Fault-tolerant-oriented wiring design method for offshore wind power collection line

Abstract

The application relates to a wiring design method of a fault-tolerant offshore wind power collection line, in particular to a redundancy wiring design method for realizing low-cost redundancy planning of a cable network under the premise of ensuring system reliability, and is suitable for the technical field of offshore wind power. The application takes a minimum spanning tree as an initial cost-optimal topology, iteratively adds a redundant line with the highest reliability contribution degree, realizes minimization of a redundancy cost under the premise of meeting a preset power supply availability requirement, and solves the problems of single cost target, ignored fault risk and wasted redundancy design cost in a traditional method.

Description

Technical Field

[0001] This invention relates to a fault-tolerant wiring design method for offshore wind power collector lines, and more particularly to a fault-tolerant redundant wiring design method for achieving low-cost redundant planning of cable networks while ensuring system reliability. It is applicable to the field of offshore wind power technology. Background Technology

[0002] Offshore wind power, as a crucial component of clean energy development, directly impacts the economic viability and reliability of its power collection system design. In offshore wind farms, turbines are connected to a substation via cables before data is transmitted to land. The reliability of the offshore wind power power collection system directly affects the power generation efficiency and operating costs of the wind farm. In the harsh marine environment, cables are susceptible to corrosion, trawling, and anchoring damage, resulting in a significantly higher failure rate than onshore cables, along with limited maintenance opportunities and high costs.

[0003] Traditional cable routing optimization methods typically prioritize minimizing total construction costs, using minimum spanning trees (MSTs) or Steiner tree models to determine cable paths connecting all wind turbines to the substation. While these methods effectively reduce initial investment, they overlook the risk of single points of failure. A failure in a critical cable can lead to large-scale turbine shutdowns and significant power generation losses.

[0004] To improve system reliability, some studies have attempted to incorporate redundancy designs into traditional cost models, such as using ring topologies or dual-feeder structures. However, existing redundancy design methods are mostly based on empirical rules or fixed topology templates, failing to rigorously quantify and correlate system-level reliability indicators (such as power supply availability) with actual engineering parameters such as cable physical failure rate, maintenance time, and the success rate of protection switching devices. This results in redundancy schemes that are often overly conservative, leading to wasted costs, or overly optimistic, failing to achieve the expected fault tolerance.

[0005] Furthermore, existing optimization models often suffer from excessive complexity, making it difficult to solve large-scale practical wind farm problems. They typically rely on general heuristic algorithms, which struggle to balance solution efficiency and solution quality. Therefore, systematically balancing reliability improvements with cost increases during the design phase, embedding fault tolerance and self-healing capabilities into the cable network topology in a quantifiable and optimizable manner, and developing efficient solution algorithms to handle large-scale engineering problems have become key technical challenges for improving the economic efficiency and operational safety of offshore wind farms throughout their entire lifecycle. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a wiring design method for fault-tolerant offshore wind power collection lines, which addresses the above-mentioned problems.

[0007] The technical solution adopted in this invention is: a wiring design method for fault-tolerant offshore wind power collector lines, comprising: S100. Model the wind turbines, combiner stations, and possible relay points of the offshore wind farm as nodes, and model the candidate cable lines between nodes as edges. Determine the weight of each edge based on the cable line cost, and construct a weighted undirected graph. S200. Based on the weighted undirected graph, generate fault scenario samples to form a fault scenario set. The fault scenario samples include the available status of each line in the weighted undirected graph. S300. Based on a weighted undirected graph, the minimum spanning tree algorithm is used to select cable lines and construct the initial set of offshore wind power collection lines. S400. Based on the line set, under each fault scenario sample, calculate the power supply availability of the line set according to the connectivity between each wind turbine and the combiner station, and then determine the power supply availability index of the line set for the fault scenario set. S500: When the power supply availability index is lower than the preset lower limit, execute step S600; otherwise, output the cable routing scheme of the offshore wind power collection line based on the line set. S600. Add an unselected line to the line set to form a temporary line set. Calculate the power supply availability index of the temporary line set and determine the contribution of the unselected line based on the availability increment and line cost. S700. For all unselected lines, filter out the lines with the highest contribution, update the line set, and return to step S400.

