Offshore wind power grid connection point determination method and device, computer equipment and storage medium

Abstract

The invention provides an offshore wind power grid connection point determination method and device, computer equipment and a storage medium, and relates to the field of offshore wind power access. The method comprises the following steps: calculating a plurality of main evaluation indexes according to access regional power grid operation data and offshore wind power planning data; for any main evaluation index, calculating a subjective weight and an objective weight of the main evaluation index, and performing combined weighting on the subjective weight and the objective weight by adopting a maximum variable coefficient method to obtain a comprehensive weight of the main evaluation index; on the basis of comprehensive weights corresponding to the main evaluation indexes, performing weighted summation on the main evaluation indexes of different offshore wind power grid-connected points to obtain a first comprehensive score, taking the offshore wind power grid-connected points with the first comprehensive scores greater than or equal to a score threshold as candidate grid-connected points, and performing secondary evaluation on the candidate grid-connected points to obtain a target grid-connected point; if all the first comprehensive scores are smaller than the score threshold value, the first comprehensive scores are calculated again.

Description

Technical Field

[0001] This application relates to the field of offshore wind power grid connection, and in particular to a method, apparatus, computer equipment and readable storage medium for determining offshore wind power grid connection points. Background Technology

[0002] With increasing global emphasis on energy security, ecological environment, and climate change, accelerating the development of new energy sources such as wind power and photovoltaics has become a common consensus and concerted action in the international community to promote energy transformation and address global climate change. In the development of new energy sources, wind power has experienced sustained and rapid growth worldwide due to its short construction cycle, low environmental requirements, abundant reserves, and high utilization rate. Because wind power generation is a low-emission, low-pollution, low-carbon electricity development model, my country has identified it as one of its important strategic choices for sustainable power development.

[0003] Offshore wind power boasts advantages such as stable wind energy, high utilization hours, minimal impact from topography, and suitability for large-scale development. Furthermore, its proximity to power load centers facilitates local grid integration, avoiding the need for long-distance transmission of large-scale wind power. By the end of 2022, my country's cumulative installed offshore wind power capacity exceeded 30 million kilowatts, ranking first globally for two consecutive years and accounting for approximately half of the total. With the gradual development of offshore wind power resources, larger single-unit capacity and larger-scale offshore wind farms will be the future development direction.

[0004] Currently, there are three methods for transmitting offshore wind power: high-voltage AC transmission, flexible DC transmission, and frequency-division transmission. High-voltage AC transmission submarine cables exhibit a significant capacitive charging effect, with the capacitive charging current increasing dramatically with transmission distance. This severely impacts the actual active power transmission capacity of the cable and increases transmission losses. Flexible DC transmission eliminates the reactive power charging problem associated with submarine cables, offering a clear economic advantage in terms of cable investment. Frequency-division transmission combines the advantages of both traditional AC and DC transmission methods. By reducing the frequency, it increases the cable's current-carrying capacity and reduces the capacitive charging current in the line, thereby improving transmission capacity and distance. It also avoids the need for offshore converter stations, significantly reducing investment and maintenance costs.

[0005] Offshore wind farms have large planned installed capacities, and the issue of wind power integration urgently needs to be addressed. The grid security after wind power integration also faces challenges. Different wind power grid connection points have varying impacts on the grid, making the selection of suitable connection points crucial for wind power integration and the safe and stable operation of the grid. Currently, the incomplete consideration of factors in site selection for large-scale offshore wind power grid connection via flexible DC / frequency division is a pressing issue that needs to be addressed. Summary of the Invention

[0006] In view of this, this application provides a method, apparatus, computer equipment and readable storage medium for determining the grid connection point of offshore wind power, which solves the problem of incomplete consideration of site selection factors for large-scale offshore wind power connected to flexible DC grid or frequency-division grid in related technologies.

[0007] In a first aspect, embodiments of this application provide a method for determining the grid connection point of offshore wind power, including: Based on the grid operation data of the access area and offshore wind power planning data, calculate several key evaluation indicators for different offshore wind power grid connection points; For any major evaluation indicator, the subjective weight of the major evaluation indicator is calculated using the three-scale improved analytic hierarchy process, the objective weight of the major evaluation indicator is calculated using the improved entropy weight method, and the maximum coefficient of variation method is used to combine and assign weights to the subjective and objective weights to obtain the comprehensive weight of the major evaluation indicator. Based on the comprehensive weights corresponding to the main evaluation indicators, the main evaluation indicators of different offshore wind power grid connection points are weighted and summed to obtain the first comprehensive score of different offshore wind power grid connection points. If there is only one offshore wind power grid connection point with a first comprehensive score greater than or equal to the score threshold, then that offshore wind power grid connection point is designated as the target grid connection point; if there are multiple offshore wind power grid connection points with a first comprehensive score greater than or equal to the score threshold, then these multiple offshore wind power grid connection points are designated as candidate grid connection points, and a second evaluation is performed on the candidate grid connection points to obtain the target grid connection point; if all first comprehensive scores are less than the score threshold, then at least one of the main evaluation indicators, the subjective weights, and the objective weights is adjusted, and the first comprehensive score is recalculated.

