Offshore wind power economic benefit assessment method and device based on accessibility

Abstract

The invention discloses an offshore wind power economic benefit assessment method and device based on reachability, and relates to the technical field of data prediction and assessment, and the method comprises the steps: determining an engineering economic benefit index based on an engineering economic benefit analysis mode, reachability influence analysis is carried out in combination with a Monte Carlo prediction method, a clustering analysis method and a Markov decision method; determining the influence of reachability on the economic benefit based on the reachability influence analysis result so as to carry out economic benefit calculation, thereby carrying out operation and maintenance business analysis; and designing an offshore wind power economic benefit evaluation model according to an operation and maintenance service analysis result so as to realize offshore wind power economic benefit evaluation. According to the method, the influence of the accessibility on the economic benefit is comprehensively considered, and the dual influence of the accessibility on the operation and maintenance cost and the power generation capacity is comprehensively considered, so that the economic benefit of the offshore wind plant is evaluated more accurately.

Description

Technical Field

[0001] This application relates to the field of data prediction and evaluation technology, specifically to a method and apparatus for evaluating the economic benefits of offshore wind power based on accessibility. Background Technology

[0002] With the increasing global demand for clean energy, offshore wind power, as one of the most promising new energy sources, is gradually becoming an important part of the energy strategies of various countries. However, the development and operation and maintenance of offshore wind power face many challenges, especially the accessibility of operation and maintenance, which significantly affects the economic benefits of wind farms. Current assessments of the economic benefits of offshore wind power mainly focus on the installed capacity, power generation efficiency, and operation and maintenance costs of wind farms, but research on how accessibility affects economic benefits is insufficient. Specifically, the economic benefit assessment of offshore wind farms is mainly based on factors such as the power generation efficiency of wind turbines, operation and maintenance costs, and construction costs. For example, the economic feasibility is measured by calculating the levelized cost of electricity (LCOE) of the wind farm. However, these methods often overlook the potential impact of operation and maintenance accessibility on economic benefits, leading to incomplete and inaccurate assessment results.

[0003] However, the operation and maintenance costs of offshore wind farms are significantly higher than those of onshore wind farms, with accessibility being a major factor. Because offshore wind farms are located far from land, maintenance personnel and equipment need to rely on ships or helicopters to reach the turbines for repairs and maintenance. Harsh weather conditions, complex sea conditions, and long voyage times all increase operation and maintenance costs, reducing the economic efficiency of the wind farm.

[0004] To improve the operation and maintenance efficiency and economic benefits of offshore wind farms, various optimization methods for operation and maintenance strategies have been proposed. For example, reducing waste of operation and maintenance resources by rationally scheduling preventative maintenance and fault repair plans; and using big data and artificial intelligence technologies to predict turbine failures and schedule maintenance tasks in advance. However, most of these methods do not fully consider the impact of accessibility on operation and maintenance strategies, resulting in limited optimization effects.

[0005] Although some scholars have begun to pay attention to the impact of accessibility on offshore wind power operation and maintenance in recent years and have tried to establish operation and maintenance models based on accessibility, most of these models remain at the theoretical level and lack practical application verification. In addition, these models often only consider the impact of accessibility on operation and maintenance costs, while ignoring its comprehensive impact on wind farm power generation and economic benefits. Specifically, (1) ignoring the impact of accessibility on operation and maintenance costs: existing assessment models usually only consider basic factors such as equipment purchase cost, construction and installation cost, and operation and maintenance cost, while ignoring the important impact of operation and maintenance accessibility on operation and maintenance costs. Offshore wind farm operation and maintenance rely on transportation tools such as ships. Under bad sea conditions, the operation and maintenance of operation and maintenance vessels are restricted from going to sea, resulting in a significant increase in operation and maintenance costs; (2) lacking a dynamic assessment mechanism: the current static assessment method is often used, which cannot accurately reflect the fluctuation of economic benefits caused by changes in weather, sea conditions and other factors during the operation and maintenance of offshore wind farms. In fact, the economic benefits of offshore wind farms change dynamically over time; (3) not fully considering the composition of downtime due to faults: when assessing economic benefits, the current model usually only considers the basic factors such as equipment purchase cost, construction and installation cost, and operation and maintenance cost, while ignoring the important impact of operation and maintenance accessibility on operation and maintenance costs. The calculation of power generation loss caused by downtime was performed, but the specific components of downtime were not analyzed in depth, such as waiting time for maintenance resources, sailing time, maintenance time, etc.; (4) Unreasonable allocation of operation and maintenance resources: Due to the neglect of the impact of accessibility on operation and maintenance costs, there are often unreasonable aspects in the current allocation of operation and maintenance resources. For example, in the selection of the number and type of operation and maintenance vessels, there may be too much reliance on experience judgment, without scientific optimization calculation, resulting in excessively high operation and maintenance costs or low operation and maintenance efficiency; Lack of comprehensive evaluation model: Currently, there is usually a lack of a comprehensive evaluation model that can comprehensively consider multiple factors (such as wind speed, wave height, operation and maintenance resources, downtime, etc.). The lack of such a model makes the evaluation of the economic benefits of offshore wind power less comprehensive and accurate.

[0006] In summary, current methods for assessing the economic benefits of offshore wind power have many shortcomings, particularly regarding the insufficient research on how accessibility affects economic benefits. Therefore, a more comprehensive and accurate accessibility-based economic benefit assessment model for offshore wind power is needed to guide development and operation decisions for offshore wind farms. Summary of the Invention

[0007] This application provides a method and apparatus for evaluating the economic benefits of offshore wind power based on accessibility. It comprehensively considers the impact of accessibility on economic benefits and the dual impact of accessibility on operation and maintenance costs and power generation, thereby more accurately evaluating the economic benefits of offshore wind farms.

[0008] In a first aspect, embodiments of this application provide a method for evaluating the economic benefits of offshore wind power based on accessibility, the method comprising: The engineering economic benefit indicators are determined based on the engineering economic benefit analysis method, and the accessibility impact analysis is carried out by combining the Monte Carlo prediction method, cluster analysis method and Markov decision method. Based on the results of the accessibility impact analysis, the impact of accessibility on economic benefits is determined, economic benefits are calculated, and thus operation and maintenance business analysis is carried out. Based on the analysis results of operation and maintenance business, an economic benefit assessment model for offshore wind power is designed to achieve the economic benefit assessment of offshore wind power.

[0009] In conjunction with the first aspect, in one implementation method, The method for determining engineering economic benefit indicators based on engineering economic benefit analysis includes measuring the power generation cost of offshore wind farms based on the cost per kilowatt-hour. The calculation method for the cost per kilowatt-hour is as follows:

[0010] in, Indicates the cost per kilowatt-hour. This indicates the average total investment in offshore wind farms up to the [number]th [year]. Annual construction costs, Indicates the first Annual maintenance fee Indicates the first Annual management fee Indicates the first Annual power generation; The project's economic benefit indicators include operation and maintenance costs, power generation benefits, and power generation losses. The operation and maintenance costs are the operation and maintenance resource costs of the vessel and the operation and maintenance resource costs of the personnel. The power generation benefits are the total power generation per unit power generation cycle. The power generation losses are the loss of power generation benefits caused by the inability to generate power normally due to shutdown.

