Single seaborne booster station position local optimization method based on force-oriented iterative algorithm

Abstract

The invention provides a single offshore booster station position local optimization method based on a force-directed iterative algorithm, and the method comprises the steps: determining an optimization region of the position of an offshore booster station in a central region of an offshore wind power plant by employing a geometric mapping method, and forming a central region Sc by taking m fans closest to the central point of the wind power plant as vertexes; determining the position of an alternative booster station in the optimization area by adopting a force steering algorithm; selecting an alternative point with the optimal economical efficiency as the final position of the offshore booster station by comparing the topological cost of the submarine cable of the current collection system generated by each alternative booster station; specific case analysis proves that the method is effective. Compared with manual site selection, the method has the advantages that site selection accuracy is improved, personal errors are reduced, submarine cable usage amount and power transmission loss are remarkably reduced due to reasonable booster station position setting, overall construction cost is reduced, and economic benefits of an offshore wind plant are improved.

Description

Technical Field

[0001] The present invention relates to the field of offshore wind farm planning and construction, and in particular to a local optimization method for uniformly selecting candidate locations of booster stations using a force-directed iterative algorithm and obtaining an offshore booster station location with the best economic efficiency. Background Art

[0002] As the global demand for clean energy continues to grow, offshore wind power, as a form of renewable energy with great potential, is receiving more and more attention. The construction scale of offshore wind farms continues to expand, and the technical level continues to improve, but at the same time it also faces many challenges, such as high construction costs, difficult operation and maintenance, and environmental impact. The offshore booster station is an important part of the offshore wind farm, responsible for boosting the low-voltage electricity generated by the wind farm to high-voltage electricity suitable for long-distance transmission. The choice of its location has an important impact on the operating efficiency, construction cost, difficulty of operation and maintenance, and environmental impact of the wind farm.

[0003] Traditional methods for selecting sites for offshore substations often rely on manual experience and simple calculations, which makes it difficult to fully consider various complex factors, such as construction costs and seabed topography. This method is not only inefficient, but also easily leads to inaccurate and unreasonable site selection results. In order to overcome the limitations of traditional site selection methods and improve the accuracy and efficiency of offshore substation site selection, automatic optimization technology has been introduced into this field. This technology automatically searches for the optimal location of the substation by constructing mathematical models and optimization algorithms, comprehensively considering multiple influencing factors. Summary of the invention

[0004] In view of the above shortcomings, the present invention proposes a local optimization method for the location of a single offshore substation based on a force-directed iterative algorithm. This method uses a geometric drawing method and a force-directed iterative algorithm to determine the optimization area and alternative booster station locations for the offshore substation location, compares the costs of the topological solutions generated by each alternative booster station, and automatically selects the final offshore booster station location with the goal of optimal economy. The present invention not only greatly improves the accuracy of site selection and reduces the interference and errors of human factors, but also effectively reduces the use of submarine cables by optimizing the layout, thereby reducing the overall construction cost. At the same time, the reasonable setting of the booster station location significantly reduces the loss during power transmission and improves the operating efficiency of offshore wind farms.

[0005] A method for local optimization of a single offshore booster station location based on a force-directed iterative algorithm of the present invention comprises the following steps:

[0006] (1) Determine the optimal location of the offshore substation. In the central area of ​​the offshore wind farm, the geometric mapping method is used to obtain the optimal location of the offshore substation. The irregular closed area S is formed with the m wind turbines closest to the center of the offshore wind farm as the vertex.c , as the central area;

[0007] (2) Determine the location of the candidate offshore booster station. Use a force-directed iterative algorithm to determine the location of the candidate offshore booster station within the optimization area, including node initialization, force calculation, node position update, and iterative process;

[0008] (3) Determine the most economical solution by comparing the cost of the submarine cable topology structure of the power collection system generated by each candidate offshore substation, and select the candidate with better economic efficiency as the final location of the offshore substation.

[0009] In the step (1), a geometric mapping method is used to determine the optimal area for the location of the offshore booster station.