[0008] Secondly, embodiments of this application provide an offshore wind power grid connection point determination device, comprising: The evaluation index calculation module is used to calculate multiple key evaluation indicators for different offshore wind power grid connection points based on grid operation data of the access area and offshore wind power planning data. The weight calculation module is used to calculate the subjective weight of any major evaluation indicator using the three-scale improved analytic hierarchy process, calculate the objective weight of the major evaluation indicator using the improved entropy weight method, and combine the subjective and objective weights using the maximum coefficient of variation method to obtain the comprehensive weight of the major evaluation indicator. The grid connection point determination module is used to perform a weighted summation of the main evaluation indicators for different offshore wind power grid connection points based on the comprehensive weights corresponding to the main evaluation indicators, so as to obtain the first comprehensive score for different offshore wind power grid connection points; and if there is only one offshore wind power grid connection point with the first comprehensive score greater than or equal to the score threshold, then the offshore wind power grid connection point is taken as the target grid connection point; if there are multiple offshore wind power grid connection points with the first comprehensive score greater than or equal to the score threshold, then the multiple offshore wind power grid connection points are taken as candidate grid connection points, and the candidate grid connection points are evaluated a second time to obtain the target grid connection point; if all the first comprehensive scores are less than the score threshold, then at least one of the main evaluation indicators, the subjective weights, and the objective weights is adjusted, and the first comprehensive score is recalculated.

[0009] Thirdly, embodiments of this application provide a computer device including a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions implementing the steps of the method as described in the first aspect when executed by the processor.

[0010] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method as described in the first aspect.

[0011] The method, apparatus, computer equipment, and readable storage medium for determining offshore wind power grid connection points in this application calculate various key evaluation indicators for each offshore wind power grid connection point based on grid operation data and offshore wind power planning data of the access area, combined with power flow calculations and simulation results. For any key evaluation indicator, the subjective weight of the key evaluation indicator is calculated using the three-scale improved analytic hierarchy process (AHP), the objective weight of the key evaluation indicator is calculated using the improved entropy weight method, and the maximum coefficient of variation method is used to combine and assign weights to the subjective and objective weights to obtain the comprehensive weight of the key evaluation indicator. Based on the comprehensive weights corresponding to the key evaluation indicators, the key evaluation indicators of different offshore wind power grid connection points are weighted and summed to obtain the first comprehensive score of different offshore wind power grid connection points. If there is only one offshore wind power grid connection point with a first comprehensive score greater than or equal to the score threshold, then that offshore wind power grid connection point is designated as the target grid connection point; if there are multiple offshore wind power grid connection points with a first comprehensive score greater than or equal to the score threshold, then these multiple offshore wind power grid connection points are designated as candidate grid connection points, and a second evaluation is performed on the candidate grid connection points to obtain the target grid connection point; if all first comprehensive scores are less than the score threshold, then at least one of the main evaluation indicators, the subjective weights, and the objective weights is adjusted, and the first comprehensive score is recalculated.

[0012] The offshore wind farm grid connection index proposed in this application comprehensively considers multiple influencing factors, ensuring the grid absorption capacity of wind power connection points, improving the safety and stability of the receiving-end grid, and enhancing the economics of wind power grid connection. Furthermore, by introducing a minimum score threshold screening and a secondary evaluation mechanism, this application effectively avoids selecting grid connection points with low scores, improving the reliability and adaptability of the scheme, especially enhancing the robustness of the selection process in complex grid environments. A dynamic adjustment mechanism, such as readjusting indicators or weights, ensures that the method can adapt to different wind power scenarios and grid conditions, improving the practicality and flexibility of the technology. The secondary evaluation, through detailed comparison of secondary indicators, further optimizes the selection accuracy, reduces subjective bias, and improves economic efficiency and safety.