[0008] Using the aforementioned techniques and a weighted undirected graph as the modeling basis, the minimum spanning tree algorithm is employed to determine the initial cost-optimal topology. Combined with fault scenario simulation, incremental redundancy optimization is achieved through iterative calculation of line reliability contributions, forming a complete design process: cost-optimal benchmark – quantitative reliability assessment – ​​incremental redundancy optimization. Fault tolerance is quantitatively integrated into the cabling design, achieving a dynamic trade-off between construction costs and system power supply reliability. This ensures that the final cabling scheme minimizes redundancy costs while meeting preset power supply reliability requirements, thereby improving the economic efficiency and operational safety of offshore wind farms throughout their entire lifecycle.

[0009] In some embodiments, step S200 includes: Based on a weighted undirected graph, a set of independent and identically distributed fault scenario samples is generated using Monte Carlo sampling. Cable line faults are defined as two-dimensional Bernoulli discrete random events. Based on the failure probability per unit time of each line, a Bernoulli test is performed on the line to determine the usability of the cable line in the fault scenario samples.

[0010] By using the above technical means, cable line faults are defined as Bernoulli discrete random events and the failure probability per unit time of the line is bound together, so that the generation of fault scenarios is associated with the actual engineering parameters of the cable, thus avoiding the one-sidedness of traditional empirical fault assumptions.

[0011] In some embodiments, step S400 includes: S410. Based on the set of lines and the availability status of each line in the fault scenario sample, determine the connectivity between each wind turbine and the combiner station. S420. Based on the proportion of ventilation fans connected to the combiner station among all fans, determine the power supply availability of the line set under the sample of the fault scenario. S430. Based on the power supply availability of the line set under each fault scenario sample, and combined with the mathematical expectation of each fault scenario sample, determine the power supply availability index of the line set for the fault scenario set.

[0012] By employing the aforementioned technical means, a power supply availability calculation system is constructed, transforming the abstract system reliability into a calculable and verifiable numerical indicator. Instantaneous power supply availability is calculated by the proportion of connected ventilation fans in a single scenario, and then combined with mathematical expectations to obtain the overall availability indicator, thus realizing the quantitative transformation from single-fault scenarios to long-term average system reliability.

[0013] In some embodiments, step S410 includes: Based on the set of lines, the availability status of each line under the fault scenario sample, combined with connectivity constraints, the connectivity between each wind turbine and the combiner station is determined. The connectivity constraints include: virtual flow source constraints for wind turbine nodes, flow conservation constraints for relay nodes, flow absorption constraints for combiner stations, total absorption flow constraints for combiner stations, and cable transmission capacity constraints.

[0014] By employing the aforementioned technical means, network flow theory is engineered and applied to determine the connectivity between wind turbines and combiner stations. The core function is to achieve accurate determination from "topological connectivity" to "effective power supply connectivity," avoiding the one-sidedness of traditional methods that only consider topological connections while ignoring cable transmission capacity.

[0015] In some embodiments, step S410 includes: If the primary path between the wind turbine and the combiner station is interrupted due to the existence of unavailable lines, then it is determined whether there is a redundant path between the wind turbine and the combiner station consisting of available lines. If a redundant path exists, the switching from the primary path to the redundant path is determined based on the probability of successful automatic switching. If the switching fails, the wind turbine and the combiner station will not be connected. If no redundant path exists, the wind turbine and the combiner station will not be connected.

[0016] By incorporating the quantification of the success probability of automatic switching into connectivity determination through the above-mentioned technical means, the actual fault tolerance effectiveness of redundant paths is truly reflected, which solves the problem of overly optimistic reliability estimation caused by existing redundancy designs that only plan the topology and ignore the actual performance of the switching device.

[0017] In some embodiments, step S410 includes: via s i This indicates the connectivity between fan i and the combiner station, s i =1 indicates that fan i is connected to the combiner station, s i =0 indicates that fan i is not connected to the combiner station; When the fan i corresponds to s i When =0, s is determined by considering the average repair time of each unavailable line. i The duration of =0 is determined, and its proportion within a unit of time is identified. Then, the corresponding s for wind turbine i is updated based on this proportion. i .