[0010] Assume that there are n wind turbines in the boundary area of ​​the offshore wind farm, and the coordinates of each wind turbine are (x1, y1), (x2, y2), ..., (x n ,y n ), the coordinates of its center point C(x c ,y c ) is calculated by the following formula:

[0011]

[0012] The distance from the center point of the offshore wind farm is C(x c ,y c ) The nearest m wind turbines are taken as vertices and connected in a clockwise direction to form an irregular closed area S c , as the central area of ​​the offshore wind farm.

[0013] Assume that the land booster station is B, connect the center point C (x c ,y c ), and get line segment BC. With the minimum distance between the offshore booster station and the wind turbine at 500 meters, draw a parallel line on both sides of line segment BC. The strip area enclosed by the two parallel lines is the same as the central area S c Intersect and obtain sub-area S1.

[0014] At the center point C(x c ,y c ) and intersect the parallel lines on both sides of BC, then area S1 is divided into two parts. The part in the direction is used as the final offshore booster station location optimization area S.

[0015] In the step (2), a force-directed iterative algorithm is used to determine the location of the candidate offshore booster station within the optimization area, including node initialization, force calculation, node location update and iterative process.

[0016] 1) Node initialization

[0017] In the algorithm, each candidate booster station location is abstracted as a node, and each node is regarded as a particle with mass and charge.

[0018] In the offshore booster station location optimization area S determined in step (1), the initial positions of r candidate nodes are randomly generated. Wherein, if the optimization area S is a concave polygon, the candidate nodes are randomly generated inside its circumscribed rectangle.

[0019] 2) Calculation of force

[0020] According to the rectangular coordinates of each candidate node, traverse each pair of candidate nodes and calculate the distance d between each pair of nodes uv :

[0021]

[0022] Where: (x u ,y u ) and (x v ,y v ) represents each pair of candidate node coordinates.

[0023] According to the rectangular coordinates of each candidate node, the candidate node P(x p ,y p ) and the distance from the center point of the offshore wind farm C(x c ,y c ) The distance d to the nearest m wind turbines pw , where the m wind turbines are numbered 1, 2, ..., m, then w = 1, 2, ..., m.

[0024]

[0025] Where: (x w ,y w ) represents the coordinates of the wind turbine numbered w among the m wind turbines.

[0026] According to the boundary coordinates of the optimization area S, calculate the candidate node P(x p ,y p ) to the distance d from the i-th edge of the boundary bi :

[0027]

[0028] Where: (x i1 ,y i1 ) and (x i2 ,y i2 ) represents the two endpoints of the i-th edge of the boundary of the optimization area S.

[0029] The repulsive force between each pair of alternative nodes is called the "internal force". When 0 ≤ d uv < a, each pair of nodes exerts F 内部 on each other, causing each pair of nodes to move away from each other.

[0030]

[0031] In the formula: a, k a are constants.

[0032] The default minimum distance between the offshore booster station and the wind turbine is 500 meters. When 0 ≤ d pw < 500, the vertexes of the boundary of the optimization region S exert a repulsive force towards the inside of the optimization region S on the alternative nodes, which is called the "vertex force".

[0033]

[0034] In the formula: k b is a constant.

[0035] For nodes close to or located on the boundary of the optimization region S, that is, when 0 ≤ d bi < c, a boundary repulsive force or boundary attractive force is introduced, which is called the "boundary force". The i-th side of the boundary of the optimization region S exerts F p perpendicular to side i towards the inside of the optimization region on the node P(x p ), y 边界i to ensure that the node does not exceed the boundary or maintains a certain distance from the boundary.

[0036] a. When the node is located inside or on the boundary of the optimization region S,

[0037]

[0038] b. When the node is located outside the boundary of the optimization region S,

[0039] F 边界i = k c2 d bi 2

[0040] In the formula: c, k c1 and k c2 are all constants.