[0013] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0014] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A flowchart illustrating the method for determining the grid connection point of offshore wind power according to an embodiment of this application is shown; Figure 2 A schematic diagram illustrating the principle of the offshore wind power grid connection point determination method according to an embodiment of this application is shown; Figure 3 A structural block diagram of the offshore wind power grid connection point determination device according to an embodiment of this application is shown; Figure 4 A structural block diagram of a computer device according to an embodiment of this application is shown. Detailed Implementation

[0015] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0016] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0017] The method, apparatus, computer equipment, and readable storage medium for determining the offshore wind power grid connection point provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0018] This application provides a method for determining the grid connection point of offshore wind power, such as... Figure 1 and Figure 2 As shown, the method includes: Step 101: Calculate multiple key evaluation indicators for different offshore wind power grid connection points based on the grid operation data of the access area and offshore wind power planning data.

[0019] In this step, based on the grid operation data of the access area and the offshore wind power planning data, combined with power flow calculations and simulation results, the main evaluation indicators for each offshore wind power grid connection point are calculated. In one embodiment of this application, the main evaluation indicators include at least two of the following: wind power absorption, wind power fluctuation impact, grid node vulnerability, short-circuit ratio of new energy power plants, inertial support of flexible DC converters or frequency-divided AC-AC converters, and construction cost.

[0020] In step 101, the main evaluation indicators for offshore wind power grid connection points are calculated as follows: (1) Wind power consumption: ; In the formula, This represents the maximum wind power absorption capacity at offshore wind power grid connection point j. To consider the maximum wind power absorption under extreme conditions, it is assumed that the load at offshore wind power grid connection point j is the daily maximum load. , This indicates the maximum power that offshore wind power at grid connection point j can transmit via the tie line. This represents the minimum output of the g-th conventional turbine connected to the offshore wind power grid connection point j. This indicates the number of all conventional turbine units connected to the offshore wind power grid connection point j.

[0021] (2) Impact of wind power fluctuations: ; ; In the formula, This indicates the steady-state output of an offshore wind farm. This represents the change in wind power output. Indicates wind power output as Time bus voltage, Indicates wind power output as Time bus voltage, This indicates that the fluctuation in wind power is Time bus The voltage change value, This refers to the set of buses connected to the area.

[0022] (3) Vulnerability of power grid nodes: For the offshore wind power grid connection point j, assuming the line Connected to it, the line transmits power of [missing information] before the wind power is connected to the grid. And the maximum transmission power is The line load rate index is calculated as follows: ; Assuming the route The voltages at grid connection point j before and after fault clearing are respectively and Then N The voltage offset index at the fault node is calculated as follows: ; Taking into account both load factor and voltage offset, the vulnerability index of offshore wind power grid connection points is calculated as follows: ; (4) Short-circuit ratio of new energy power plants: ; In the formula, The actual operating voltage of the busbar at the grid connection point. The nominal voltage of the busbar at the grid connection point. The equivalent impedance from the system side of the grid connection point of the new energy power station, The actual apparent power of new energy injected into the grid connection point.

[0023] (5) Inertial support for flexible DC converter / frequency divider AC-AC converter: When offshore wind farms are connected via flexible DC / frequency division transmission, the DC capacitors in the converters have the ability to temporarily store energy and have significant frequency support potential. When the system frequency exceeds the specified dead zone, the corresponding inertial support strategy will be activated.

[0024] The converter can provide an inertial constant of approximately: ; in, For the maximum permissible DC voltage deviation, This represents the frequency deviation range corresponding to the DC link inertial control. N arm The number of subbridge arms of the converter. N sm Each sub-arm contains a number of sub-modules. For submodule unit capacitors, V dc0 This refers to either the DC bus voltage or the voltage of the cascaded modules of the frequency divider AC-AC converter bridge arm. f 0 represents the system's rated frequency. S C This refers to the capacity of the converter or frequency divider AC-AC converter.

[0025] Limited by the submodule capacitance value, maximum DC voltage deviation range, and maximum frequency deviation range, for a given converter, the submodule capacitance value and maximum DC voltage deviation range are the same at different connection points. When the grid frequency changes, by altering the DC capacitor voltage of the converter in the flexible DC / frequency division system, the DC capacitor can absorb or release a certain amount of electrical energy to offset some of the impact of suddenly switched loads on the AC system. Therefore, the maximum load suddenly switched at the grid connection point can be used to reflect the inertial support effect of the converter.

[0026] ; In the formula, This indicates the maximum load that is switched on at point j, the grid connection point for offshore wind power.

[0027] (6) Construction cost: ; In the formula, The length of the submarine cable between the offshore wind farm and the grid connection point j.

[0028] This application embodiment constructs an index system that comprehensively considers various influencing factors such as wind power absorption, wind power fluctuation impact, grid node vulnerability, short-circuit ratio of new energy power plants, inertial support of AC-AC frequency converters, and construction costs. This solves the problem of incomplete consideration of factors in the site selection of large-scale offshore wind power connected to the grid via flexible DC or frequency-division grid in related technologies.

