Design method and system of offshore wind power collection system

Abstract

The application discloses a design method and system of an offshore wind power power collection system, which is applied to the power system transmission and distribution field and comprises the following steps: obtaining equipment data and fault related data of an offshore wind power cluster and constructing a comprehensive database, then screening and optimizing wind turbine model data from the comprehensive database, and generating an offshore wind turbine string scheme in combination with a submarine cable hierarchical matching strategy; after obtaining an offshore wind turbine string combination scheme from the offshore wind turbine string scheme, screening and subsequent optimization are performed on the offshore wind turbine string combination scheme, dynamic operation data of each offshore wind turbine string optimization scheme in different frequency intervals is further calculated, evaluation results of each offshore wind turbine string optimization scheme are obtained based on at least reliability dimension results and operation dimension results, and finally, the best offshore wind turbine string optimization scheme is determined. The design method of the offshore wind power power collection system can significantly improve the operation reliability of the offshore wind power power collection system and effectively guarantee the stable operation of the system under different working conditions.

Description

Technical Field

[0001] This invention relates to the field of power system transmission and distribution technology, and in particular to a design method and system for an offshore wind power collection system. Background Technology

[0002] As the global energy structure shifts towards cleaner energy, offshore wind power, with its abundant resources, high power generation efficiency, and lack of reliance on land resources, has become an important direction for new energy development, and its development focus is gradually shifting from nearshore wind areas to deep-sea wind areas. As a crucial link connecting wind turbines to the onshore power grid, the design rationality of the offshore wind power collection system directly determines the power generation efficiency, operational reliability, and investment economy of the wind power cluster, making it one of the core technologies in the entire offshore wind power project development.

[0003] Current technologies for designing offshore wind power collection systems focus on economic efficiency, using turbine cost as the sole metric and neglecting the overall operational stability of the system. For example, turbine string topologies designed using this approach may exacerbate grid operational risks when frequency deviations occur in the offshore wind power grid due to load fluctuations and turbine output variations, making it difficult for the collection system to meet the long-term stable power generation requirements of offshore wind power projects. Summary of the Invention

[0004] This invention provides a design method and system for offshore wind power collection systems to solve the technical problem of balancing system reliability and dynamic operating performance under complex operating conditions during the design process of offshore wind power collection systems. It aims to achieve global optimization design of offshore wind power collection systems and provide a highly reliable and frequency-adaptive optimal design scheme for their development.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a design method for an offshore wind power collection system, comprising: Acquire equipment and fault-related data from offshore wind power clusters to construct a comprehensive database; With the objective function of minimizing the equipment failure rate of offshore wind turbines, and based on the comprehensive database, the optimal wind turbine model data is obtained at least according to the preset single-unit capacity constraints of the offshore wind turbines. Based on the preferred wind turbine model data, and in accordance with the submarine cable graded matching strategy, various offshore wind turbine string schemes are generated; Integrate the various offshore wind turbine string schemes and list offshore wind turbine string combination schemes from them; Based on known data from offshore wind farms, the various offshore wind turbine string combination schemes are processed with the capacity of the offshore wind farms as a constraint to obtain an optimized offshore wind turbine string scheme. Calculate the dynamic operating data of each of the aforementioned offshore wind turbine string optimization schemes in the selected frequency range; The evaluation results of each offshore wind turbine string optimization scheme are obtained based at least on the reliability dimension results and the operation dimension results, wherein the operation dimension results are obtained by analyzing the dynamic operation data; Based on the evaluation results, an optimal offshore wind turbine string optimization scheme is determined, wherein the optimal offshore wind turbine string optimization scheme serves as the basis for dynamic regulation of the offshore wind power collection system within the selected frequency range.

[0006] As one preferred embodiment, the objective function is to minimize the equipment failure rate of the offshore wind turbine, and based on the comprehensive database, at least according to preset single-unit capacity constraints of the offshore wind turbine, to obtain preferred wind turbine model data, including: The fault-related data is retrieved from the comprehensive database to obtain the equipment failure rate of the offshore wind turbine; The equipment data is retrieved from the comprehensive database to obtain the single-unit capacity data of the offshore wind turbine; Based on the equipment failure rate and single-unit capacity data of the offshore wind turbines, and according to the objective function and the preset constraints, the preferred wind turbine models are selected.

[0007] As one preferred embodiment, the step of combining the preferred wind turbine model data and generating various offshore wind turbine string schemes according to the submarine cable hierarchical matching strategy includes: The equipment data is extracted from the comprehensive database, and combined with the preferred wind turbine model data, the range of the number of offshore wind turbines in the offshore wind turbine string scheme is determined; For the number of offshore wind turbines, different types of submarine cables are adapted according to the transmission power gradient to obtain the corresponding submarine cable model data. The transmission power gradient is obtained by superimposing the power of the offshore wind turbines in a series structure. By integrating the submarine cable model data and the corresponding preferred wind turbine model data, each offshore wind turbine string scheme is obtained.

[0008] As one preferred embodiment, the process of processing each offshore wind turbine string combination scheme based on known offshore wind farm data, with the capacity of the offshore wind farm as a constraint, to obtain an optimized offshore wind turbine string scheme includes: Based on the data of the offshore wind farm, the constraints of the offshore wind farm are defined, wherein the constraints include at least the capacity of the offshore wind farm. Select the first offshore wind turbine string combination scheme that satisfies the constraints from all the described offshore wind turbine string combination schemes; Based on a greedy algorithm, the submarine cable path of the first offshore wind turbine string combination scheme is optimized to obtain the corresponding optimized offshore wind turbine string scheme.

[0009] As one preferred embodiment, the optimization of the submarine cable path of the first offshore wind turbine string combination scheme based on a greedy algorithm yields a corresponding optimized offshore wind turbine string scheme, including: The coordinate information of the target nodes in the first offshore wind turbine string combination scheme is extracted respectively to obtain the distance matrix corresponding to each of the first offshore wind turbine string combination schemes; Based on the distance matrix, with the shortest total length of the submarine cable path as the optimization objective, the optimal submarine cable path information corresponding to each of the first offshore wind turbine string combination schemes is obtained. The optimal submarine cable path information is integrated into the corresponding first offshore wind turbine string combination scheme to obtain the offshore wind turbine string optimization scheme.