[0011] In conjunction with the first aspect, in one implementation method, The specific implementation steps for the Monte Carlo prediction method include: Set a fan with If there are 100 components, and all components are sampled, then the sampling state of a fan is: ,in, Indicates the first The status of each component Indicates the status of the fan. When this happens, it means the fan has stopped due to a malfunction. When the time is right, it means the fan is fault-free and can be operated; Using Monte Carlo methods for probability statistics, employing... Indicates the status of offshore wind farms Average probability: , This indicates the number of wind turbines in an offshore wind farm that require maintenance. This indicates the total number of wind turbines in an offshore wind farm. Setting up an offshore wind farm with a total of Typhoon machine, number In this calculation, the failure probability of a single wind turbine is: The number of failures in an offshore wind farm can then be estimated as follows: ; For cluster analysis, the specific implementation steps include: At the same time, the wind turbine status is When this happens, it means the fan has stopped due to a malfunction. When the fan is in a fault-free state, it can be operated. Combining the two states of fault repair and regular maintenance, the fan status can be specifically divided into: At that time, the wind turbine has already issued a maintenance alarm signal, or is in a state of delayed maintenance due to weather accessibility issues. At that time, the wind turbine does not require maintenance or repair, or although the wind turbine can generate electricity, it requires regular maintenance; Assuming that the offshore wind farm has a total of Typhoon generators, based on operational monitoring status and daily maintenance plans, have The typhoon turbines require maintenance. Among them, the number of turbines that have issued maintenance alarm signals and those whose maintenance has been delayed is [number missing]. The number of wind turbines that did not trigger an alarm but require maintenance according to the scheduled maintenance plan is [number missing]. tower; by Using these wind turbines as cluster centers, k-means clustering was employed to initially divide the offshore wind farm's turbines awaiting maintenance. The alarm fan is used as the initial condensation point for calculation. Taiwanese fans awaiting repair Distance of alarm fan ,Will The fans awaiting maintenance are divided into Class, calculate initial The mean of each class is calculated for each fan under maintenance up to the initial value. Use the Euclidean distance between classes to achieve classification; For the Markov decision-making method, the specific implementation steps include: Representing a Markov chain:

[0012] in, Represents a Markov chain. Let be the wind turbine state set, representing the set of all possible states of the wind turbine. These numbers represent the fan's condition as follows: intact, good, relatively good, dangerous, and faulty, respectively. Let represent the state transition probability matrix, where Indicates wind turbine Always in a state of readiness hour, Shifting to a new state The probability, These represent the states of intact, good, relatively good, dangerous, and faulty, respectively. Let represent the initial probability distribution, where express At time t, the probability matrix of each degenerate state. For row vectors, express Always in a state of readiness The probability of; A wind turbine state prediction model is established by using a Markov process and combining it with a state transition probability matrix.

[0013] in, Indicates in The probability distribution vector of the wind turbine state at time t is given. This represents the probability distribution vector of the wind turbine state at the initial moment. Represents the state transition probability matrix Power of 1 Indicates at any intermediate time. The wind turbine state probability distribution vector. Represents the state transition probability matrix Power of 1.

[0014] In conjunction with the first aspect, in one implementation method, The impact of accessibility on economic benefits includes the impact of accessibility on operation and maintenance activities, and an analysis of the operation and maintenance waiting time caused by accessibility. Regarding the impact of accessibility on operations and maintenance activities, weather conditions are specifically divided into four basic weather events. If the weather is in the first basic weather event, maintenance can be carried out immediately without waiting. If the weather is in the second, third, or fourth basic weather event, maintenance will be delayed. The first type of basic weather event is when the weather is accessible and continuous, with the duration of accessibility longer than the maintenance time, which is sufficient to complete the fault repair task. The second type of basic weather event is when the weather is inaccessible, making it impossible to carry out the maintenance task. The third type of basic weather event is when the weather was inaccessible before the fault occurred, but became accessible and continuous after the fault occurred, although the duration of accessibility is less than the maintenance time, making it impossible to complete the maintenance task. The fourth type of basic weather event is when the weather was accessible and continuous both before and after the fault occurred, but the remaining duration after the fault occurred is less than the maintenance time, making it impossible to complete the maintenance task. If the weather is accessible and persistent, but the duration of accessibility or the remaining duration after the fault occurs is less than the repair time, then repair cannot be performed. The event is converted to a second type of basic weather event, and we need to wait until the weather changes from inaccessible to accessible. Then we need to further determine whether the repair can be completed within the duration of accessibility. If the repair can be completed, then it is a first type of basic weather event, and the repair can be performed. If the duration of accessible weather is less than the repair time, then it is converted to a third type of basic weather event, and we continue to wait until the weather is accessible and the duration meets the requirements before the repair is performed.

[0015] In conjunction with the first aspect, in one implementation method, the analysis of maintenance waiting time caused by reachability specifically includes: Set the average maintenance time to Weather reachability This indicates the proportion of available days to the total number of days, representing the downtime for maintenance. Represented as: ; Calculate waiting time for reachability weather :

[0016] in, This represents the weather accessibility factor, used to reflect how quickly the proportion of maintenance time in downtime changes with airworthiness rate. This indicates the percentage of days throughout the year when weather conditions are suitable for sailing.

[0017] In conjunction with the first aspect, in one implementation method, the economic benefit calculation includes the power generation revenue of the offshore wind farm, the operation and maintenance transportation costs of the offshore wind farm, the downtime of the wind turbines, the availability rate of the wind farm, and the resource utilization rate.

[0018] In conjunction with the first aspect, in one implementation method, The revenue generated by offshore wind farms specifically includes: Setting up an offshore wind farm with a total of Typhoon machine, number Typhoon machine The output power at time is Then in terms of duration Actual power generation of the entire site during the time period Represented as: ; Calculation duration Ideal power generation of the entire site during the time period :

[0019] in, express time, The sum of the power output of the typhoon generators under normal operating conditions; Calculation duration During the time period, the total power loss was... : ; The specific transportation costs for the operation and maintenance of offshore wind farms include: Calculate the total annual cost of the vessel:

[0020] in, This indicates the total annual cost of the vessel. This indicates the ship's annual fixed costs. This represents the unit time cost of a ship. Indicates the time a ship spends at sea to carry out a mission; Calculate human resource costs:

[0021] in, This indicates human resources costs. This refers to fixed personnel costs. Indicates the number of people. This indicates subsidies for going overseas. Indicates the number of days spent at sea; The specific downtime of the wind turbines includes: Calculate downtime:

[0022] in, Indicates the downtime. This indicates the downtime due to a fault, referring to the period from when the fan stops operating due to a fault until the fault is repaired. , Indicates preparation time. Indicates sailing time. , This indicates the distance from the maintenance center to the offshore wind turbine. Indicates ship speed. Indicates the repair time. Indicates weather-related downtime. , This indicates that the wind speed is lower than the cut-in wind speed. Time, This indicates that the wind speed is higher than the cut-out wind speed. Time, Indicates the planned maintenance and repair time; For wind farm availability, the specific components include: Calculate the available runtime of the fan:

[0023] in, This indicates the availability of operating time for the wind turbine. Indicates the operating time of the fan. Indicates the downtime of the fan; Calculate the technical power generation availability of offshore wind farms:

[0024] in, Indicates the availability of power generation capacity. This represents the actual power generation of the entire site. This represents the ideal power generation for the entire site; Regarding resource utilization rate, it specifically includes: The total working time of a single vessel is calculated based on its outbound and return travel times and maintenance duration for a single maintenance task. The total man-hours are calculated based on the personnel's waiting time, sailing time, and maintenance time.

[0025] In conjunction with the first aspect, in one implementation, the operation and maintenance business analysis includes the determination of operation and maintenance strategies, operation and maintenance processes, and operation and maintenance constraints.

[0026] In conjunction with the first aspect, in one implementation method, the design of the offshore wind power economic benefit assessment model specifically includes: Design an economic benefit assessment model for offshore wind power, and determine the business logic for operation and maintenance, the business logic for operation and maintenance personnel, the business logic for operation and maintenance vessels, and the business logic for spare parts.

[0027] Secondly, embodiments of this application provide an accessibility-based offshore wind power economic benefit assessment device, the accessibility-based offshore wind power economic benefit assessment device comprising: The accessibility impact analysis module is used to determine the engineering economic benefit indicators based on the engineering economic benefit analysis method, and to conduct accessibility impact analysis by combining the Monte Carlo prediction method, cluster analysis method and Markov decision method. The Operations and Maintenance Business Analysis module is used to determine the impact of accessibility on economic benefits based on the results of accessibility impact analysis, in order to calculate economic benefits and thus conduct operations and maintenance business analysis. The execution module is used to design an offshore wind power economic benefit assessment model based on the results of operation and maintenance business analysis, thereby realizing the offshore wind power economic benefit assessment.