[0018] By incorporating the mean repair time into connectivity determination through the above technical means, and updating the time percentage of the wind turbine connectivity status by combining the mean repair time, the one-sidedness of traditional methods that only assess reliability based on the probability of failure while ignoring the duration of failure is solved, so that the reliability assessment can truly reflect the impact of long-term unavailability after a line failure on the power supply of the system.

[0019] In some embodiments, the contribution of the line is determined based on the ratio of the availability increment before and after the line is added to the cost of the line.

[0020] By combining availability increments with line costs through the above-mentioned technical means, redundancy optimization no longer involves blindly adding lines, but instead prioritizes lines that can bring the greatest reliability improvement per unit cost. Under the premise of meeting the preset power supply availability requirements, redundancy costs are minimized, solving the problem that existing redundancy designs are either too costly or lack reliability, and achieving a precise quantitative trade-off between cost and reliability.

[0021] A wiring design device for fault-tolerant offshore wind power collector lines, comprising: The undirected graph generation module is used to model wind turbines, combiner stations, and possible relay points of offshore wind farms as nodes, candidate cable lines between nodes as edges, determine the weight of each edge based on the cable line cost, and construct a weighted undirected graph. The fault scenario generation module is used to generate fault scenario samples based on a weighted undirected graph to form a fault scenario set. The fault scenario samples include the available status of each line in the weighted undirected graph. The initial route generation module is used to select cable routes based on a weighted undirected graph using the minimum spanning tree algorithm, and to construct the initial route set for offshore wind power collection lines. The availability calculation module is used to calculate the power supply availability of the line set based on the connectivity between each wind turbine and the combiner station under each fault scenario sample, and then determine the power supply availability index of the line set for the fault scenario set. The availability judgment module is used to execute the line addition module when the power supply availability index is lower than the preset index lower limit; otherwise, it outputs the cable routing scheme of the offshore wind power collection line based on the line set. The line addition module is used to add an unselected line to the line set, forming a temporary line set, calculate the power supply availability index of the temporary line set, and determine the contribution of the unselected line based on the availability increment and line cost. The route set update module is used to filter out the routes with the highest contribution from all unselected routes, update the route set, and return it to the availability calculation module.

[0022] A storage medium storing a computer program executable by a processor, wherein the computer program, when executed, implements the steps of the wiring design method for the offshore wind power collector line.

[0023] A wiring design device for offshore wind power collector lines includes a memory and a processor. The memory stores a computer program that can be executed by the processor. When the computer program is executed, it implements the steps of the wiring design method for the offshore wind power collector lines.

[0024] The beneficial effects of this invention are: This invention uses the minimum spanning tree as the initial cost-optimal topology, and by iteratively adding redundant lines with the highest reliability contribution, it minimizes the redundancy cost while meeting the preset power supply availability requirements. This solves the problems of traditional methods that ignore fault risk and waste redundancy design costs due to a single cost objective.

[0025] This invention employs Monte Carlo sampling for fault scenario simulation and a greedy incremental redundancy optimization strategy, which significantly reduces computational complexity while balancing solution efficiency and solution quality. It also constructs a power supply availability calculation system, transforming abstract system reliability into calculable and verifiable numerical indicators, making the reliability comparison of different topology schemes objective, and providing clear numerical basis for redundancy optimization.

[0026] This invention quantifies and integrates core engineering parameters such as failure probability per unit time, transmission capacity, success probability of automatic switching, and average repair time into the entire process of fault scenario generation, connectivity determination, and availability assessment. This binds redundant design with the actual fault characteristics and maintenance capabilities of the cable, avoiding the one-sidedness of experience-based design and ensuring the practical implementation of fault tolerance. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating the wiring design method for offshore wind power collector lines in this embodiment.

[0028] Figure 2 This is a schematic diagram of the basic scenario of the offshore wind farm to be optimized in the embodiment.

[0029] Figure 3 This is a schematic diagram of the fault-tolerant cable routing scheme obtained after optimization in the embodiment. Detailed Implementation

[0030] The embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. The step numbers in the following embodiments are set only for ease of explanation, and there is no limitation on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0031] In the description of this invention, "multiple" means two or more. The use of "first" and "second" is for distinguishing technical features only and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or the order of the indicated technical features. Furthermore, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art.