[0010] As one preferred embodiment, the step of calculating the dynamic operating data of each of the offshore wind turbine string optimization schemes within the selected frequency range includes: Extract the equipment data from each of the aforementioned offshore wind turbine string optimization schemes; The device data is divided into intervals according to the preset frequency intervals to obtain frequency interval data; Based on the frequency range data, the dynamic operating data corresponding to each of the offshore wind turbine string optimization schemes is calculated.

[0011] As one preferred embodiment, the step of dividing the device data into intervals according to the preset frequency interval to obtain frequency interval parameters includes: Extract parameters that are strongly correlated with frequency from the device data, determine the parameter range that needs to be divided by frequency, and obtain frequency-sensitive data; Based on the frequency-sensitive data, key frequency data within each preset frequency range are collected; By integrating the key frequency data, the frequency range data is obtained.

[0012] As one preferred embodiment, the evaluation results of each offshore wind turbine string optimization scheme are obtained based at least on reliability and operational dimension results, including: An evaluation model is established based on the reliability dimension results and the operational dimension results. The evaluation model is used to calculate the evaluation index of each offshore wind turbine string optimization scheme in the selected frequency range. By integrating the evaluation indices, the evaluation results corresponding to each of the offshore wind turbine string optimization schemes are obtained.

[0013] As one preferred embodiment, determining the optimal offshore wind turbine string optimization scheme based on the evaluation results includes: For each of the aforementioned offshore wind turbine string optimization schemes, the optimal frequency evaluation index is selected from the evaluation indices of each of the aforementioned frequency ranges. The optimal frequency evaluation indices are sorted in descending order to obtain the ranking results corresponding to each of the offshore wind turbine string optimization schemes, and the optimal offshore wind turbine string optimization scheme is determined.

[0014] Another embodiment of the present invention provides a design system for an offshore wind power collection system, comprising: The module is used to acquire equipment data and fault-related data of offshore wind power clusters and build a comprehensive database; The filtering module is used to obtain preferred wind turbine model data based on the comprehensive database, with the objective function of minimizing the equipment failure rate of offshore wind turbines and at least according to the preset single-unit capacity constraints of the offshore wind turbines. The matching module is used to combine the preferred wind turbine model data and generate various offshore wind turbine string schemes according to the submarine cable graded matching strategy. A combination module is used to integrate the various offshore wind turbine string schemes, and to list offshore wind turbine string combination schemes. The optimization module is used to process each of the offshore wind turbine string combination schemes based on known offshore wind farm data and with the capacity of the offshore wind farm as a constraint, to obtain an optimized offshore wind turbine string scheme. The calculation module is used to calculate the dynamic operating data of each of the offshore wind turbine string optimization schemes in the selected frequency range; An evaluation module is used to obtain an evaluation result for each of the offshore wind turbine string optimization schemes based at least on reliability dimension results and operational dimension results, wherein the operational dimension results are obtained by analyzing the dynamic operational data; The selection module is used to determine the optimal offshore wind turbine string optimization scheme based on the evaluation results, wherein the optimal offshore wind turbine string optimization scheme serves as the basis for dynamic regulation of the offshore wind power collection system within the selected frequency range.

[0015] Compared with the prior art, the beneficial effects of the embodiments of the present invention are at least one of the following: (1) This invention acquires equipment data and fault-related data of offshore wind power clusters and constructs a comprehensive database. It then selects and optimizes wind turbine model data from this database, and generates offshore wind turbine string schemes by combining submarine cable grading and matching strategies. After listing the offshore wind turbine string schemes, it obtains combined offshore wind turbine string schemes and filters and optimizes them based on preset constraints. Furthermore, it calculates the dynamic operating data of each optimized offshore wind turbine string scheme in different frequency ranges, and obtains the evaluation results of each optimized offshore wind turbine string scheme based at least on reliability and operation dimension results. Finally, it determines the optimal optimized offshore wind turbine string scheme. This invention effectively solves the problem of existing design methods struggling to balance the overall benefits of the system, breaks the limitation of traditional design relying solely on power frequency parameters, and provides accurate data support for subsequent full-frequency operating condition evaluation. The optimal optimized offshore wind turbine string scheme determined through the evaluation results ensures that the system has high reliability, low operating losses, and reasonable investment costs, adapting to the needs of offshore wind farms of different scales from nearshore to deep-sea areas. It provides strong technical support for the efficient implementation and long-term stable operation of offshore wind power projects, and promotes the high-quality development of the offshore wind power industry.

[0016] (2) The design of combining wind turbine selection and submarine cable grading in this invention ensures that the single wind turbine string scheme is superior in terms of equipment adaptability and transmission efficiency, avoiding resource waste or transmission bottlenecks caused by a single submarine cable specification. It accurately matches the corresponding transmission capacity of the collection submarine cable for different numbers / capacities of wind turbines, significantly improving the technical adaptability and operational stability of the design, and helping to further improve the overall technical performance of the offshore wind power collection system design.

[0017] (3) This invention takes "reliability-dynamic operational stability" as the core of the dual-dimensional quantitative evaluation to achieve in-depth optimization of the system scheme. Based on the normalization of fault loss power, investment cost and frequency adaptive loss, the weight coefficients are readjusted: the reliability index is given a higher weight, while the internal weight allocation of the dynamic operation index is refined, the weight of the initial investment cost is significantly reduced, and the weight of the operation loss that is closely related to long-term benefits is significantly increased. In this way, a comprehensive evaluation index with reliability as the absolute dominant factor is formed, so as to achieve a comprehensive and scientific evaluation of the offshore wind power collection system, accurately select the optimal scheme, and efficiently balance the system reliability requirements and dynamic operation performance objectives. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the design method of an offshore wind power collection system in one embodiment of the present invention. Figure 2 This is a schematic diagram of the design system of an offshore wind power collection system in one embodiment of the present invention; Figure label: Module 11, Filtering Module 12, Matching Module 13, Combining Module 14, Optimizing Module 15, Calculating Module 16, Evaluating Module 17, and Selecting Module 18. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] In the description of this application, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0021] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. The terms "vertical," "horizontal," "left," "right," "upper," "lower," and similar expressions used herein are for illustrative purposes only and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0022] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0023] One embodiment of the present invention provides a design method for an offshore wind power collection system. For details, please refer to [link to relevant documentation]. Figure 1 , Figure 1 The diagram shown illustrates a design method for an offshore wind power collection system according to one embodiment of the present invention, comprising steps S1 to S8: S1: Acquire equipment data and fault-related data of offshore wind power clusters to build a comprehensive database; The constructed comprehensive database includes at least equipment data and fault-related data, as well as the mapping and correlation characteristics of each data with frequency changes. It provides accurate, reliable and multi-dimensional data support for subsequent wind turbine selection, scheme evaluation from the dimensions of reliability and operation, and full-band optimization. It is the foundation for ensuring the scientificity and feasibility of the entire design method.