[0041] Then the boundary force received by the node is:

[0042]

[0043] When the optimization region S is a concave polygon, the randomly generated initial node positions may be outside the boundary of the optimization region S. Similarly, with the help of boundary forces, such nodes are moved to the inside of the boundary of S.

[0044] 3) Update of node location

[0045] For each node, all internal forces F 内部 , Vertex Force F 顶点 and the boundary force F 边界 The vector sum of

[0046]

[0047] The node position is updated according to the magnitude and direction of the resultant force. At the same time, the new position is checked to see if it meets the boundary conditions to ensure that the new position of the node is within the optimization region S.

[0048] 4) Iteration process

[0049] Repeat the steps of calculating the execution force and updating the node position until the node position reaches the specified number of iterations t. At this point, the r candidate nodes can be evenly distributed inside the optimization area S.

[0050] In the step (3), for the candidate offshore substation locations that can meet the same collection system submarine cable topology constraints, only the submarine cable costs of the difference edges are recalculated without regenerating the complete submarine cable topology.

[0051] The constraints on the submarine cable topology of the offshore wind farm collection system mainly include the maximum current-carrying capacity of the submarine cable, the avoidance of submarine cable crossing, and the number of outgoing lines from the offshore substation. When the wind turbine capacities are the same, the maximum current-carrying capacity of the submarine cable can only consider the maximum number of wind turbines that the submarine cable can carry.

[0052] The r candidate nodes are numbered 1, 2, 3, ..., r respectively. The candidate node 1 is taken as the offshore booster station location. The existing collection system topology optimization algorithm is used to generate a submarine cable topology structure T1 with better economy and satisfying the constraints.

[0053] Traverse all candidate nodes except node 1. For candidate nodes that can meet the same constraints as the cable topology T1 of the power collection system, only the cable cost of each difference edge is recalculated, and there is no need to regenerate the complete cable topology. For candidate nodes i that cannot meet the same constraints as the topology T1, the topology T1 needs to be regenerated. i , where i = 2, 3, 4, ..., r, and calculate the corresponding cost.

[0054] The costs of the submarine cable topology of the power collection system generated by each candidate node are compared, and the candidate point i with the best economic efficiency is selected as the final offshore booster station location.

[0055] Beneficial effects: Compared with manual site selection, the present invention not only greatly improves the accuracy of site selection and reduces the interference and errors caused by human factors, but also effectively reduces the use of submarine cables by optimizing the layout, thereby reducing the overall construction cost. At the same time, the reasonable location of the booster station significantly reduces the loss during power transmission and improves the operating efficiency of the offshore wind farm. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a working diagram of a method for local optimization of a single offshore booster station location based on a force-directed iterative algorithm according to the present invention;

[0057] Figure 2 The central area S of the offshore wind farm determined by the present invention is c ;

[0058] Figure 3 The central area sub-area S1 determined by the present invention;

[0059] Figure 4 The optimal region S for offshore booster stations determined by the present invention;

[0060] Figure 5 The initial candidate node diagram of the offshore booster station randomly selected by the present invention;

[0061] Figure 6 Final offshore booster station candidate node diagram determined by the present invention

[0062] Figure 7 This is the manual layout diagram of the offshore booster station and wind turbines of the H16 wind farm;

[0063] Figure 8 Cost bar chart of topological schemes obtained by artificially arranging offshore booster stations and alternative nodes for H16 wind farm;

[0064] Fig. 9 The topological connection diagram of the collection system generated for the H16 wind farm based on the optimal offshore substation location. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] A local optimization method for the location of a single offshore booster station based on a force-directed iterative algorithm, such as Figure 1 As shown, its specific implementation includes the following steps:

[0067] (1) Determine the optimal location of the offshore substation. In the central area of ​​the offshore wind farm, the geometric mapping method is used to obtain the optimal location of the offshore substation. The irregular closed area S is formed with the m wind turbines closest to the center of the offshore wind farm as the vertex. c , as the central area;

[0068] (2) Determine the location of the candidate offshore booster station. Use a force-directed iterative algorithm to determine the location of the candidate offshore booster station within the optimization area, including node initialization, force calculation, node position update, and iterative process;

[0069] (3) Determine the most economical solution by comparing the cost of the submarine cable topology structure of the collection system generated by each alternative offshore substation and select the alternative point with better economic efficiency as the final location of the offshore substation.