[0032] Example 1: As Figure 1 As shown, this embodiment presents a wiring design method for fault-tolerant offshore wind power collector lines, specifically including the following steps:

[0033] S100. Model the wind turbines, combiner stations, and possible relay points of the offshore wind farm as nodes, and model the candidate cable lines between nodes as edges. Determine the weight of each edge based on the cable line cost, and construct a weighted undirected graph.

[0034] In this embodiment, the offshore wind farm is assumed to consist of a collection of wind turbines. Convergence Station Assembly and possible relay node set Composition, a set consisting of all nodes. .

[0035] In the ocean, the permitted cable paths form a weighted undirected graph. Each candidate edge The attribute is a tuple To indicate, among which It is the path length. It is the unit cost. It is the probability of failure per unit time. It is the transmission capacity. It's the probability of automatic switching succeeding. It is the average repair time. and Representing edges respectively Outflow nodes and inflow nodes.

[0036] S200. Based on a weighted undirected graph, generate fault scenario samples to form a fault scenario set. The fault scenario sample includes the availability status (available or unavailable) of each line in the weighted undirected graph.

[0037] This embodiment is based on a weighted undirected graph and uses Monte Carlo sampling to generate a set of independent and identically distributed fault scenarios to approximate the probability constraint of the expected availability.

[0038] Each line With a given failure probability per unit time This represents the probability that a failure (leading to a disconnection) will occur within any given year. To handle randomness, the failure is treated as a two-dimensional Bernoulli event, and a sampled set of scenarios is obtained through Monte Carlo simulation. .

[0039] For each scenario For each line To conduct a Bernoulli trial, define: (1.1)

[0040] S300. Based on a weighted undirected graph, the minimum spanning tree algorithm is used to select cable routes and construct the initial set of offshore wind power collection lines. .

[0041] S400, based on line sets Under each fault scenario sample, the power supply availability of the line set is calculated based on the connectivity between each wind turbine and the combiner station, thereby determining the power supply availability index of the line set for the fault scenario set. .

[0042] S410. Based on the line set, combined with the availability status of each line in the fault scenario sample, and combined with the transmission capacity... Automatic switching success rate and average repair time In addition, connectivity constraints are used to determine the connectivity between each wind turbine and the combiner station.

[0043] In this embodiment, connectivity constraints include: virtual flow source constraints at wind turbine nodes (each wind turbine can emit a maximum of 1 unit of virtual flow), flow conservation constraints at relay nodes, flow absorption constraints at combiner stations (the combiner station only absorbs flow and does not emit flow), total absorbed flow constraints at combiner stations (the total flow absorbed by the combiner station is equal to the sum of the virtual flows of the connected wind turbines), and cable transmission capacity constraints (the total virtual flow carried by a single line does not exceed its transmission capacity). ).

[0044] This embodiment uses binary variables. Characterizing the fan Connectivity with the combiner station For connectivity, If the connection is not established, the determination is made by combining the availability status of the line with multi-dimensional connectivity constraints. The specific rules include: A. If the main path between the wind turbine and the combiner station is interrupted due to an unavailable line (there is line e on the main path and...) If the condition is met, then it is determined whether there is a redundant path consisting of available lines between the wind turbine and the combiner station.

[0045] If at least one redundant path exists, then the success rate of automatic handover is used as the basis. Determine the success of the switch from the primary path to the redundant path. If the switch is successful, then... If the switching fails, the wind turbine and the combiner station cannot be connected via this redundant path. If all redundant paths fail to switch, then the following condition is met: ; If no redundant path exists, then the wind turbine and the combiner station are not connected, and the determination is made accordingly. .

[0046] B. When fan i corresponds to At the same time, the average repair time of each unavailable line is taken into account. (such as coastal routes) (Value range: 24-72 hours) Determine Duration (after successful repair) i =1), determine the proportion of this duration in the unit time, and use (1-( (Continued time percentage) as the corresponding wind turbine i (e.g., 0.9) to allow the connectivity status to reflect the long-term effects of the fault.