[0028] The beneficial effects of the technical solutions provided in this application include: (1) The impact of accessibility on economic benefits is fully considered, and the dual impact of accessibility on operation and maintenance costs (including ship costs, personnel costs, etc.) and power generation (by affecting downtime) is comprehensively considered, so as to more accurately assess the economic benefits of offshore wind farms; (2) Provide scientific basis for operation and maintenance decision-making. By simulating the operation and maintenance process under different accessibility conditions, the impact of accessibility on economic benefits can be quantified, providing a scientific basis for the optimization of operation and maintenance strategies. For example, it can analyze the operation and maintenance costs and power generation under different ship configurations and different weather conditions to help decision-makers select the optimal operation and maintenance plan. (3) Improving operation and maintenance efficiency and economic benefits can help offshore wind farms reduce operation and maintenance costs and increase power generation, thereby improving overall economic benefits. By optimizing operation and maintenance strategies, downtime caused by poor accessibility and waste of operation and maintenance resources can be reduced, further improving the operation efficiency and profitability of wind farms. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating the economic benefit assessment method for offshore wind power based on accessibility. Figure 2 This is a logic analysis diagram of the cost per kilowatt-hour. Figure 3 This is a schematic diagram of the maintenance phase of an offshore wind turbine. Figure 4 A flowchart for dispatching and maintenance of offshore wind turbines in case of malfunction; Figure 5 A graph showing the relationship between weather availability and downtime; Figure 6 A graph showing the actual maintenance time of offshore wind turbines; Figure 7 Flowchart for planned maintenance dispatching; Figure 8 Flowchart for dispatching maintenance services for failures; Figure 9This is a schematic diagram of the functional modules of the offshore wind power economic benefit assessment device based on accessibility in this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0031] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0032] Firstly, this application provides an accessibility-based method for evaluating the economic benefits of offshore wind power. This method involves collecting information on wind farm meteorological conditions, marine environment, seaworthiness of vessels and supporting equipment, basic climbing facilities, and personnel and equipment conditions. Through systematic research on multiple factors, an accessibility analysis model is established based on influencing factors such as meteorological and marine environmental conditions, as well as personnel and equipment resources. By studying the characteristics, operation and maintenance resources, and operation and maintenance strategies of offshore wind farms, the Monte Carlo method is used to simulate the operation and maintenance process of the wind farm. This allows for a detailed analysis of the wind farm's annual power generation, operation and maintenance costs, and the utilization of operation and maintenance resources, thereby optimizing operation and maintenance resources and strategies.

[0033] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating the accessibility-based economic benefit assessment method for offshore wind power presented in this application. Figure 1 As shown, the methods for evaluating the economic benefits of offshore wind power based on accessibility include: S1: Determine the engineering economic benefit indicators based on the engineering economic benefit analysis method, and conduct accessibility impact analysis by combining Monte Carlo prediction method, cluster analysis method and Markov decision method; S2: Based on the results of the accessibility impact analysis, determine the impact of accessibility on economic benefits, calculate economic benefits, and then conduct operation and maintenance business analysis; S3: Based on the analysis results of operation and maintenance business, design an economic benefit assessment model for offshore wind power to achieve economic benefit assessment of offshore wind power.

[0034] Furthermore, in one embodiment, the engineering economic benefit indicators are determined based on an engineering economic benefit analysis method. Specifically, the power generation cost of the offshore wind farm is measured based on the cost per kilowatt-hour, and the calculation method for the cost per kilowatt-hour is as follows:

[0035] in, Indicates the cost per kilowatt-hour. This indicates the average total investment in offshore wind farms up to the [number]th [year]. Annual construction costs, Indicates the first Annual maintenance fee Indicates the first Annual management fee Indicates the first Annual power generation.

[0036] Specifically, in the logic of engineering economic benefit analysis, the Levelized Cost of Energy (LCOE) is an indicator that measures the net present value of the average power generation cost of an offshore wind farm over its life cycle. LCOE represents the average revenue per unit of electricity generated required to recover the costs of building and operating the power plant over an assumed financial life and operating period. The principle behind using the LCOE method to measure the power generation cost of an offshore wind farm is the ratio of the net present value of wind power costs to the economic time value of output. The above formula is the expression for the levelized cost of energy.

[0037] The cost per kilowatt-hour (kWh) is the cost generated per unit of electricity supplied to the grid by a wind power project. Simply put, it's the ratio of cumulative sales cost to cumulative power generation. When considering the kWh, it's necessary to understand it from two perspectives: cost and benefit. This mainly includes factors such as... Figure 2 As shown.

[0038] Depend on Figure 2 It is known that the total cost of a wind farm mainly includes construction costs and operating costs. Construction costs primarily occur during the construction phase, while operating costs are the main factor related to accessibility. Operating costs can be further divided into maintenance costs and management costs. Analysis of factors affecting accessibility shows that the most direct factor influencing accessibility is transportation costs for operation and maintenance. Therefore, the main cost related to accessibility is the cost of operation and maintenance vessels. Wind farm efficiency primarily refers to the amount of electricity generated. Accessibility affects availability, and thus wind farm power generation. High availability requires high accessibility, which in turn requires high-performance operation and maintenance vessels. Pursuing high-performance operation and maintenance vessels inevitably leads to increased vessel costs, which in turn increases wind farm efficiency. However, wind farm efficiency has an upper limit. Once wind farm accessibility reaches a certain level, the impact of increased costs on wind farm efficiency will gradually decrease. There will then be a specific value between the two, which serves as the economic accessibility indicator for the wind farm. At this value, the cost per kilowatt-hour of the wind farm is optimal.

[0039] Furthermore, the engineering economic benefit indicators include operation and maintenance costs, power generation benefits, and power generation losses. The operation and maintenance costs are the operation and maintenance resource costs of the ship and the operation and maintenance resource costs of the personnel. The power generation benefits are the total power generation per unit power generation cycle. The power generation losses are the loss of power generation benefits caused by the inability to generate power normally due to shutdown.

[0040] The goal of offshore wind power operation and maintenance (O&M) is to minimize the cost of completing maintenance tasks within the planned timeframe, under the constraints of offshore maintenance vessels, personnel, and weather conditions. This aims to reduce downtime losses, lower O&M costs, and improve wind farm efficiency. Assuming component maintenance costs are fixed, we only consider variable costs related to accessibility, including personnel, vessel, and route transportation costs, downtime losses, and costs incurred due to delayed maintenance caused by unfavorable conditions (weather, effective working time limitations, etc.). Therefore, the O&M economic benefit calculation can consider three aspects: O&M costs, power generation benefits, and power generation losses.

[0041] Operation and maintenance costs include the cost of vessel operation and maintenance resources and the cost of personnel operation and maintenance resources. The cost of vessel operation and maintenance resources requires accounting for vessel leasing fees and the cost of each voyage; the cost of personnel operation and maintenance resources requires accounting for annual personnel costs and the cost of each voyage. Operation and maintenance costs essentially focus on the expenses of operation and maintenance transportation, mainly consisting of fixed costs and variable costs (such as fuel consumption) of the vessel.

[0042] Power generation efficiency refers to the total power generation of the entire wind farm over a single power generation cycle (e.g., 365 days). The amount of wind energy generated per unit time over a given area primarily depends on wind speed, while power generation measures the amount of electrical energy converted per unit time. Using wind speed as input and power as output, the wind speed-power transfer characteristic of a wind turbine (or simply wind turbine) describes the input-output relationship. The total power generation of the entire wind farm is obtained by summing the actual power generation of all wind turbines over a given period.

[0043] Power generation loss refers to the loss of power generation benefits caused by the inability to generate electricity normally due to downtime. Offshore wind turbines will experience power generation losses due to accessibility limitations. Power generation losses can be identified by calculating the downtime of all turbines in the site based on operation and maintenance log data and comparing the downtime caused by fault repairs and routine maintenance with the power generation time of turbines that are generating electricity normally.

