A method, system, device and medium for offshore wind power transmission system planning decision

Abstract

The application discloses a kind of offshore wind power transmission system planning decision method, system, equipment and medium, it is related to offshore wind power planning technical field, the method includes: based on the wind power collection demand of region to be decided, generate multiple candidate planning schemes;According to the predetermined ac / dc power flow model, each candidate planning scheme is carried out power flow calculation, and the operating state data corresponding to each candidate planning scheme is obtained;According to the operating state data corresponding to each candidate planning scheme, each candidate planning scheme is carried out index calculation from the several evaluation dimensions of pre-set, and multiple index values of each candidate planning scheme are obtained by evaluation, and according to multiple index values of each candidate planning scheme, candidate planning scheme is sorted, and the offshore wind power transmission system planning scheme of region to be decided is decided to obtain.By implementing the present application, the accuracy of large-scale offshore wind power transmission system planning decision can be improved.

Description

Technical Field

[0001] This application relates to the field of offshore wind power planning technology, and in particular to a planning decision-making method, system, equipment and medium for offshore wind power transmission systems. Background Technology

[0002] As offshore wind power develops towards deep-sea and large-scale applications, planning decisions for large-scale offshore wind power transmission systems have gradually become a research hotspot. However, current research on planning decisions for large-scale offshore wind power transmission systems generally suffers from the following shortcomings: (1) It focuses only on a single link in offshore wind power transmission, such as planning only the layout of offshore wind turbines and the site selection of onshore converter stations, lacking overall planning of the entire land-sea process during offshore wind power transmission. This results in planning schemes that are only suitable for a single link, and the accuracy of overall planning cannot meet actual needs; (2) In the planning decision-making process of offshore wind power transmission, simplified power flow calculation models are usually used to assist in the nonlinearity of power flow calculation. However, the simplified models do not fully incorporate the coupling characteristics and nonlinear features of the system, and cannot accurately depict the line losses or the mutual influence between land and sea in the planning decision scheme. The accuracy of planning decisions still has considerable room for optimization. Therefore, how to improve the accuracy of planning decisions for large-scale offshore wind power transmission systems remains an urgent problem to be solved by existing technologies. Summary of the Invention

[0003] This application provides a planning and decision-making method, system, equipment, and medium for offshore wind power transmission systems to solve the technical problem that the planning and decision-making accuracy of existing large-scale offshore wind power transmission systems cannot meet practical needs.

[0004] According to a first aspect of the embodiments of this application, a planning and decision-making method for an offshore wind power transmission system is provided, comprising: Based on the wind power aggregation demand of the area to be decided, multiple candidate planning schemes are generated; wherein, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided; each candidate planning scheme is obtained by combining an offshore aggregation scheme and an onshore access scheme. Based on the preset AC / DC power flow model, power flow calculations are performed on each candidate planning scheme to obtain the corresponding operating status data for each candidate planning scheme; wherein, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operating characteristics of offshore wind power; Based on the operational status data corresponding to each candidate planning scheme, indicators are calculated for each candidate planning scheme from several preset evaluation dimensions. Multiple indicator values ​​are obtained for each candidate planning scheme. Based on the multiple indicator values ​​of each candidate planning scheme, the candidate planning schemes are ranked, and a decision is made to obtain the offshore wind power transmission system planning scheme for the area to be decided.

[0005] This application first generates multiple candidate planning schemes based on the wind power aggregation needs of the region to be decided, by combining offshore aggregation and onshore access schemes. Then, based on a pre-set AC / DC power flow model, it performs power flow calculations on each candidate scheme to obtain corresponding operational status data. Next, based on the operational status data, it calculates indicators for each candidate scheme from several evaluation dimensions, obtaining multiple indicator values ​​for each candidate scheme, and thus ranking and deciding to obtain the offshore wind power transmission system planning scheme for the region to be decided. By generating multiple candidate planning schemes by combining offshore aggregation and onshore access schemes based on the wind power aggregation needs of the region to be decided, this application avoids the inaccuracy of overall planning decisions caused by existing methods that only focus on solving a single aspect. This approach addresses practical needs by comprehensively covering both offshore and onshore planning decisions. The comprehensiveness of the planning coverage ensures the accuracy of overall planning decisions for large-scale offshore wind power transmission systems, thus meeting practical requirements. By simulating the offshore wind power output characteristics of the decision-making area, the wind power aggregation demand is obtained. Furthermore, by analyzing the AC / DC hybrid characteristics and onshore-sea coupled operation characteristics of offshore wind power, an AC / DC power flow model is constructed. This model fully integrates system characteristics into demand simulation and power flow calculation, improving the accuracy of these processes and leading to more accurate wind power aggregation demand. This further enhances the accuracy of power flow calculations, ultimately improving the accuracy of subsequent planning decisions to meet practical needs.

[0006] In some embodiments of this application, generating multiple candidate planning schemes based on the wind power aggregation demand of the area to be decided specifically includes: Based on the wind power aggregation needs of the area to be decided, and according to the preset multiple submarine cable settings and multiple converter platform selections, multiple offshore aggregation schemes are determined. Based on the resource allocation of the area to be decided, multiple converter schemes are designed for each marine aggregation scheme, resulting in multiple onshore access schemes corresponding to each marine aggregation scheme. Each marine access scheme is combined with its corresponding multiple land access schemes to construct multiple candidate planning schemes.

[0007] This application first determines multiple offshore aggregation schemes based on the wind power aggregation needs to be decided, according to various submarine cable configurations and converter platform selections. Simultaneously, considering the resource allocation of the region to be decided, multiple converter schemes are designed for each offshore aggregation scheme to obtain multiple onshore access schemes. Then, each offshore aggregation scheme is combined with its corresponding multiple onshore access schemes to construct multiple candidate planning schemes. By using various submarine cable configurations and converter platform selections, combined with the wind power aggregation needs of the region to be decided, the technical feasibility and economic differences in the offshore wind power aggregation process can be fully considered. Diversified equipment selection improves the technical adaptability of the offshore aggregation schemes. By matching multiple converter schemes for each offshore aggregation scheme based on the resource allocation of the region to be decided, the resource allocation constraints of onshore access and the constraints of offshore aggregation can be fully considered, ensuring an organic connection between the onshore and offshore aggregation schemes. This ensures the feasibility of the onshore access schemes for offshore aggregation, thereby ensuring the feasibility of the multiple candidate planning schemes obtained by combining each offshore aggregation scheme with its corresponding multiple onshore access schemes. Thus, the comprehensiveness of the planning coverage guarantees the accuracy of the overall planning decision for a large-scale offshore wind power transmission system, meeting actual needs.

[0008] In some embodiments of this application, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided, specifically: Based on the preset power transmission planning boundary and wind turbine physical model, the output uncertainty of offshore wind power in each time period within the preset season of the decision-making area is fitted and sampled to generate multiple random scenarios of offshore wind power output. Clustering is performed on the multiple random scenarios of offshore wind power output to obtain multiple typical scenario clusters that characterize the offshore wind power output characteristics of the decision-making area. Based on the multiple typical scenario clusters, the wind power aggregation demand of the decision-making area is determined.

