Offshore wind plant regular layout design method based on double-layer design strategy

Abstract

The invention provides an offshore wind power plant regular layout design method based on a double-layer design strategy, and the method comprises the steps: converting the design of a wind turbine arrangement scheme in a planning field into the design of a wind turbine arrangement scheme in a feasible region, and enabling the feasible region to be equal to the planning field, or enabling the feasible region to be a region after a limiting region is removed from the planning field; the outer boundary coincides with the boundary of the planning field area; in the outer-layer design, the feasible change range of the row number of the wind turbines is determined according to the characteristic length of a feasible region in the main wind direction, sub-problems needing to be optimized are determined by taking the row number as distinction, inner-layer design is carried out on the sub-problems determined by any row number, and the point position coordinates and generating capacity of the wind turbines of different wind turbine arrangement schemes are calculated; and selecting the scheme with the maximum generating capacity as an optimization calculation result of the sub-problems, comparing the optimization calculation results of the sub-problems, and giving a final recommended wind power plant layout design scheme. According to the method, the optimal combination of the row number, the row spacing and the number of units in each row can be given, and the regular layout of the limited area in the field can be automatically avoided.

Description

Technical Field

[0001] The invention belongs to the field of wind farm planning and design, and specifically relates to a regular layout design method for an offshore wind farm based on a double-layer design strategy. Background Art

[0002] In recent years, energy and environmental issues have become increasingly prominent. As a renewable and clean energy, wind energy has received more and more attention, and the wind power industry has developed rapidly. Wind turbines are important devices for absorbing and converting wind energy. When developing wind power projects, the first thing that must be solved is to provide a wind farm layout plan that meets the actual needs of the project based on wind resource conditions and related limiting factors. This directly determines the final benefits of the project development.

[0003] Compared with land, the wind direction distribution at sea is more concentrated. In engineering practice, in order to meet the navigation needs of ships and facilitate the installation and operation of wind turbines, the layout of wind farms needs to be as regular as possible, that is, wind turbines are required to be arranged in "rows". When there is an obvious main wind direction, in order to fully utilize wind energy resources and reduce the adverse effects of the wake effect, each row of wind turbines is usually arranged perpendicular to the main wind direction. Following this engineering principle, when designing the layout of wind power projects, engineers often give several alternative plans by changing the number of wind turbine rows, row spacing, and the number of wind turbines in each row, and then give the final recommended wind farm layout through calculation and comparison. Limited by the limited number of comparison options and the subjectivity of manual experience, it is difficult to obtain the best engineering quality solution with the best economic efficiency based on the above method. Especially when there is a restricted area where wind turbines cannot be arranged in the site, it is very difficult to determine the optimal combination of the above multiple variables based on experience alone. In recent years, intelligent optimization algorithms have been widely used in the field of wind farm layout design. However, during the optimization iteration process, most of them only restrict the spacing between adjacent wind turbines without considering the "regular layout" requirements that are more concerned in engineering practice. In the given layout plan, each wind turbine is distributed in the field in an approximately "scattered" manner, which has poor practicality.

[0004] In view of the strong practical needs of engineering and the above-mentioned drawbacks, on the basis of following the engineering principle that wind turbine rows should be arranged approximately perpendicular to the main wind direction, it is urgent to propose an intelligent layout design method that can automatically give the optimal combination of multi-dimensional variables such as the number of wind turbine rows, row spacing, and the number of wind turbines in each row, and can accurately identify and avoid restricted areas within the site. Summary of the invention

[0005] The purpose of the present invention is to propose a regular layout design method for offshore wind farms based on a double-layer design strategy for situations where there is an obvious main wind direction, taking into account the complex constraints of the planned area that may include restricted areas where wind turbines cannot be arranged, so as to obtain a better engineering quality solution with better economy.

