Optimal configuration method and device for DC circuit breaker of offshore wind plant

Abstract

The invention provides an optimal configuration method and device for an offshore wind power plant direct current circuit breaker, and relates to the technical field of wind power plant configuration optimization. The method comprises the following steps: performing reliability evaluation on electrical equipment in a target topological structure by adopting a Markov chain to obtain fault data of the electrical equipment; and according to the multiple fan power scenes and the fault data, element state sampling is performed on the target topological structure under each candidate configuration scheme based on a sequential Monte Carlo double sampling method, fan output power corresponding to each candidate configuration scheme is obtained, and an optimal configuration scheme is determined. According to the invention, the dynamic fault characteristics of the electrical equipment can be accurately described, and the coupling problem of the output randomness of the fan and the uncertainty of the equipment fault can be efficiently solved. Quantitative performance evaluation of different network structures in a complex random environment is realized, an optimal switch configuration decision basis considering reliability and economical efficiency is provided, and the adaptability of a power distribution network to wind power fluctuation and the power supply reliability are effectively improved.

Description

Technical Field

[0001] This disclosure relates to the field of wind farm configuration optimization technology, and in particular to a method and apparatus for optimizing the configuration of DC circuit breakers in offshore wind farms. Background Technology

[0002] In power collection systems, the selection of switch configurations is crucial, affecting not only system reliability and stability but also the project's economics and operating costs. On one hand, optimizing switch configurations can improve system reliability, reduce the likelihood of fault occurrence and propagation, thereby lowering maintenance and repair costs and improving the availability and overall efficiency of the wind farm. On the other hand, an excessive pursuit of reliability may increase construction and operation and maintenance costs, impacting the project's economics and return on investment. Therefore, balancing reliability and economy and optimizing switch configurations when faced with different options presents a challenge. Summary of the Invention

[0003] This disclosure aims to at least partially address one of the technical problems in the related art.

[0004] Therefore, the first aspect of this disclosure proposes an optimized configuration method for DC circuit breakers in offshore wind farms, comprising the following steps: Determine the target topology of the offshore wind farm's power collection system and multiple candidate configuration schemes for DC circuit breakers under the target topology; A Markov chain is used to perform a reliability assessment on the electrical equipment in the target topology to obtain fault data of the electrical equipment, including failure rate and repair rate. Based on multiple preset wind turbine power scenarios and the fault data, the component state of the target topology under each candidate configuration scheme is sampled using the sequential Monte Carlo double sampling method to obtain the wind turbine output power corresponding to each candidate configuration scheme. The reliability index of each candidate configuration scheme is determined based on the wind turbine's output power corresponding to each candidate configuration scheme; The optimal configuration scheme is determined from the multiple candidate configuration schemes based on the reliability index.

[0005] A second aspect of this disclosure provides an optimized configuration device for DC circuit breakers in offshore wind farms, comprising: The first determining module is used to determine the target topology of the offshore wind farm collection system and multiple candidate configuration schemes of DC circuit breakers under the target topology. The first evaluation module is used to perform a reliability evaluation of the electrical equipment in the target topology using a Markov chain, and to obtain the fault data of the electrical equipment, including the failure rate and the repair rate. The second evaluation module is used to sample the component states of the target topology under each candidate configuration scheme based on the sequential Monte Carlo double sampling method according to the preset multiple wind turbine power scenarios and the fault data, so as to obtain the wind turbine output power corresponding to each candidate configuration scheme. The third evaluation module is used to determine the reliability index of each candidate configuration scheme based on the wind turbine's output power corresponding to each candidate configuration scheme; The second determining module is used to determine an optimal configuration scheme from the plurality of candidate configuration schemes based on the reliability index. A third aspect of this disclosure provides an electronic device, including: a processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method described in the first aspect above.