[0024] The equipment data refers to the collection of basic and performance parameters of various key physical devices in the offshore wind power collection system, including offshore wind turbine data and AC collection submarine cable data. The offshore wind turbine data to be obtained includes at least the single-unit capacity P, the equivalent unit price C, and the rotor diameter D. The single-unit capacity of an offshore wind turbine refers to the maximum continuous electrical power output of a single offshore wind turbine under rated operating conditions; the equivalent unit price refers to the comprehensive cost index of all purchase, installation, and supporting costs of the offshore wind turbine allocated to its unit rated capacity. The single-unit capacity and equivalent unit price are used to calculate the investment cost of the wind turbines in the offshore wind power collection system; the rotor diameter is used to determine the layout design of the offshore wind power collection system. In a preferred embodiment of the invention, the wind turbines adopt a chain topology, and the spacing between adjacent wind turbines is set to seven times the rotor diameter. The AC collection submarine cable data includes at least the cable's transmission capacity S, AC resistance value R, and cost and installation fee K. cable The transmission capacity S is used to match the output capacity of the wind turbine. Different types of wind turbine strings should use wind turbine strings with different transmission capacities. The AC resistance value R is used to calculate the transmission loss of the current collector cable, so as to more comprehensively evaluate the system's economics, cost, and installation expenses K. cable Used to calculate the investment cost of submarine current collector cables.

[0025] Fault-related data refers to the set of key parameters used to evaluate the reliability and operational stability of offshore wind power collection systems. It includes at least the equipment failure rate λ (times / year) and failure duration of the wind turbine, collection cable, and circuit breaker in the offshore wind power collection system. T r These data are the core inputs for subsequent evaluation of the solution from a reliability perspective.

[0026] To support subsequent optimization within the selected frequency range, the comprehensive database needs to clearly define the mapping and correlation characteristics of each data point as a function of frequency, including the wind turbine unit price and frequency correlation model, the submarine cable current carrying capacity frequency correlation model, and the submarine cable resistance frequency correlation model.

[0027] The relationship model between wind turbine unit price and frequency is as follows: in, This indicates that the operating frequency is At that time, the equivalent unit price of the wind turbine, The system's operating frequency, This refers to the base unit price or reference unit price of the fan at a power frequency of 50Hz.

[0028] The frequency correlation model for submarine cable current carrying capacity is: in, I a This refers to the allowable current carrying capacity of the submarine cable at the operating frequency f. I a0 Here, f represents the base current carrying capacity of the same submarine cable at a power frequency of 50Hz, where f is the system's operating frequency. This represents the correction factor for the current carrying capacity based on the frequency.

[0029] The frequency-resistance correlation model for submarine cables is: in, R ac This represents the AC resistance per unit length of the submarine cable at the operating frequency f. R ac0 f represents the power frequency submarine cable resistance, and f represents the system operating frequency. This represents the correction factor for AC resistance based on frequency.

[0030] S2: Taking the lowest equipment failure rate of offshore wind turbines as the objective function, and based on a comprehensive database, obtain the optimal wind turbine model data, at least according to the preset single-unit capacity constraints of offshore wind turbines. Among them, the optimal wind turbine model data refers to selecting high-reliability wind turbine models and a complete set of key parameters from a comprehensive database, with the core objective of "lowest equipment failure rate" and comprehensively considering constraints such as single-unit capacity and rotor diameter. Specifically, high-reliability wind turbine models suitable for offshore wind power collection systems are selected from the comprehensive database, firstly by establishing a set of parameters based on min(λ). fanThe objective function is to minimize the wind turbine failure rate, where λ represents the failure rate of a specific wind turbine model obtained from a comprehensive database. Minimizing the failure rate is chosen because in a marine environment, a high failure rate leads to enormous maintenance costs and significant power generation losses. By minimizing the failure rate, the availability and operational stability of the entire offshore wind power collection system can be improved from the outset. Simultaneously, necessary constraints are set to ensure that the selected offshore wind turbine model meets basic engineering requirements: single-unit capacity constraints (e.g., P≥8MW) to adapt to the large-capacity development needs of offshore wind farms; and rotor diameter constraints (e.g., D≥180m) closely related to the layout design of the offshore wind power collection system, ensuring the overall power generation efficiency of the collection system.

[0031] Preferably, in one embodiment of the present invention, the objective function is to minimize the equipment failure rate of the offshore wind turbine, and based on a comprehensive database, preferred wind turbine model data is obtained, including: (The data is based on a predetermined single-unit capacity constraint of the offshore wind turbine, and includes:) The equipment failure rate of offshore wind turbines is obtained by retrieving fault-related data from the comprehensive database. Equipment data is retrieved from the comprehensive database to obtain the single-unit capacity data of the offshore wind turbine; Based on the equipment failure rate and single-unit capacity data of offshore wind turbines, and using the objective function and preset constraints, the preferred wind turbine models are selected.