[0006] The technical solution of the present invention is: A method for designing a regular layout of an offshore wind farm based on a double-layer design strategy, characterized in that the method for designing a regular layout of an offshore wind farm converts the design of a wind turbine arrangement scheme in a planned area into the design of a wind turbine arrangement scheme in a feasible domain, wherein the feasible domain is equal to the planned area, or if there is a restricted area in the planned area, the feasible domain is the area after the restricted area is removed from the planned area, and the outer boundary coincides with the boundary of the planned area, and the regular layout design of the offshore wind farm is performed through a double-layer design strategy; The double-layer design includes an outer layer design and an inner layer design. In the outer layer design, the feasible variation range of the number of wind turbine rows is determined according to the characteristic length of the feasible domain along the main wind direction, and the number of rows is used as a distinction to determine the sub-problem to be optimized. For any sub-problem with a determined number of rows, the inner layer design is entered. Under the principle of regular arrangement of wind turbines with equal spacing in each row and the number of wind turbines in the feasible domain being exactly equal to the demand, the row spacing and the number of wind turbines in each row are used as design variables to calculate the coordinates of wind turbine points and their power generation for different wind turbine arrangement schemes, and the scheme with the largest power generation is selected as the optimization calculation result output of the sub-problem. Then, by comparing the optimization calculation results of each sub-problem, the final recommended wind farm layout design scheme is given, and the outer layer design is completed.

[0007] On the basis of adopting the above technical solutions, the present invention may also adopt the following further technical solutions, or use these further technical solutions in combination: The offshore wind farm regular layout design method specifically comprises the following steps: Step 1: Data acquisition and parameter setting; Step 2: Enter the outer design stage, calculate the feasible variation range of the number of wind turbine rows in the feasible domain according to the characteristic length of the feasible domain along the main wind direction, and determine the number of optimization sub-problems accordingly; Step 3: Select one of the optimization sub-problems with a fixed number of rows in step 2, enter the inner layer design, determine the design variables to be optimized and their feasible range of variation, and use the intelligent optimization algorithm to initialize the population; Step 4: For one of the individuals in the population, that is, a set of design variables, calculate the coordinates of the wind turbine points under the corresponding arrangement scheme, and determine whether the total number of wind turbines in the feasible region is consistent with the required number. If they are different, go directly to step 6; if they are the same, go to step 5; Step 5: Calculate the distance between any two wind turbines and determine whether it is greater than the minimum distance threshold. ; Step 6: For individuals that meet the constraints of steps 4 and 5, use the analytical model to calculate the wind farm power generation under the corresponding arrangement scheme; otherwise, take the power generation as a minimum value; based on the power generation results, calculate the individual fitness; Step 7: Replace an individual, repeat steps 4-6, and loop through all individuals in the population; Step 8: According to the parameter settings in step 1, determine whether the calculation result meets the convergence standard or reaches the maximum allowed number of iterations; if neither is satisfied, update the population according to the individual fitness and repeat steps 4-7; otherwise, the calculation result is used as the optimization calculation result of the sub-problem and proceed to step 9; Step 9: Replace a sub-problem, repeat the inner layer design of steps 3-8, loop through all optimization sub-problems, obtain the optimization calculation results of each sub-problem, and then give the final recommended wind farm layout design plan by comparing the optimization calculation results of each sub-problem to complete the outer layer design.

[0008] The data acquisition and parameter setting of step 1 specifically include: obtaining the boundary coordinates of the feasible domain, wind resource data, and basic parameters of the built-in wind turbines; calculating the total number of wind turbines that need to be installed in the feasible domain according to the capacity requirements and the rated power of the built-in wind turbines. ; Determine the values ​​of the necessary parameters in the intelligent optimization algorithm, including population size, maximum allowed number of iterations , iterative convergence residual , and set the minimum spacing threshold that adjacent wind turbines must meet during the optimization calculation process ; Set the value range of each design variable related to the wind farm layout, including the lower limit of the number of rows, the lower limit of the row spacing, the lower limit of the spacing within a row, and the lower limit of the number of wind turbines in each row.

[0009] Step 2 is as follows: According to the relative position relationship with the main wind direction, the boundary lines of the first and last rows of wind turbines are determined with the approximate perpendicularity to the main wind direction as the judgment standard. By calculating the spacing between the two boundary lines, the characteristic length of the feasible domain is obtained; according to the characteristic length and the lower limit of the row spacing set in step 1, the upper limit of the number of wind turbine rows that can be arranged in the feasible domain is determined. ; Combined with the lower limit of the number of rows set in step 1, the feasible variation range of the number of wind turbine rows is obtained, and then according to the difference in the number of rows, the entire wind farm layout design problem is transformed into multiple independent sub-problems.