[0006] The optimized configuration method for DC circuit breakers in offshore wind farms disclosed herein accurately characterizes the dynamic fault characteristics of electrical equipment through Markov chains, providing an accurate basis for component state transition probabilities for reliability assessment. It utilizes a sequential Monte Carlo double sampling method to efficiently handle the coupling problem between the randomness of wind turbine output and the uncertainty of equipment failure, evaluating each candidate configuration scheme and eliminating sampling error differences in traditional serial evaluation, ensuring the fairness and accuracy of scheme comparison. By calculating the maximum output power of wind turbines under each configuration scheme, the reliability assessment results are transformed into directly comparable power supply capacity indicators, realizing quantitative performance evaluation of different network structures under complex stochastic environments. This provides a basis for optimal switch configuration decisions that balance reliability and economy for power grid planning with a high proportion of renewable energy, effectively improving the adaptability of the distribution network to wind power fluctuations and the reliability of power supply.

[0007] Additional aspects and advantages of this disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0008] The above and / or additional aspects and advantages of this disclosure will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which: Figure 1 A flowchart illustrating an optimized configuration method for a DC circuit breaker in an offshore wind farm, provided as an embodiment of this disclosure; Figure 2 A schematic diagram of a Markov model of a basic component of an electrical device provided in an embodiment of this disclosure; Figure 3 A Markov two-state fault variation diagram for a component is provided in an embodiment of this disclosure; Figure 4 A schematic diagram of fault data obtained by reliability assessment using a Markov chain, provided as an embodiment of this disclosure; Figure 5 A flowchart for calculating the reliability of a current collector system is provided as an embodiment of this disclosure; Figure 6 A series-parallel collector system topology diagram provided in this disclosure embodiment; Figure 7 This is a schematic diagram illustrating the reliability calculation results under a series-parallel collector system topology provided in an embodiment of this disclosure; Figure 8 A schematic diagram illustrating the life-cycle loss cost of a series-parallel collector system topology provided in this embodiment of the disclosure; Figure 9 A two-stage boost collector system topology diagram provided in this disclosure embodiment; Figure 10 This is a schematic diagram illustrating the reliability calculation results of a two-stage boost collector system topology provided in an embodiment of this disclosure. Figure 11 A schematic diagram illustrating the total lifecycle loss cost of a two-stage boost collector system topology provided in this disclosure embodiment; Figure 12 This is a schematic diagram of an optimized configuration device for a DC circuit breaker in an offshore wind farm, provided as an embodiment of the present disclosure. Detailed Implementation

[0009] Embodiments of this disclosure are described in detail below, examples of which are illustrated 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 intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0010] Specifically, the optimized configuration method and apparatus for DC circuit breakers in offshore wind farms according to embodiments of the present disclosure are described below with reference to the accompanying drawings.

[0011] Figure 1 This is a flowchart illustrating an optimized configuration method for DC circuit breakers in offshore wind farms, provided as an embodiment of this disclosure. Figure 1 As shown, the optimized configuration method for the DC circuit breaker in this offshore wind farm may include the following steps: Step 101: Determine the target topology of the offshore wind farm collection system and multiple candidate configuration schemes for DC circuit breakers under the target topology.

[0012] Optionally, the multiple candidate configuration schemes of the DC circuit breaker can be multiple DC circuit breaker configuration rates under the target topology.

[0013] Optionally, the target topology may include any of the following: serial-parallel topology, parallel-serial topology, matrix topology, two-stage boost topology, centralized boost topology, and terminal boost topology.

[0014] Step 102: Use Markov chains to perform reliability assessment on electrical equipment in the target topology to obtain fault data of electrical equipment, including failure rate and repair rate.

[0015] Offshore wind farm power collection systems are mainly composed of a series of electrical devices connected in a specific manner. The correctness and rationality of these connections directly impact the system's reliability. The electrical equipment in a power collection system typically consists of multiple components, and the overall operating state of the equipment is determined by the availability of these basic components. Stochastic processes describe the state transition relationships between random events. In this embodiment, a Markov process is used to describe the state of a multi-state system or component at a given moment. Markov chains are used to assess the reliability of the equipment components. Figure 2 This diagram illustrates a Markov model of a basic component of an electrical device according to an embodiment of this disclosure. The component exists in two states: normal and faulty, transitioning between these states with a fixed probability. Here, λ represents the component's failure rate, and μ represents its maintenance rate.

