Optimization method and system for site selection of offshore converter station

Abstract

The invention relates to an optimization method and system for site selection of an offshore converter station, and the method comprises the following steps: obtaining site selection related data, including coordinates and submarine topography of an offshore wind plant booster station and an onshore converter station access point; judging whether the offshore converter station and the booster station and the offshore converter station and the land converter station are straight lines or not according to the submarine topography; if not, introducing a zigzag coefficient, and calculating the length of a cable from the offshore converter station to the booster station and the length of a cable from the offshore converter station to the access point of the onshore converter station; constructing an offshore converter station site selection optimization problem, including constructing a cost objective function by taking the minimization of the total cost of laying cables of the offshore converter station as an objective, and constructing constraint conditions by taking the non-cross constraint and the boundary constraint as constraints; and solving the offshore converter station site selection optimization problem by using a particle swarm algorithm to obtain the optimal offshore converter station site selection.

Description

Technical Field

[0001] The present application relates to the technical field of offshore wind power generation, and mainly to an optimization method and system for selecting a site for an offshore converter station. Background Art

[0002] With the development of large-scale deep-sea offshore wind power generation, the scheme of collecting multiple offshore wind farms through offshore converter stations and then sending them out through DC lines, and then converting them into AC power and incorporating them into the large power grid at onshore converter stations has been widely used. The site selection of offshore converter stations has become a key factor affecting engineering plans and costs. Multiple offshore wind farms each have booster stations, and offshore converter stations need to be set up near these booster stations. The cable path from the converter station to each booster station must be the shortest and non-crossing. At the same time, the converter station should be close to the land side to shorten the length of the DC cable to the land.

[0003] At present, the site selection of offshore converter stations not only needs to consider the offshore factors, but also needs to be coordinated with the onshore power grid. However, the existing site selection schemes often focus too much on the length of the DC cable from the offshore converter station to the land, while ignoring the location of the access point of the onshore power grid, the grid capacity, and the stability of power transmission. This may lead to compatibility problems when offshore wind power is connected to the onshore power grid, affecting the stable transmission of electricity; at the same time, the existing site selection method often fails to fully consider the geographical environment factors, resulting in the need to change the cable path during the actual construction process, adding additional costs and construction difficulties.

[0004] For example, a Chinese invention patent with publication number "CN114693094A" discloses a "Converter Station Planning Method, Device, Electronic Equipment and Storage Medium", which specifically discloses "obtaining basic data of the power grid; the power grid includes converter stations; based on the basic data, determining a converter station planning set; the converter station planning set includes: multiple converter station planning schemes; the converter station planning scheme enables the power grid to meet preset operating constraints; determining the power outage loss corresponding to the converter station planning scheme under preset disaster conditions; selecting the converter station planning scheme with the smallest power outage loss from the converter station planning set as the target converter station planning scheme", but this method relies on static data for the generation of the converter station planning set, does not involve a dynamic adjustment mechanism, and cannot adapt to new demands after power grid expansion or environmental changes; in addition, the method does not specify the specific generation method of the converter station planning set, resulting in low efficiency or strong subjectivity in scheme screening, and cannot deeply explore the optimal offshore converter station site selection. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present application provides a method and system for optimizing the site selection of an offshore converter station.

[0006] The technical solution of this application is as follows:

[0007] On the one hand, the present invention proposes an optimization method for the location selection of an offshore converter station. The method includes:

[0008] Obtain location selection-related data, including the coordinates of the offshore wind farm booster station, the onshore converter station access point, and the seabed topography; judge whether it is a straight line between the offshore converter station and the booster station, and between the offshore converter station and the onshore converter station according to the seabed topography; if it is not a straight line, introduce a tortuosity coefficient, and calculate the cable length from the offshore converter station to the booster station and the cable length from the offshore converter station to the onshore converter station access point;

[0009] Construct an optimization problem for the location selection of the offshore converter station, including constructing a cost objective function with the minimization of the total cable laying cost of the offshore converter station as the goal, and constructing constraint conditions with non-crossing constraints and boundary constraints;

[0010] Use the particle swarm optimization algorithm to solve the optimization problem for the location selection of the offshore converter station to obtain the optimal location of the offshore converter station.

[0011] Preferably, the method further includes data cleaning of the location selection-related data, and the data cleaning includes processing missing values, outliers, and data format standardization.