[0047] S420. Based on the proportion of ventilation fans connected to the combiner station among all fans, determine the power supply availability of the line set under the fault scenario sample.

[0048] This embodiment describes the operation of each fan under fault scenario m. The summation of the values ​​is used as the ratio of the total number of remaining wind turbines to the power supply availability under fault scenario m.

[0049] S430. Based on the power supply availability of the line set under each fault scenario sample, and combined with the mathematical expectation of each fault scenario sample, determine the power supply availability index of the line set for the fault scenario set.

[0050] In this embodiment, the entire network is viewed as a multi-source, multi-sink system. Given the cabling scheme, the power supply availability of the network can be expressed using the following mathematical expectation. To indicate: (1.2) Decision variables are considered to be of the following three types, including binary 0-1 variables. , indicating edge Whether it is laid as a primary or backup; binary 0-1 variable , indicating in the scene In the event of a malfunction, the fan Can a connection be established to a certain merge station through an existing and currently available edge sequence? (Non-negative variables) , indicating in the scene Below is the fan. Virtual unit flow at the edge The flow rate is important to note; this variable is used to determine connectivity, not the actual current. The objective function is the cable cost of the collector line system.

[0051] (1.3a) (1.3b) (1.3c) (1.3d) (1.3e) (1.3f) (1.3g) (1.3h) (1.3i) (1.3j) In equation (1.3a) The total path cost of the collector network; Equation (1.3b) indicates that the power supply availability of the system needs to be higher than the lower limit. Equation (1.3c) corresponds to the virtual flow source constraint of the wind turbine node, indicating that the wind turbine node is a unit virtual flow source, if Then the fan In the sample One unit of virtual flow needs to be emitted; Equation (1.3d) corresponds to the flow conservation constraint of the relay node, indicating that the flow of the relay node is conserved; Equation (1.3e) corresponds to the flow absorption constraint of the combiner station, indicating that the combiner station is allowed to absorb flow but does not generate flow; Equation (1.3f) corresponds to the total absorption flow constraint of the combiner station, indicating that all combiner stations have a certain influence on the wind turbine. The total absorption is Equation (1.3g) represents the edge in the sample. A flow is only permitted when the cable is available and laid (otherwise it is prohibited); Equation (1.3h) corresponds to the cable transmission capacity constraint, indicating that the total aggregated virtual flow of an edge does not exceed its capacity. Equation (1.3i) indicates that if If the source cannot send a stream, then equation (1.3j) is the variable domain.

[0052] Mathematical expectation in this embodiment The calculation can be approximated using Monte Carlo simulation, and the formula is shown below.

[0053] (1.4) In the formula, Set of fault scenarios Number of fault scenarios.

[0054] S500, when the power supply availability index is lower than the preset lower limit value If the condition is met, proceed to step S600; otherwise, output the cable routing scheme for offshore wind power collection lines based on the line set.

[0055] S600 is a set of lines. Add an unselected route To form a temporary set of routes The power supply availability index of the temporary line set is calculated using the method in step S400. The contribution of the unselected line is determined based on availability increments and line costs. The formula for calculating contribution is as follows: (1.5)

[0056] S700: For all unselected lines, repeat step S600 to select the line with the highest contribution. Update the route set Then return to step S400.

[0057] For ease of understanding, this embodiment selects an offshore wind farm containing 36 wind turbines as the experimental scenario. The turbine locations and seabed topographic constraints are shown in the attached figure. Figure 2 As shown.

[0058] First, the traditional minimum spanning tree method was used for cabling optimization to obtain an initial topology with a total cost equal to the baseline of 100%. However, Monte Carlo simulation evaluation showed that the system's annual availability was only 82.3%. Subsequently, the method proposed in this invention was applied, setting a system availability target of 90% as an optimization constraint. The model automatically identifies critical vulnerable paths in the network by quantifying cable failure rates and repair time parameters.