[0016] Availability is the probability that a component or system is operating normally at a given moment. The average failure rate and average repair rate of a device composed of r components are calculated using the following formula:

[0017]

[0018]

[0019]

[0020] in, The number of components in an electrical device. For the first Failure rate of individual components For the first Repair rate of individual components. The availability of electrical equipment refers to the probability of its operating state. The unavailability of electrical equipment, i.e., the probability of a fault state.

[0021] A Markov chain is used to divide a time-continuous stochastic process into a finite number of discrete states (the number of states depends on the required accuracy of the model). The set of all discrete states and the transition relationships between them constitute a Markov chain. For a Markov chain with N states, the transition rate between state i and state j can be expressed as:

[0022] in, The transfer rate (times / hour) This represents the number of transitions from state i to state j. Let represent the duration of state i over the entire statistical period. Markov process approximation can be described as the limiting state probability remaining constant during further transitions.

[0023] For ease of analysis, the state transition matrix is ​​defined as follows: its dimension is the number of states, meaning each state corresponds to one column and one row in the transition matrix. If there is a transition from state i to state j, then the transition rate is... An element is assigned to the element in the i-th row and j-th column of the matrix; otherwise, the element is zero. The diagonal elements of the state transition matrix are equal to 1 minus the sum of the remaining elements in that row. A transition matrix containing N states can be represented as:

[0024] According to the Markov process approximation principle, the following equation holds:

[0025] For ease of solving, the above equation can be rewritten as:

[0026] Transpose both sides of the above equation to get:

[0027] in, It is the identity matrix. Here is the state transition matrix. Let be the probability vector of the state.

[0028] The above equation is a system of linear equations with N unknowns. Solving this system of equations will give the probability of each state. However, since the rank of the matrix TI is N-1, that is, only N-1 equations in the above equation are independent. We need to add an equation that is linearly independent of the N equations in the above equation in order to obtain a unique solution.

[0029] Based on the normality of probability and the countable additivity, we can obtain:

[0030] Where P represents the probability of a state occurring, and N is the number of states.

[0031]

[0032] The above equation is a system of linear equations with N unknowns. The probability of each state occurring can be obtained by solving the system of linear equations. The frequency of entering state n can be expressed as:

[0033] in, Let be the probability of state i. It is the transition rate of leaving state i. Let be the transition number when leaving state i.

[0034] The average duration of stay in each state is the reciprocal of the sum of the transition rates from leaving that state, as shown in the following formula:

[0035] in, Let be the average duration of remaining in state i. The frequency and duration in both states are given by the following formulas:

[0036]

[0037] In reliability assessment, the exponential distribution is the most important distribution type. Assuming the duration of a certain state of a random event follows an exponential distribution, its cumulative probability distribution function can be expressed as:

[0038] in, Let T represent the cumulative distribution function of the state duration, and let T represent the average duration of the state. Generate one uniformly distributed random number R, and ensure that:

[0039] Using the inverse transform method, we can obtain:

[0040] Where D represents the actual duration of the state, T represents the average duration of the state, and R is a random number in the interval [0, 1]. Figure 3 This invention provides a Markov two-state fault variation diagram for a component, as shown in the embodiments of this disclosure. Taking electrical equipment such as fans, cables, and DC / DC transformers as examples, Figure 4 This is a schematic diagram of fault data obtained by using a Markov chain for reliability assessment, as provided in an embodiment of this disclosure.

[0041] Step 103: Based on multiple preset wind turbine power scenarios and fault data, the component state of the target topology under each candidate configuration scheme is sampled using the sequential Monte Carlo double sampling method to obtain the wind turbine output power corresponding to each candidate configuration scheme.

[0042] Each wind turbine output scenario includes the wind turbine's power generation at multiple moments within a preset time period. In some embodiments of this disclosure, multiple wind turbine power scenarios can be simulated based on historical data from offshore wind farms.

[0043] In some embodiments of this disclosure, for each candidate configuration scheme, multiple wind turbine power scenarios can be probabilistically sampled based on the sequential Monte Carlo double sampling method, and the component state of the target topology can be sampled based on fault data to obtain the double sampling state; the wind turbine power that the target topology can deliver under the double sampling state can be determined. Figure 5 A flowchart for calculating the reliability of a current collector system is provided for an embodiment of this disclosure.