[0009] This application first uses a pre-defined transmission planning boundary and a wind turbine physical model to fit and sample the output uncertainty of offshore wind power in different time periods within a pre-defined season in the decision-making area, generating multiple random scenarios of offshore wind power output. This allows for full consideration of the uncertainty characteristics of offshore wind power during the planning stage, and by fitting and sampling based on seasonal characteristics, it adapts to the seasonal differences of offshore wind power, improving the timeliness and representativeness of scenario generation. Then, it clusters these multiple random scenarios to obtain multiple typical scenario clusters representing the output characteristics of offshore wind power in the decision-making area. This reduces the computational scale while preserving the uncertainty characteristics of offshore wind power, and uses typical scenario features to characterize the output characteristics of offshore wind power, providing a basis for determining subsequent wind power aggregation needs. Thus, by using a scenario-based uncertainty quantification method, it improves the accuracy of determining wind power aggregation needs, thereby meeting the accuracy requirements of subsequent planning decisions for large-scale offshore wind power transmission systems.

[0010] In some embodiments of this application, the step of performing power flow calculations on each candidate planning scheme according to a preset AC / DC power flow model to obtain the operating status data corresponding to each candidate planning scheme specifically includes: Based on the preset AC / DC power flow model, and using the Newton-Raphson method, iterative power flow calculations are performed on each candidate planning scheme. During the iteration process, the AC and DC power flows of the corresponding candidate planning scheme are solved alternately until the AC and DC power flows of the corresponding candidate planning scheme meet the convergence conditions, and then the calculation stops, thus obtaining the operating status data corresponding to each candidate planning scheme.

[0011] This application first uses the AC / DC power flow model and the Newton-Raphson method to iteratively calculate the power flow for each candidate planning scheme. During the iteration process, the AC and DC power flows of the corresponding candidate planning scheme are solved alternately until both the AC and DC power flows of the corresponding candidate planning scheme meet the convergence conditions, and then the operation status data is obtained. By solving the AC and DC power flows of the candidate planning scheme alternately using the Newton-Raphson method, the different characteristics of AC and DC power flows can be handled separately, avoiding the solution difficulties caused by unified AC / DC modeling, improving the accuracy and efficiency of power flow solution, and thus providing corresponding data support for subsequent planning decisions.

[0012] In some embodiments of this application, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power, specifically: The characteristics of AC / DC hybrid offshore wind power are analyzed to determine the offshore-land power transmission model between offshore wind power and onshore AC system. Based on the offshore-land power transmission model and the characteristics of the converter station of onshore AC system, the onshore power transmission model between the converter station and the corresponding AC bus of onshore AC system is determined. Based on the onshore power transmission model, the first imbalance and the second imbalance are determined. Based on the AC / DC hybrid characteristics of offshore wind power, the AC / DC power relationship of offshore wind power is analyzed to determine the third imbalance quantity. Based on the characteristics of sea-land coupled operation, the current balance relationship of DC network nodes is analyzed to determine the fourth unbalance quantity. An AC / DC power flow model is constructed based on the first imbalance, the second imbalance, the third imbalance, and the fourth imbalance.

[0013] This application first analyzes the AC / DC hybrid characteristics of offshore wind power to determine the land-sea power transmission model between offshore wind power and the onshore AC system. Then, combining the characteristics of the converter stations of the onshore AC system, it determines the onshore power transmission model between the converter stations and the corresponding AC buses of the onshore AC system, thereby determining the first and second imbalances. Based on the AC / DC hybrid characteristics of offshore wind power, it analyzes the AC / DC power relationship of offshore wind power to determine the third imbalance. Finally, it analyzes the current balance relationship of DC network nodes through the sea-land coupled operation characteristics to determine the fourth imbalance. Based on each imbalance, it constructs an AC / DC power flow model, which can comprehensively characterize the power transmission characteristics of offshore wind power from the physical mechanism level. The AC / DC model fully incorporates system characteristics, improves the accuracy of power flow calculation, and improves the accuracy of subsequent planning decisions to meet practical needs.

[0014] In some embodiments of this application, the step of calculating indicators for each candidate planning scheme based on the operational status data corresponding to each candidate planning scheme from several preset evaluation dimensions, and evaluating and obtaining multiple indicator values ​​for each candidate planning scheme, specifically includes: Based on the operational status data corresponding to each candidate planning scheme, indicators are calculated for each candidate planning scheme from several preset evaluation dimensions to obtain multiple indicator values ​​for each candidate planning scheme; wherein, the evaluation dimensions include technical dimension, economic dimension and environmental dimension.

[0015] This application first calculates indicators for each candidate planning scheme based on the operational status data corresponding to each candidate planning scheme from multiple evaluation dimensions, including technical, economic and environmental dimensions. The evaluation obtains multiple indicator values ​​for each candidate planning scheme, which can quantify the technical feasibility, economic feasibility and environmental feasibility of the planning scheme, comprehensively evaluate and reflect the feasibility of the planning scheme, and thus provide corresponding data support for subsequent planning decisions.

[0016] In some embodiments of this application, the step of ranking the candidate planning schemes based on multiple index values ​​for each candidate planning scheme to obtain a planning scheme for the offshore wind power transmission system of the area to be decided specifically includes: Based on multiple index values ​​of each candidate planning scheme, and using several preset multi-attribute decision-making methods, the ranking of each candidate planning scheme is comprehensively determined, and based on the ranking of each candidate planning scheme, the planning scheme of the offshore wind power transmission system for the area to be decided is obtained; wherein, the multi-attribute decision-making methods include the approximation ideal solution ranking method, the multi-objective optimization method based on ratio analysis, and the complex ratio evaluation method.

[0017] This application first determines the ranking of each candidate planning scheme based on multiple indicator values ​​of each candidate planning scheme, using multi-attribute decision-making schemes including the approximation of ideal solution ranking method, multi-objective optimization method based on ratio analysis, and complex ratio evaluation method. This results in a comprehensive decision on the planning scheme for the offshore wind power transmission system of the area to be decided. Through the collaborative decision-making of multiple multi-attribute decision-making schemes, the limitations of a single decision-making method can be reduced, the one-sidedness of a single decision-making method can be avoided, and the comprehensiveness and reliability of the planning scheme ranking can be improved, thereby improving the accuracy of planning decisions to meet actual needs.