[0044] Furthermore, in the accessibility impact analysis, the specific implementation steps for the Monte Carlo prediction method include: S101: Set a fan to have If there are 100 components, and all components are sampled, then the sampling state of a fan is: ,in, Indicates the first The status of each component Indicates the status of the fan. When this happens, it means the fan has stopped due to a malfunction. When the time is right, it means the fan is fault-free and can be operated; It should be noted that the Monte Carlo method is a statistical simulation method that randomly samples a series of data. To calculate the probability of a random event, a large number of experiments can be conducted, and the probability distribution of the event can be estimated by calculating its frequency of occurrence. This method will be used to simulate random failures of offshore wind turbine components, predict the timing of failures, and guide the design of operation and maintenance cycles. S102: Using Monte Carlo methods for probability statistics, employing... Indicates the status of offshore wind farms Average probability: , This indicates the number of wind turbines in an offshore wind farm that require maintenance. This represents the total number of wind turbines in an offshore wind farm; that is, using Monte Carlo probability statistics, with a sufficiently large number of iterations, the result is... Indicates the status of offshore wind farms The average probability; S103: Setting up shared offshore wind farms Typhoon machine, number In this calculation, the failure probability of a single wind turbine is: The number of failures in an offshore wind farm can then be estimated as follows: ; When calculating the economic benefits of the project, the wind turbine failure rate is used as a random variable, and samples are randomly selected from the interval [0.1]. The value was calculated multiple times using a simulation model and the Monte Carlo statistical method. Approaching The variance coefficient can be calculated to measure the accuracy of the model.

[0045] For cluster analysis, the specific implementation steps include: S111: At the same time, the fan status is... When this happens, it means the fan has stopped due to a malfunction. When the fan is in a fault-free state, it can be operated. Combining the two states of fault repair and regular maintenance, the fan status can be specifically divided into: At that time, the wind turbine has already issued a maintenance alarm signal, or is in a state of delayed maintenance due to weather accessibility issues. At that time, the wind turbine does not require maintenance or repair, or although the wind turbine can generate electricity, it requires regular maintenance; Clustering analysis is a commonly used algorithm in deep learning. It separates objects of different classes based on their differences. The goal of clustering analysis is to separate mixed data as much as possible, maximize the similarity of objects of the same class, and minimize the similarity of different objects. S112: Assuming that the offshore wind farm has a total of Typhoon generators, based on operational monitoring status and daily maintenance plans, have The typhoon turbines require maintenance. Among them, the number of turbines that have issued maintenance alarm signals and those whose maintenance has been delayed is [number missing]. The number of wind turbines that did not trigger an alarm but require maintenance according to the scheduled maintenance plan is [number missing]. tower; S113: with Using these wind turbines as cluster centers, k-means clustering was employed to initially divide the offshore wind farm's turbines awaiting maintenance. The alarm fan is used as the initial condensation point for calculation. Taiwanese fans awaiting repair Distance of alarm fan ,Will The fans awaiting maintenance are divided into Class, calculate initial The mean of each class is calculated for each fan under maintenance up to the initial value. Use the Euclidean distance between classes to achieve classification; Specifically, when scheduling maintenance, priority is given to units with operational alarms and units whose maintenance has been delayed, based on the urgency of the maintenance tasks. Using these types of wind turbines (those that have issued maintenance alarm signals and those whose maintenance has been delayed) as cluster centers, k-means clustering is used to initially divide the offshore wind farm's turbines awaiting maintenance. First, select... The alarm fan is used as the initial condensation point for calculation. Taiwanese fans awaiting repair Distance of alarm fan ,Will The fans awaiting maintenance are divided into Class, calculate initial The mean of each class is calculated for each fan under maintenance up to the initial value. Euclidean distance of the class; If the fan awaiting repair is closest to its original class, its classification remains unchanged; otherwise, it will be assigned to the closest class, and the mean of each class will be recalculated as the clustering point of the new class. This process continues until the centroids of each class no longer change or vary within a small range, at which point the classification ends. Fans awaiting repair, fans with delayed repairs, and fans scheduled for repair are clustered relatively evenly. This category facilitates the rational allocation of resources for operation and maintenance.

[0046] Because offshore wind farms have limited operation and maintenance resources (ships, personnel, etc.), it is assumed that the number of operation and maintenance vessels is [number missing]. When doing so, the following situations need to be considered: If the number of wind turbines to be repaired is equal to the number of ships to be repaired, that is... Then maintenance work can be carried out simultaneously; If the number of wind turbines awaiting repair exceeds the number of available maintenance vessels, that is... Therefore, it is necessary to follow the principles of analysis of variance, using the number of available ships as an example. As the number of partitions, the distance between partitions is used as the class interval. The partitions are merged into classes before the operation and maintenance work is performed.

[0047] When calculating the economic benefits of the project, clusters are automatically generated based on the random distribution of wind turbine failures, and maintenance requests are issued. The number of maintenance vessels can be used as an input variable in the model to assess the economic benefits under different maintenance resource conditions.

[0048] Furthermore, for the Markov decision-making method, the specific implementation steps include: S121: Represent the Markov chain:

[0049] in, Represents a Markov chain. Let be the wind turbine state set, representing the set of all possible states of the wind turbine. These numbers represent the fan's condition as follows: intact, good, relatively good, dangerous, and faulty, respectively. Let represent the state transition probability matrix, where Indicates wind turbine Always in a state of readiness hour, Shifting to a new state The probability, These represent the states of intact, good, relatively good, dangerous, and faulty, respectively. At this time, the fan is in a faulty state. , Let represent the initial probability distribution, where express At time t, the probability matrix of each degenerate state. For row vectors, express Always in a state of readiness The probability of; During operation, offshore wind turbines are affected by environmental factors such as waves, wind speed, and salt spray corrosion. The aging and failure of their equipment is a random process. The stochastic probability model takes into account the historical operating conditions of the system, which is more in line with the actual situation of equipment aging. Especially when the wind turbine monitoring signal is missing, the stochastic probability model can quantify the deterioration process of the system and further predict the condition of the offshore wind turbine, thereby obtaining a more appropriate maintenance strategy. S122: A wind turbine state prediction model is established by using a Markov process and combining it with a state transition probability matrix.

[0050] in, Indicates in The probability distribution vector of the wind turbine state at time t is given. This represents the probability distribution vector of the wind turbine state at the initial moment. Represents the state transition probability matrix Power of 1 Indicates at any intermediate time. The wind turbine state probability distribution vector. Represents the state transition probability matrix Power of 1.

[0051] When calculating the economic benefits of the project, wind turbine condition prediction data is combined with the Monte Carlo method for iterative statistics to calculate the impact of wind turbine condition under different prediction result distributions on the economic benefits of the project, and variance analysis is used to obtain the operation and maintenance requirements under different wind turbine conditions.

[0052] Furthermore, in this application, the impact of accessibility on economic benefits includes the impact of accessibility on operation and maintenance activities, and an analysis of the operation and maintenance waiting time caused by accessibility.

[0053] Based on relevant standards, the daily maintenance and management of offshore wind turbine (wind turbine) equipment can be divided into planned maintenance and fault maintenance. The main task of planned maintenance is to conduct regular inspections, maintenance, and upkeep of the wind turbine according to its technical requirements and operating time. Scheduled maintenance plans are usually formulated based on a period of operating time, such as 500 hours, six months, or one year. The content of scheduled maintenance is relatively fixed and generally has standardized procedures and requirements. Each scheduled maintenance for each wind turbine requires approximately 80-100 man-hours (the time varies depending on the specific wind turbine requirements and maintenance frequency). In addition to scheduled maintenance, planned maintenance also includes planned repairs based on the wind turbine's operating status, including minor technical modifications. These repairs are carried out during periods of low wind speed, while ensuring the wind turbine's normal operation.

[0054] The main task of fault-based maintenance is to troubleshoot temporary faults, including prediction, inspection, cleaning, adjustment, lubrication, and parts replacement. There is no fixed timeframe or set work content. The experience, technical skill, and knowledge of the personnel determine the speed and effectiveness of the process, directly impacting the normal operation of the wind power plant. The speed, passenger capacity, and wave resistance of the maintenance vessel determine its ability to reach the sea when a fault occurs. Faster, larger-capacity, and more wave-resistant maintenance vessels can increase accessibility time and improve the efficiency of fault-based maintenance.