[0044] The sequential Monte Carlo method, based on equipment failure and repair rates, uses computer-generated pseudo-random numbers to sample the operating states of equipment, determining the start-up and shutdown sequence of equipment within a preset time period (e.g., 8760 hours per year). Failures are analyzed hourly, sequentially for each hourly segment. Then, based on the equipment's position in the system, its impact on the reliability of related loads is assessed, equipment state sampling is performed, and equipment failure analysis is conducted. The time of entry and exit from each failure is determined to calculate the duration of each system failure. Once the preset time period is calculated, the system's reliability index for that period can be obtained. The system is simulated for multiple preset time periods using the same method, and its average reliability index is calculated.

[0045] The sequential Monte Carlo method preserves the temporal nature of the system, such as the load changes over time, and can simulate the duration of the system in each state. Therefore, this algorithm can be used to obtain the reliability indicators of each load in the power collection system, such as the system average outage frequency SAIFI, the system average outage duration SAIDI, the average power availability ASAI, and the expected power shortage EENS.

[0046] Step 104: Determine the reliability index of each candidate configuration scheme based on the wind turbine's output power corresponding to each candidate configuration scheme.

[0047]

[0048]

[0049] in, This serves as a reliability metric for candidate configuration schemes. The power output of the wind turbine corresponding to the candidate configuration scheme. This refers to the number of wind turbines in an offshore wind farm. This refers to the rated power of the fan. For the preset time period, The topological equivalent outage rate of the collector system.

[0050] Step 105: Determine the optimal configuration scheme from multiple candidate configuration schemes based on reliability indicators.

[0051] In some embodiments of this disclosure, in addition to selecting an optimized configuration scheme based on reliability, a comprehensive evaluation can also be conducted in conjunction with economic indicators.

[0052] In one implementation, the initial investment cost and life-cycle loss cost of each candidate configuration scheme can be determined; the economic indicators of each candidate configuration scheme can be determined based on the initial investment cost and life-cycle loss cost; the comprehensive evaluation index of each candidate configuration scheme can be determined based on the economic indicators and reliability indicators; and the optimal configuration scheme can be determined from multiple candidate configuration schemes based on the comprehensive evaluation index of each candidate scheme.

[0053] The comprehensive evaluation indicators can be referenced using the following formula:

[0054]

[0055] in, For comprehensive evaluation indicators, For the cost of wind turbines, For cable costs, For the cost of DC / DC converters, To increase the cost of the boost platform, This represents the total loss cost of the current collection system over its operational lifespan. For the opportunity cost of failure, Cost of loss per unit of failure, This serves as a reliability metric for candidate configuration schemes. This refers to the lifespan of a wind farm (e.g., 25 years).

[0056] By implementing the embodiments of this disclosure, the dynamic fault characteristics of electrical equipment are accurately characterized by Markov chains, providing an accurate basis for component state transition probabilities for reliability assessment. The sequential Monte Carlo double sampling method is used to efficiently handle the coupling problem between the randomness of wind turbine output and the uncertainty of equipment failure, evaluating each candidate configuration scheme and eliminating sampling error differences in traditional serial evaluation, ensuring the fairness and accuracy of scheme comparison. By calculating the maximum output power of wind turbines under each configuration scheme, the reliability assessment results are transformed into directly comparable power supply capacity indicators, realizing quantitative performance evaluation of different network structures under complex random environments. This provides an optimal switch configuration decision basis that balances reliability and economy for power grid planning with a high proportion of new energy sources, effectively improving the distribution network's adaptability to wind power fluctuations and power supply reliability.

[0057] To better understand the optimized configuration method of DC circuit breakers for offshore wind farms proposed in the embodiments of this disclosure, the following configuration optimization example selects typical topologies of series and parallel types: series-parallel type and two-stage boost type.

[0058] Assuming a wind farm capacity of 300MW, a turbine rated output power of 10MW, and a terminal voltage of 5kV, the wind farm will have a total of 30 turbines. The collection line voltage is 50kV. The distance between adjacent turbines on the same feeder is set to 5-10 times the rotor diameter (D), and the distance between adjacent feeders is set to 7-12D. Therefore, in this example, the distance between wind turbines on the same feeder is set to 10D, the distance between adjacent feeders is set to 10D, and the distance between the feeder DC / DC converter and the platform DC / DC converter is set to 5km.