[0018] According to a second aspect of the embodiments of this application, an offshore wind power transmission system planning and decision-making system is provided, including a scheme generation module, a power flow calculation module and an evaluation and decision-making module; The scheme generation module is used to generate multiple candidate planning schemes based on the wind power aggregation demand of the area to be decided; wherein, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided; each candidate planning scheme is obtained by combining an offshore aggregation scheme and an onshore access scheme; The power flow calculation module is used to perform power flow calculations for each candidate planning scheme according to a preset AC / DC power flow model, and obtain the corresponding operating status data for each candidate planning scheme; wherein, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power; The evaluation and decision-making module is used to calculate indicators for each candidate planning scheme from several preset evaluation dimensions based on the operation status data corresponding to each candidate planning scheme, evaluate and obtain multiple indicator values ​​for each candidate planning scheme, and sort the candidate planning schemes according to the multiple indicator values ​​of each candidate planning scheme to obtain the offshore wind power transmission system planning scheme for the area to be decided.

[0019] In some embodiments of this application, the scheme generation module includes a marine scheme determination unit, a land-based scheme determination unit, and a candidate scheme generation unit; The offshore scheme determination unit is used to determine multiple offshore aggregation schemes based on the wind power aggregation needs of the area to be decided, and according to the preset multiple submarine cable settings and multiple converter platform selections. The land-based scheme determination unit is used to combine the resource allocation of the area to be decided and design multiple converter schemes for each marine aggregation scheme to obtain multiple land-based access schemes corresponding to each marine aggregation scheme. The candidate scheme generation unit is used to combine each marine convergence scheme with multiple corresponding land access schemes to construct multiple candidate planning schemes.

[0020] In some embodiments of this application, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided, specifically: Based on the preset power transmission planning boundary and wind turbine physical model, the output uncertainty of offshore wind power in each time period within the preset season of the decision-making area is fitted and sampled to generate multiple random scenarios of offshore wind power output. Clustering is performed on the multiple random scenarios of offshore wind power output to obtain multiple typical scenario clusters that characterize the offshore wind power output characteristics of the decision-making area. Based on the multiple typical scenario clusters, the wind power aggregation demand of the decision-making area is determined.

[0021] In some embodiments of this application, the power flow calculation module includes a power flow calculation unit; the power flow calculation unit is used to perform iterative power flow calculations on each candidate planning scheme according to a preset AC / DC power flow model and based on the Newton-Raphson method. During the iteration process, the AC power flow and DC power flow of the corresponding candidate planning scheme are solved alternately until the AC power flow and DC power flow of the corresponding candidate planning scheme meet the convergence condition, and then stop, thereby obtaining the running status data corresponding to each candidate planning scheme.

[0022] In some embodiments of this application, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power, specifically: The characteristics of AC / DC hybrid offshore wind power are analyzed to determine the offshore-land power transmission model between offshore wind power and onshore AC system. Based on the offshore-land power transmission model and the characteristics of the converter station of onshore AC system, the onshore power transmission model between the converter station and the corresponding AC bus of onshore AC system is determined. Based on the onshore power transmission model, the first imbalance and the second imbalance are determined. Based on the AC / DC hybrid characteristics of offshore wind power, the AC / DC power relationship of offshore wind power is analyzed to determine the third imbalance quantity. Based on the characteristics of sea-land coupled operation, the current balance relationship of DC network nodes is analyzed to determine the fourth unbalance quantity. An AC / DC power flow model is constructed based on the first imbalance, the second imbalance, the third imbalance, and the fourth imbalance.

[0023] In some embodiments of this application, the evaluation and decision-making module includes a scheme evaluation unit; the scheme evaluation unit is used to calculate indicators for each candidate planning scheme from several preset evaluation dimensions based on the operational status data corresponding to each candidate planning scheme, and evaluate to obtain multiple indicator values ​​for each candidate planning scheme; wherein, the evaluation dimensions include technical dimensions, economic dimensions and environmental dimensions.

[0024] In some embodiments of this application, the evaluation decision module includes a ranking decision unit; the ranking decision unit is used to comprehensively decide the ranking of each candidate planning scheme based on multiple index values ​​of each candidate planning scheme and several preset multi-attribute decision methods, and to determine the offshore wind power transmission system planning scheme for the area to be decided based on the ranking of each candidate planning scheme; wherein, the multi-attribute decision methods include the approximation ideal solution ranking method, the multi-objective optimization method based on ratio analysis, and the complex ratio evaluation method.

[0025] This application first generates multiple candidate planning schemes based on the wind power aggregation needs of the region to be decided, by combining offshore aggregation and onshore access schemes. Then, based on a pre-set AC / DC power flow model, power flow calculations are performed on each candidate planning scheme to obtain corresponding operational status data. Based on the operational status data, indicators are calculated for each candidate planning scheme from several evaluation dimensions to obtain multiple indicator values ​​for each candidate planning scheme, thereby ranking and deciding to obtain the planning scheme for the offshore wind power transmission system of the region to be decided. By generating multiple candidate planning schemes by combining offshore aggregation and onshore access schemes based on the wind power aggregation needs of the region to be decided, this application avoids the problem of existing schemes that focus only on solving a single aspect, resulting in insufficient accuracy of overall planning decisions. It can comprehensively cover both offshore and onshore planning decisions, ensuring the accuracy of overall planning decisions for large-scale offshore wind power transmission systems through comprehensive planning coverage, thus meeting practical needs. Furthermore, by analyzing the AC / DC hybrid characteristics and onshore-sea coupled operation characteristics of offshore wind power, an AC / DC power flow model is constructed. This model fully incorporates system characteristics, improving the accuracy of power flow calculations, and consequently, improving the accuracy of subsequent planning decisions to meet practical needs.

[0026] According to a third aspect of the embodiments of this application, a computer device is provided, comprising: a processor; a memory; and a computer program stored in the memory and configured to be executed by the processor; wherein the processor executes the computer program to implement the offshore wind power transmission system planning and decision-making method of this application.

[0027] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a plurality of instructions adapted for loading by a processor to execute a planning and decision-making method for an offshore wind power transmission system as described in this application. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating a planning and decision-making method for an offshore wind power transmission system according to certain embodiments of this application. Figure 2This is a modular structure diagram of a planning and decision-making system for an offshore wind power transmission system, as shown in certain embodiments of this application. Detailed Implementation

[0029] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below in conjunction with the accompanying drawings are exemplary and are only used to explain some embodiments of this application, and should not be construed as limiting the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments shown in this application without inventive effort are within the protection scope of this application.

[0030] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, unless otherwise explicitly specified, "a plurality of" or "several" means two or more.

[0031] Current research on planning and decision-making for large-scale offshore wind power transmission systems generally suffers from the following shortcomings: (1) It focuses only on a single link in offshore wind power transmission, such as planning only the layout of offshore wind turbines and the site selection of onshore converter stations, lacking overall planning of the entire land-sea process in the offshore wind power transmission process. As a result, the planning scheme is only suitable for a single link, and the accuracy of the overall planning cannot meet the actual needs; (2) In the planning and decision-making process of offshore wind power transmission, based on the nonlinearity of power flow calculation, a simplified power flow calculation model is usually used for assistance. However, the simplified model does not fully incorporate the system coupling characteristics and nonlinear features, and cannot accurately characterize the line loss or the mutual influence between land and sea in the planning and decision-making scheme. The accuracy of the planning and decision-making still has a large room for optimization. Therefore, how to improve the accuracy of planning and decision-making for large-scale offshore wind power transmission systems is still an urgent problem to be solved by existing technologies.