[0029] Furthermore, this application considers the inertial support effect of the flexible DC / frequency division transmission converter on the grid connection point, proposes an evaluation index for the inertial support effect of the converter, and effectively utilizes the frequency support of the receiving-end grid by the flexible DC / frequency division transmission method.

[0030] In one embodiment of this application, after calculating the values ​​of various indicators for different offshore wind power grid connection points, the method further includes: performing dimensionless and normalized processing on each major evaluation indicator; Specifically, the main evaluation indicators are dimensionless and normalized, including: Assuming there are m offshore wind power grid connection points, which are selectable grid connection points, and each offshore wind power grid connection point has n main evaluation indicators, a data matrix can be established: ; in, For the j-th offshore wind power grid connection point, the i-th main evaluation indicator is... , m represents the number of offshore wind power grid connection points, and n represents the number of main evaluation indicators for offshore wind power grid connection points.

[0031] Among the above indicators, and The higher the indicator value, the better the node. The smaller the indicator value, the better the node.

[0032] Processing data matrices using dimensionless normalization formulas The dimensionless normalized data matrix is ​​obtained. This allows the data to be in Within the range, the larger the data value, the better the indicator value.

[0033] The dimensionless normalization formula is: ; ; in, For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. Let be the minimum value of the i-th main evaluation index for the j-th offshore wind power grid connection point. It represents the maximum value of the i-th main evaluation index for the j-th offshore wind power grid connection point.

[0034] Step 102: For any major evaluation indicator, calculate the subjective weight of the major evaluation indicator using the three-scale improved analytic hierarchy process, calculate the objective weight of the major evaluation indicator using the improved entropy weight method, and combine the subjective weight and objective weight using the maximum coefficient of variation method to obtain the comprehensive weight of the major evaluation indicator.

[0035] In this step, based on the normalized main evaluation indicators, the subjective weights of the main evaluation indicators are calculated using the three-scale improved analytic hierarchy process (AHP) with a range of (0,1,-1). The objective weights of the main evaluation indicators are calculated based on the improved entropy weight method. Then, the maximum coefficient of variation method is used to combine the subjective and objective weights to obtain the comprehensive weight of each indicator. .

[0036] In one embodiment of this application, the subjective weights of the main evaluation indicators are calculated using the three-scale improved analytic hierarchy process, including: For n key evaluation indicators, a comparison matrix A is constructed using the three-scale improved analytic hierarchy process based on (0,1,-1), where A is: ; in, It can be 1, 0, or -1. , t , A value of 1 indicates that the primary evaluation indicator i is more important than the primary evaluation indicator t. A value of 0 indicates that the main evaluation indicator i is as important as the main evaluation indicator t. When the value is -1, it indicates that the main evaluation indicator t is more important than the main evaluation indicator i.

[0037] Based on the comparison matrix A, the judgment matrix D is obtained, and D is: ; in, ; The subjective weight of the i-th main evaluation indicator is obtained based on the judgment matrix D. The formula for calculating the subjective weight is as follows: ; In one embodiment of this application, the objective weights of the main evaluation indicators are calculated using the improved entropy weight method, including: According to the definition of entropy, the entropy value of the i-th main evaluation indicator is calculated using the following formula: ; in, , And set when hour, , For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. , m represents the number of offshore wind power grid connection points, and n represents the number of main evaluation indicators for offshore wind power grid connection points; According to the entropy weight method, the objective weight of the i-th main evaluation indicator is calculated. The formula for calculating the objective weight is: ; In one embodiment of this application, the maximum coefficient of variation method is used to combine subjective and objective weights to obtain the comprehensive weights of the main evaluation indicators, including: Subjective weight is Objective weight is The combined weight is Calculate the vector between the j-th offshore wind power grid connection point and the average value. Weighted distance, weighted distance The calculation formula is as follows: ; ; in, For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. For comprehensive weighting, , The comprehensive weight of the i-th main evaluation indicator, and the coefficient of variation. , Let be the standard deviation of the i-th evaluation index value for the j-th offshore wind power grid connection point. Let m be the average value of the i-th evaluation index for the j-th offshore wind power grid-connected point, m be the number of offshore wind power grid-connected points, and n be the number of main evaluation indicators for the offshore wind power grid-connected points; coefficient of variation The larger the value, the greater the variability in the distribution of the i-th main evaluation indicator in the comprehensive evaluation, the greater the information content, the stronger the information discrimination ability of the main evaluation indicator, and the greater its weight.