[0059] Figure 6 This is a topology diagram of a series-parallel power collection system provided in an embodiment of this disclosure. The characteristic of the series topology is that the voltage is boosted by a series connection of wind turbines, rather than by a DC-DC converter. The voltage level of the bus is 50kV, and the voltage at the wind turbine ports is 5kV; therefore, 10 wind turbines are connected in series, forming three parallel strings. On the series feeder, if one wind turbine fails and disconnects from the grid, the line is broken, and all wind turbines on the feeder will also disconnect from the grid. If a DC circuit breaker is installed at the wind turbine terminal, the circuit breaker can disconnect the wind turbine output line to isolate the fault and connect the bypass, without affecting the output power of other wind turbines. Figure 7 This is a schematic diagram illustrating the reliability calculation results under a series-parallel collector system topology provided in an embodiment of this disclosure. Figure 8This diagram illustrates the lifecycle loss cost of a series-parallel collector system topology provided in this embodiment. SP represents the series-parallel structure, SP_0 is the traditional switch configuration scheme, with a 0% circuit breaker configuration rate at the output ports of each wind turbine except for the busbar, and SP_100 is the full configuration scheme, with DC circuit breakers configured at the output ports of each wind turbine, i.e., a configuration rate of 100%. The others represent partial configuration schemes for each configuration rate.

[0060] As shown in the figure, the equivalent outage rate Qn of the topology is below 10%. Reliability continuously improves with increasing circuit breaker configuration rate, reaching a maximum of around 1%. Throughout the entire lifecycle, wind turbines and cables remain constant as fixed assets. While increasing the circuit breaker configuration rate obviously increases circuit breaker costs, the improved reliability translates to increased power output from the wind farm, leading to increased network losses and reduced opportunity costs. The lifecycle cost decreases continuously with increasing switch configuration rate, reaching its lowest point at a 100% configuration rate. Therefore, the optimal configuration scheme for the 300MW wind farm series-parallel topology in this example is the fully configured scheme.

[0061] Figure 9 This is a topology diagram of a two-stage boost-type current collector system provided in an embodiment of this disclosure. The wind turbine is equipped with a DC transformer for the first voltage boost, and the voltage is then fed into a busbar connected in parallel with the wind turbine. After a second voltage boost via an offshore booster platform, the voltage is transmitted, hence the name two-stage boost-type. The voltage level of the busbar is also set to 50kV. Figure 10 This is a schematic diagram illustrating the reliability calculation results of a two-stage boost collector system topology provided in an embodiment of this disclosure. Figure 11 This diagram illustrates the lifecycle loss cost of a two-stage boost collector system topology provided in this embodiment. LJ_0 represents a conventional switch configuration scheme, with a 0% circuit breaker configuration rate at each wind turbine output port except for the busbar. LJ_100 represents a fully configured scheme, with DC circuit breakers configured at each wind turbine outlet, i.e., a 100% configuration rate. The others represent partial configuration schemes for each configuration rate.

[0062] As shown in the figure, the topological equivalent outage rate Qn is below 10%. With the increase in circuit breaker configuration rate, reliability continuously improves, reaching a maximum of around 1%. Furthermore, its topological equivalent outage rate is lower than that of the series-parallel topology, indicating better reliability. However, its economic efficiency is lower than the series-parallel structure. The DC SP structure does not include feeder DC / DC converters and platform DC / DC converters, eliminating converter investment and loss costs. Therefore, the total economic cost of the SP structure is significantly lower than that of the parallel structure. In terms of the entire life cycle, wind turbines, cables, DC transformers, and offshore platforms remain unchanged as fixed assets. With the increase in circuit breaker configuration rate, circuit breaker costs obviously increase. Improved reliability means increased power output from the wind farm, leading to increased network losses and reduced opportunity costs. The life cycle cost continuously decreases with the increase in switch configuration rate, reaching its lowest point at a 100% configuration rate. Therefore, the optimal configuration scheme for the two-stage boost topology of the 300MW wind farm in this example is the fully configured scheme.