[0070] (4) Perform case analysis and optimization.

[0071] Based on the above steps, the present invention proposes a local optimization method for the location of a single offshore booster station based on a force-directed iterative algorithm.

[0072] The geometric mapping method is used to determine the optimal area for the location of the offshore booster station.

[0073] Assume that there are n wind turbines in the boundary area of ​​the offshore wind farm (the location of the n wind turbines is determined by the wind resources in the offshore wind farm area and determined according to the 2000 National Geodetic Coordinate System). The coordinates of each wind turbine are (x1, y1), (x2, y2), ..., (x n ,y n ), the coordinates of its center point C(x c ,y c ) is calculated by the following formula:

[0074]

[0075] The distance from the center point of the offshore wind farm is C(x c ,y c ) The nearest m wind turbines are taken as vertices and connected in a clockwise direction to form an irregular closed area S c ,like Figure 2 As shown, it serves as the central area of ​​the offshore wind farm.

[0076] Assume that the land booster station is B (the location of n booster stations is determined by the power construction plan of the offshore wind farm and is determined according to the 2000 National Geodetic Coordinate System), connect the center point C (x c ,y c ), get the line segment BC. With the minimum distance between the offshore booster station and the wind turbine as 500 meters, (here it refers to the straight-line distance of 500 meters. The safe distance between the offshore booster station and the wind turbine is generally not less than 500 meters. In order to reduce the impact of electromagnetic interference and noise on the operation of the wind turbine, ensure that the equipment of the wind turbine and the booster station can work normally. At the same time, it provides sufficient safety buffer space for maintenance personnel, which is helpful for fault inspection and maintenance. In addition, the laying requirements of submarine cables are also considered to ensure the operability of construction and the stability of power transmission. Finally, in order to reduce the mutual interference between the wind turbine and the booster station in the environment and structure, and adapt to the complex environmental conditions of the offshore wind farm), draw a parallel line on both sides of the line segment BC. The strip area enclosed by the two parallel lines and the central area S c Intersect, such as Figure 3 As shown, a sub-region S1 is obtained.

[0077] At the center point C(x c ,y c ) and intersect the parallel lines on both sides of BC, then area S1 is divided into two parts. The part in the direction is taken as the final offshore booster station location optimization area S, such as Figure 4 shown.

[0078] A force-directed iterative algorithm is used to determine the locations of candidate offshore booster stations within the optimization area, including node initialization, force calculation, node location update and iterative process.

[0079] 1) Node initialization

[0080] In the algorithm, each candidate booster station location is abstracted as a node, and each node is regarded as a particle with mass and charge.

[0081] exist Figure 4 In the determined offshore booster station location optimization area S, the initial positions of r candidate nodes are randomly generated, such as Figure 5 As shown in FIG. 1 , when the optimization area S is a concave polygon, a method of randomly generating candidate nodes inside its circumscribed rectangle is adopted.

[0082] 2) Calculation of force

[0083] According to the rectangular coordinates of each candidate node, traverse each pair of candidate nodes and calculate the distance d between each pair of nodes uv :

[0084]

[0085] Where: (x u , y u ) and (x v , y v ) represent the coordinates of each pair of alternative nodes.

[0086] According to the rectangular coordinates of each alternative node, calculate the distances d p between the alternative node P(x p , y c ) and the m turbines closest to the center point C(x c , y pw ) of the offshore wind farm. Among them, the numbers of the m turbines are 1, 2,..., m, then w = 1, 2,..., m.

[0087]

[0088] Where: (x w , y w ) represents the coordinates of the turbine numbered w among the m turbines.