[0010] In step 3, the design variables to be optimized are determined in the following way: The number of wind turbine rows is The sub-problem involves the set of all design variables: , where the set of design variables is The design variables in are expressed as , defined as i Row of wind turbines and i+1 The percentage of the row endpoint distance of the wind turbine row to the length of the outer boundary line of the feasible region, the design variable set The design variables in are expressed as , defined as j The spacing between wind turbines in a row; Determine the design variables based on the feasible region geometry and the parameter settings in step 1 d i %and a j The feasible change range is determined, and the intelligent optimization algorithm is used to complete the population initialization.

[0011] In step 4, the specific layout of the wind farm is determined in the following way: Step 4.1, calculating equations expressing the left boundary line and the right boundary line of the planned site, wherein the left boundary line and the right boundary line are respectively the boundary line of the planned site on the left side and the right side of the main wind direction; Step 4.2, according to the design variable set , cut the left boundary line and the right boundary line respectively to obtain the endpoint coordinates on both sides of each row of wind turbines; Step 4.3, according to the design variable set , each row of wind turbines determined by the endpoints on both sides of each row of wind turbines is equally divided to obtain the specific position of the wind turbines.

[0012] When judging whether the wind turbine location is located in the feasible region in step 4, if there is no restricted area in the planned area, whether the wind turbine location is located in the feasible region is determined by judging the relative position relationship between the wind turbine location and the planned area; When there is a restricted area where wind turbines cannot be arranged in the planning area, it is also necessary to determine the relative position relationship between each wind turbine point and the restricted area, and then determine the number of wind turbines that fall within the feasible region. The judgment method is: According to the coordinates of each boundary point of the restricted area, the area of ​​the restricted area is calculated using the vector outer product; According to the wind turbine location to be determined The coordinates of the wind turbine points are calculated by using the vector outer product. The sum of the areas of all triangles formed by two adjacent vertices in the restricted area as triangle vertices; If the sum of the areas is equal to the restricted area, and the areas of all triangles are greater than 0, the wind turbine location Located in the restricted area; otherwise, the wind turbine location is outside the restricted area; By determining the relative position relationship between each wind turbine point and the restricted area one by one, the number of wind turbines within the feasible region can be determined. If the number is the same as the number of wind turbines required in step 1, proceed to the next step; otherwise, proceed directly to step 6.

[0013] In step 5, continue with the wind turbine point collection in step 4 , calculate the distance between any two points and determine whether it is greater than the minimum distance threshold set in step 1 :

[0014] The step 6 is specifically as follows: For individuals that simultaneously meet the five constraints, the wind farm power generation under the corresponding arrangement scheme is calculated using the analytical model according to the wind resource data input in step 1.

[0015] In step 8, the population is updated according to the individual fitness by the following method: individuals with larger fitness values ​​are selected as fathers, and after crossover mutation, a new generation of population is formed.

[0016] In summary, the technical solution of the present invention has the following beneficial effects: compared with the manual selection method commonly used in current wind power engineering practice, the present invention uses an intelligent optimization algorithm to iteratively optimize the layout scheme, effectively avoiding the influence of human subjective factors, and can automatically give the optimal combination of the number of rows, row spacing, and the number of wind turbines in each row, significantly improving the reliability of the layout design scheme. More importantly, compared with the prior art, the proposed method also fully considers the "regular arrangement" requirements that are the focus of engineering practice, as well as the complex constraints that may include restricted areas where wind turbines cannot be arranged in the field. On the basis of automatic identification, the wind turbine point intelligently avoids the restricted area, which greatly expands the application scenarios of the present invention and provides a more scientific and practical technical path for solving the layout design problems of offshore wind farms in the presence of obvious main wind directions. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of the wind farm rule layout design method based on the double-layer design strategy of the present invention.

[0018] Figure 2 It is a schematic diagram of the wind farm layout strategy in the inner layer design stage of the present invention.

[0019] Figure 3 (a) shows the wind turbine position of the present invention Schematic diagram of the method for determining the relative position relationship with the restricted area within the planned site, demonstrating the wind turbine location. Outside the feasible region (within the restricted area).

[0020] Figure 3 (b) shows the wind turbine position of the present invention Schematic diagram of the method for determining the relative position relationship with the restricted area within the planned site, demonstrating the wind turbine location. Within the feasible region (outside the restricted area).

[0021] Figure 4 This is a geometric diagram of a wind farm in Example 1 of the present invention.

[0022] Figure 5 This is the wind rose diagram in Example 1 of the present invention.

[0023] Figure 6 This is the optimal wind farm layout design solution when the number of rows is 4 in Example 1 of the present invention.