[0012] Preferably, the cable length from the offshore converter station to the booster station is calculated, and is expressed by the formula If it is a straight line between the offshore converter station and the booster station, then α i = 1, where L i represents the cable length from the offshore converter station to the i-th booster station, α i represents the first tortuosity coefficient of the i-th booster station, (x, y) represents the coordinates of the offshore converter station, (x i , y i ) represents the coordinates of the i-th booster station, n represents the number of booster stations, and i represents the index value of the i-th booster station;

[0013] The cable length from the offshore converter station to the onshore converter station access point is calculated, and is expressed by the formula If it is a straight line between the offshore converter station and the onshore converter station, then α0 = 1, where L0 represents the cable length from the offshore converter station to the onshore converter station access point, α0 represents the second tortuosity coefficient, and (x0, y0) represents the coordinates of the onshore converter station access point.

[0014] Preferably, the cost objective function is constructed, and is expressed by the formula:

[0015]

[0016] In the formula, C represents the cost objective function; k0 represents the cable laying cost coefficient of the offshore converter station onshore converter station access point; k iIt represents the cable laying cost coefficient from the offshore converter station to the i-th step-up substation.

[0017] Preferably, the non-crossing constraint is specifically defined based on the vector cross product method and is expressed by the formula:

[0018] D1 = (x1 - x)(y2 - y1) - (y1 - y)(x2 - x1);

[0019] D2 = (x1 - x)(y0 - y) - (y1 - y)(x0 - x);

[0020] D3 = (x0 - x2)(y - y2) - (y0 - y2)(x - x2);

[0021] D4 = (x0 - x2)(y1 - y2) - (y0 - y2)(x1 - x2);

[0022] In the formula, D1 represents the result of the first vector cross product; D2 represents the result of the second vector cross product; D3 represents the result of the third vector cross product; D4 represents the result of the fourth vector cross product; (x1, y1) represents the coordinates of the preset first step-up substation; (x2, y2) represents the coordinates of the preset second step-up substation;

[0023] If D1 × D2 ≥ 0 and D3 × D4 < 0, then the current offshore converter station location is eliminated; otherwise, the current offshore converter station location is retained;

[0024] The boundary constraint is expressed by the formula:

[0025] f(x, y) ≤ 0;

[0026] In the formula, f() represents the boundary equation.

[0027] Preferably, the particle swarm optimization algorithm is used to solve the problem of optimizing the location of the offshore converter station. The particle swarm optimization algorithm includes an initialization stage, an update stage, and a fitness calculation stage, specifically:

[0028] The initialization stage is specifically to initialize the candidate set of the offshore converter station location points and the optimal position of each offshore converter station location point; the candidate set of the offshore converter station location points is expressed as where (x j , y j ) represents the coordinates of the j-th offshore converter station location point, m represents the number of offshore converter station location points, and j represents the index value of the j-th offshore converter station location point; the optimal position of each offshore converter station location point is expressed as where represents the optimal position of the j-th offshore converter station location point; represents the position of the j-th offshore converter station location point;

[0029] The update stage specifically updates the positions of the siting points of each offshore converter station, which can be expressed by the formula:

[0030]

[0031] In the formula, represents the velocity of the j-th siting point of the offshore converter station at the (t + 1)-th iteration; ω represents the preset inertial weight; c1 represents the preset first learning factor; c2 represents the preset second learning factor; r1 represents the first random number; r2 represents the second random number; represents the optimal position of the candidate set of the siting points of the offshore converter station at the t-th iteration; t represents the index value of the t-th iteration;

[0032] The fitness calculation stage specifically calculates the corresponding fitness according to the positions of the siting points of each offshore converter station; if the fitness of the current siting point of the offshore converter station is less than the fitness of the optimal position of the current siting point of the offshore converter station, then update the optimal position of the current siting point of the offshore converter station to the position of the current siting point of the offshore converter station; further, if the fitness of the updated position of the siting point of the offshore converter station is less than the fitness of the optimal position of the candidate set of the siting points of the offshore converter station, then update the optimal position of the candidate set of the siting points of the offshore converter station to the position of the current updated siting point of the offshore converter station;

[0033] Iteratively optimize the process until the maximum number of iterations is reached or the fitness of the optimal position of the candidate set of the siting points of the offshore converter station converges, so as to obtain the optimal siting of the offshore converter station.