[0032] Based on the above technical background, please refer to Figure 1 This application provides a planning and decision-making method for offshore wind power transmission systems, including steps S101 to S103, each step of which is as follows: Step S101: Based on the wind power aggregation demand of the area to be decided, generate multiple candidate planning schemes; wherein, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided; each candidate planning scheme is obtained by combining an offshore aggregation scheme and an onshore access scheme.

[0033] In some embodiments of this application, generating multiple candidate planning schemes based on the wind power aggregation demand of the area to be decided specifically includes: Based on the wind power aggregation needs of the area to be decided, and according to the preset multiple submarine cable settings and multiple converter platform selections, multiple offshore aggregation schemes are determined. Based on the resource allocation of the area to be decided, multiple converter schemes are designed for each marine aggregation scheme, resulting in multiple onshore access schemes corresponding to each marine aggregation scheme. Each marine access scheme is combined with its corresponding multiple land access schemes to construct multiple candidate planning schemes.

[0034] Specifically, when determining the offshore wind farm aggregation scheme, the coordinates and installed capacity of the offshore wind farm cluster, as well as the wind power aggregation needs of the area to be decided, are taken into account. Various different submarine cable configurations are considered, including cable type and transmission capacity, as well as various different converter platform selections, including converter platform selection and rated capacity, resulting in multiple offshore wind power aggregation schemes. When determining the onshore access scheme, the ecological constraints of the landing point in the area to be decided, onshore corridor resources, potential access site conditions, and other resource allocations are considered. Different landing points, onshore converter sites, and onshore DC channel paths connecting to each offshore aggregation scheme are matched, resulting in multiple onshore access schemes corresponding to each offshore aggregation scheme. This application first determines multiple offshore aggregation schemes based on the wind power aggregation needs to be decided, according to various submarine cable configurations and converter platform selections. Simultaneously, considering the resource allocation of the region to be decided, multiple converter schemes are designed for each offshore aggregation scheme to obtain multiple onshore access schemes. Then, each offshore aggregation scheme is combined with its corresponding multiple onshore access schemes to construct multiple candidate planning schemes. By using various submarine cable configurations and converter platform selections, combined with the wind power aggregation needs of the region to be decided, the technical feasibility and economic differences in the offshore wind power aggregation process can be fully considered. Diversified equipment selection improves the technical adaptability of the offshore aggregation schemes. By matching multiple converter schemes for each offshore aggregation scheme based on the resource allocation of the region to be decided, the resource allocation constraints of onshore access and the constraints of offshore aggregation can be fully considered, ensuring an organic connection between the onshore and offshore aggregation schemes. This ensures the feasibility of the onshore access schemes for offshore aggregation, thereby ensuring the feasibility of the multiple candidate planning schemes obtained by combining each offshore aggregation scheme with its corresponding multiple onshore access schemes. Thus, the comprehensiveness of the planning coverage guarantees the accuracy of the overall planning decision for a large-scale offshore wind power transmission system, meeting actual needs.

[0035] In some embodiments of this application, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided, specifically: Based on the preset power transmission planning boundary and wind turbine physical model, the output uncertainty of offshore wind power in each time period within the preset season of the decision-making area is fitted and sampled to generate multiple random scenarios of offshore wind power output. Clustering is performed on the multiple random scenarios of offshore wind power output to obtain multiple typical scenario clusters that characterize the offshore wind power output characteristics of the decision-making area. Based on the multiple typical scenario clusters, the wind power aggregation demand of the decision-making area is determined.

[0036] Specifically, the power transmission planning boundary is constructed by setting the scale, spatial layout, and temporal evolution path of offshore wind power through historical planning data of offshore wind power in other regions, and clarifying the planning spatial scope and scenario assumptions. When generating random scenarios of offshore wind power output, the probability density function of the uncertainty parameters of offshore wind power in each period of the preset season in the region to be decided is first fitted by the power transmission planning boundary and the physical model of the wind turbine, combined with the historical wind speed data of the region to be decided, and the corresponding cumulative distribution function is obtained by integral calculation. Then, the parameters of the cumulative distribution function are sampled by Latin hypercube sampling technology to generate multiple random scenarios of offshore wind power output. When determining the wind power aggregation demand in the region to be decided, the wind power aggregation demand in the region to be decided is obtained by comprehensively summarizing the scenario characteristics of each typical scenario cluster. Specifically, the scenario characteristics of a typical scenario cluster correspond to a wind power aggregation demand in the region to be decided.

[0037] This application first uses a pre-defined transmission planning boundary and a wind turbine physical model to fit and sample the output uncertainty of offshore wind power in different time periods within a pre-defined season in the decision-making area, generating multiple random scenarios of offshore wind power output. This allows for full consideration of the uncertainty characteristics of offshore wind power during the planning stage, and by fitting and sampling based on seasonal characteristics, it adapts to the seasonal differences of offshore wind power, improving the timeliness and representativeness of scenario generation. Then, it clusters these multiple random scenarios to obtain multiple typical scenario clusters representing the output characteristics of offshore wind power in the decision-making area. This reduces the computational scale while preserving the uncertainty characteristics of offshore wind power, and uses typical scenario features to characterize the output characteristics of offshore wind power, providing a basis for determining subsequent wind power aggregation needs. Thus, by using a scenario-based uncertainty quantification method, it improves the accuracy of determining wind power aggregation needs, thereby meeting the accuracy requirements of subsequent planning decisions for large-scale offshore wind power transmission systems.

[0038] Step S102: Based on the preset AC / DC power flow model, perform power flow calculations for each candidate planning scheme to obtain the corresponding operating status data for each candidate planning scheme; wherein, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power.

[0039] In some embodiments of this application, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power, specifically: The characteristics of AC / DC hybrid offshore wind power are analyzed to determine the offshore-land power transmission model between offshore wind power and onshore AC system. Based on the offshore-land power transmission model and the characteristics of the converter station of onshore AC system, the onshore power transmission model between the converter station and the corresponding AC bus of onshore AC system is determined. Based on the onshore power transmission model, the first imbalance and the second imbalance are determined. Based on the AC / DC hybrid characteristics of offshore wind power, the AC / DC power relationship of offshore wind power is analyzed to determine the third imbalance quantity. Based on the characteristics of sea-land coupled operation, the current balance relationship of DC network nodes is analyzed to determine the fourth unbalance quantity. An AC / DC power flow model is constructed based on the first imbalance, the second imbalance, the third imbalance, and the fourth imbalance.