[0024] Figure 7 This is the optimal wind farm layout design solution when the number of rows is 3 in Example 1 of the present invention. DETAILED DESCRIPTION

[0025] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments, which are intended to explain the present invention rather than to limit it.

[0026] like Figure 1 As shown, a method for designing a regular layout of an offshore wind farm based on a double-layer design strategy of the present invention comprises the following steps: Step 1 is data acquisition and parameter setting, which specifically includes obtaining the boundary coordinates of the feasible domain. The feasible domain is equal to the planned site, or is included in the planned site and the outer boundary coincides with the boundary of the planned site. The boundary of the planned site is the outer boundary of the feasible domain. If the planned site contains a restricted area where wind turbines cannot be arranged, the boundary of the restricted area is the inner boundary of the feasible domain; wind resource data, various basic parameters of built-in wind turbines, etc.; according to the capacity requirements and the rated power of the built-in wind turbines, calculate the total number of wind turbines that need to be installed in the feasible domain ; Determine the values ​​of the necessary parameters in the intelligent optimization algorithm, including population size, maximum allowed number of iterations, iterative convergence residual, etc., and set the minimum spacing threshold that adjacent wind turbines must meet during the optimization calculation process ; Set the value range of each design variable related to the wind farm layout, including the lower limit of the number of rows, the lower limit of the row spacing, the lower limit of the spacing within a row, and the lower limit of the number of wind turbines in each row.

[0027] Step 2, enter the outer layer design stage, calculate the feasible variation range of the number of wind turbine rows in the feasible domain according to the "characteristic length" along the main wind direction, and determine the number of optimization sub-problems accordingly; specifically: According to the relative position relationship with the main wind direction, the boundary lines of the first and last rows of wind turbines are determined with the approximate perpendicularity to the main wind direction as the judgment standard. By calculating the distance between these two boundary lines, the "characteristic length" of the feasible domain is obtained; according to the "characteristic length" and the lower limit of the row spacing set in step 1, the upper limit of the number of wind turbine rows that can be arranged in the feasible domain is determined. Combined with the lower limit of the number of rows set in step 1, the feasible variation range of the number of wind turbine rows is obtained, and then according to the difference in the number of rows, the entire wind farm layout design problem can be transformed into multiple independent sub-problems.

[0028] Step 3: For one of the optimization sub-problems with a fixed number of rows in step 2, enter the inner layer design to determine the design variables to be optimized. At the same time, according to the feasible domain geometry information and the parameter settings in step 1, determine the feasible variation range of each design variable, and use the intelligent optimization algorithm to initialize the population.

[0029] In step 3, the design variables to be optimized can be determined by referring to the following method: Step 3.1, such as Figure 2 As shown in the figure, except for the first and last rows of wind turbines that have been determined to be arranged on two outer boundaries approximately perpendicular to the main wind direction, the endpoints of the remaining rows of wind turbines need to be determined by cutting the other outer boundary lines of the planned site (distinguished by the left and right sides of the wind turbine row, hereinafter referred to as the "left boundary line" and the "right boundary line") in proportion. Specifically, for a row of wind turbines with The sub-problem is to determine ( ) row spacing, record the i Row and No. i +1) The ratio of the distance between the endpoints of a row to the length of the boundary line they are on is , then the set of this type of design variables can be expressed as ; In step 3.2, in addition to the row spacing, another necessary design variable is the number of wind turbines in each row. Since the total number of wind turbines to be installed in the field has been limited in step 1, , so we only need to determine The number of wind turbines in a row can be used to determine the distribution of the entire field. j The number of wind turbines in the row is , then the set of this type of design variables can be expressed as .

[0030] In summary, for the number of wind turbine rows The sub-problem involves the following set of all design variables: .

[0031] Step 3.3: Determine the design variables based on the feasible region geometry information and the parameter settings in step 1.d i %and a j The feasible change range is determined, and the intelligent optimization algorithm is used to complete the population initialization.

[0032] Step 4: For one of the individuals in the population, i.e., a set of design variables, the coordinates of the wind turbine points under the corresponding arrangement scheme are calculated according to the values, and then it is determined whether the total number of wind turbines in the feasible domain (inside the planning area and outside the restricted area where wind turbines cannot be arranged) is the same as the required number. If they are different, go directly to step 6; if they are the same, go to step 5.