[0038] The combined weighting model is constructed as follows: ; ; in, The subjective weight of the i-th primary evaluation indicator. The objective weight of the i-th main evaluation indicator. The coefficient is the subjective weight. The coefficient representing the objective weight; Construct the Lagrangian function as follows: ; Solving using the Lagrange extremum method, we obtain: ; right and After normalization, we get: ; The normalized comprehensive weight of the i-th primary evaluation index is: .

[0039] Step 103: Based on the comprehensive weights corresponding to the main evaluation indicators, the main evaluation indicators of different offshore wind power grid connection points are weighted and summed to obtain the first comprehensive score of different offshore wind power grid connection points.

[0040] In this step, through dimensionless and normalization processing, and by using the subjective weighting method of the improved three-scale hierarchical analysis, the objective weighting method of the improved entropy weight method, and the subjective and objective weighting combination method based on the maximum coefficient of variation method, different offshore wind farm grid connection points are scored, providing reliable data support for optimizing the selection of offshore wind farm grid connection points.

[0041] Step 104: If there is only one offshore wind power grid connection point with a first comprehensive score greater than or equal to the score threshold, then that offshore wind power grid connection point is taken as the target grid connection point; if there are multiple offshore wind power grid connection points with a first comprehensive score greater than or equal to the score threshold, then the multiple offshore wind power grid connection points are taken as candidate grid connection points, and a second evaluation is performed on the candidate grid connection points to obtain the target grid connection point; if all first comprehensive scores are less than the score threshold, then at least one of the main evaluation indicators, subjective weights, and objective weights is adjusted, and the first comprehensive score is recalculated.

[0042] In this step, the obtained multiple first comprehensive scores are compared with a score threshold, which is a minimum score threshold Tmin dynamically set based on historical data, expert experience, or simulation analysis. The following situations may occur after the comparison: (1) If there is only one offshore wind power grid connection point with a first comprehensive score greater than or equal to the score threshold, then that offshore wind power grid connection point shall be regarded as the target grid connection point, that is, the optimal grid connection point. For example, if there are 10 offshore wind power grid connection points, and only one of them has a first comprehensive score exceeding the score threshold, then that offshore wind power grid connection point shall be regarded as the target grid connection point.

[0043] (2) If there are multiple offshore wind power grid connection points with a first comprehensive score greater than or equal to the score threshold, then these multiple offshore wind power grid connection points are used as candidate grid connection points, and a second evaluation is conducted on the candidate grid connection points to obtain the target grid connection point. For example, if there are 10 offshore wind power grid connection points, and only 7 of them have a first comprehensive score that exceeds the score threshold, then these 7 offshore wind power grid connection points are all used as candidate grid connection points, and a second evaluation is conducted to finally determine a target grid connection point.

[0044] In one embodiment of this application, a secondary evaluation of candidate grid connection points is performed to obtain target grid connection points, including: calculating a second comprehensive score for candidate grid connection points based on secondary evaluation indicators; determining the maximum value in the second comprehensive score, and using the candidate grid connection point corresponding to the maximum value as the target grid connection point.

[0045] In this embodiment, secondary evaluation indicators, such as line transmission efficiency, environmental adaptability, and operation and maintenance costs, are introduced. These indicators have low weight or are not included in the calculation of the first comprehensive score. A second comprehensive score is calculated for each candidate node based on these secondary evaluation indicators. The calculation method can involve dimensionless and normalized processing, and utilizing a subjective weighting method based on a three-scale improved analytic hierarchy process, an objective weighting method based on an improved entropy weighting method, or a combined subjective and objective weighting method based on the maximum coefficient of variation method to calculate the second comprehensive score for each offshore wind farm grid-connected point. Based on the ranking of the second comprehensive scores, the offshore wind farm grid-connected point corresponding to the highest value is selected as the target grid-connected point. If multiple grid-connected points have similar scores after the second evaluation, the target grid-connected point can be further determined by combining expert decision-making or simulation verification.

[0046] (3) If all first comprehensive scores are less than the score threshold, adjust at least one of the main evaluation indicators, subjective weights and objective weights, recalculate the first comprehensive scores, and then conduct a second evaluation.

[0047] If all offshore wind farm grid connection points score below the score threshold, the main evaluation indicators will be adjusted, such as adding indicators for grid fault recovery capability and environmental adaptability, or the weight calculation method will be adjusted, such as modifying the scaling value of subjective weights or the entropy parameter of objective weights, to obtain a new first comprehensive score, and the score threshold will be applied again for screening.

[0048] Finally, the optimal grid connection point is output, and the obtained target grid connection point is used as the optimization result for offshore wind farm grid connection planning.