[0063] Figure 12 This is a schematic diagram of an optimized configuration device for a DC circuit breaker in an offshore wind farm, provided as an embodiment of this disclosure. Figure 12 As shown, the optimized configuration device for the DC circuit breaker of the offshore wind farm may include: a first determination module 1201, a first evaluation module 1202, a second evaluation module 1203, a third evaluation module 1204, and a second determination module 1205.

[0064] The first determining module 1201 is used to determine the target topology of the offshore wind farm collection system and multiple candidate configuration schemes of DC circuit breakers under the target topology.

[0065] The first evaluation module 1202 is used to perform reliability evaluation on electrical equipment in the target topology using Markov chains, and obtain fault data of the electrical equipment, including failure rate and repair rate.

[0066] The second evaluation module 1203 is used to sample the component states of the target topology under each candidate configuration scheme based on the sequential Monte Carlo double sampling method according to multiple preset wind turbine power scenarios and fault data, so as to obtain the wind turbine output power corresponding to each candidate configuration scheme.

[0067] The third evaluation module 1204 is used to determine the reliability index of each candidate configuration scheme based on the wind turbine's output power corresponding to each candidate configuration scheme.

[0068] The second determining module 1205 is used to determine the optimal configuration scheme from multiple candidate configuration schemes based on reliability indicators.

[0069] In some embodiments of this disclosure, the second evaluation module 1203 is specifically used to: for each candidate configuration scheme, perform probability sampling on multiple wind turbine power scenarios based on the sequential Monte Carlo double sampling method, and perform component state sampling on the target topology based on fault data to obtain a double sampling state; and determine the wind turbine output power of the target topology under the double sampling state.

[0070] In some embodiments of this disclosure, the reliability index of a candidate configuration scheme is determined based on the wind turbine's output power corresponding to the candidate configuration scheme, including:

[0071]

[0072] in, This serves as a reliability metric for candidate configuration schemes. The power output of the wind turbine corresponding to the candidate configuration scheme. This refers to the number of wind turbines in an offshore wind farm. This refers to the rated power of the fan. For the preset time period, The topological equivalent outage rate of the collector system.

[0073] In some embodiments of this disclosure, the second determining module 1205 is specifically used for: determining the initial investment cost and the life-cycle loss cost of each candidate configuration scheme; determining the economic indicators of each candidate configuration scheme based on the initial investment cost and the life-cycle loss cost of each candidate configuration scheme; determining the comprehensive evaluation index of each candidate configuration scheme based on the economic indicators and the reliability indicators; and determining the optimal configuration scheme among multiple candidate configuration schemes based on the comprehensive evaluation index of each candidate scheme.

[0074] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0075] To implement the above embodiments, this disclosure also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments. To implement the above embodiments, this disclosure also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0076] To implement the above embodiments, this disclosure also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0077] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this disclosure. In this specification, the 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. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0078] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0079] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of this disclosure includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of this disclosure pertain.

[0080] 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-included 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. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), 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). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the 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 a computer memory.

[0081] It should be understood that various parts of this disclosure 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.

[0082] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0083] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0084] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A method for optimal configuration of offshore wind farm DC circuit breakers, characterized in that, The method comprises the following steps: determining a target topology of a power collection system of an offshore wind farm and a plurality of candidate configuration schemes of a DC circuit breaker under the target topology; performing reliability evaluation on electrical equipment in the target topology by using a Markov chain to obtain failure data of the electrical equipment, the failure data comprising a failure rate and a repair rate; based on a plurality of preset wind turbine power scenarios and the failure data, performing element state sampling on the target topology under each of the candidate configuration schemes based on a sequential Monte Carlo double sampling method to obtain wind turbine deliverable power corresponding to each of the candidate configuration schemes; determining a reliability index of each of the candidate configuration schemes based on the wind turbine deliverable power corresponding to each of the candidate configuration schemes; determining an optimized configuration scheme from the plurality of candidate configuration schemes according to the reliability index.