[0055] Furthermore, regarding the impact of accessibility on operations and maintenance activities, weather conditions are specifically categorized into four basic weather events. If the weather falls under the first basic weather event category, maintenance can be performed immediately without waiting. If the weather falls under the second, third, or fourth basic weather event category, maintenance will be delayed. Specifically, after a failure occurs in an offshore wind turbine, the actual maintenance process can be divided into four stages: (1) the dispatch center receives the alarm signal, the on-duty personnel formulate maintenance strategies, and arrange the maintenance phase; (2) the maintenance resource (personnel, spare parts, transportation resources) preparation phase; (3) the waiting phase for suitable offshore operating weather; and (4) the stage of executing maintenance activities, such as... Figure 3 As shown.

[0056] The execution of these four phases requires the collaborative efforts of the dispatch center, spare parts warehouse, vessel crews, and maintenance personnel. Because offshore wind turbine maintenance is highly dependent on weather accessibility, when the dispatch center receives a maintenance request, it first checks the weather forecast, assuming the vessel, spare parts, and personnel are all available, to determine if the current weather is suitable for dispatching a maintenance vessel. Since maintenance requires a considerable amount of time to complete after the vessel arrives at the faulty turbine, the dispatch center needs to calculate the sum of the vessel's travel time, estimated maintenance time, and return time to determine if the duration of available weather is sufficient. If it is, and the entire maintenance cycle is met, the dispatch center can then dispatch the work order to execute the fault repair. Figure 4 The diagram shown is a schematic of the offshore wind turbine fault repair and dispatch process.

[0057] Offshore weather conditions have a significant impact on the maintenance process of wind farms. On the one hand, maintenance activities can only be carried out when the weather is favorable, i.e., when the wind speed and wave height are low enough. On the other hand, the replacement of some large components takes a long time and requires a sustained period of favorable weather to complete the maintenance task. Otherwise, it will lead to a long downtime and economic losses.

[0058] Further analysis reveals the causal events that may lead to weather inaccessibility or insufficient accessibility duration to meet maintenance requirements. Weather conditions are categorized into four basic weather events: The first category is where the weather is accessible and persistent, with an accessibility duration longer than the maintenance time, sufficient to complete the fault repair task; the second category is where the weather is inaccessible, making it impossible to carry out the maintenance task; the third category is where the weather was inaccessible before the fault occurred, but became accessible and persistent after the fault occurred, although the accessibility duration is less than the maintenance time, making it impossible to complete the maintenance task; and the fourth category is where the weather was accessible and persistent both before and after the fault occurred, but the remaining duration after the fault occurred is less than the maintenance time, making it impossible to complete the maintenance task.

[0059] If the weather is accessible and persistent, but the duration of accessibility or the remaining duration after the fault occurs is less than the repair time, then repair cannot be performed. The event is converted to a second type of basic weather event, and we need to wait until the weather changes from inaccessible to accessible. Then we need to further determine whether the repair can be completed within the duration of accessibility. If the repair can be completed, then it is a first type of basic weather event, and the repair can be performed. If the duration of accessible weather is less than the repair time, then it is converted to a third type of basic weather event, and we continue to wait until the weather is accessible and the duration meets the requirements before the repair is performed.

[0060] Further analysis of the operational waiting time caused by reachability issues includes: S201: Set the average maintenance time as follows Weather reachability This indicates the proportion of available days to the total number of days, representing the downtime for maintenance. Represented as: ; Because the downtime required to replace small components differs from that required to replace large components during maintenance, based on historical data analysis, we assume the average maintenance time for replacing small components... =24 hours, average maintenance time when replacing major components =96 hours, then when there are large changes, we can get as follows Figure 5 The maintenance time trend chart shown; by Figure 5 It can be seen that when maintaining the same component, as the weather availability rate increases, the waiting time for available weather decreases, and the downtime caused by maintenance decreases. S202: Calculate the waiting time for reachability weather. :

[0061] in, The weather accessibility factor reflects how quickly the proportion of maintenance time in downtime changes with airworthiness rate. It can be fitted from historical maintenance data of the wind farm. The calculation formula can be used to obtain the trend of change between the two, such as Figure 6 As shown, by Figure 6 It can be seen that as the weather suitability rate increases, the proportion of average maintenance time in the actual maintenance time gradually increases, meaning that weather waiting time gradually decreases. This indicates the percentage of days throughout the year when weather conditions are suitable for sailing.

[0062] Even under the same weather conditions, the waiting time for maintenance varies depending on the components being maintained. Maintenance of large components of offshore wind turbines (such as gearboxes and blades) takes longer, requiring a larger weather window and resulting in longer downtime. Maintenance of smaller components, on the other hand, is quicker, typically completed within a working day, with minimal downtime.

[0063] Assuming sufficient personnel, vessels, and spare parts are available, the actual maintenance time is only affected by weather conditions. Let's assume the percentage of days with suitable weather for sailing throughout the year is h. When h is low, maintenance accessibility is considered poor, leading to increased actual maintenance time. Conversely, a higher h indicates a shorter waiting time for weather accessibility, resulting in longer actual maintenance time. If the waiting time for weather accessibility is sufficiently short, the actual maintenance time can be considered close to the overall repair time.

[0064] Many conditions must be met to ensure the smooth execution of operation and maintenance processes, typically involving constraints such as maintenance vessels, personnel, spare parts, and weather. A scientific operation and maintenance plan must also consider the cost-effectiveness of performing maintenance actions and wind turbine power generation losses from both safety and cost calculation perspectives. Therefore, when calculating the economic benefits of offshore wind farm projects, models need to be established from several perspectives, including operation and maintenance, power generation, wind turbines, weather, and maintenance resources.

[0065] Furthermore, in this application, the economic benefit calculation includes the power generation revenue of the offshore wind farm, the operation and maintenance transportation costs of the offshore wind farm, the downtime of the wind turbines, the availability rate of the wind farm, and the resource utilization rate.

[0066] In this application, the revenue generated by offshore wind farms specifically includes: S211: Set the total number of offshore wind farms Typhoon machine, number Typhoon machine The output power at time is Then in terms of duration Actual power generation of the entire site during the time period Represented as: ; Based on the normal operation and maintenance of offshore wind turbines and the above theoretical foundation, the power generation revenue of offshore wind farms can be calculated; over a period of time... Inside, the power generation of a single wind turbine unit is... The wind speed within a given time period determines the speed; multiple wind turbines (set as follows) The total power generation is from Typhoon turbine units Composition of total power generation over a period of time; Based on the real-time wind speed recorded at the wind farm and the wind power curve, the power output of a single wind turbine can be calculated. The power generation at any given moment is used to calculate the total power generation of the entire site; S212: Calculation duration Ideal power generation of the entire site during the time period :

[0067] in, express time, The sum of the power output of the typhoon generators under normal operating conditions; Lost electricity is used to calculate the loss incurred when electricity should have been generated but was not; time, The sum of the power output of the typhoon generators under normal operating conditions is calculated over a time period. The ideal power generation of the entire site is calculated using the above formula; S213: Calculation duration During the time period, the total power loss was... : .

[0068] In this application, the transportation costs for the operation and maintenance of offshore wind farms specifically include: S221: Calculate the total annual cost of a vessel:

[0069] in, This indicates the total annual cost of the vessel. This indicates the ship's annual fixed costs. This represents the unit time cost of a ship. Indicates the time a ship spends at sea to carry out a mission; The operation and maintenance transportation costs of offshore wind farms consist of two parts: fixed costs and task execution costs. S222: Calculate human resource costs:

[0070] in, This indicates human resources costs. This refers to fixed personnel costs. Indicates the number of people. This indicates subsidies for going overseas. This indicates the number of person-days spent at sea. Human resource costs consist of fixed costs and hourly costs.

[0071] In this application, the wind turbine downtime specifically includes: Calculate downtime:

[0072] in, Indicates the downtime. This indicates the downtime due to a fault, referring to the period from when the fan stops operating due to a fault until the fault is repaired. , This refers to the preparation time, specifically the period during which a wind turbine malfunctions and the wait for repair resources and favorable weather conditions. The decision-making logic includes the preparation time for spare parts and components, the preparation time for vessels and personnel, and the waiting time until weather conditions allow for departure. Indicates sailing time. , This indicates the distance from the maintenance center to the offshore wind turbine. Indicates ship speed. Indicates the repair time. This refers to the weather-related downtime, specifically the period during which the wind turbine itself can operate normally, but the wind speed is lower than the cut-in wind speed or higher than the cut-out wind speed, causing the wind turbine to be unable to generate electricity. , This indicates that the wind speed is lower than the cut-in wind speed. Time, This indicates that the wind speed is higher than the cut-out wind speed. Time, This indicates the planned maintenance time, specifically the time during which the turbine will be shut down to ensure its stable operation.