[0089] According to the boundary coordinates of the optimization region S, calculate the distance d p from the alternative node P(x p , y bi ) to the i-th side of the boundary:

[0090]

[0091] Where: (x i1 , y i1 ) and (x i2 , y i2 ) represent the two endpoints of the i-th side of the boundary of the optimization region S.

[0092] The repulsive force between each pair of alternative nodes is called the "internal force". When 0 ≤ d uv < a, each pair of nodes exerts F 内部 on each other, causing each pair of nodes to move away from each other.

[0093]

[0094] Where: a, k a are constants.

[0095] By default, the minimum distance between the offshore substation and the turbines is 500 meters. When 0 ≤ d pw < 500, the vertices of the boundary of the optimization region S exert a repulsive force on the alternative nodes towards the inside of the optimization region S, which is called the "vertex force".

[0096]

[0097] where: k b is a constant.

[0098] For nodes close to or located on the boundary of the optimization region S, that is, when 0 ≤ d bi < c, a boundary repulsive force or boundary attractive force, called "boundary force", is introduced. The i-th side of the boundary of the optimization region S exerts a force F p , y p ) perpendicular to side i and towards the interior of the optimization region to ensure that the node does not exceed the boundary or maintains a certain distance from the boundary. 边界i

[0099] a. When the node is located inside or on the boundary of the optimization region S,

[0100]

[0101] b. When the node is located outside the boundary of the optimization region S,

[0102] F 边界i = k c2 d bi 2

[0103] where: c, k c1 and k c2 are all constants.

[0104] Then the boundary force received by the node is:

[0105]

[0106] For the case where the optimization region S is a concave polygon, the randomly generated initial node positions may be located outside the boundary of the optimization region S. Similarly, with the help of the boundary force, such nodes are moved to the interior of the boundary of S.

[0107] 3) Update of node positions

[0108] For each node, the vector sum of all the internal forces F 内部 , vertex forces F 顶点 and boundary forces F 边界 received by it is taken as the resultant force

[0109]

[0110] The position of the node is updated according to the magnitude and direction of the resultant force. At the same time, check whether the new position satisfies the boundary conditions to ensure that the new position of the node is located inside the optimization region S.

[0111] 4) Iteration process ​

[0112] Repeat the steps of calculating the execution force and updating the node position until the node position reaches the specified number of iterations t. At this point, the r candidate nodes can be evenly distributed inside the optimization area S, such as Figure 6 shown.

[0113] For the alternative offshore substation locations that can meet the constraints of the same collection system submarine cable topology, only the submarine cable cost of the difference edge is recalculated without regenerating the complete submarine cable topology.

[0114] The constraints on the submarine cable topology of the offshore wind farm collection system mainly include the maximum current-carrying capacity of the submarine cable, the avoidance of submarine cable crossing, and the number of outgoing lines from the offshore substation. When the wind turbine capacities are the same, the maximum current-carrying capacity of the submarine cable can only consider the maximum number of wind turbines that the submarine cable can carry.

[0115] The r candidate nodes are numbered 1, 2, 3, ..., r respectively. The candidate node 1 is taken as the offshore booster station location. The existing collection system topology optimization algorithm is used to generate a submarine cable topology structure T1 with better economy and satisfying the constraints.

[0116] Traverse all candidate nodes except node 1. For candidate nodes that can meet the same constraints as the cable topology T1 of the power collection system, only the cable cost of each difference edge is recalculated, and there is no need to regenerate the complete cable topology. For candidate nodes i that cannot meet the same constraints as the topology T1, the topology T1 needs to be regenerated. i , where i = 2, 3, 4, ..., r, and calculate the corresponding cost.

[0117] The costs of the submarine cable topology of the power collection system generated by each candidate node are compared, and the candidate point i with the best economic efficiency is selected as the final offshore booster station location.

[0118] A case analysis is carried out, and the relevant parameters of the Dafeng H16 offshore wind farm collector cable are shown in Table 1.