[0033] For any individual in the population, the specific layout of the wind farm can be determined according to the value of the design variable: Step 4.1: Calculate the equations of the lines where the "left boundary line" and "right boundary line" of the field are located. Figure 2 , for the endpoint and The "left boundary line" , the equation of the line on which it lies is:

[0034] in, .

[0035] Similarly, according to the endpoint and , we can get the straight line equation of the “right boundary line”.

[0036] Step 4.2: Based on the variable set , cut the “left boundary line” and the “right boundary line” respectively to obtain the endpoint coordinates on both sides of each row of wind turbines.

[0037] Specifically, for the number of rows The sub-problem of "left boundary line" is divided into copy, remember , ,but That is On this boundary line, each cutting point can be expressed as ,in For the cutting point The horizontal coordinate of is calculated as follows: .

[0038] Similarly, the "right boundary line" is also divided into copy, remember , ,but That is The dividing points on the boundary line can be expressed as ,in For the cutting point The horizontal coordinate of is calculated as follows: .

[0039] Step 4.3: Based on the variable set , divide each wind turbine row determined by the above endpoints into equal parts, thereby obtaining the point coordinates of each wind turbine. j Take a wind turbine row as an example, the number of wind turbines in the row is expressed as , then the point coordinates of the mth wind turbine in the row are It can be determined by the following formula:

[0040] Step 4.4: When there is a restricted area in the planning area where wind turbines cannot be deployed, it is necessary to determine the relative position relationship between the wind turbine points determined above and the restricted area, and then determine the number of wind turbines that fall within the feasible domain (inside the planning area and outside the restricted area). As an example of the relative position relationship, Figure 3 (a) shows that the wind turbine point W is located in the restricted area. As shown in Figure 3 (b), the wind turbine position W is located in the restricted area. In addition, the judgment method is briefly described as follows: First, according to the boundary points of the restricted area ( ) coordinates, use the vector outer product to calculate the area of ​​the restricted area ,in , .

[0041] Similarly, according to the wind turbine location The coordinates of the boundary points of the restricted area ( ) coordinates, using the vector outer product, calculate the triangle Area .

[0042] Contrast triangle If the area of ​​the restricted area is equal to the area of ​​the restricted area, then ,and are all greater than 0, it is easy to know that the wind turbine position Located in restricted area inside (excluding the boundary); otherwise, the wind turbine point Located in restricted area Outside (including borders).

[0043] By determining the relative position relationship between each wind turbine point and the restricted area one by one, the number of wind turbines within the feasible region can be determined. If the number is the same as the number of wind turbines required in step 1, proceed to the next step; otherwise, proceed directly to step 6.

[0044] The step 5 is specifically as follows: Continue with the wind turbine point collection in step 4 , calculate the distance between any two points and determine whether it is greater than the minimum distance threshold set in step 1 :

[0045] in, , Respectively refer to and A wind turbine.

[0046] The step 6 is specifically as follows: For individuals that meet the constraints in steps 4 and 5 at the same time, the wind farm power generation under the corresponding arrangement scheme is calculated using the analytical model according to the wind resource data input in step 1. Otherwise, the power generation is taken as a small value, such as 0.001. The power generation calculation result is used as the fitness value of the individual. The arrangement scheme corresponding to the individual with a larger fitness value is more likely to be selected by the algorithm.

[0047] Step 1: Figure 4 The geometric information of the feasible domain in Example 1 is summarized. The overall shape is a trapezoid, where the purple line represents the boundary of the planned area, which is also the outer boundary of the feasible domain. The red dotted line is the inner boundary of the feasible domain, and the surrounding area is the restricted area inside it. In the southwest of the planning area, there are multiple wind turbines that have been built, represented by red squares. The wind turbines planned to be installed in the planning area are the same as the built wind turbines, with a rotor diameter of D=260m and a rated power of 18MW. After processing the wind resource data for a full year at the height of the wind turbine hub, the wind rose is obtained as follows Figure 6 As shown, there is a clear main wind direction.

[0048] Assuming the capacity requirement is 300MW, combined with the wind turbine rated power of 18MW, it can be determined that a total of 17 wind turbines need to be installed in the site.

[0049] The genetic algorithm is used for optimization calculation, the goal is set to maximize the power generation of the wind farm, the population size is 100, the maximum allowed number of iterations is 100, and the iterative convergence residual is 0.001. During the optimization calculation process, the minimum spacing threshold of adjacent wind turbines is set to 3D.