[0034] Preferably, the method further includes detecting the change of the siting of the offshore converter station, specifically arranging monitoring devices in the siting area and the surrounding area of the siting of the offshore converter station; using the monitoring devices to obtain siting data in real time, and evaluating the degree of change of the seabed environment based on the data analysis algorithm to obtain an evaluation result;

[0035] Judge the influence of the degree of change of the seabed environment on the siting of the offshore converter station according to the evaluation result. If the influence program exceeds the set threshold, adjust the siting of the offshore converter station.

[0036] On the other hand, the present invention also proposes an optimization system for the siting of an offshore converter station. The system includes a data acquisition module, a cable length calculation module, an optimization problem construction module, a solution module, and a result output module, wherein:

[0037] The cable length calculation module is used to judge whether it is a straight line between the offshore converter station and the booster station, and between the offshore converter station and the onshore converter station according to the seabed topography; if it is not a straight line, introduce a tortuosity coefficient, and calculate the cable length from the offshore converter station to the booster station and the cable length from the offshore converter station to the access point of the onshore converter station;

[0038] The optimization problem construction module is used to construct the optimization problem of the offshore converter station site selection, including constructing a cost objective function with the minimization of the total cost of laying cables for the offshore converter station as the goal, and constructing constraint conditions with non-crossing constraints and boundary constraints as the constraints;

[0039] The solving module is used to solve the optimization problem of the offshore converter station site selection by using the particle swarm algorithm to obtain the optimal offshore converter station site selection;

[0040] The result output module is used to display the optimal offshore converter station site selection.

[0041] On the other hand, the present invention also proposes an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements an optimization method for the site selection of an offshore converter station as described in any embodiment of the present invention.

[0042] On the other hand, the present invention also proposes a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements an optimization method for the site selection of an offshore converter station as described in any embodiment of the present invention.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] 1) The present invention provides an optimization method and system for the site selection of an offshore converter station, obtains site selection-related data including the coordinates of the offshore wind farm booster station, the onshore converter station access point, and the seabed topography, etc., improves the scientificity and rationality of the site selection; and judges whether it is a straight line between the offshore converter station and the booster station, and between the offshore converter station and the onshore converter station according to the seabed topography, enhances the accurate calculation ability of the actual cable laying length, and enhances the adaptability of the scheme to different geographical environments;

[0045] 2) The present invention provides an optimization method and system for the site selection of an offshore converter station, constructs a cost objective function with the minimization of the total cost of laying cables for the offshore converter station as the goal, and an optimization problem for the site selection of an offshore converter station including constraint conditions such as non-crossing constraints and boundary constraints, enhances the processing ability of various complex situations and constraint conditions in the site selection process, and improves the accuracy of the site selection;

[0046] 3) The present invention provides an optimization method and system for the site selection of an offshore converter station, uses the particle swarm algorithm to solve the optimization problem of the offshore converter station site selection, improves the calculation efficiency of the entire site selection optimization process, enhances the ability to find the global optimal site selection scheme, and improves the quality and efficiency of the site selection scheme. Description of the Drawings

[0047] Figure 1It is the flowchart of the method of the embodiment of the present invention. Detailed implementation manners

[0048] The following describes the detailed implementation manners of the present invention to facilitate those skilled in the art to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the detailed implementation manners. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0049] The present invention provides the following technical solutions: an optimization method and system for the location selection of an offshore converter station.

[0050] Embodiment 1

[0051] Specifically refer to Figure 1 , this embodiment provides an optimization method for the location selection of an offshore converter station, and the specific steps include:

[0052] S1. Obtain the data related to the location selection, including the coordinates of the offshore wind farm booster station, the onshore converter station access point, and the seabed topography;

[0053] The method further includes data cleaning of the data related to the location selection, and the data cleaning includes processing missing values, outliers, and unifying the data format;

[0054] S2. Judge whether it is a straight line between the offshore converter station and the booster station, and between the offshore converter station and the onshore converter station according to the seabed topography; if it is not a straight line, introduce a tortuosity coefficient, and calculate the cable length from the offshore converter station to the booster station and the cable length from the offshore converter station to the onshore converter station access point;

[0055] S21. Calculate the cable length from the offshore converter station to the booster station, which is expressed by the formula If it is a straight line between the offshore converter station and the booster station, then α i = 1, where L i represents the cable length from the offshore converter station to the i-th booster station, α i represents the first tortuosity coefficient of the i-th booster station, (x, y) represents the coordinates of the offshore converter station, (x i , y i ) represents the coordinates of the i-th booster station, n represents the number of booster stations, and i represents the index value of the i-th booster station;

[0056] S22. Calculate the cable length from the offshore converter station to the onshore converter station access point, which is expressed by the formula If the distance between the offshore converter station and the onshore converter station is a straight line, then α0 = 1, where L0 represents the cable length from the offshore converter station to the access point of the onshore converter station, α0 represents the second tortuosity coefficient, and (x0, y0) represents the coordinates of the access point of the onshore converter station.