[0040] Specifically, ignoring the converter reactor resistance and system harmonic components, the AC / DC hybrid characteristics of offshore wind power are analyzed to determine the active and reactive power transmitted between offshore wind power and the onshore AC system via the onshore converter. The resulting power transmission model between offshore wind power and the onshore AC system is as follows: ; in, These refer to the active and reactive power transmitted between offshore wind power and the onshore AC system via onshore converters; This is the fundamental phasor of the AC bus line voltage; The fundamental phasor of the converter bridge output line voltage is derived from the DC-side voltage. DC voltage utilization rate related to pulse width modulation method and adjustment system A joint decision, for ; for Lagging behind Angle; These are the fundamental reactances of the converter reactor and the AC filter, respectively.

[0041] Specifically, based on the land-sea power transmission model, and considering that the magnitude of active and reactive power transmitted between the onshore converter station and the AC system is influenced by the effective value of the converter bridge output line voltage... The limitations of this land-based AC system's converter station characteristics make the first The admittance of each converter station is , This allows us to determine the active and reactive power transmitted between the onshore converter station and its AC bus, resulting in the following onshore power transmission model for the onshore AC system: ; in, The first The active and reactive power transmitted between an onshore converter station and its AC bus; The first DC voltage utilization rate, modulation index, fundamental phasor of corresponding AC bus line voltage, and DC side voltage of each onshore converter station; For the first The corresponding lag angle in each onshore converter station; The first The resistance and fundamental reactance of the converter reactor in an onshore converter station; Thus, the first imbalance quantity is obtained. Second unbalance quantity for: ; Furthermore, based on the hybrid AC / DC characteristics of offshore wind power, there exists an AC / DC power relationship where the active power injected via DC is equal to the power on the AC side, i.e., a third imbalance. for: ; in, The first The DC-side voltage and current of each onshore converter station; and the phase difference from Become This is because the voltage phase reference on the converter bridge side is different from before.

[0042] Due to the first imbalance Second imbalance With the third imbalance quantity In the expression, the converter has To make the variables solvable, it is necessary to model the current balance relationship of DC network nodes using Kirchhoff's current law based on the characteristics of land-sea coupling operation. The DC network topology is described using the node admittance matrix after elimination of variables at tie nodes, based on the power system node voltage method. An additional DC network equation is added to characterize the balance between the power injected into the grid by DC nodes and the current flowing out of the DC network, resulting in a fourth imbalance quantity. for: ; in, To eliminate the tie nodes, the first node in the DC network node admittance matrix is... Line number Column elements; This represents the number of voltage source converters in the DC network. By supplementing the DC network equations, the number of variables is made strictly equal to the number of equations, thus enabling the flexible DC system power flow model to have unique solvability.

[0043] Furthermore, after obtaining the first to fourth imbalance quantities, expanding the corresponding equations using Taylor series and neglecting higher-order terms, the matrix form of the power flow correction equations based on the Newton-Raphson method is obtained as follows: ; in, ; This is the corresponding Jacobian matrix; .

[0044] This application first analyzes the AC / DC hybrid characteristics of offshore wind power to determine the land-sea power transmission model between offshore wind power and the onshore AC system. Then, combining the characteristics of the converter stations of the onshore AC system, it determines the onshore power transmission model between the converter stations and the corresponding AC buses of the onshore AC system, thereby determining the first and second imbalances. Based on the AC / DC hybrid characteristics of offshore wind power, it analyzes the AC / DC power relationship of offshore wind power to determine the third imbalance. Finally, it analyzes the current balance relationship of DC network nodes through the sea-land coupled operation characteristics to determine the fourth imbalance. Based on each imbalance, it constructs an AC / DC power flow model, which can comprehensively characterize the power transmission characteristics of offshore wind power from the physical mechanism level. The AC / DC model fully incorporates system characteristics, improves the accuracy of power flow calculation, and improves the accuracy of subsequent planning decisions to meet practical needs.

[0045] In some embodiments of this application, the step of performing power flow calculations on each candidate planning scheme according to a preset AC / DC power flow model to obtain the operating status data corresponding to each candidate planning scheme specifically includes: Based on the preset AC / DC power flow model, and using the Newton-Raphson method, iterative power flow calculations are performed on each candidate planning scheme. During the iteration process, the AC and DC power flows of the corresponding candidate planning scheme are solved alternately until the AC and DC power flows of the corresponding candidate planning scheme meet the convergence conditions, and then the calculation stops, thus obtaining the operating status data corresponding to each candidate planning scheme.

[0046] Specifically, before the initial power flow calculation, since the onshore converters connected to the grid use a combination of control variables controlling the DC-side voltage and AC-side reactive power, the AC bus type of the converter station can be set as a PQ node, with its power and voltage parameters given by setpoints. For converters with constant DC voltage control, since the DC system losses are unknown before the calculation, their AC bus active power parameters can be estimated using the following formula: ; Among them, subscript This indicates a converter controlled by constant DC voltage. The active power of the AC bus of a converter controlled by constant DC voltage; For converter The active power setpoint for the AC circuit. During the iterative, alternating solution process... The DC power flow results are corrected, and there are constraints: if the reactive power required for the converter to achieve the predetermined control target exceeds the reactive power limit injected into the AC bus of the corresponding onshore-offshore interconnected converter station, then the converter's control setpoint or control mode needs to be adjusted; if the reactive power calculated by the onshore power transmission model using DC variables or control parameters is less than the reactive power calculated by the corresponding AC power flow results, then there is no need to correct the AC bus power flow calculation parameters again using the DC power flow results. Therefore, the convergence criterion for iterative and alternating solutions is: ; in, To calculate the allowable error; For the first AC power flow calculation results in alternating solution of each iteration; For the first The corresponding power calculated by the land power transmission model in the alternating solution of the next iteration.

[0047] Specifically, based on the AC / DC power flow model, the steps for iterative power flow calculation using the Newton-Raphson method are as follows: (1) Input AC network power flow calculation data, including the node type and parameters of the AC bus of the converter station, which are determined by its control mode and set value, and set the number of alternating solutions. ; (2) The AC bus voltage of each converter station is obtained by AC power flow calculation. And injected reactive power The initial values ​​of the DC variables are estimated using the following formula: ; in, For converter Initial values ​​for the variable iteration; These are the rated and set values ​​of the DC voltage, respectively. (3) Iteratively solve the power flow correction equation in matrix form until convergence; where, if the DC voltage of a converter station exceeds the limit, adjust the DC voltage setting value of the converter station to control the DC voltage; if the regulation of a converter station exceeds the limit, set the regulation of the converter station to 1 in the subsequent calculation, and remove the reactive power correction equation of the converter station, i.e. the second unbalance quantity, from the power flow correction equation. (4) AC bus voltage through each converter station DC variable and control parameters The corresponding power was calculated using a land-based power transmission model. If the convergence criterion is met, then convergence is determined, the calculation ends, and the DC-side voltage, current, AC-side phase angle, and modulation index of each converter station are obtained; otherwise, the calculation continues using... Modify the AC power flow calculation parameters for the corresponding AC bus and increase the number of alternating solutions. Return to step 2 and iterate to solve again.

