned site, and use a genetic algorithm to determine the optimal first variable.

8. A storage medium having stored thereon a computer program executable by a processor, characterized in that: When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering the booster station as described in any one of claims 1 to 6 are implemented.

9. An offshore wind farm layout optimization design device, comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, characterized in that: When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering the booster station as described in any one of claims 1 to 6 are implemented.

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