[0073] Specifically, wind turbine downtime means a loss of power generation. Downtime includes downtime due to turbine malfunction, weather-related downtime, and downtime during scheduled turbine maintenance. If insufficient resources such as vessels and personnel lead to turbine malfunctions, resulting in prolonged downtime, a decision can be made after weighing the costs of increased resources against the power generation benefits of reduced downtime. If weather-related downtime is significant, turbines with higher downtime wind speeds may be selected; alternatively, it could indicate that the area is unsuitable for offshore wind turbine deployment.

[0074] The calculation logic is as follows: For For any potential failure, calculate the resource preparation time (spare parts preparation, vessel preparation, and personnel preparation). Once spare parts, vessels, and personnel are ready, calculate the waiting time for suitable weather conditions for departure, and calculate the sailing time. Using these three timeframes, determine when maintenance can begin. The calculation process is as follows:

[0075] in, , , These are the waiting times for spare parts, maintenance personnel, and maintenance vessels, respectively. We are waiting for weather conditions to allow us to set sail.

[0076] for Weather-related factors can affect wind turbine operation. Weather-related downtime is calculated based on the time the turbine is not generating power due to wind speeds falling below the cut-in wind speed or rising above the cut-out wind speed, under normal turbine operating conditions. The simulation system's logic uses the recorded wind speed conditions at the wind farm location as the lower and upper limits of the cut-in and cut-out wind speeds, respectively. Time spent with wind speeds below the cut-in wind speed or below the cut-out wind speed is considered a weather-related downtime. Simulation System Design The timer records the downtime due to weather conditions based on the set cut-in and cut-out wind speed thresholds. Summing these times gives the total downtime due to weather. .

[0077] for This refers to the time the wind turbines are shut down due to annual planned maintenance. The simulation system sets a status timer. Impact Factors affecting the status timer: Maintenance status. When the wind turbine is in a planned maintenance state, the timer starts... Timing. The system calculation logic for wind turbine maintenance time is as follows: when the vessel arrives at the wind turbine and begins to execute planned maintenance work, The status timer starts counting down. Once maintenance is complete, a "maintenance complete" signal is sent, and the status timer stops counting down. The accumulated time of the status timer is the maintenance completion time. .

[0078] In this application, the availability of wind farms specifically includes: S231: Calculate the availability of the fan's operating time:

[0079] in, This indicates the availability of operating time for the wind turbine. Indicates the operating time of the fan. Indicates the downtime of the fan; According to DNV-GL, an internationally recognized authoritative certification and consulting organization in the wind power field, availability is a method to measure the power generation potential of a wind turbine or wind farm. If a wind turbine is "available" and connected to the grid, it should generate electricity under suitable wind conditions. The availability indicators of a wind farm include operating time availability and technical power generation availability. The operating time availability is the ratio of the sum of the operating times of all wind turbines in the wind farm to the total operating time of the wind turbines. The total operating time of a single wind turbine consists of the operating time and the downtime. S232: Calculation of the technical availability of power generation for offshore wind farms:

[0080] in, Indicates the availability of power generation capacity. This represents the actual power generation of the entire site. This represents the ideal power generation of the entire site.

[0081] In this application, resource utilization rate specifically includes: S241: The total working time of a vessel is calculated based on the outbound and return times and maintenance time of a single vessel performing a maintenance task. S242: Calculate the total man-hours based on the man-hours of waiting, sailing, and maintenance.

[0082] Resource utilization rate primarily analyzes the use of resources such as ships and personnel. The purpose of calculating resource utilization rate is to optimize resource use. The number of days a ship is in use consists of working days and waiting days. Different types of ships can perform different tasks, so the working days and waiting days can be calculated separately for each ship type to determine the utilization rate of that type of ship, and finally, the overall utilization rate of the ship can be calculated.

[0083] For vessel usage calculations, the details of vessel usage need to include the working hours. Depending on the vessel configuration, calculations can be performed separately for different vessel types, that is, based on the outbound and return travel times and maintenance duration of a single vessel performing a maintenance task.

[0084] For personnel working hours calculation, personnel working hours are divided into waiting time, navigation time, and maintenance time. Among them: waiting time refers to the time when personnel are not performing maintenance tasks; navigation time refers to the time when personnel go to and from the wind farm to perform maintenance tasks; maintenance time refers to the time when personnel perform maintenance tasks at the wind farm.

[0085] Furthermore, in this application, the operation and maintenance business analysis includes the determination of operation and maintenance strategies, operation and maintenance processes, and operation and maintenance constraints.

[0086] Offshore wind turbines are characterized by their wide distribution, multiple management layers, and high maintenance difficulty. The complex marine hydrological and meteorological environment, with alternating monsoons and typhoons, and the corrosive effects of seawater on wind turbines, coupled with limitations in water transportation and manpower, significantly reduces the effective operating time for daily maintenance and management. Special weather conditions (such as heavy fog and typhoons) can further impact offshore operation and maintenance, directly affecting power generation efficiency. Based on relevant standards, the daily maintenance and management of offshore wind turbine equipment can be divided into planned maintenance and fault maintenance. For planned maintenance and fault maintenance of offshore wind farms, virtual simulation and computer modeling can be used to simulate data, thereby rationally selecting maintenance strategies and allocating maintenance resources under limited data recording and operation and maintenance conditions, improving power generation efficiency and reducing maintenance costs.

[0087] For the operation and maintenance process, both planned maintenance and fault-based maintenance require the management center to determine the accessibility of maintenance vessels and rationally allocate maintenance resources such as vessels and personnel based on the constraints of marine weather conditions. Therefore, following the description of the operation and maintenance strategy in the previous section and combining it with the actual workflow of offshore wind power, the process of dispatching planned maintenance work is described, such as... Figure 7 As shown.

[0088] The planned maintenance dispatching process is divided into four parts: spare parts warehouse, vessel crews, dispatch center, and maintenance crews. The process is as follows: The dispatch center formulates and reviews the maintenance plan. After formulating the plan, it first checks if the current weather conditions permit departure. If so, it checks if there are available spare parts. If not, it notifies the spare parts warehouse to prepare them. If spare parts are sufficient, it checks if there are available vessels and if there are enough personnel. When weather conditions are favorable, spare parts, vessels, and personnel are sufficient, the dispatch center issues a work order. The relevant department receives the order and prepares to depart.

[0089] For fault-based maintenance dispatching processes, such as Figure 8 As shown, the fault-based maintenance dispatching operation is divided into five parts: vessel crew, spare parts warehouse, dispatch center, maintenance crew, and wind turbine. The fault-based maintenance dispatching process is as follows: First, the wind turbine sends a fault maintenance request. The maintenance crew receives the fault information. The dispatch center registers the maintenance request and formulates a maintenance plan. After formulating the maintenance plan, it first checks whether the current weather conditions allow for departure. If the current conditions allow for departure, it continues to check whether there are corresponding spare parts. If not, it notifies the spare parts warehouse to prepare them. If there are sufficient spare parts, it continues to check whether there are available vessels and whether there are enough inspection personnel. Under favorable weather conditions, with sufficient spare parts, vessels, and personnel, the dispatch center issues a work order. After receiving the order, the relevant department prepares to depart.

[0090] For the operation and maintenance constraints of this application, the maintenance vessel departs from the port on shore, completes the maintenance task, and then sails back to the port. Each unit is maintained by only one maintenance vessel and one group of personnel per day. The personnel and spare parts on the maintenance vessel meet the maximum load requirements, and the working time of the maintenance vessel meets the working time requirements. Then the number of maintenance vessels and the maintenance sequence of the units need to meet the following conditions: (1) The number of maintenance vessels cannot exceed the maximum number of vessels; (2) There are restrictions on the wind turbine maintenance sequence; (3) There are restrictions on the daily effective working time of the maintenance vessel; (4) There are restrictions on maintenance downtime and delayed maintenance time; (5) Each wind turbine is maintained by only one maintenance vessel per day, and there are restrictions on the number of times the vessel maintains the wind turbine per day; (6) The maintenance route needs to meet certain conditions, that is, each maintenance vessel departs from the port every day, completes the task, and then returns to the port.