[0048] This application first uses the AC / DC power flow model and the Newton-Raphson method to iteratively calculate the power flow for each candidate planning scheme. During the iteration process, the AC and DC power flows of the corresponding candidate planning scheme are solved alternately until both the AC and DC power flows of the corresponding candidate planning scheme meet the convergence conditions, and then the operation status data is obtained. By solving the AC and DC power flows of the candidate planning scheme alternately using the Newton-Raphson method, the different characteristics of AC and DC power flows can be handled separately, avoiding the solution difficulties caused by unified AC / DC modeling, improving the accuracy and efficiency of power flow solution, and thus providing corresponding data support for subsequent planning decisions.

[0049] Step S103: Based on the operational status data corresponding to each candidate planning scheme, calculate the indicators for each candidate planning scheme from several preset evaluation dimensions, evaluate and obtain multiple indicator values ​​for each candidate planning scheme, and rank the candidate planning schemes according to the multiple indicator values ​​of each candidate planning scheme to obtain the offshore wind power transmission system planning scheme for the area to be decided.

[0050] In some embodiments of this application, the step of calculating indicators for each candidate planning scheme based on the operational status data corresponding to each candidate planning scheme from several preset evaluation dimensions, and evaluating and obtaining multiple indicator values ​​for each candidate planning scheme, specifically includes: Based on the operational status data corresponding to each candidate planning scheme, indicators are calculated for each candidate planning scheme from several preset evaluation dimensions to obtain multiple indicator values ​​for each candidate planning scheme; wherein, the evaluation dimensions include technical dimension, economic dimension and environmental dimension.

[0051] Specifically, the evaluation dimensions of the candidate planning schemes include technical, economic and environmental dimensions; the technical dimension includes wind power penetration rate and engineering implementation technology adaptability coefficient; the economic dimension includes investment cost and operating cost; and the environmental dimension includes annual carbon emission reduction and sea area occupied per unit of electricity.

[0052] More specifically, wind power penetration rate in the technological dimension Characterized by the proportion of wind power in the DC channel, reflecting the channel utilization efficiency, the calculation formula is: ; in, For time, For periodicity; For time The corresponding wind power input via DC channel, and the active power injected by offshore wind power via DC in the third imbalance quantity. equal; This refers to the rated capacity of the DC channel; In the technical dimension, the engineering implementation technology adaptability coefficient The degree of matching between the technical conditions such as the site location and access routes and the proposed solution reflects the feasibility of the engineering technology implementation. The calculation formula is as follows: ; in, These are the measured and design values ​​of the geological bearing capacity of the converter station site, respectively. Sensitive area avoidance rate for submarine cable routes.

[0053] More specifically, investment costs in the economic dimension This represents the total one-time investment during the project construction phase, reflecting the scale of the project's investment. The calculation formula is: ; ; ; ; in, These are the investment costs for the converter station, the transmission line, and the land area, respectively. These are the numbers for the converter station, submarine cable, and overhead line, respectively. This represents the total number of converter stations; The unit costs are for converter stations, submarine cables, overhead lines, and land area, respectively. Rated capacity of the converter station; These refer to the lengths of submarine cables and overhead lines, respectively. The area occupied; Operating costs in the economic dimension This represents the total annual operation, maintenance, and repair costs during the project's operational period, calculated using the following formula: ; ; ; in, The costs are for the inspection of equipment and access routes, respectively. These are the annual inspection costs per unit capacity of equipment, per unit length of submarine cable, and per unit length of overhead line.

[0054] More specifically, annual carbon emission reductions in the environmental dimension The formula for calculating the total emission reduction of offshore wind power replacing thermal power is as follows: ; in, The average carbon emission factor for thermal power plants; For time intervals; In the environmental dimension, the area occupied by a unit of electricity in the sea is... It is used to measure the efficiency of marine resource utilization, and the calculation formula is: ; in, For lifecycle; These represent the number of offshore converter platforms and submarine cables, respectively; the numerator in the formula represents the total sea area, and the denominator represents the total power generation over the entire life cycle.

[0055] This application first calculates indicators for each candidate planning scheme based on the operational status data corresponding to each candidate planning scheme from multiple evaluation dimensions, including technical, economic and environmental dimensions. The evaluation obtains multiple indicator values ​​for each candidate planning scheme, which can quantify the technical feasibility, economic feasibility and environmental feasibility of the planning scheme, comprehensively evaluate and reflect the feasibility of the planning scheme, and thus provide corresponding data support for subsequent planning decisions.

[0056] In some embodiments of this application, the step of ranking the candidate planning schemes based on multiple index values ​​for each candidate planning scheme to obtain a planning scheme for the offshore wind power transmission system of the area to be decided specifically includes: Based on multiple index values ​​of each candidate planning scheme, and using several preset multi-attribute decision-making methods, the ranking of each candidate planning scheme is comprehensively determined, and based on the ranking of each candidate planning scheme, the planning scheme of the offshore wind power transmission system for the area to be decided is obtained; wherein, the multi-attribute decision-making methods include the approximation ideal solution ranking method, the multi-objective optimization method based on ratio analysis, and the complex ratio evaluation method.

[0057] Specifically, to reduce subjective bias in the ranking decision-making process and adapt to specific planning needs, three multi-attribute decision-making methods are adopted: the Approximation to Ideal Solution Ranking Method (TOPSIS), the Multi-Objective Optimization Method based on Ratio Analysis (MOORA), and the Complex Proportional Evaluation Method (COPRAS). In the decision-making process of each multi-attribute method, the TOPSIS method calculates the relative closeness of each scheme to the positive and negative ideal solutions and ranks them accordingly; the MOORA method considers both ideal and negative ideal solutions as dual benchmarks for scheme discrimination; and the COPRAS method distinguishes between benefit-type and cost-type indicators and quantifies the contribution of extreme value indicators to the overall evaluation effect. In the final decision, the ranking of candidate planning schemes obtained by each decision method is mapped to a score value related to that ranking. For each candidate planning scheme, the weighted sum of its scores under all decision methods is calculated to obtain the expected score for each candidate planning scheme. Then, based on the expected scores, the ranking is obtained from high to low, and the scheme with the highest ranking (i.e., the highest score) is selected as the offshore wind power transmission system planning scheme for the area to be decided.

[0058] This application first determines the ranking of each candidate planning scheme based on multiple indicator values ​​of each candidate planning scheme, using multi-attribute decision-making schemes including the approximation of ideal solution ranking method, multi-objective optimization method based on ratio analysis, and complex ratio evaluation method. This results in a comprehensive decision on the planning scheme for the offshore wind power transmission system of the area to be decided. Through the collaborative decision-making of multiple multi-attribute decision-making schemes, the limitations of a single decision-making method can be reduced, the one-sidedness of a single decision-making method can be avoided, and the comprehensiveness and reliability of the planning scheme ranking can be improved, thereby improving the accuracy of planning decisions to meet actual needs.