[0049] The offshore wind farm grid connection index proposed in this application comprehensively considers multiple influencing factors, ensuring the grid absorption capacity of wind power connection points, improving the safety and stability of the receiving-end grid, and enhancing the economics of wind power grid connection. Furthermore, by introducing a minimum score threshold screening and a secondary evaluation mechanism, this application effectively avoids selecting grid connection points with low scores, improving the reliability and adaptability of the scheme, especially enhancing the robustness of the selection process in complex grid environments. A dynamic adjustment mechanism, such as readjusting indicators or weights, ensures that the method can adapt to different wind power scenarios and grid conditions, improving the practicality and flexibility of the technology. The secondary evaluation, through detailed comparison of secondary indicators, further optimizes the selection accuracy, reduces subjective bias, and improves economic efficiency and safety.

[0050] As a specific implementation of the above-mentioned method for determining the grid connection point of offshore wind power, this application provides an apparatus for determining the grid connection point of offshore wind power. For example... Figure 3 As shown, the offshore wind power grid connection point determination device 300 includes: an evaluation index calculation module 301, a weight calculation module 302, and a grid connection point determination module 303.

[0051] Among them, the evaluation index calculation module 301 is used to calculate multiple main evaluation indicators for different offshore wind power grid connection points based on the grid operation data of the access area and the offshore wind power planning data. The weight calculation module 302 is used to calculate the subjective weight of any major evaluation indicator using the three-scale improved analytic hierarchy process, calculate the objective weight of the major evaluation indicator using the improved entropy weight method, and combine the subjective weight and objective weight using the maximum coefficient of variation method to obtain the comprehensive weight of the major evaluation indicator. The grid connection point determination module 303 is used to perform weighted summation of the main evaluation indicators of different offshore wind power grid connection points based on the comprehensive weights corresponding to the main evaluation indicators, so as to obtain the first comprehensive score of different offshore wind power grid connection points; and if there is only one offshore wind power grid connection point with the first comprehensive score greater than or equal to the score threshold, then the offshore wind power grid connection point is taken as the target grid connection point; if there are multiple offshore wind power grid connection points with the first comprehensive score greater than or equal to the score threshold, then the multiple offshore wind power grid connection points are taken as candidate grid connection points, and the candidate grid connection points are evaluated a second time to obtain the target grid connection point; if all the first comprehensive scores are less than the score threshold, then at least one of the main evaluation indicators, subjective weights and objective weights is adjusted, and the first comprehensive score is recalculated.

[0052] Furthermore, the device also includes a data processing module for performing dimensionless and normalized processing on each major evaluation indicator; The dimensionless and normalized processing of the main evaluation indicators includes: Establish a data matrix ,in, For the j-th offshore wind power grid connection point, the i-th main evaluation indicator is... , m represents the number of offshore wind power grid connection points, and n represents the number of main evaluation indicators for offshore wind power grid connection points; Processing data matrices using dimensionless normalization formulas The dimensionless normalized data matrix is ​​obtained. The dimensionless normalization formula is: ; in, For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. Let be the minimum value of the i-th main evaluation index for the j-th offshore wind power grid connection point. It represents the maximum value of the i-th main evaluation index for the j-th offshore wind power grid connection point.

[0053] Furthermore, several key evaluation indicators include at least two of the following: wind power absorption, impact of wind power fluctuations, grid node vulnerability, short-circuit ratio of new energy power plants, inertial support of flexible DC converters or frequency-divided AC-AC converters, and construction cost.

[0054] Furthermore, the weight calculation module 302 is specifically used for: For n key evaluation indicators, a comparison matrix A is constructed using the three-scale improved analytic hierarchy process based on (0,1,-1), where A is: ; in, It can be 1, 0, or -1. , t , A value of 1 indicates that the primary evaluation indicator i is more important than the primary evaluation indicator t. A value of 0 indicates that the main evaluation indicator i is as important as the main evaluation indicator t. When the value is -1, it indicates that the main evaluation indicator t is more important than the main evaluation indicator i. Based on the comparison matrix A, the judgment matrix D is obtained, and D is: ; in, ; The subjective weight of the i-th main evaluation indicator is obtained based on the judgment matrix D. The formula for calculating the subjective weight is as follows: .

[0055] Furthermore, the weight calculation module 302 is specifically used for: According to the definition of entropy, the entropy value of the i-th main evaluation indicator is calculated using the following formula: ; in, , And set when hour, , For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. , m represents the number of offshore wind power grid connection points, and n represents the number of main evaluation indicators for offshore wind power grid connection points; According to the entropy weight method, the objective weight of the i-th main evaluation indicator is calculated. The formula for calculating the objective weight is: .