[0119] Table 1 Dafeng H16 wind farm collection cable price and current carrying capacity parameters

[0120]

[0121] right Figure 7 The Dafeng H16 offshore wind farm was used for case testing, and the location of the offshore substation of the Dafeng H16 wind farm was locally optimized. First, the geometric mapping method of the present invention was used to determine the optimal area for the offshore substation of the H16 wind farm. Second, the force-directed iterative algorithm of the present invention was used to determine four candidate nodes for the offshore substation. Subsequently, the comparison was performed. Figure 8The cost of the topological schemes obtained by manually arranging the offshore substation and various alternative nodes was analyzed. It was found that the topological scheme obtained by alternative node 4 had the lowest cost, and it was 192,700 yuan lower than that of manually arranging the nodes.

[0122] Figure 8 It is a cost bar chart of the topological scheme obtained by manually arranging offshore booster stations and various alternative nodes.

[0123] Fig. 9 It is a topological connection diagram of the power collection system generated based on the optimal offshore booster station location in the present invention.

[0124] It can be seen that compared with the traditional offshore booster station site selection method, this invention reduces the interference and error of human factors, effectively reduces the use of submarine cables, and greatly improves the accuracy of site selection and the economy of the collection line layout plan. This method provides a new tool for the planning and construction of offshore wind farms and has broad application prospects.

Claims

1. A method for local optimization of a single offshore booster station location based on a force-directed iterative algorithm, characterized in that: The steps include: (1) Determine the optimal location of the offshore substation: In the central area of ​​the offshore wind farm, the geometric mapping method is used to obtain the optimal location of the offshore substation. The irregular closed area S is formed with the m wind turbines closest to the center of the offshore wind farm as the vertex. c , as the central area; (2) Determine the location of the candidate offshore booster station; use a force-directed iterative algorithm to determine the location of the candidate offshore booster station within the optimization area, including node initialization, force calculation, node position update, and iterative process; (3) Determine the most economical solution; by comparing the costs of the submarine cable topology structure of the collection system generated by each alternative offshore substation, select the alternative point with better economic efficiency as the final location of the offshore substation.

2. The method for local optimization of a single offshore booster station location based on a force-directed iterative algorithm according to claim 1, characterized in that: In the step (1), a geometric mapping method is used to determine the optimal area for the location of the offshore booster station; Assume that there are n wind turbines in the boundary area of ​​the offshore wind farm, and the coordinates of each wind turbine are (x1, y1), (x2, y2), ..., (x n ,y n ), the coordinates of its center point C(x c ,y c ) is calculated by the following formula: The distance from the center point of the offshore wind farm is C(x c ,y c ) The nearest m wind turbines are taken as vertices and connected in a clockwise direction to form an irregular closed area S c , as the central area of ​​the offshore wind farm; Assume that the land booster station is B, connect the center point C (x c ,y c ), get line segment BC; with the minimum distance between the offshore booster station and the wind turbine being 500 meters, draw a parallel line on both sides of line segment BC; the strip area enclosed by the two parallel lines and the central area S c Intersect and obtain sub-area S1. At the center point C(x c ,y c ) and intersect the parallel lines on both sides of BC, then area S1 is divided into two parts. The part in the direction is used as the final offshore booster station location optimization area S.