[0059] Compared to existing technologies, this application first generates multiple candidate planning schemes based on the wind power aggregation needs of the region to be decided, by combining offshore aggregation schemes and onshore access schemes. Then, based on a preset AC / DC power flow model, power flow calculations are performed on each candidate planning scheme to obtain corresponding operational status data. Based on the operational status data, indicators are calculated for each candidate planning scheme from several evaluation dimensions to obtain multiple indicator values ​​for each candidate planning scheme, thereby ranking and deciding to obtain the planning scheme for the offshore wind power transmission system of the region to be decided. By generating multiple candidate planning schemes by combining offshore aggregation schemes and onshore access schemes based on the wind power aggregation needs of the region to be decided, this application avoids the problem that existing methods, which only focus on solving a single aspect, result in the overall planning decision-making accuracy failing to meet practical needs. It can comprehensively cover both offshore and onshore planning decisions, ensuring the accuracy of overall planning decisions for large-scale offshore wind power transmission systems through comprehensive planning coverage, thus meeting practical needs. Furthermore, by analyzing the AC / DC hybrid characteristics and onshore-sea coupled operation characteristics of offshore wind power, an AC / DC power flow model is constructed. This model fully incorporates system characteristics, improving the accuracy of power flow calculations, and consequently, improving the accuracy of subsequent planning decisions to meet practical needs.

[0060] For a method corresponding to the one described above, please refer to [link / reference]. Figure 2 The present application provides a planning and decision-making system for offshore wind power transmission systems, including a scheme generation module 210, a power flow calculation module 220, and an evaluation and decision-making module 230. The scheme generation module 210 is used to generate multiple candidate planning schemes based on the wind power aggregation demand of the area to be decided; wherein, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided; each candidate planning scheme is obtained by combining an offshore aggregation scheme and an onshore access scheme. The power flow calculation module 220 is used to perform power flow calculations for each candidate planning scheme according to a preset AC / DC power flow model, and obtain the corresponding operating status data for each candidate planning scheme; wherein, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power; The evaluation and decision module 230 is used to calculate indicators for each candidate planning scheme from several preset evaluation dimensions based on the operation status data corresponding to each candidate planning scheme, evaluate and obtain multiple indicator values ​​for each candidate planning scheme, and sort the candidate planning schemes according to the multiple indicator values ​​of each candidate planning scheme to obtain the offshore wind power transmission system planning scheme for the area to be decided.

[0061] In some embodiments of this application, the scheme generation module 210 includes a marine scheme determination unit, a land-based scheme determination unit, and a candidate scheme generation unit; The offshore scheme determination unit is used to determine multiple offshore aggregation schemes based on the wind power aggregation needs of the area to be decided, and according to the preset multiple submarine cable settings and multiple converter platform selections. The land-based scheme determination unit is used to combine the resource allocation of the area to be decided and design multiple converter schemes for each marine aggregation scheme to obtain multiple land-based access schemes corresponding to each marine aggregation scheme. The candidate scheme generation unit is used to combine each marine convergence scheme with multiple corresponding land access schemes to construct multiple candidate planning schemes.

[0062] In some embodiments of this application, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided, specifically: Based on the preset power transmission planning boundary and wind turbine physical model, the output uncertainty of offshore wind power in each time period within the preset season of the decision-making area is fitted and sampled to generate multiple random scenarios of offshore wind power output. Clustering is performed on the multiple random scenarios of offshore wind power output to obtain multiple typical scenario clusters that characterize the offshore wind power output characteristics of the decision-making area. Based on the multiple typical scenario clusters, the wind power aggregation demand of the decision-making area is determined.

[0063] In some embodiments of this application, the power flow calculation module 220 includes a power flow calculation unit; the power flow calculation unit is used to perform iterative power flow calculations on each candidate planning scheme according to a preset AC / DC power flow model and based on the Newton-Raphson method. During the iteration process, the AC power flow and DC power flow of the corresponding candidate planning scheme are solved alternately until the AC power flow and DC power flow of the corresponding candidate planning scheme meet the convergence condition, and then stop, thereby obtaining the running status data corresponding to each candidate planning scheme.

[0064] In some embodiments of this application, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power, specifically: The characteristics of AC / DC hybrid offshore wind power are analyzed to determine the offshore-land power transmission model between offshore wind power and onshore AC system. Based on the offshore-land power transmission model and the characteristics of the converter station of onshore AC system, the onshore power transmission model between the converter station and the corresponding AC bus of onshore AC system is determined. Based on the onshore power transmission model, the first imbalance and the second imbalance are determined. Based on the AC / DC hybrid characteristics of offshore wind power, the AC / DC power relationship of offshore wind power is analyzed to determine the third imbalance quantity. Based on the characteristics of sea-land coupled operation, the current balance relationship of DC network nodes is analyzed to determine the fourth unbalance quantity. An AC / DC power flow model is constructed based on the first imbalance, the second imbalance, the third imbalance, and the fourth imbalance.

[0065] In some embodiments of this application, the evaluation and decision module 230 includes a scheme evaluation unit; the scheme evaluation unit is used to calculate indicators for each candidate planning scheme from a number of preset evaluation dimensions based on the operation status data corresponding to each candidate planning scheme, and evaluate to obtain multiple indicator values ​​for each candidate planning scheme; wherein, the evaluation dimensions include technical dimensions, economic dimensions and environmental dimensions.

[0066] In some embodiments of this application, the evaluation decision module 230 includes a ranking decision unit; the ranking decision unit is used to comprehensively decide the ranking of each candidate planning scheme based on multiple index values ​​of each candidate planning scheme and several preset multi-attribute decision methods, and to determine the offshore wind power transmission system planning scheme for the area to be decided based on the ranking of each candidate planning scheme; wherein, the multi-attribute decision methods include the approximation ideal solution ranking method, the multi-objective optimization method based on ratio analysis, and the complex ratio evaluation method.

[0067] This application first generates multiple candidate planning schemes based on the wind power aggregation needs of the region to be decided, by combining offshore aggregation and onshore access schemes. Then, based on a pre-set AC / DC power flow model, power flow calculations are performed on each candidate planning scheme to obtain corresponding operational status data. Based on the operational status data, indicators are calculated for each candidate planning scheme from several evaluation dimensions to obtain multiple indicator values ​​for each candidate planning scheme, thereby ranking and deciding to obtain the planning scheme for the offshore wind power transmission system of the region to be decided. By generating multiple candidate planning schemes by combining offshore aggregation and onshore access schemes based on the wind power aggregation needs of the region to be decided, this application avoids the problem of existing schemes that focus only on solving a single aspect, resulting in insufficient accuracy of overall planning decisions. It can comprehensively cover both offshore and onshore planning decisions, ensuring the accuracy of overall planning decisions for large-scale offshore wind power transmission systems through comprehensive planning coverage, thus meeting practical needs. Furthermore, by analyzing the AC / DC hybrid characteristics and onshore-sea coupled operation characteristics of offshore wind power, an AC / DC power flow model is constructed. This model fully incorporates system characteristics, improving the accuracy of power flow calculations, and consequently, improving the accuracy of subsequent planning decisions to meet practical needs.