[0057] S3. Construct the optimization problem for the location of the offshore converter station, including constructing a cost objective function with the goal of minimizing the total cost of laying cables for the offshore converter station, and constructing constraint conditions with non-crossing constraints and boundary constraints.

[0058] S31. Construct the cost objective function, which is expressed by the formula:

[0059]

[0060] In the formula, C represents the cost objective function; k0 represents the cable laying cost coefficient for the access point of the offshore converter station to the onshore converter station; k i represents the cable laying cost coefficient from the offshore converter station to the i-th booster station.

[0061] S32. The non-crossing constraint is specifically defined based on the vector cross product method and is expressed by the formula:

[0062] D1 = (x1 - x)(y2 - y1) - (y1 - y)(x2 - x1);

[0063] D2 = (x1 - x)(y0 - y) - (y1 - y)(x0 - x);

[0064] D3 = (x0 - x2)(y - y2) - (y0 - y2)(x - x2);

[0065] D4 = (x0 - x2)(y1 - y2) - (y0 - y2)(x1 - x2);

[0066] In the formula, D1 represents the result of the first vector cross product; D2 represents the result of the second vector cross product; D3 represents the result of the third vector cross product; D4 represents the result of the fourth vector cross product; (x1, y1) represents the coordinates of the preset first booster station; (x2, y2) represents the coordinates of the preset second booster station.

[0067] If D1 × D2 ≥ 0 and D3 × D4 < 0, then reject the current location of the offshore converter station; otherwise, retain the current location of the offshore converter station.

[0068] S33. The boundary constraint is expressed by the formula:

[0069] f(x, y) ≤ 0;

[0070] In the formula, f() represents the boundary equation.

[0071] S4. Solve the problem of optimizing the location of the offshore converter station using the particle swarm optimization algorithm. The particle swarm optimization algorithm includes an initialization stage, an update stage, and a fitness calculation stage, specifically as follows:

[0072] S41. The initialization stage is specifically to initialize the candidate set of offshore converter station location points and the optimal position of each offshore converter station location point. The candidate set of offshore converter station location points is expressed as j = 1,..., m, where (x j , y j ) represents the coordinates of the j-th offshore converter station location point, m represents the number of offshore converter station location points, and j represents the index value of the j-th offshore converter station location point. The optimal position of each offshore converter station location point is expressed as where represents the optimal position of the j-th offshore converter station location point; represents the position of the j-th offshore converter station location point;

[0073] S42. The update stage is specifically to update the position of each offshore converter station location point, which is expressed by the formula:

[0074]

[0075] In the formula, represents the velocity of the j-th offshore converter station location point at the (t + 1)-th iteration; ω represents the preset inertia weight; c1 represents the preset first learning factor; c2 represents the preset second learning factor; r1 represents the first random number; r2 represents the second random number; represents the optimal position of the candidate set of offshore converter station location points at the t-th iteration; t represents the index value of the t-th iteration;

[0076] S43. The fitness calculation stage is specifically to calculate the corresponding fitness according to the position of each offshore converter station location point. If the fitness of the current offshore converter station location point is less than the fitness of the optimal position of the current offshore converter station location point, then update the optimal position of the current offshore converter station location point to the position of the current offshore converter station location point. Further, if the fitness of the updated position of the offshore converter station location point is less than the fitness of the optimal position of the candidate set of offshore converter station location points, then update the optimal position of the candidate set of offshore converter station location points to the position of the currently updated offshore converter station location point;

[0077] S5. Iteratively optimize the process until the maximum number of iterations is reached or the fitness of the optimal position of the candidate set of offshore converter station location points converges, and obtain the optimal location of the offshore converter station;

[0078] S6. The method further includes detecting changes in the location selection of the offshore converter station, specifically by arranging monitoring devices in the location selection area and its surrounding area of the offshore converter station; using the monitoring devices to obtain location selection data in real time, evaluating the degree of change in the seabed environment based on a data analysis algorithm to obtain an evaluation result;

[0079] Judging the influence of the degree of change in the seabed environment on the location selection of the offshore converter station according to the evaluation result. If the influence program exceeds the set threshold, adjust the location selection of the offshore converter station.