[0091] Furthermore, this application designs an economic benefit assessment model for offshore wind power, and determines the business logic of operation and maintenance, the business logic of operation and maintenance personnel, the business logic of operation and maintenance vessels, and the business logic of spare parts.

[0092] For the design of the offshore wind power economic benefit assessment model, offshore wind turbine operation and maintenance (O&M) is based on the turbine's operating status, the type of turbine failure, and weather conditions to formulate a reasonable O&M plan. An overall O&M logic is designed, with the O&M center dispatching O&M work orders based on resource availability and weather accessibility. The O&M center monitors the entire system's operational status. Upon receiving a new maintenance request, the dispatch center verifies the turbine failure type in the work order, provides corresponding handling solutions based on different failure types, checks weather forecast information, and determines the work order dispatch plan based on weather accessibility. The O&M vessel is dispatched, and the work order is marked as resolved after the maintenance issue is resolved.

[0093] For operation and maintenance (O&M) logic, wind turbines operate in two states: normal operation and shutdown. When the wind speed exceeds the rated power's corresponding wind speed, the turbine stops operating. When the wind speed is less than or equal to the corresponding wind speed threshold, the turbine automatically returns to normal operation. O&M personnel perform scheduled maintenance on the turbines every two weeks. Upon completion of maintenance, a "repaired" message is triggered, and the turbine receiving the message resumes normal operation. Each month, a turbine may experience a failure leading to a shutdown. When a turbine fails and shuts down, it automatically reports its location and fault type to the dispatch center, awaiting repair by maintenance vessels and personnel. Once repair is completed and a "repaired" message is triggered, the turbine returns to normal operation.

[0094] For the business logic of operations and maintenance personnel, there are two states: rest and work. When the operations and maintenance personnel are in the work state, they receive a maintenance order from the maintenance center. Then, the operations and maintenance personnel wait for the order to prepare to go to sea. When they receive the "setout" command, the operations and maintenance personnel go to sea to carry out offshore operations. When the maintenance is completed, the "back" message is triggered, and the operations and maintenance personnel return to the maintenance center. When the operations and maintenance personnel resume their normal work state, it means that the operations and maintenance personnel have completed a complete offshore operations and maintenance operation.

[0095] For the operational logic of maintenance vessels, the vessel is initially at anchor. Upon receiving a new maintenance order, the vessel enters the spare parts phase and determines the necessary spare parts based on the type of wind turbine malfunction. Once the spare parts and the vessel are ready, the current weather conditions are assessed to determine if sailing is suitable. If the wave height is below the safe sailing height threshold at this time, personnel are notified to sail to the wind farm for maintenance. After maintenance is completed, the dispatch center is consulted for any other maintenance requests. If so, the vessel continues sailing to a new location for maintenance; otherwise, it returns to the maintenance center. When the vessel returns to anchor, it signifies the completion of a full-scale offshore maintenance mission.

[0096] For spare parts and components, this business logic is incorporated into vessel preparation. Upon receiving a maintenance dispatch order, the operations and maintenance center checks the fault type and prepares spare parts and components accordingly. If spare parts and components are unavailable or insufficient, the waiting time for these components needs to be calculated. If spare parts and components are sufficient, their status is set to ready. After both spare parts and vessel preparation are complete, accessibility is assessed.

[0097] This application incorporates accessibility as a key factor into the offshore wind power economic benefit assessment model, filling a gap in existing technology. By comprehensively considering the impact of accessibility on operation and maintenance costs and power generation, it provides more comprehensive and accurate assessment results. The offshore wind farm operation and maintenance simulation model built using AnyLogic simulation software can simulate the operation and maintenance process under different accessibility conditions, providing a scientific basis for actual operation and maintenance decisions. The model has strong adaptability and scalability, and can be adjusted and optimized according to the actual conditions of different wind farms. Through simulation, economic benefit indicators under different operation and maintenance strategies can be quickly calculated, helping decision-makers to make quick decisions. At the same time, it can also compare and analyze multiple operation and maintenance schemes, select the optimal scheme, and improve decision-making efficiency. Based on a large amount of historical data and actual operation and maintenance experience, the reliability and accuracy of the assessment results are ensured. Through continuous optimization and improvement of the model, its predictive accuracy and applicability can be further improved.

[0098] Secondly, embodiments of this application also provide an offshore wind power economic benefit assessment device based on accessibility.

[0099] In one embodiment, reference is made to Figure 9 , Figure 9 This is a schematic diagram of the functional modules of the offshore wind power economic benefit assessment device based on accessibility, as described in this application. Figure 9 As shown, the offshore wind power economic benefit assessment device based on accessibility includes: an accessibility impact analysis module, an operation and maintenance business analysis module, and an execution module.

[0100] The accessibility impact analysis module is used to determine the economic benefit indicators of the project based on the engineering economic benefit analysis method, and to conduct accessibility impact analysis by combining Monte Carlo prediction method, cluster analysis method and Markov decision method; the operation and maintenance business analysis module is used to determine the impact of accessibility on economic benefits based on the accessibility impact analysis results, so as to perform economic benefit calculation and thus conduct operation and maintenance business analysis; the execution module is used to design an offshore wind power economic benefit assessment model based on the operation and maintenance business analysis results, so as to realize the offshore wind power economic benefit assessment.

[0101] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0102] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0103] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0104] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0105] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0106] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for assessing economic benefits of offshore wind power based on reachability, characterized in that, The accessibility-based offshore wind power economic benefit assessment method includes: The engineering economic benefit indicators are determined based on the engineering economic benefit analysis method, and the accessibility impact analysis is carried out by combining the Monte Carlo prediction method, cluster analysis method and Markov decision method. Based on the results of the accessibility impact analysis, the impact of accessibility on economic benefits is determined, economic benefits are calculated, and thus operation and maintenance business analysis is carried out. Based on the analysis results of operation and maintenance business, an economic benefit assessment model for offshore wind power is designed to achieve the economic benefit assessment of offshore wind power.

2. The method for evaluating the economic benefits of offshore wind power based on accessibility as described in claim 1, characterized in that: The method for determining engineering economic benefit indicators based on engineering economic benefit analysis includes measuring the power generation cost of offshore wind farms based on the cost per kilowatt-hour. The calculation method for the cost per kilowatt-hour is as follows: wherein, represents the average annual cost of electricity, represents the average annual cost of electricity, represents the average annual cost of electricity, represents the average annual cost of electricity, represents the average annual cost of electricity, represents the average annual cost of electricity, represents the average annual cost of electricity, represents the average annual cost of electricity, represents the average annual cost of electricity, The project's economic benefit indicators include operation and maintenance costs, power generation benefits, and power generation losses. The operation and maintenance costs are the operation and maintenance resource costs of the vessel and the operation and maintenance resource costs of the personnel. The power generation benefits are the total power generation per unit power generation cycle. The power generation losses are the loss of power generation benefits caused by the inability to generate power normally due to shutdown.