[0032] The process involves accessing equipment and fault-related data for offshore wind turbines from a comprehensive database, iterating through all turbine models and calculating their failure rate (λ), unit capacity (P), and impeller diameter (D). Assuming the preset constraints are a unit capacity of P ≥ 8MW and an impeller diameter of D ≥ 180m, the selection logic is as follows: first, initial screening is performed based on the constraints of P ≥ 8MW and D ≥ 180m to exclude turbine models that do not meet the technical specifications; then, among the remaining candidate turbine models, their λ values ​​are directly compared, and the models with the lowest failure rate (λ) are selected as the output. Finally, the output result is the optimized turbine model data. This dataset contains all the key parameters of the optimized models, including the equipment failure rate (λ), unit capacity (P), and impeller diameter (D) used for screening, as well as their equivalent unit price (C) and failure time, retrieved from the comprehensive database. T r These data form the direct inputs for the subsequent calculations: the unit price C is used to calculate the investment cost, while the equipment failure rate λ is related to the downtime. T r This is an indispensable foundational data for subsequent calculations of reliability dimensions such as power loss due to faults.

[0033] S3: Based on the data of the selected wind turbine models, generate various offshore wind turbine string schemes according to the submarine cable graded matching strategy; Among them, the submarine cable graded matching strategy is a method for refined cable selection for offshore wind power collection systems. Its core principle is to match submarine cables of different specifications to different sections of the wind turbine series circuit according to the actual transmission power of each section. The offshore wind turbine series scheme refers to the specific configuration design scheme of connecting multiple offshore wind turbines in series through collection submarine cables to form an independent power generation unit.

[0034] Preferably, in one embodiment of the present invention, by combining preferred wind turbine model data and according to a submarine cable hierarchical matching strategy, various offshore wind turbine string schemes are generated, including: Equipment data is extracted from the comprehensive database and combined with the optimized wind turbine model data to determine the range of the number of offshore wind turbines in the offshore wind turbine string scheme; For the number of offshore wind turbines, different types of submarine cables are adapted according to the transmission power gradient to obtain the corresponding submarine cable model data. The transmission power gradient is obtained by superimposing the power of the offshore wind turbines in a series structure. By integrating the data on submarine cable models and the corresponding preferred wind turbine models, various offshore wind turbine string schemes are obtained.

[0035] Specifically, when determining the range of the number of wind turbines in an offshore wind turbine string scheme, it is necessary to extract the current-carrying capacity data of the AC current collector submarine cable from a comprehensive database based on the preferred wind turbine model data. The lower limit for the number of wind turbines in an offshore wind turbine string is typically set at two units to form a basic series structure; the upper limit is... (Submarine cable current carrying capacity) is a constraint, where n For the number of wind turbines, P This refers to the single-unit capacity of offshore wind turbines. U is the rated current carrying capacity of the submarine cable. N The rated voltage is given, and cosφ is the power factor, with a value of 0.9. This constraint ensures that the maximum output power of the wind turbine string does not exceed the safe transmission capacity of the submarine cable.

[0036] For each specific offshore wind turbine, a graded matching strategy for submarine cables is implemented. When a single turbine string consists of two turbines, only the power transmission requirement of rated power P1 needs to be considered. The submarine cable model with the closest rated current carrying capacity to P1 and meeting the safety margin requirements is selected from the comprehensive database. This process follows the formula: , where I cable For submarine cable current carrying capacity, U N Initial matching optimization is achieved by minimizing the current difference, based on the system's rated voltage. When the single-string wind turbine is expanded to three turbines, the system needs to meet both P1 and 2P1 power transmission conditions. Building upon the submarine cable already determined in the previous step, and based on the principle of graded matching of submarine cables, a new collector cable adapted to 2P1 power is added. This selected submarine cable must meet the following requirements: Furthermore, for a series structure consisting of n identical offshore wind turbines, the power to be transmitted in each segment of the submarine cable from the last turbine to the confluence point exhibits an increasing gradient distribution: P, 2P, 3P, ..., (n-1)P. The submarine cable graded matching strategy selects the technically optimal submarine cable model for each of these n-1 different power levels. The minimum current difference is min( ), where I cable By querying information from a comprehensive database, the submarine cable model with the closest current carrying capacity and not less than the calculated value can be selected for each power level, thereby achieving precise "on-demand matching" that ensures both technical feasibility and avoids capacity waste.

[0037] Finally, the determined preferred wind turbine model data, the specific number of turbines n in series, and the n-1 types of submarine cables and their corresponding lengths determined through the submarine cable classification and matching strategy are systematically integrated to form a complete offshore wind turbine string scheme. The length of each submarine cable segment can be calculated based on the rotor diameter D of the turbine model, following the rule that the spacing between adjacent offshore wind turbines in a chain topology is 7D. However, for wind turbine strings using different turbine types, the distance between adjacent wind turbines and the length of the current collection submarine cable will vary due to differences in blade diameter.

[0038] S4: Integrate the various offshore wind turbine string schemes and list the offshore wind turbine string combination schemes; The offshore wind turbine string combination scheme refers to the layout planning of combining multiple offshore wind turbine strings of different types or quantities to achieve the target total installed capacity of the wind farm. Total installed capacity refers to the sum of the rated power of all wind turbine generators in the target wind farm. Specifically, various offshore wind turbine string schemes are integrated to form an offshore wind turbine string scheme library. Based on this, an exhaustive method is used to generate feasible offshore wind turbine string combination schemes. Each wind turbine string type in the offshore wind turbine string scheme library is considered a basic building block. By systematically changing the number of each wind turbine string type used, all possible combinations are traversed to select those combinations whose sum of the capacities of all wind turbine string types meets or exceeds the total installed capacity requirement of the wind farm. Through this comprehensive traversal, all feasible combination schemes that meet the capacity requirements are finally selected, providing a complete set of candidate schemes for subsequent optimization and selection. This method ensures that no possible feasible schemes are overlooked, laying a solid foundation for selecting the optimal configuration.

[0039] S5: Based on the known data of offshore wind farms, the combination schemes of each offshore wind turbine string are processed with the capacity of the offshore wind farm as a constraint to obtain the optimized scheme of offshore wind turbine string. Among them, the known data of offshore wind farms refers to the basic information that has been determined in the project design stage and serves as the input condition for system design, including at least the total installed capacity of the target wind farm and the rated voltage of the system; the offshore wind turbine string optimization scheme refers to the optimal solution obtained after reliability screening and path optimization among all feasible combinations that meet the total installed capacity of the wind farm.