[0080] Embodiment 2

[0081] This embodiment provides an optimization system for the location selection of an offshore converter station. The system includes a data acquisition module, a cable length calculation module, an optimization problem construction module, a solution module, and a result output module, where:

[0082] The data acquisition module is used to acquire location selection-related data, including the coordinates of the offshore wind farm booster station, the onshore converter station access point, and the seabed topography; and transmit the location selection-related data to the cable length calculation module;

[0083] The cable length calculation module is used to judge whether it is a straight line between the offshore converter station and the booster station, and between the offshore converter station and the onshore converter station access point according to the seabed topography; if it is not a straight line, introduce a tortuosity coefficient and calculate the cable length from the offshore converter station to the booster station and the cable length from the offshore converter station to the onshore converter station access point;

[0084] The optimization problem construction module is used to construct an optimization problem for the location selection of the offshore converter station, including constructing a cost objective function with the minimum total cost of laying cables for the offshore converter station as the goal, and constructing constraint conditions with non-crossing constraints and boundary constraints;

[0085] The solution module is used to solve the optimization problem for the location selection of the offshore converter station by using a particle swarm algorithm to obtain the optimal location selection of the offshore converter station;

[0086] The result output module is used to display the optimal location selection of the offshore converter station.

[0087] Embodiment 3

[0088] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements an optimization method for the location selection of an offshore converter station as described in any embodiment of the present invention.

[0089] Embodiment 4

[0090] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements an optimization method for the location selection of an offshore converter station as described in any embodiment of the present invention.

[0091] It should be noted that the systems, electronic devices, and computer-readable storage media described in the present invention are all based on the same principle as the method described in Embodiment 1, and will not be elaborated herein.

[0092] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. An optimization method for the location selection of an offshore converter station, characterized in that, The method includes: Obtaining site selection related data, including the coordinates of the offshore wind farm booster station and the onshore converter station access point, and the seabed topography; judging whether it is a straight line between the offshore converter station and the booster station, and between the offshore converter station and the onshore converter station according to the seabed topography; if it is not a straight line, introducing a tortuosity coefficient, and calculating the cable length from the offshore converter station to the booster station and the cable length from the offshore converter station to the onshore converter station access point; Constructing an offshore converter station site selection optimization problem, including constructing a cost objective function with the minimization of the total cable laying cost of the offshore converter station as the goal, and constructing constraint conditions with non-crossing constraints and boundary constraints; Using the particle swarm optimization algorithm to solve the offshore converter station site selection optimization problem to obtain the optimal offshore converter station site selection.

2. The optimization method for the location selection of an offshore converter station according to claim 1, characterized in that The method further includes data cleaning of the site selection related data, and the data cleaning includes processing missing values, outliers, and data format standardization.

3. The optimization method for the location selection of an offshore converter station according to claim 1, characterized in that Calculate the cable length from the offshore converter station to the step-up substation, which is expressed by the formula α i ≥ 1, i = 1, ..., n. If it is a straight line between the offshore converter station and the step-up substation, then α i = 1, where L i represents the cable length from the offshore converter station to the i-th step-up substation, α i represents the first bending coefficient of the i-th step-up substation, (x, y) represents the coordinates of the offshore converter station, (x i , y i ) represents the coordinates of the i-th step-up substation, n represents the number of step-up substations, and i represents the index value of the i-th step-up substation; Calculate the cable length from the offshore converter station to the onshore converter station access point, which is expressed by the formula as α0 ≥ 1; if it is a straight line between the offshore converter station and the onshore converter station, then α0 = 1, where L0 represents the cable length from the offshore converter station to the onshore converter station access point, α0 represents the second tortuosity coefficient, and (x0, y0) represents the coordinates of the onshore converter station access point.

4. The optimization method for the site selection of an offshore converter station according to claim 1, characterized in that, Constructing a cost objective function, which is expressed by the formula: In the formula, C represents the cost objective function; k0 represents the cable laying cost coefficient at the connection point of the onshore converter station of the offshore converter station; k i represents the cable laying cost coefficient from the offshore converter station to the i-th booster station.