[0056] Furthermore, the weight calculation module 302 is specifically used for: Calculate the vector of the j-th offshore wind power grid connection point and the average value. Weighted distance, weighted distance The calculation formula is as follows: ; ; in, For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. For comprehensive weighting, , The comprehensive weight of the i-th main evaluation indicator, and the coefficient of variation. , Let be the standard deviation of the i-th evaluation index value for the j-th offshore wind power grid connection point. is the average value of the i-th evaluation index of the j-th offshore wind power grid connection point, m is the number of offshore wind power grid connection points, and n is the number of main evaluation indicators of the offshore wind power grid connection points; The combined weighting model is constructed as follows: ; ; in, The subjective weight of the i-th primary evaluation indicator. The objective weight of the i-th main evaluation indicator. The coefficient is the subjective weight. The coefficient representing the objective weight; Construct the Lagrangian function as follows: ; Solving using the Lagrange extremum method, we obtain: ; right and After normalization, we get: ; The normalized comprehensive weight of the i-th primary evaluation index is: .

[0057] Furthermore, the grid connection point determination module 303 is specifically used for: Based on secondary evaluation indicators, calculate the second comprehensive score of candidate grid connection points; The maximum value in the second comprehensive score is determined, and the candidate grid connection point corresponding to the maximum value is taken as the target grid connection point.

[0058] The offshore wind power grid connection point determination device 300 in this application embodiment can be a computer device or a component within a computer device, such as an integrated circuit or a chip. The offshore wind power grid connection point determination device 300 provided in this application embodiment can achieve... Figure 1 The various processes implemented in the method for determining the grid connection point of offshore wind power will not be described in detail here to avoid repetition.

[0059] This application also provides a computer device, such as... Figure 4 As shown, the computer device 400 includes a processor 401 and a memory 402. The memory 402 stores programs or instructions that can run on the processor 401. When the program or instructions are executed by the processor 401, they implement the various steps of the above-described method embodiment for determining the grid connection point of offshore wind power and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0060] The memory 402 can be used to store software programs and various data. The memory 402 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 402 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 402 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0061] Processor 401 may include one or more processing units; optionally, processor 401 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 401.

[0062] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described offshore wind power grid connection point determination method embodiment and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0063] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0064] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for determining the grid connection point of offshore wind power, characterized in that, include: Based on the grid operation data of the access area and offshore wind power planning data, calculate several key evaluation indicators for different offshore wind power grid connection points; For any major evaluation indicator, the subjective weight of the major evaluation indicator is calculated using the three-scale improved analytic hierarchy process, the objective weight of the major evaluation indicator is calculated using the improved entropy weight method, and the maximum coefficient of variation method is used to combine and assign weights to the subjective and objective weights to obtain the comprehensive weight of the major evaluation indicator. Based on the comprehensive weights corresponding to the main evaluation indicators, the main evaluation indicators of different offshore wind power grid connection points are weighted and summed to obtain the first comprehensive score of different offshore wind power grid connection points. If there is only one offshore wind power grid connection point with a first comprehensive score greater than or equal to the score threshold, then that offshore wind power grid connection point will be taken as the target grid connection point. If there are multiple offshore wind power grid connection points with a first comprehensive score greater than or equal to the score threshold, then these multiple offshore wind power grid connection points are used as candidate grid connection points, and a second evaluation is performed on the candidate grid connection points to obtain the target grid connection point; if all first comprehensive scores are less than the score threshold, then at least one of the main evaluation indicators, the subjective weights, and the objective weights is adjusted, and the first comprehensive score is recalculated.

2. The method according to claim 1, characterized in that, After calculating the various index values ​​for different offshore wind power grid connection points, the method further includes: The main evaluation indicators were dimensionless and normalized. The dimensionless and normalized processing of the main evaluation indicators includes: Establish a data matrix ,in, For the j-th offshore wind power grid connection point, the i-th main evaluation indicator is... , m represents the number of offshore wind power grid connection points, and n represents the number of main evaluation indicators for offshore wind power grid connection points; Processing data matrices using dimensionless normalization formulas The dimensionless normalized data matrix is ​​obtained. The dimensionless normalization formula is: ； in, For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. Let be the minimum value of the i-th main evaluation index for the j-th offshore wind power grid connection point. It represents the maximum value of the i-th main evaluation index for the j-th offshore wind power grid connection point.

3. The method according to claim 1, characterized in that, Several key evaluation indicators include at least two of the following: wind power consumption, impact of wind power fluctuations, grid node vulnerability, short-circuit ratio of new energy power plants, inertial support of flexible DC converters or frequency-divided AC-AC converters, and construction cost.