[0040] Preferably, in one embodiment of the present invention, based on known data from offshore wind farms, the various offshore wind turbine string combination schemes are processed under the constraint of the offshore wind farm capacity to obtain an optimized offshore wind turbine string scheme, including: Based on data from offshore wind farms, the constraints on offshore wind farms are defined, including at least the capacity of the offshore wind farms. Select the first offshore wind turbine string combination scheme that meets the constraints from all offshore wind turbine string combination schemes; Based on a greedy algorithm, the submarine cable path of the first offshore wind turbine string combination scheme is optimized to obtain the corresponding optimized offshore wind turbine string scheme.

[0041] Based on the fundamental data of offshore wind farms, the total installed capacity of the wind farms is clearly defined as the core constraint. Under this premise, with the goal of optimizing system reliability, the schemes that meet the capacity requirements are selected from the offshore wind turbine string combination schemes obtained in step S4. Specifically, by calculating and comparing the reliability indicators of each combination scheme, the schemes with the highest reliability are selected as the first offshore wind turbine string combination scheme. The reliability dimension indicators mainly cover the power loss due to faults and the system fault tolerance coefficient. The calculation of power loss due to faults takes into account the failure rate and repair time of wind turbines, submarine cables, and circuit breakers, while the system fault tolerance coefficient reflects the system's ability to maintain operation when components fail.

[0042] The formula for calculating power loss due to faults is as follows: in, This represents the power loss due to faults, referring to the annual power generation lost by the wind turbine series due to a fault. λ For equipment failure rate, For the time of failure; The capacity of the fan string is obtained by multiplying the number of fans in the fan string by the capacity of each fan. T The annual operating hours are set to 8760 hours.

[0043] The formula for calculating the system's fault tolerance coefficient is as follows: in, This is the system's fault tolerance coefficient. This represents the power loss due to a fault.E total This represents the total annual power generation, which is calculated by considering the capacity of the wind turbines. and annual operating hours T The product of is obtained, where T The value is also taken as 8760 hours.

[0044] Preferably, in one embodiment of the present invention, the submarine cable path of the first offshore wind turbine string combination scheme is optimized based on a greedy algorithm to obtain a corresponding optimized offshore wind turbine string scheme, including: The coordinate information of the target nodes in the first offshore wind turbine string combination scheme is extracted respectively to obtain the distance matrix corresponding to each of the first offshore wind turbine string combination schemes; Based on the distance matrix, with the shortest total length of the submarine cable path as the optimization objective, the optimal submarine cable path information corresponding to each first offshore wind turbine string combination scheme is obtained. The optimal submarine cable path information is integrated into the corresponding first offshore wind turbine string combination scheme to obtain the offshore wind turbine string optimization scheme.

[0045] Greedy algorithms are a design philosophy that adopts the optimal decision at each step, taking advantage of the current state. Their core logic is to obtain a globally better solution through a series of locally optimal choices. Specifically, constructing the distance matrix requires extracting the coordinates of all wind turbine strings (as target nodes) and the offshore converter station in each scheme, calculating the relative distances between nodes, and forming a distance matrix. Secondly, based on this distance matrix, with the shortest total cable path length as the optimization objective, a greedy algorithm is applied for path planning. The specific process involves starting from the converter station, selecting the nearest unconnected wind turbine string to the current node for connection, gradually building connection paths until all wind turbine strings are connected to the system, thus obtaining the connection scheme with the shortest total path. Finally, the obtained optimal cable path information (including the specific length of each path segment) is integrated with the corresponding first offshore wind turbine string combination scheme, ultimately outputting an optimized offshore wind turbine string scheme containing the optimal path information.

[0046] S6: Calculate the dynamic operating data of each of the offshore wind turbine string optimization schemes in the selected frequency range; Among them, the selected frequency range refers to the non-power frequency operating frequency range that is pre-defined during the design process for system optimization and evaluation; dynamic operating data reveals how system costs and losses change with the operating variable of frequency, and serves as a bridge connecting "equipment frequency characteristics" and "comprehensive performance of the solution", providing a core basis for subsequently selecting the most economically efficient operating solution across the entire frequency band.

[0047] Preferably, in one embodiment of the present invention, the dynamic operating data of each offshore wind turbine string optimization scheme in the selected frequency range are calculated, including: Extract equipment data from the optimization scheme of each offshore wind turbine string; Based on the preset frequency range, the device data is divided into intervals to obtain frequency interval data; Based on frequency range data, dynamic operating data corresponding to the optimization scheme for each offshore wind turbine string is calculated.

[0048] Specifically, equipment data is extracted from the optimized scheme of each offshore wind turbine string. This data originates from the comprehensive database constructed in step S1 and the optimization results of the preceding steps, mainly including: the combination configuration of the wind turbine string, the model and length of each section of submarine cable, and frequency-related basic equipment parameters obtained from the database. Based on a preset full-band frequency range, the equipment data is divided into intervals to obtain frequency interval data. The frequency intervals at least cover the low-frequency (e.g., 16.67Hz-25Hz), power frequency (50Hz), and medium-frequency (e.g., 50Hz-100Hz) ranges. The specific division process includes: identifying and extracting parameters strongly correlated with frequency changes from the equipment data, i.e., frequency-sensitive data, mainly including the wind turbine unit price, submarine cable current carrying capacity, and submarine cable AC resistance; then, based on the mapping correlation characteristics of each data point in step S1 with frequency changes, key frequency data is collected within each preset frequency interval.

[0049] Preferably, in one embodiment of the present invention, the device data is divided into intervals according to a preset frequency interval to obtain frequency interval parameters, including: Extract parameters that are strongly correlated with frequency from the equipment data, determine the parameter range that needs to be divided by frequency, and obtain frequency-sensitive data; Based on frequency-sensitive data, key frequency data within preset frequency ranges are collected; By integrating the data from various key frequencies, frequency range data is obtained.