[0059] After optimization using a heuristic algorithm based on redundant incremental greed, the following results were obtained: Figure 3 The redundant cabling scheme shown adds six redundant cables to the critical backbone path. The optimized total cost increases to 122.5% of the baseline, but the system's annual availability significantly improves to 91.6%, meeting the preset target. In contrast, if an empirical dual-ring network redundancy design is used, the total cost reaches 152.3% of the baseline, while the system availability is 94.7%. This demonstrates that the method of this invention can achieve a similar level of high reliability with a lower cost increment.

[0060] In a large-scale scenario test involving 200 wind turbines, the heuristic algorithm proposed in this invention completed the optimization solution within 30 minutes, while the mixed integer programming method using precise modeling failed to obtain a feasible solution after 2 hours, demonstrating the efficiency and practicality of the method in this invention when dealing with large-scale practical problems.

[0061] Example 2: This example is a wiring design device for fault-tolerant offshore wind power collector lines, including: The undirected graph generation module is used to model wind turbines, combiner stations, and possible relay points of offshore wind farms as nodes, candidate cable lines between nodes as edges, determine the weight of each edge based on the cable line cost, and construct a weighted undirected graph. The fault scenario generation module is used to generate fault scenario samples based on a weighted undirected graph to form a fault scenario set. The fault scenario samples include the available status of each line in the weighted undirected graph. The initial route generation module is used to select cable routes based on a weighted undirected graph using the minimum spanning tree algorithm, and to construct the initial route set for offshore wind power collection lines. The availability calculation module is used to calculate the power supply availability of the line set based on the connectivity between each wind turbine and the combiner station under each fault scenario sample, and then determine the power supply availability index of the line set for the fault scenario set. The availability judgment module is used to execute the line addition module when the power supply availability index is lower than the preset index lower limit; otherwise, it outputs the cable routing scheme of the offshore wind power collection line based on the line set. The line addition module is used to add an unselected line to the line set, forming a temporary line set, calculate the power supply availability index of the temporary line set, and determine the contribution of the unselected line based on the availability increment and line cost. The route set update module is used to filter out the routes with the highest contribution from all unselected routes, update the route set, and return it to the availability calculation module.

[0062] Example 3: This example is a storage medium that stores a computer program that can be executed by a processor. When the computer program is executed, it implements the steps of the wiring design method for offshore wind power collection lines described in Example 1.

[0063] Example 4: This example is a wiring design device for offshore wind power collection lines, which has a memory and a processor. The memory stores a computer program that can be executed by the processor. When the computer program is executed, it implements the steps of the wiring design method for offshore wind power collection lines described in Example 1.

[0064] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0065] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0066] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the aforementioned program can be printed, because the aforementioned program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0067] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0068] In the foregoing description of this specification, references to terms such as "one embodiment," "another embodiment," or "some embodiments" indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0069] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0070] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A wiring design method for fault-tolerant offshore wind power collector lines, characterized in that, include: S100. Model the wind turbines, combiner stations, and possible relay points of the offshore wind farm as nodes, and model the candidate cable lines between nodes as edges. Determine the weight of each edge based on the cable line cost, and construct a weighted undirected graph. S200. Based on the weighted undirected graph, generate fault scenario samples to form a fault scenario set. The fault scenario samples include the available status of each line in the weighted undirected graph. S300. Based on a weighted undirected graph, the minimum spanning tree algorithm is used to select cable lines and construct the initial set of offshore wind power collection lines. S400. Based on the line set, under each fault scenario sample, calculate the power supply availability of the line set according to the connectivity between each wind turbine and the combiner station, and then determine the power supply availability index of the line set for the fault scenario set. S500: When the power supply availability index is lower than the preset lower limit, execute step S600; otherwise, output the cable routing scheme of the offshore wind power collection line based on the line set. S600. Add an unselected line to the line set to form a temporary line set. Calculate the power supply availability index of the temporary line set and determine the contribution of the unselected line based on the availability increment and line cost. S700. For all unselected lines, filter out the lines with the highest contribution, update the line set, and return to step S400.

2. The wiring design method for fault-tolerant offshore wind power collector lines according to claim 1, characterized in that, Step S200 includes: Based on a weighted undirected graph, a set of independent and identically distributed fault scenario samples is generated using Monte Carlo sampling. Cable line faults are defined as two-dimensional Bernoulli discrete random events. Based on the failure probability per unit time of each line, a Bernoulli test is performed on the line to determine the usability of the cable line in the fault scenario samples.