[0050] The value ranges of various parameters related to the layout of the wind farm are set as follows: the lower limit of the number of rows is 3, the lower limit of the row spacing is 7D, the lower limit of the spacing within a row is 3D, and the lower limit of the number of wind turbines in each row is 2.

[0051] Take the boundary point C located in the southwest corner of the planning area 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 two-dimensional rectangular coordinate system. In this coordinate system, the coordinates of each point on the boundary of the planning area are , , , , the coordinates of each boundary point in the internal restricted area are , , , (Unit: ); Step 2: Based on the "characteristic length" of the planned site along the main wind direction and the lower limit of the row spacing 7D set in step 1, the upper limit of the number of wind turbine rows that can be arranged in the feasible domain can be obtained. = 4. Combined with the lower limit of 3 set in step 1, it can be determined that Example 1 includes two optimization sub-problems (the number of rows is 3 and 4 respectively).

[0052] Step 3: For any of the above sub-problems, in order to determine the layout of the entire field, it is necessary to first integrate the optimization design variables involved. Specifically, for the sub-problem with 3 rows, it is obvious that only the spacing between the first and second rows needs to be determined, and the design variables are expressed as , and the number of wind turbines in the first and second rows, respectively, the design variables are expressed as Similarly, for the subproblem with 4 rows, the design variables related to the row spacing include , the design variables related to the number of wind turbines in each row include .

[0053] Next, take the number of rows as 4 and take the value as Take an example of a set of design variables and describe steps 4-6 in detail.

[0054] Step 4: First, determine the equations of the lines where the "left boundary line" and "right boundary line" of the planned site are located. Figure 4 As shown, in this example, "Left Border" The equation of the line is: ; "Right Border" The equation of the line is: ; Furthermore, the intersection points of each wind turbine row and the outer boundary line of the site are calculated: "Left Border" The coordinates of the dividing points on and ; "Right Border" The coordinates of the dividing points on and .

[0055] Next, wind turbines For example, calculate the location of each wind turbine in a row. , according to the calculation formula , the coordinates of the wind turbine points in the row are , , Similarly, the coordinates of the points of other rows of wind turbines can be calculated.

[0056] Judging the relative position relationship between the wind turbine locations determined above and the restricted area within the planned site, the calculation results show that the number of wind turbines in the feasible domain is 17, which just matches the demand.

[0057] Step 5: Continue with the wind turbine coordinate set in step 4 and calculate the distance between any two points. , meeting the minimum spacing threshold requirement set in step 1.

[0058] Step 6: Based on the wind turbine coordinate set in step 4, combined with the wind resource data input in step 1, the wind farm power generation is calculated using the analytical model as the individual fitness value. Specifically, in this example: The velocity loss in the wake area of ​​any isolated wind turbine is calculated using the Gaussian model:

[0059]

[0060]

[0061] in, is the effective wind speed at the wind turbine, is the thrust coefficient of the wind turbine, D is the diameter of the wind rotor, is the wheel hub height, Respectively represent the streamwise, lateral and vertical distances relative to the center point of the wind rotor; is the wake attenuation coefficient, which is used to quantify the change of wake velocity loss and influence range with downstream distance. It has a strong positive correlation with turbulence intensity and is calculated as follows:

[0062]

[0063] in, is the inflow turbulence intensity, The additional turbulence intensity generated by the operation of the wind turbine can be estimated by the following empirical calculation formula:

[0064] in, is the axial induction factor of the wind turbine, and the calculation formula is:

[0065] For wind turbines operating in the wake area of ​​multiple upstream wind turbines, the linear superposition method is used to quantify the influence of the wake superposition effect. For example, the effective wind speed sensed by a wind turbine is calculated by the following formula:

[0066] in, is the inflow wind speed, Refers to the number When the front row wind turbines are operating in isolation, their wakes are Speed ​​loss at .

[0067] Steps 7 and 8: Based on the genetic algorithm, through repeated optimization iterations, the combination of design variable values ​​that meet the output standard is obtained as follows: , the corresponding wind farm layout is shown in Figure 6 The average wake loss for the entire field is 3.78%.

[0068] Similarly, for the sub-problem with 3 rows, refer to the above steps for optimization calculation and obtain the combination of design variable values ​​that meets the output standard: , the corresponding wind farm layout is shown in Figure 7 The average wake loss for the entire field is 4.87%.