[0050] Frequency-sensitive data refers to key equipment parameters whose values ​​change significantly with the system operating frequency f. Key frequency data refers to the set of parameter values ​​obtained by calculating frequency-sensitive data at a series of representative frequency points within a selected frequency range; it can be understood as the sampled values ​​of frequency-sensitive data at specific frequency points. Frequency range data refers to the complete set of all key frequency data within the entire selected frequency range (e.g., low frequency, power frequency, and medium frequency). Specifically, in one embodiment of the present invention, several representative frequency points (e.g., 20Hz, 50Hz, and 75Hz) are selected in the low-frequency, power frequency, and medium-frequency ranges, respectively, and the unit price of the wind turbine, the current carrying capacity of the submarine cable, and the AC resistance of the submarine cable at these frequency points are calculated for each scheme. Finally, the parameter calculation results at all selected frequency points are integrated to form systematic frequency range data.

[0051] Ultimately, dynamic operational data is a key input for subsequent comprehensive evaluation, mainly including two core indicators: one is the investment cost C. inv Its value is the investment cost C of the wind turbine string. string Compared with the optimized submarine cable investment cost C cable The sum of the costs is as follows: the investment cost of the wind turbine string and the investment cost of the submarine cable after path optimization are as follows: the unit price of frequency-related equipment (such as wind turbines) and the amount of materials used have been updated according to the frequency range data; the second is the frequency adaptive loss, which takes into account the impact of frequency changes on the resistance of the submarine cable.

[0052] The formula for calculating frequency adaptive loss is as follows: C loss =3×I 2 ×R ac ×L Among them, C loss For frequency-adaptive loss cost, I is the operating current of the submarine cable, and R is the operating current. ac L is the AC resistance of the submarine cable, and L is the total length of the submarine cable (the total length of the submarine cable in the wind turbine string and the sending submarine cable from the wind turbine string to the converter station).

[0053] The above calculations provide the dynamic performance of each optimization scheme in different frequency ranges, laying the foundation for the next step of establishing an evaluation model and optimizing frequencies.

[0054] S7: Based at least on the reliability dimension results and the operation dimension results, obtain the evaluation results of the optimization scheme for each offshore wind turbine string, wherein the operation dimension results are obtained by analyzing the dynamic operation data; Among them, the reliability dimension results refer to a series of indicators that quantitatively evaluate the offshore wind turbine string optimization scheme from the perspective of system availability and stability, mainly including power loss due to failure and system fault tolerance coefficient; the operation dimension results refer to a set of key indicators that quantitatively evaluate the long-term operating cost of the offshore wind turbine string optimization scheme at different frequencies from the perspective of system operation economy, mainly including investment cost and frequency adaptive loss.

[0055] Preferably, in one embodiment of the present invention, the evaluation results of the optimization scheme for each offshore wind turbine string are obtained based at least on the reliability dimension results and the operation dimension results, including: An evaluation model is established based on the results from the reliability dimension and the operational dimension. The evaluation model is used to calculate the evaluation index of each offshore wind turbine string optimization scheme in the selected frequency range. By integrating the evaluation indices, the evaluation results corresponding to the optimization scheme for each offshore wind turbine string are obtained.

[0056] The evaluation model is a mathematical tool used to quantify and score the comprehensive performance of different offshore wind turbine string optimization schemes at different frequencies and to make horizontal comparisons. Specifically, the core input of the evaluation model includes two quantitative structures: one is the reliability dimension result, mainly covering power loss due to failure and the system's fault tolerance coefficient; the other is the operation dimension result, obtained through analysis of dynamic operation data, mainly including investment cost and frequency adaptive loss. To eliminate the influence of different indicator dimensions and to make comprehensive comparisons, the above indicators need to be normalized. A linear normalization method is used to map each indicator value to the [0, 1] interval. Based on normalization, an evaluation model is constructed: in, S(f) Represents frequency f The evaluation index below, and ω represents the maximum investment cost and loss cost among all evaluated options, respectively, and ω is the weight coefficient of each evaluation indicator, ω1=0.8, ω2=0.05, ω3=0.15. This weight system supports dynamic adjustment according to actual engineering needs.

[0057] This evaluation system eliminates the dimensions of different indicators through normalization and condenses multi-dimensional evaluations (reliability, investment, and operational losses) into a single comprehensive score through weighted summation. S(f), It precisely matches the special application scenario requirements of offshore wind power, where maintenance is difficult and failure costs are high.

[0058] S8: Based on the evaluation results, determine the optimal offshore wind turbine string optimization scheme, wherein the optimal offshore wind turbine string optimization scheme serves as the basis for dynamic regulation of the offshore wind power collection system within the selected frequency range.

[0059] Preferably, in one embodiment of the present invention, determining the optimal offshore wind turbine string optimization scheme based on the evaluation results includes: For each offshore wind turbine string optimization scheme, the optimal frequency evaluation index is selected from the evaluation indices of each frequency range. The optimal frequency evaluation indices are sorted in descending order to obtain the ranking results corresponding to each offshore wind turbine string optimization scheme, and the optimal offshore wind turbine string optimization scheme is determined.

[0060] The optimal offshore wind turbine string optimization scheme is the globally optimal solution determined after screening, optimization, and evaluation through all steps of the design method. Specifically, for each offshore wind turbine string optimization scheme, the highest-valued evaluation index is selected from multiple evaluation indices calculated across the entire frequency band (low frequency, power frequency, and medium frequency) as the optimal frequency evaluation index for that scheme. This operation aims to determine the optimal operating frequency point where each scheme has the greatest performance potential. For example, scheme A may have an evaluation index of 0.85 at power frequency (50Hz), 0.72 at low frequency (20Hz), and 0.88 at medium frequency (75Hz). Therefore, the optimal frequency evaluation index for scheme A is determined to be 0.88, and its corresponding optimal operating frequency is 75Hz. This process completes the longitudinal frequency optimization for each scheme.

[0061] Subsequently, the optimal frequency evaluation indices of each offshore wind turbine string optimization scheme were summarized and sorted in descending order of numerical value, thus obtaining the final performance ranking of all candidate schemes. The scheme with the highest optimal frequency evaluation index was determined as the optimal offshore wind turbine string optimization scheme, completing a comprehensive horizontal comparison among all schemes. The determined optimal offshore wind turbine string optimization scheme, along with its corresponding optimal operating frequency, constitutes the final design scheme for the deep-sea wind power cluster collection system. This scheme is not only statically optimal in terms of topology, equipment selection, and path layout, but also clarifies the operating frequency that the system should adopt to maximize its overall life-cycle benefits under specific operating conditions.