3. The wiring design method for fault-tolerant offshore wind power collector lines according to claim 1, characterized in that, Step S400 includes: S410. Based on the set of lines and the availability status of each line in the fault scenario sample, determine the connectivity between each wind turbine and the combiner station. S420. Based on the proportion of ventilation fans connected to the combiner station among all fans, determine the power supply availability of the line set under the sample of the fault scenario. S430. Based on the power supply availability of the line set under each fault scenario sample, and combined with the mathematical expectation of each fault scenario sample, determine the power supply availability index of the line set for the fault scenario set.

4. The wiring design method for fault-tolerant offshore wind power collector lines according to claim 3, characterized in that, Step S410 includes: Based on the set of lines, the availability status of each line under the fault scenario sample, combined with connectivity constraints, the connectivity between each wind turbine and the combiner station is determined. The connectivity constraints include: virtual flow source constraints for wind turbine nodes, flow conservation constraints for relay nodes, flow absorption constraints for combiner stations, total absorption flow constraints for combiner stations, and cable transmission capacity constraints.

5. The wiring design method for fault-tolerant offshore wind power collector lines according to claim 3 or 4, characterized in that, Step S410 includes: If the primary path between the wind turbine and the combiner station is interrupted due to the existence of unavailable lines, then it is determined whether there is a redundant path between the wind turbine and the combiner station consisting of available lines. If a redundant path exists, the switching from the primary path to the redundant path is determined based on the probability of successful automatic switching. If the switching fails, the wind turbine and the combiner station will not be connected. If no redundant path exists, the wind turbine and the combiner station will not be connected.

6. The wiring design method for fault-tolerant offshore wind power collector lines according to claim 3, characterized in that, Step S410 includes: via s i This indicates the connectivity between fan i and the combiner station, s i =1 indicates that fan i is connected to the combiner station, s i =0 indicates that fan i is not connected to the combiner station; When the fan i corresponds to s i When =0, s is determined by considering the average repair time of each unavailable line. i The duration of =0 is determined, and its proportion within a unit of time is identified. Then, the corresponding s for wind turbine i is updated based on this proportion. i .

7. The wiring design method for fault-tolerant offshore wind power collector lines according to claim 1, characterized in that, The contribution of the line is determined based on the ratio of the availability increment before and after the line is added to the cost of the line.

8. A wiring design device for fault-tolerant offshore wind power collector lines, characterized in that, include: The undirected graph generation module is used to model wind turbines, combiner stations and possible relay points of offshore wind farms as nodes, candidate cable lines between nodes as edges, determine the weight of each edge based on the cable line cost, and construct a weighted undirected graph. The fault scenario generation module is used to generate fault scenario samples based on a weighted undirected graph to form a fault scenario set. The fault scenario samples include the available status of each line in the weighted undirected graph. The initial route generation module is used to select cable routes based on a weighted undirected graph using the minimum spanning tree algorithm, and to construct the initial route set for offshore wind power collection lines. The availability calculation module is used to calculate the power supply availability of the line set based on the connectivity between each wind turbine and the combiner station under each fault scenario sample, and then determine the power supply availability index of the line set for the fault scenario set. The availability judgment module is used to execute the line addition module when the power supply availability index is lower than the preset index lower limit; otherwise, it outputs the cable routing scheme of the offshore wind power collection line based on the line set. The line addition module is used to add an unselected line to the line set, forming a temporary line set, calculate the power supply availability index of the temporary line set, and determine the contribution of the unselected line based on the availability increment and line cost. The route set update module is used to filter out the routes with the highest contribution from all unselected routes, update the route set, and return it to the availability calculation module.

9. A storage medium having a computer program stored thereon that can be executed by a processor, characterized in that, When the computer program is executed, it implements the steps of the wiring design method for offshore wind power collection lines according to any one of claims 1 to 7.

10. A wiring design device for offshore wind power collector lines, comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, characterized in that, When the computer program is executed, it implements the steps of the wiring design method for offshore wind power collection lines according to any one of claims 1 to 7.

Images