3. The method for local optimization of a single offshore booster station location based on a force-directed iterative algorithm according to claim 1, characterized in that: In the step (2), a force-directed iterative algorithm is used to determine the location of the candidate offshore booster station within the optimization area, including node initialization, force calculation, node location update and iterative process; 1) Node initialization In the algorithm, each candidate booster station location is abstracted as a node, and each node is regarded as a particle with mass and charge; In the offshore booster station location optimization area S determined in step (1), r initial positions of candidate nodes are randomly generated; wherein, if the optimization area S is a concave polygon, the candidate nodes are randomly generated inside its circumscribed rectangle; 2) Calculation of force According to the rectangular coordinates of each candidate node, traverse each pair of candidate nodes and calculate the distance d between each pair of nodes uv : Where: (x u ,y u ) and (x v ,y v ) represents each pair of candidate node coordinates; According to the rectangular coordinates of each candidate node, the candidate node P(x p ,y p ) and the distance from the center point of the offshore wind farm C(x c ,y c ) The distance d to the nearest m wind turbines pw , where m wind turbines are numbered 1, 2, ..., m, then w = 1, 2, ..., m; Where: (x w ,y w ) represents the coordinates of the wind turbine numbered w among the m wind turbines. According to the boundary coordinates of the optimization area S, calculate the candidate node P(x p ,y p ) to the distance d from the i-th edge of the boundary bi : Where: (x i1 ,y i1 ) and (x i2 ,y i2 ) represents the two endpoints of the i-th edge of the boundary of the optimization area S; The repulsive force between each pair of alternative nodes is called the "internal force"; when 0 ≤ d uv < a, each pair of nodes exerts F 内部 on each other, causing each pair of nodes to move away from each other; Where: a, k a is a constant; The default minimum distance between the offshore booster station and the wind turbine is 500 meters. pw When <500, the vertices on the boundary of the optimization region S exert a repulsive force on the candidate nodes toward the inside of the optimization region S, which is called "vertex force"; Where: k b is a constant. For nodes close to or located on the boundary of the optimization region S, that is, when 0 ≤ d bi <c, a boundary repulsive force or boundary attractive force, called "boundary force", is introduced; the i-th side of the boundary of the optimization region S exerts F p ,y p ) perpendicular to side i towards the interior of the optimization region to ensure that the nodes do not exceed the boundary or maintain a certain distance from the boundary;​​ a. When the node is located inside or at the boundary of the optimization area S, b. When the node is outside the boundary of the optimization area S, Where: c, k c1 and k c2 are all constants; The boundary force on the node is for: When the optimization region S is a concave polygon, the randomly generated initial node position may be outside the boundary of the optimization region S. Similarly, with the help of boundary forces, such nodes are moved to the inside of the boundary of S. 3) Update of node location For each node, all internal forces F 内部 , Vertex Force F 顶点 and the boundary force F 边界 The vector sum of Update the position of the node according to the magnitude and direction of the resultant force; at the same time, check whether the new position meets the boundary conditions to ensure that the new position of the node is within the optimization region S; 4) Iteration process Repeat the steps of calculating the execution force and updating the node position until the node position reaches the specified number of iterations t; at this point, the r candidate nodes can be evenly distributed inside the optimization area S.

4. The method for local optimization of a single offshore booster station location based on a force-directed iterative algorithm according to claim 1, characterized in that: In the step (3), for the candidate offshore substation locations that can meet the constraints of the same collection system submarine cable topology structure, only the submarine cable cost of the difference edge is recalculated, without regenerating the complete submarine cable topology; The constraints on the submarine cable topology of the offshore wind farm collection system mainly include the maximum current-carrying capacity of the submarine cable, the avoidance of submarine cable crossing, and the number of outgoing lines from the offshore substation. When the wind turbine capacities are the same, the maximum current-carrying capacity of the submarine cable can only consider the maximum number of wind turbines that the submarine cable can carry. Define r candidate nodes as 1, 2, 3, ..., r, and take candidate node 1 as the location of the offshore booster station. Use the existing collector system topology optimization algorithm to generate a submarine cable topology structure T1 that is more economical and meets the constraints. Traverse all candidate nodes except node 1. For candidate nodes that can meet the same constraints as the cable topology T1 of the power collection system, only the cable cost of each difference edge is recalculated, and there is no need to regenerate the complete cable topology. For candidate nodes i that cannot meet the same constraints as the topology T1, the topology T1 needs to be regenerated. i , where i = 2, 3, 4, ..., r, and calculate the corresponding cost; The costs of the submarine cable topology of the power collection system generated by each candidate node are compared, and the candidate point i with the best economic efficiency is selected as the final offshore booster station location.

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