[0062] In actual operation, system operators can use this scheme to dynamically adjust the frequency within the selected frequency range. For example, when pursuing ultimate efficiency, they can switch to medium-frequency operation, or use low-frequency operation when the equipment is started or specific maintenance needs are required. This achieves a high-efficiency balance between the reliability, economy and operational flexibility of the power collection system, providing core technical support for the efficient and stable development and operation of large-scale deep-sea wind power.

[0063] Another embodiment of the present invention provides a design system for an offshore wind turbine power collection system. For details, please refer to [link to relevant documentation]. Figure 2 , Figure 2 The diagram shown is a schematic design system diagram of an offshore wind turbine power collection system according to one embodiment of the present invention, which includes: Module 11 is used to acquire equipment data and fault-related data of offshore wind power clusters and build a comprehensive database; The screening module 12 is used to obtain preferred wind turbine model data based on the comprehensive database, with the objective function of minimizing the equipment failure rate of the offshore wind turbine and at least according to the preset single-unit capacity constraints of the offshore wind turbine. Matching module 13 is used to combine the preferred wind turbine model data and generate various offshore wind turbine string schemes according to the submarine cable hierarchical matching strategy. Combination module 14 is used to integrate the various offshore wind turbine string schemes and list offshore wind turbine string combination schemes therefrom; The optimization module 15 is used to process each of the offshore wind turbine string combination schemes based on the known data of the offshore wind farm, with the capacity of the offshore wind farm as a constraint, to obtain an optimized offshore wind turbine string scheme. Calculation module 16 is used to calculate the dynamic operating data of each of the offshore wind turbine string optimization schemes in the selected frequency range; Evaluation module 17 is used to obtain evaluation results for each of the offshore wind turbine string optimization schemes based at least on reliability dimension results and operation dimension results, wherein the operation dimension results are obtained by analyzing the dynamic operation data; Selection module 18 is used to determine the optimal offshore wind turbine string optimization scheme based on the evaluation results, wherein the optimal offshore wind turbine string optimization scheme serves as the basis for dynamic regulation of the offshore wind power collection system in the selected frequency range.

[0064] Compared with the prior art, the beneficial effects of the embodiments of the present invention are at least one of the following: (1) This invention acquires equipment data and fault-related data of offshore wind power clusters and constructs a comprehensive database. It then selects and optimizes wind turbine model data from this database, and generates offshore wind turbine string schemes by combining submarine cable grading and matching strategies. After listing the offshore wind turbine string schemes, it obtains combined offshore wind turbine string schemes and filters and optimizes them based on preset constraints. Furthermore, it calculates the dynamic operating data of each optimized offshore wind turbine string scheme in different frequency ranges, and obtains the evaluation results of each optimized offshore wind turbine string scheme based at least on reliability and operation dimension results. Finally, it determines the optimal optimized offshore wind turbine string scheme. This invention effectively solves the problem of existing design methods struggling to balance the overall benefits of the system, breaks the limitation of traditional design relying solely on power frequency parameters, and provides accurate data support for subsequent full-frequency operating condition evaluation. The optimal optimized offshore wind turbine string scheme determined through the evaluation results ensures that the system has high reliability, low operating losses, and reasonable investment costs, adapting to the needs of offshore wind farms of different scales from nearshore to deep-sea areas. It provides strong technical support for the efficient implementation and long-term stable operation of offshore wind power projects, and promotes the high-quality development of the offshore wind power industry.

[0065] (2) The design of combining wind turbine selection and submarine cable grading in this invention ensures that the single wind turbine string scheme is superior in terms of equipment adaptability and transmission efficiency, avoiding resource waste or transmission bottlenecks caused by a single submarine cable specification. It accurately matches the corresponding transmission capacity of the collection submarine cable for different numbers / capacities of wind turbines, significantly improving the technical adaptability and operational stability of the design, and helping to further improve the overall technical performance of the offshore wind power collection system design.

[0066] (3) This invention takes "reliability-dynamic operation stability" as the core of the dual-dimensional quantitative evaluation to achieve in-depth optimization of the system scheme. On the basis of normalizing the power loss due to failure, investment cost and frequency adaptive loss, the weight coefficients are readjusted: the reliability index is given a higher weight, while the internal weight allocation of the dynamic operation index is refined, the weight of the initial investment cost is significantly reduced, and the weight of the operation loss that is closely related to the long-term benefits is significantly increased. In this way, a comprehensive evaluation index with reliability as the absolute leader is formed, so as to achieve a comprehensive and scientific evaluation of the offshore wind power collection system, accurately select the optimal scheme, and efficiently balance the system reliability requirements and dynamic operation performance objectives.

[0067] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method of designing an offshore wind power collection system, characterized by, include: Acquire equipment and fault-related data from offshore wind power clusters to construct a comprehensive database; With the objective function of minimizing the equipment failure rate of offshore wind turbines, and based on the comprehensive database, the optimal wind turbine model data is obtained at least according to the preset single-unit capacity constraints of the offshore wind turbines. Based on the preferred wind turbine model data, and in accordance with the submarine cable graded matching strategy, various offshore wind turbine string schemes are generated; Integrate the various offshore wind turbine string schemes and list offshore wind turbine string combination schemes from them; Based on known data from offshore wind farms, the various offshore wind turbine string combination schemes are processed with the capacity of the offshore wind farms as a constraint to obtain an optimized offshore wind turbine string scheme. Calculate the dynamic operating data of each of the aforementioned offshore wind turbine string optimization schemes in the selected frequency range; The evaluation results of each offshore wind turbine string optimization scheme are obtained based at least on the reliability dimension results and the operation dimension results, wherein the operation dimension results are obtained by analyzing the dynamic operation data; Based on the evaluation results, an optimal offshore wind turbine string optimization scheme is determined, wherein the optimal offshore wind turbine string optimization scheme serves as the basis for dynamic regulation of the offshore wind power collection system within the selected frequency range.