3. The method for evaluating the economic benefits of offshore wind power based on accessibility as described in claim 1, characterized in that: The specific implementation steps for the Monte Carlo prediction method include: Set a fan has a component, sample all components, then a fan sampling state is , The state of the th component is represented by , and the fan state is represented by When , it means that the fan stops running due to a fault, and when , it means that the fan can run without a fault. The Monte Carlo method is used for probability statistics, and the following equation is used to represent the average probability of the occurrence of a state of the offshore wind farm: to represent the number of wind turbines in the offshore wind farm that need maintenance, to represent the total number of wind turbines in the offshore wind farm;​​ Setting up an offshore wind farm with a total of Typhoon machine, number In this calculation, the failure probability of a single wind turbine is: The number of failures in an offshore wind farm can then be estimated as follows: ; For cluster analysis, the specific implementation steps include: At the same time, the wind turbine status is When this happens, it means the fan has stopped due to a malfunction. When the fan is in a fault-free state, it can be operated. Combining the two states of fault repair and regular maintenance, the fan status can be specifically divided into: At that time, the wind turbine has already issued a maintenance alarm signal, or is in a state of delayed maintenance due to weather accessibility issues. At that time, the wind turbine does not require maintenance or repair, or although the wind turbine can generate electricity, it requires regular maintenance; Assuming that the offshore wind farm has a total of Typhoon generators, based on operational monitoring status and daily maintenance plans, have The typhoon turbines require maintenance. Among them, the number of turbines that have issued maintenance alarm signals and those whose maintenance has been delayed is [number missing]. The number of wind turbines that did not trigger an alarm but require maintenance according to the scheduled maintenance plan is [number missing]. tower; by Using these wind turbines as cluster centers, k-means clustering was employed to initially divide the offshore wind farm's turbines awaiting maintenance. The alarm fan is used as the initial condensation point for calculation. Taiwanese fans awaiting repair Distance of alarm fan ,Will The fans awaiting maintenance are divided into Class, calculate initial The mean of each class is calculated for each fan under maintenance up to the initial value. Use the Euclidean distance between classes to achieve classification; For the Markov decision-making method, the specific implementation steps include: Representing a Markov chain: in, Represents a Markov chain. Let be the wind turbine state set, representing the set of all possible states of the wind turbine. These numbers represent the fan's condition as follows: intact, good, relatively good, dangerous, and faulty, respectively. Let represent the state transition probability matrix, where Indicates wind turbine Always in a state of readiness hour, Shifting to a new state The probability, These represent the states of intact, good, relatively good, dangerous, and faulty, respectively. Let represent the initial probability distribution, where express At time t, the probability matrix of each degenerate state. For row vectors, express Always in a state of readiness The probability of; A wind turbine state prediction model is established by using a Markov process and combining it with a state transition probability matrix. in, Indicates in The probability distribution vector of the wind turbine state at time t is given. This represents the probability distribution vector of the wind turbine state at the initial moment. Represents the state transition probability matrix Power of 1 Indicates at any intermediate time. The wind turbine state probability distribution vector. Represents the state transition probability matrix Power of 1.

4. The method for evaluating the economic benefits of offshore wind power based on accessibility as described in claim 1, characterized in that: The impact of accessibility on economic benefits includes the impact of accessibility on operation and maintenance activities, and an analysis of the operation and maintenance waiting time caused by accessibility. Regarding the impact of accessibility on operations and maintenance activities, weather conditions are specifically divided into four basic weather events. If the weather is in the first basic weather event, maintenance can be carried out immediately without waiting. If the weather is in the second, third, or fourth basic weather event, maintenance will be delayed. The first type of basic weather event is when the weather is accessible and continuous, with the duration of accessibility longer than the maintenance time, which is sufficient to complete the fault repair task. The second type of basic weather event is when the weather is inaccessible, making it impossible to carry out the maintenance task. The third type of basic weather event is when the weather was inaccessible before the fault occurred, but became accessible and continuous after the fault occurred, although the duration of accessibility is less than the maintenance time, making it impossible to complete the maintenance task. The fourth type of basic weather event is when the weather was accessible and continuous both before and after the fault occurred, but the remaining duration after the fault occurred is less than the maintenance time, making it impossible to complete the maintenance task. If the weather is accessible and persistent, but the duration of accessibility or the remaining duration after the fault occurs is less than the repair time, then repair cannot be performed. The event is converted to a second type of basic weather event, and we need to wait until the weather changes from inaccessible to accessible. Then we need to further determine whether the repair can be completed within the duration of accessibility. If the repair can be completed, then it is a first type of basic weather event, and the repair can be performed. If the duration of accessible weather is less than the repair time, then it is converted to a third type of basic weather event, and we continue to wait until the weather is accessible and the duration meets the requirements before the repair is performed.

5. The method for evaluating the economic benefits of offshore wind power based on accessibility as described in claim 4, characterized in that, The analysis of maintenance wait times caused by reachability specifically includes: Set the average maintenance time to Weather reachability This indicates the proportion of available days to the total number of days, representing the downtime for maintenance. Represented as: ； Calculate waiting time for reachability weather : in, This represents the weather accessibility factor, used to reflect how quickly the proportion of maintenance time in downtime changes with airworthiness rate. This indicates the percentage of days throughout the year when weather conditions are suitable for sailing.

6. The method for evaluating the economic benefits of offshore wind power based on accessibility as described in claim 1, characterized in that: The economic benefits calculation includes the power generation revenue of offshore wind farms, the operation and maintenance transportation costs of offshore wind farms, the downtime of wind turbines, the availability rate of wind farms, and the resource utilization rate.

7. The method for evaluating the economic benefits of offshore wind power based on accessibility as described in claim 5, characterized in that: The revenue generated by offshore wind farms specifically includes: Setting up an offshore wind farm with a total of Typhoon machine, number Typhoon machine The output power at time is Then in terms of duration Actual power generation of the entire site during the time period Represented as: ； Calculation duration Ideal power generation of the entire site during the time period : in, express time, The sum of the power output of the typhoon generators under normal operating conditions; Calculation duration During the time period, the total power loss was... : ； The specific transportation costs for the operation and maintenance of offshore wind farms include: Calculate the total annual cost of the vessel: in, This indicates the total annual cost of the vessel. This indicates the ship's annual fixed costs. This represents the unit time cost of a ship. Indicates the time a ship spends at sea to carry out a mission; Calculate human resource costs: in, This indicates human resources costs. This refers to fixed personnel costs. Indicates the number of people. This indicates subsidies for going overseas. Indicates the number of days spent at sea; The specific downtime of the wind turbines includes: Calculate downtime: in, Indicates the downtime. This indicates the downtime due to a fault, referring to the period from when the fan stops operating due to a fault until the fault is repaired. , Indicates preparation time. Indicates sailing time. , This indicates the distance from the maintenance center to the offshore wind turbine. Indicates ship speed. Indicates the repair time. Indicates weather-related downtime. , This indicates that the wind speed is lower than the cut-in wind speed. Time, This indicates that the wind speed is higher than the cut-out wind speed. Time, Indicates the planned maintenance and repair time; For wind farm availability, the specific components include: Calculate the available runtime of the fan: in, This indicates the availability of operating time for the wind turbine. Indicates the operating time of the fan. Indicates the downtime of the fan; Calculate the technical power generation availability of offshore wind farms: in, Indicates the availability of power generation capacity. This represents the actual power generation of the entire site. This represents the ideal power generation for the entire site; Regarding resource utilization rate, it specifically includes: The total working time of a single vessel is calculated based on its outbound and return travel times and maintenance duration for a single maintenance task. The total man-hours are calculated based on the personnel's waiting time, sailing time, and maintenance time.

8. The method for evaluating the economic benefits of offshore wind power based on accessibility as described in claim 1, characterized in that: The operation and maintenance business analysis includes the determination of operation and maintenance strategies, operation and maintenance processes, and operation and maintenance constraints.

9. The method for evaluating the economic benefits of offshore wind power based on accessibility as described in claim 1, characterized in that, The design of the offshore wind power economic benefit assessment model specifically includes: Design an economic benefit assessment model for offshore wind power, and determine the business logic for operation and maintenance, the business logic for operation and maintenance personnel, the business logic for operation and maintenance vessels, and the business logic for spare parts.

10. An offshore wind power economic benefit assessment device based on accessibility, characterized in that, The accessibility-based offshore wind power economic benefit assessment device includes: The accessibility impact analysis module is used to determine the engineering economic benefit indicators based on the engineering economic benefit analysis method, and to conduct accessibility impact analysis by combining the Monte Carlo prediction method, cluster analysis method and Markov decision method. The Operations and Maintenance Business Analysis module is used to determine the impact of accessibility on economic benefits based on the results of accessibility impact analysis, in order to calculate economic benefits and thus conduct operations and maintenance business analysis. The execution module is used to design an offshore wind power economic benefit assessment model based on the results of operation and maintenance business analysis, thereby realizing the offshore wind power economic benefit assessment.

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