5. The optimization method for the location selection of an offshore converter station according to claim 1, characterized in that The non-crossing constraint is specifically defined based on the vector cross product method, and is expressed by the formula: D1 = (x1 - x)(y2 - y1) - (y1 - y)(x2 - x1); D2 = (x1 - x)(y0 - y) - (y1 - y)(x0 - x); D3 = (x0 - x2)(y - y2) - (y0 - y2)(x - x2); D4 = (x0 - x2)(y1 - y2) - (y0 - y2)(x1 - x2); In the formula, D1 represents the result of the first vector cross product; D2 represents the result of the second vector cross product; D3 represents the result of the third vector cross product; D4 represents the result of the fourth vector cross product; (x1, y1) represents the preset coordinates of the first booster station; (x2, y2) represents the preset coordinates of the second booster station; If D1 × D2 ≥ 0 and D3 × D4 < 0, then eliminate the current offshore converter station site selection; otherwise, retain the current offshore converter station site selection; The boundary constraint is expressed by the formula: f(x, y) ≤ 0; In the formula, f() represents the boundary equation.

6. The optimization method for the location selection of an offshore converter station according to claim 1, wherein Using the particle swarm optimization algorithm to solve the offshore converter station site selection optimization problem, the particle swarm optimization algorithm includes an initialization stage, an update stage, and a fitness calculation stage, specifically: The specific initialization stage is to initialize the candidate set of the offshore converter station location points and the optimal location of each offshore converter station location point; the candidate set of the offshore converter station location points is expressed as where (x j , y j ) represents the coordinates of the j-th offshore converter station location point, m represents the number of offshore converter station location points, and j represents the index value of the j-th offshore converter station location point; the optimal location of each offshore converter station location point is expressed as where represents the optimal location of the j-th offshore converter station location point; represents the location of the j-th offshore converter station location point; The update stage is specifically to update the position of each offshore converter station site selection point, which is expressed by the formula: In the formula, represents the velocity of the j-th offshore converter station siting point at the (t + 1)-th iteration; ω represents the preset inertial weight; c1 represents the preset first learning factor; c2 represents the preset second learning factor; r1 represents the first random number; r2 represents the second random number; represents the optimal position of the candidate set of offshore converter station siting points at the t-th iteration; t represents the index value of the t-th iteration; The fitness calculation stage is specifically to calculate the corresponding fitness according to the position of each offshore converter station site selection point; if the fitness of the current offshore converter station site selection point is less than the fitness of the optimal position of the current offshore converter station site selection point, then update the optimal position of the current offshore converter station site selection point to the position of the current offshore converter station site selection point; further, if the fitness of the updated position of the offshore converter station site selection point is less than the fitness of the optimal position of the offshore converter station site selection point candidate set, then update the optimal position of the offshore converter station site selection point candidate set to the position of the current updated offshore converter station site selection point; Iteratively optimize the process until the maximum number of iterations is reached or the fitness of the optimal position of the offshore converter station site selection point candidate set converges to obtain the optimal offshore converter station site selection.

7. An optimization method for the site selection of an offshore converter station according to claim 1, characterized in that The method further includes detecting changes in the location selection of the offshore converter station, specifically by arranging monitoring devices in the location selection area and its surrounding area of the offshore converter station; using the monitoring devices to obtain location selection data in real time, and evaluating the degree of change in the seabed environment based on a data analysis algorithm to obtain an evaluation result; Judging the influence of the degree of change in the seabed environment on the location selection of the offshore converter station according to the evaluation result. If the influence program exceeds the set threshold, adjust the location selection of the offshore converter station.

8. An optimization system for the location selection of an offshore converter station, characterized in that, The system includes a data acquisition module, a cable length calculation module, an optimization problem construction module, a solution module, and a result output module, where: The data acquisition module is used to acquire location selection related data, including the coordinates of the offshore wind farm booster station, the onshore converter station access point, and the seabed topography; and transmit the location selection related data to the cable length calculation module; The cable length calculation module is used to judge whether it is a straight line between the offshore converter station and the booster station, and between the offshore converter station and the onshore converter station according to the seabed topography; if it is not a straight line, introduce a tortuosity coefficient to calculate the cable length from the offshore converter station to the booster station and the cable length from the offshore converter station to the onshore converter station access point; The optimization problem construction module is used to construct an offshore converter station location selection optimization problem, including constructing a cost objective function with the minimum total cost of laying cables for the offshore converter station as the goal, and constructing constraint conditions with non-crossing constraints and boundary constraints; The solution module is used to solve the offshore converter station location selection optimization problem by using the particle swarm algorithm to obtain the optimal location selection of the offshore converter station; The result output module is used to display the optimal location selection of the offshore converter station.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements an optimization method for the location selection of an offshore converter station as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements an optimization method for the location selection of an offshore converter station as described in any one of claims 1 to 7.

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