2. The design method for an offshore wind power collection system as described in claim 1, characterized in that, The objective function is to minimize the equipment failure rate of the offshore wind turbine, and based on the comprehensive database, at least according to preset single-unit capacity constraints of the offshore wind turbine, to obtain optimal wind turbine model data, including: The fault-related data is retrieved from the comprehensive database to obtain the equipment failure rate of the offshore wind turbine; The equipment data is retrieved from the comprehensive database to obtain the single-unit capacity data of the offshore wind turbine; Based on the equipment failure rate and single-unit capacity data of the offshore wind turbines, and according to the objective function and the preset constraints, the preferred wind turbine models are selected.

3. The design method for an offshore wind power collection system as described in claim 1, characterized in that, The process involves combining the preferred wind turbine model data with a submarine cable tiered matching strategy to generate various offshore wind turbine string schemes, including: The equipment data is extracted from the comprehensive database, and combined with the preferred wind turbine model data, the range of the number of offshore wind turbines in the offshore wind turbine string scheme is determined; For the number of offshore wind turbines, different types of submarine cables are adapted according to the transmission power gradient to obtain the corresponding submarine cable model data. The transmission power gradient is obtained by superimposing the power of the offshore wind turbines in a series structure. By integrating the submarine cable model data and the corresponding preferred wind turbine model data, each offshore wind turbine string scheme is obtained.

4. The design method for an offshore wind power collection system as described in claim 1, characterized in that, The process involves processing various offshore wind turbine string combination schemes based on known offshore wind farm data, using the capacity of the offshore wind farm as a constraint, to obtain an optimized offshore wind turbine string scheme, including: Based on the data of the offshore wind farm, the constraints of the offshore wind farm are defined, wherein the constraints include at least the capacity of the offshore wind farm. Select the first offshore wind turbine string combination scheme that satisfies the constraints from all the described offshore wind turbine string combination schemes; Based on a greedy algorithm, the submarine cable path of the first offshore wind turbine string combination scheme is optimized to obtain the corresponding optimized offshore wind turbine string scheme.

5. The design method for an offshore wind power collection system as described in claim 4, characterized in that, The optimization of the submarine cable path for the first offshore wind turbine string combination scheme based on the greedy algorithm yields the corresponding optimized offshore wind turbine string scheme, including: The coordinate information of the target nodes in the first offshore wind turbine string combination scheme is extracted respectively to obtain the distance matrix corresponding to each of the first offshore wind turbine string combination schemes; Based on the distance matrix, with the shortest total length of the submarine cable path as the optimization objective, the optimal submarine cable path information corresponding to each of the first offshore wind turbine string combination schemes is obtained. The optimal submarine cable path information is integrated into the corresponding first offshore wind turbine string combination scheme to obtain the offshore wind turbine string optimization scheme.

6. The design method of an offshore wind power collection system as described in claim 1, characterized in that, The calculation of dynamic operating data for each of the offshore wind turbine string optimization schemes within the selected frequency range includes: Extract the equipment data from each of the aforementioned offshore wind turbine string optimization schemes; The device data is divided into intervals according to the preset frequency intervals to obtain frequency interval data; Based on the frequency range data, the dynamic operating data corresponding to each of the offshore wind turbine string optimization schemes is calculated.

7. The design method for an offshore wind power collection system as described in claim 6, characterized in that, The step of dividing the device data into intervals according to the preset frequency interval to obtain frequency interval parameters includes: Extract parameters that are strongly correlated with frequency from the device data, determine the parameter range that needs to be divided by frequency, and obtain frequency-sensitive data; Based on the frequency-sensitive data, key frequency data within each preset frequency range are collected; By integrating the key frequency data, the frequency range data is obtained.

8. The design method of an offshore wind power collection system as described in claim 1, characterized in that, The evaluation results for each offshore wind turbine string optimization scheme are obtained based at least on reliability and operational dimension results, including: An evaluation model is established based on the reliability dimension results and the operational dimension results. The evaluation model is used to calculate the evaluation index of each offshore wind turbine string optimization scheme in the selected frequency range. By integrating the evaluation indices, the evaluation results corresponding to each of the offshore wind turbine string optimization schemes are obtained.

9. The design method of an offshore wind power collection system as described in claim 1, characterized in that, The process of determining the optimal offshore wind turbine string optimization scheme based on the evaluation results includes: For each of the aforementioned offshore wind turbine string optimization schemes, the optimal frequency evaluation index is selected from the evaluation indices of each of the aforementioned frequency ranges. The optimal frequency evaluation indices are sorted in descending order to obtain the ranking results corresponding to each of the offshore wind turbine string optimization schemes, and the optimal offshore wind turbine string optimization scheme is determined.

10. A design system for an offshore wind power collection system, characterized in that, include: The module is used to acquire equipment data and fault-related data of offshore wind power clusters and build a comprehensive database; The filtering module is used to obtain preferred wind turbine model data based on the comprehensive database, with the objective function of minimizing the equipment failure rate of offshore wind turbines and at least according to the preset single-unit capacity constraints of the offshore wind turbines. The matching module is used to combine the preferred wind turbine model data and generate various offshore wind turbine string schemes according to the submarine cable graded matching strategy. A combination module is used to integrate the various offshore wind turbine string schemes, and to list offshore wind turbine string combination schemes. The optimization module is used to process each of the offshore wind turbine string combination schemes based on the known data of the offshore wind farm, with the capacity of the offshore wind farm as a constraint, to obtain an optimized offshore wind turbine string scheme. The calculation module is used to calculate the dynamic operating data of each of the offshore wind turbine string optimization schemes in the selected frequency range; An evaluation module is used to obtain an evaluation result for each of the offshore wind turbine string optimization schemes based at least on reliability dimension results and operational dimension results, wherein the operational dimension results are obtained by analyzing the dynamic operational data; The selection module is used to determine the optimal offshore wind turbine string optimization scheme based on the evaluation results, wherein the optimal offshore wind turbine string optimization scheme serves as the basis for dynamic regulation of the offshore wind power collection system within the selected frequency range.

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