[0069] Figure 6 and Figure 7 In this example, the wind turbine locations designed are marked with Arabic numerals 1-17, and Arabic numerals 18-36 are the locations of the built wind turbines.

[0070] The step 9: returning to the outer layer design stage, comparing the calculation results of the two sub-problems of 3 and 4 wind turbine rows, because the whole field wake loss is smaller when the number of rows is 4, that is, the corresponding annual power generation is higher, so this layout scheme is finally recommended.

[0071] In the present invention, in the outer layer design stage, the feasible variation range of the number of wind turbine rows is determined according to the "characteristic length" of the feasible domain along the main wind direction, and then the entire wind farm layout design problem is divided into multiple independent sub-problems according to the difference in the number of rows. For any of the above sub-problems with a fixed number of rows, the inner layer design stage is entered, and the intelligent optimization algorithm is used to achieve the maximum annual power generation. Through repeated optimization iterations, the optimal combination of row spacing and the number of wind turbines in the row is obtained on the basis of automatic identification and avoidance of restricted areas. Returning to the outer layer design stage, the final recommended wind farm layout design is given by comparing the calculation results of each optimization sub-problem.

[0072] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for designing regular layout of offshore wind farms based on a double-layer design strategy, characterized in that: The offshore wind farm regular layout design method converts the design of the wind turbine arrangement scheme in the planned site into the design of the wind turbine arrangement scheme in the feasible domain, and the feasible domain is equal to the planned site, or if there is a restricted area in the planned site, the feasible domain is the area after the restricted area is removed from the planned site, and the outer boundary coincides with the boundary of the planned site, and the offshore wind farm regular layout design is performed through a double-layer design strategy; The double-layer design includes an outer layer design and an inner layer design. In the outer layer design, the feasible variation range of the number of wind turbine rows is determined according to the characteristic length of the feasible domain along the main wind direction, and the number of rows is used as a distinction to determine the sub-problem to be optimized. For any sub-problem with a determined number of rows, the inner layer design is entered. Under the principle of regular arrangement of wind turbines with equal spacing in each row and the number of wind turbines in the feasible domain being exactly equal to the demand, the row spacing and the number of wind turbines in each row are used as design variables to calculate the coordinates of wind turbine points and their power generation for different wind turbine arrangement schemes, and the scheme with the largest power generation is selected as the optimization calculation result output of the sub-problem. Then, by comparing the optimization calculation results of each sub-problem, the final recommended wind farm layout design scheme is given, and the outer layer design is completed.

2. A method for designing a regular layout of an offshore wind farm based on a double-layer design strategy as claimed in claim 1, characterized in that: The specific steps include: Step 1: Data acquisition and parameter setting; Step 2: Enter the outer design stage, calculate the feasible variation range of the number of wind turbine rows in the feasible domain according to the characteristic length of the feasible domain along the main wind direction, and determine the number of optimization sub-problems accordingly; Step 3: Select one of the optimization sub-problems with a fixed number of rows in step 2, enter the inner layer design, determine the design variables to be optimized and their feasible range of variation, and use the intelligent optimization algorithm to initialize the population; Step 4: For one of the individuals in the population, that is, a set of design variables, calculate the coordinates of the wind turbine points under the corresponding arrangement scheme, and determine whether the total number of wind turbines in the feasible region is consistent with the required number. If they are different, go directly to step 6; if they are the same, go to step 5; Step 5: Calculate the distance between any two wind turbines and determine whether it is greater than the minimum distance threshold. ; Step 6: For individuals that meet the constraints of steps 4 and 5, use the analytical model to calculate the wind farm power generation under the corresponding arrangement scheme; otherwise, take the power generation as a minimum value; based on the power generation results, calculate the individual fitness; Step 7: Replace an individual, repeat steps 4-6, and loop through all individuals in the population; Step 8: According to the parameter settings in step 1, determine whether the calculation result meets the convergence standard or reaches the maximum allowed number of iterations; if neither is satisfied, update the population according to the individual fitness and repeat steps 4-7; otherwise, the calculation result is used as the optimization calculation result of the sub-problem and proceed to step 9; Step 9: Replace a sub-problem, repeat the inner layer design of steps 3-8, loop through all optimization sub-problems, obtain the optimization calculation results of each sub-problem, and then give the final recommended wind farm layout design plan by comparing the optimization calculation results of each sub-problem to complete the outer layer design.