4. The method according to claim 1, characterized in that, The calculation of the subjective weights of the main evaluation indicators using the three-scale improved analytic hierarchy process includes: For n key evaluation indicators, a comparison matrix A is constructed using the three-scale improved analytic hierarchy process based on (0,1,-1), where A is: ； in, It can be 1, 0, or -1. , t , A value of 1 indicates that the primary evaluation indicator i is more important than the primary evaluation indicator t. A value of 0 indicates that the main evaluation indicator i is as important as the main evaluation indicator t. When the value is -1, it indicates that the main evaluation indicator t is more important than the main evaluation indicator i. Based on the comparison matrix A, the judgment matrix D is obtained, and D is: ； in, ; The subjective weight of the i-th main evaluation indicator is obtained based on the judgment matrix D. The formula for calculating the subjective weight is as follows: 。 5. The method according to claim 1, characterized in that, The method of calculating the objective weights of the main evaluation indicators using the improved entropy weight method includes: According to the definition of entropy, the entropy value of the i-th main evaluation indicator is calculated using the following formula: ； in, , And set when hour, , For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. , m represents the number of offshore wind power grid connection points, and n represents the number of main evaluation indicators for offshore wind power grid connection points; According to the entropy weight method, the objective weight of the i-th main evaluation indicator is calculated. The formula for calculating the objective weight is: 。 6. The method according to claim 1, characterized in that, The method of maximum coefficient of variation is used to combine subjective and objective weights to obtain the comprehensive weights of the main evaluation indicators, including: Calculate the vector of the j-th offshore wind power grid connection point and the average value. Weighted distance, weighted distance The calculation formula is as follows: ； ； in, For the j-th offshore wind power grid connection point after dimensionless normalization, the i-th main evaluation index is given. For comprehensive weighting, , The comprehensive weight of the i-th main evaluation indicator, and the coefficient of variation. , Let be the standard deviation of the i-th evaluation index value for the j-th offshore wind power grid connection point. is the average value of the i-th evaluation index of the j-th offshore wind power grid connection point, m is the number of offshore wind power grid connection points, and n is the number of main evaluation indicators of the offshore wind power grid connection points; The combined weighting model is constructed as follows: ； ； in, The subjective weight of the i-th primary evaluation indicator. The objective weight of the i-th main evaluation indicator. The coefficient is the subjective weight. The coefficient representing the objective weight; Construct the Lagrangian function as follows: ； Solving using the Lagrange extremum method, we obtain: ； right and After normalization, we get: ； The normalized comprehensive weight of the i-th primary evaluation index is: 。 7. The method according to claim 1, characterized in that, A secondary evaluation of the candidate grid connection sites was conducted to determine the target grid connection sites, including: Based on secondary evaluation indicators, calculate the second comprehensive score of candidate grid connection points; The maximum value in the second comprehensive score is determined, and the candidate grid connection point corresponding to the maximum value is taken as the target grid connection point.

8. A device for determining the grid connection point of offshore wind power, characterized in that, include: The evaluation index calculation module is used to calculate multiple key evaluation indicators for different offshore wind power grid connection points based on grid operation data of the access area and offshore wind power planning data. The weight calculation module is used to calculate the subjective weight of any major evaluation indicator using the three-scale improved analytic hierarchy process, calculate the objective weight of the major evaluation indicator using the improved entropy weight method, and combine the subjective and objective weights using the maximum coefficient of variation method to obtain the comprehensive weight of the major evaluation indicator. The grid connection point determination module is used to perform weighted summation of the main evaluation indicators of different offshore wind power grid connection points based on the comprehensive weights corresponding to the main evaluation indicators, and obtain the first comprehensive score of different offshore wind power grid connection points. Furthermore, if there is only one offshore wind power grid connection point with a first comprehensive score greater than or equal to the score threshold, then that offshore wind power grid connection point will be taken as the target grid connection point. If there are multiple offshore wind power grid connection points with a first comprehensive score greater than or equal to the score threshold, then these multiple offshore wind power grid connection points are used as candidate grid connection points, and a second evaluation is performed on the candidate grid connection points to obtain the target grid connection point; if all first comprehensive scores are less than the score threshold, then at least one of the main evaluation indicators, the subjective weights, and the objective weights is adjusted, and the first comprehensive score is recalculated.

9. A computer device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that run on the processor, the program or instructions being executed by the processor to implement the steps of the offshore wind power grid connection point determination method as described in any one of claims 1 to 7.

10. A readable storage medium having a program or instructions stored thereon, characterized in that, When the program or instructions are executed by the processor, they implement the steps of the offshore wind power grid connection point determination method as described in any one of claims 1 to 7.

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