2. The method of claim 1, wherein, based on a plurality of preset wind turbine power scenarios and the failure data, performing element state sampling on the target topology under each of the candidate configuration schemes based on a sequential Monte Carlo double sampling method to obtain wind turbine deliverable power corresponding to each of the candidate configuration schemes, comprising: for each of the candidate configuration schemes, performing probability sampling on the plurality of wind turbine power scenarios based on the sequential Monte Carlo double sampling method, and performing element state sampling on the target topology based on the failure data to obtain a double sampling state; determining wind turbine deliverable power of the target topology in the double sampling state.

3. The method of claim 1, wherein, determining a reliability index of a candidate configuration scheme based on wind turbine deliverable power corresponding to the candidate configuration scheme, comprising: wherein, is a reliability index of the candidate configuration scheme, is a deliverable power of the wind turbine corresponding to the candidate configuration scheme, is a number of wind turbines of the offshore wind farm, is a rated power of the wind turbine, is a preset time period, is a topology equivalent outage rate of the power collection system.

4. The method of claim 1, wherein, the determining an optimized configuration scheme from the plurality of candidate configuration schemes according to the reliability index, comprising: determining an initial investment cost and a life cycle loss cost of each of the candidate configuration schemes; determining an economic index of each of the candidate configuration schemes according to the initial investment cost and the life cycle loss cost of each of the candidate configuration schemes; determining a comprehensive evaluation index of each of the candidate configuration schemes based on the economic index and the reliability index; determining an optimized configuration scheme from the plurality of candidate configuration schemes based on the comprehensive evaluation index of each of the candidate configuration schemes.

5. The method of claim 1, wherein, The target topology comprises any one of the following: a series-parallel topology, a parallel-series topology, a matrix topology, a two-stage boosting topology, a centralized boosting topology, and a machine-end boosting topology.

6. An apparatus for optimizing configuration of a DC circuit breaker for an offshore wind farm, characterized in that, comprising: a first determination module configured to determine a target topology of a power collection system of an offshore wind farm and a plurality of candidate configuration schemes of a DC circuit breaker under the target topology; a first evaluation module configured to perform reliability evaluation on electrical equipment in the target topology by using a Markov chain to obtain failure data of the electrical equipment, the failure data comprising a failure rate and a repair rate; a second evaluation module configured to perform element state sampling on the target topology under each of the candidate configuration schemes based on a sequential Monte Carlo double sampling method according to a plurality of preset wind turbine power scenarios and the failure data to obtain wind turbine deliverable power corresponding to each of the candidate configuration schemes; A third evaluation module is configured to determine a reliability index of each candidate configuration scheme based on the fan deliverable power corresponding to each candidate configuration scheme; A second determination module is configured to determine an optimal configuration scheme from the plurality of candidate configuration schemes according to the reliability index.

7. The apparatus of claim 6, wherein, The second evaluation module is specifically configured to: For each candidate configuration scheme, perform probabilistic sampling on the plurality of fan power scenarios based on a sequential Monte Carlo double sampling method, and perform element state sampling on the target topology based on the fault data, to obtain a double sampling state; Determine the fan deliverable power of the target topology under the double sampling state.

8. The apparatus of claim 6, wherein, The reliability index of a candidate configuration scheme is determined based on the fan deliverable power corresponding to the candidate configuration scheme, including: wherein, is a reliability index of the candidate configuration scheme, is a deliverable power of the wind turbine corresponding to the candidate configuration scheme, is a number of wind turbines of the offshore wind farm, is a rated power of the wind turbine, is a preset time period, is a topology equivalent outage rate of the power collection system.

9. The apparatus of claim 6, wherein, The second determination module is specifically configured to: Determine an initial investment cost and a life cycle loss cost of each candidate configuration scheme; Determine an economic index of each candidate configuration scheme according to the initial investment cost and the life cycle loss cost of each candidate configuration scheme; Determine a comprehensive evaluation index of each candidate configuration scheme based on the economic index and the reliability index; Determine an optimal configuration scheme from the plurality of candidate configuration schemes based on the comprehensive evaluation index of each candidate scheme.

10. An electronic device, comprising: Including: A processor, and a memory connected in communication with the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method in any one of claims 1-5.

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