3. A method for designing a regular layout of an offshore wind farm based on a double-layer design strategy as claimed in claim 2, characterized in that: The data acquisition and parameter setting of step 1 specifically include: Obtain the boundary coordinates of the feasible domain, wind resource data, and basic parameters of the built-in wind turbines; calculate the total number of wind turbines required to be installed in the feasible domain based on capacity requirements and the rated power of the built-in wind turbines ; Determine the values ​​of the necessary parameters in the intelligent optimization algorithm, including population size, maximum allowed number of iterations, iterative convergence residual, and set the minimum spacing threshold that adjacent wind turbines must meet during the optimization calculation process ; Set the value range of each design variable related to the wind farm layout, including the lower limit of the number of rows, the lower limit of the row spacing, the lower limit of the spacing within a row, and the lower limit of the number of wind turbines in each row.

4. A method for designing a regular layout of an offshore wind farm based on a double-layer design strategy as claimed in claim 2, characterized in that: Step 2 is as follows: According to the relative position relationship with the main wind direction, the boundary lines where the first and last rows of wind turbines are located are determined with the approximate perpendicularity to the main wind direction as the judgment standard. By calculating the distance between the two boundary lines, the characteristic length of the feasible region is obtained. According to the characteristic length and the lower limit of the row spacing set in step 1, determine the upper limit of the number of wind turbine rows that can be arranged in the feasible domain ; Combined with the lower limit of the number of rows set in step 1, the feasible variation range of the number of wind turbine rows is obtained, and then according to the difference in the number of rows, the entire wind farm layout design problem is transformed into multiple independent sub-problems.

5. The offshore wind farm rule layout design method based on a double-layer design strategy as claimed in claim 2, characterized in that: In step 3, the design variables to be optimized are determined in the following way: For wind turbine rows The sub-problem involves the set of all design variables: , where the set of design variables is The design variables in are expressed as , defined as i Row of wind turbines and i +1 The percentage of the row endpoint distance of the wind turbine row to the length of the outer boundary line of the feasible region, the design variable set The design variables in are expressed as , defined as j The spacing between wind turbines in a row; Determine the design variables based on the feasible region geometry and the parameter settings in step 1 d i %and a j The feasible change range is determined, and the intelligent optimization algorithm is used to complete the population initialization.

6. A method for designing the regular layout of an offshore wind farm based on a double-layer design strategy as claimed in claim 5, characterized in that: In step 4, the specific layout of the wind farm is determined in the following way: Step 4.1, calculating equations expressing the left boundary line and the right boundary line of the planned site, wherein the left boundary line and the right boundary line are respectively the boundary line of the planned site on the left side and the right side of the main wind direction; Step 4.2, according to the design variable set , cut the left boundary line and the right boundary line respectively to obtain the endpoint coordinates on both sides of each row of wind turbines; Step 4.3, according to the design variable set , each row of wind turbines determined by the endpoints on both sides of each row of wind turbines is equally divided to obtain the specific position of the wind turbines.

7. The offshore wind farm rule layout design method based on a double-layer design strategy as claimed in claim 2, characterized in that: When judging whether the wind turbine location is located in the feasible region in step 4, if there is no restricted area in the planned area, whether the wind turbine location is located in the feasible region is determined by judging the relative position relationship between the wind turbine location and the planned area; When there is a restricted area where wind turbines cannot be arranged in the planning area, it is also necessary to determine the relative position relationship between each wind turbine point and the restricted area, and then determine the number of wind turbines that fall within the feasible region. The judgment method is: According to the coordinates of each boundary point of the restricted area, the area of ​​the restricted area is calculated using the vector outer product; According to the wind turbine location to be determined The coordinates of the wind turbine points are calculated by using the vector outer product. The sum of the areas of all triangles formed by two adjacent vertices in the restricted area as triangle vertices; If the sum of the areas is equal to the restricted area, and the areas of all triangles are greater than 0, the wind turbine location Located in the restricted area; otherwise, the wind turbine location is outside the restricted area; By determining the relative position relationship between each wind turbine point and the restricted area one by one, the number of wind turbines within the feasible region can be determined. If the number is the same as the number of wind turbines required in step 1, proceed to the next step; otherwise, proceed directly to step 6.

8. The offshore wind farm rule layout design method based on a double-layer design strategy as claimed in claim 2, characterized in that: In step 8, the population is updated according to the individual fitness by the following method: individuals with larger fitness values ​​are selected as fathers, and after crossover mutation, a new generation of population is formed.

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