[0068] It should be understood that the system provided in this application is corresponding to the aforementioned method. The offshore wind power transmission system planning and decision-making system provided in this application can realize the offshore wind power transmission system planning and decision-making method provided in any one of the embodiments of this application.

[0069] Adaptively, embodiments of this application also provide a computer device and a computer-readable storage medium.

[0070] The computer device includes: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor; The processor executes the computer program to implement a planning and decision-making method for an offshore wind power transmission system according to this application.

[0071] The computer-readable storage medium stores multiple instructions that are adapted for a processor to load in order to execute a planning and decision-making method for an offshore wind power transmission system according to this application.

[0072] The above description represents some embodiments of this application, providing a further detailed explanation of the purpose, technical solution, and beneficial effects of this application. It should be understood that the above-described embodiments of this application should not be construed as limiting this application. In particular, any changes, modifications, equivalent substitutions, and variations made by those skilled in the art within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A planning and decision-making method for offshore wind power transmission systems, characterized in that, include: Based on the wind power aggregation demand of the area to be decided, multiple candidate planning schemes are generated; wherein, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided; each candidate planning scheme is obtained by combining an offshore aggregation scheme and an onshore access scheme. Based on the preset AC / DC power flow model, power flow calculations are performed on each candidate planning scheme to obtain the corresponding operating status data for each candidate planning scheme; wherein, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operating characteristics of offshore wind power; Based on the operational status data corresponding to each candidate planning scheme, indicators are calculated for each candidate planning scheme from several preset evaluation dimensions. Multiple indicator values ​​are obtained for each candidate planning scheme. Based on the multiple indicator values ​​of each candidate planning scheme, the candidate planning schemes are ranked, and a decision is made to obtain the offshore wind power transmission system planning scheme for the area to be decided.

2. The offshore wind power transmission system planning and decision-making method according to claim 1, characterized in that, The process of generating multiple candidate planning schemes based on the wind power aggregation needs of the area to be decided includes: Based on the wind power aggregation needs of the area to be decided, and according to the preset multiple submarine cable settings and multiple converter platform selections, multiple offshore aggregation schemes are determined. Based on the resource allocation of the area to be decided, multiple converter schemes are designed for each marine aggregation scheme, resulting in multiple onshore access schemes corresponding to each marine aggregation scheme. Each marine access scheme is combined with its corresponding multiple land access schemes to construct multiple candidate planning schemes.

3. The offshore wind power transmission system planning and decision-making method according to claim 1, characterized in that, The wind power aggregation demand was determined by simulating the offshore wind power output characteristics of the area to be decided, specifically: Based on the preset power transmission planning boundary and wind turbine physical model, the output uncertainty of offshore wind power in each time period within the preset season of the decision-making area is fitted and sampled to generate multiple random scenarios of offshore wind power output. Clustering is performed on the multiple random scenarios of offshore wind power output to obtain multiple typical scenario clusters that characterize the offshore wind power output characteristics of the decision-making area. Based on the multiple typical scenario clusters, the wind power aggregation demand of the decision-making area is determined.

4. The offshore wind power transmission system planning and decision-making method according to claim 1, characterized in that, The step of performing power flow calculations on each candidate planning scheme based on a preset AC / DC power flow model to obtain the corresponding operating status data for each candidate planning scheme specifically includes: Based on the preset AC / DC power flow model, and using the Newton-Raphson method, iterative power flow calculations are performed on each candidate planning scheme. During the iteration process, the AC and DC power flows of the corresponding candidate planning scheme are solved alternately until the AC and DC power flows of the corresponding candidate planning scheme meet the convergence conditions, and then the calculation stops, thus obtaining the operating status data corresponding to each candidate planning scheme.

5. The offshore wind power transmission system planning and decision-making method according to claim 1, characterized in that, The AC / DC power flow model is constructed through the analysis of the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power, specifically as follows: The characteristics of AC / DC hybrid offshore wind power are analyzed to determine the offshore-land power transmission model between offshore wind power and onshore AC system. Based on the offshore-land power transmission model and the characteristics of the converter station of onshore AC system, the onshore power transmission model between the converter station and the corresponding AC bus of onshore AC system is determined. Based on the onshore power transmission model, the first imbalance and the second imbalance are determined. Based on the AC / DC hybrid characteristics of offshore wind power, the AC / DC power relationship of offshore wind power is analyzed to determine the third imbalance quantity. Based on the characteristics of sea-land coupled operation, the current balance relationship of DC network nodes is analyzed to determine the fourth unbalance quantity. An AC / DC power flow model is constructed based on the first imbalance, the second imbalance, the third imbalance, and the fourth imbalance.

6. The offshore wind power transmission system planning and decision-making method according to claim 1, characterized in that, The step involves calculating indicators for each candidate planning scheme based on the operational status data corresponding to each candidate planning scheme, from several preset evaluation dimensions, to obtain multiple indicator values ​​for each candidate planning scheme. Specifically, this includes: Based on the operational status data corresponding to each candidate planning scheme, indicators are calculated for each candidate planning scheme from several preset evaluation dimensions to obtain multiple indicator values ​​for each candidate planning scheme; wherein, the evaluation dimensions include technical dimension, economic dimension and environmental dimension.

7. The offshore wind power transmission system planning and decision-making method according to claim 1, characterized in that, The process of ranking candidate planning schemes based on multiple indicator values ​​for each scheme to obtain a planning scheme for the offshore wind power transmission system in the area to be decided includes: Based on multiple index values ​​of each candidate planning scheme, and using several preset multi-attribute decision-making methods, the ranking of each candidate planning scheme is comprehensively determined, and based on the ranking of each candidate planning scheme, the planning scheme of the offshore wind power transmission system for the area to be decided is obtained; wherein, the multi-attribute decision-making methods include the approximation ideal solution ranking method, the multi-objective optimization method based on ratio analysis, and the complex ratio evaluation method.

8. A planning and decision-making system for offshore wind power transmission systems, characterized in that, It includes a scheme generation module, a power flow calculation module, and an evaluation and decision-making module; The scheme generation module is used to generate multiple candidate planning schemes based on the wind power aggregation demand of the area to be decided; wherein, the wind power aggregation demand is determined by simulating the offshore wind power output characteristics of the area to be decided; each candidate planning scheme is obtained by combining an offshore aggregation scheme and an onshore access scheme; The power flow calculation module is used to perform power flow calculations for each candidate planning scheme according to a preset AC / DC power flow model, and obtain the corresponding operating status data for each candidate planning scheme; wherein, the AC / DC power flow model is constructed by analyzing the AC / DC hybrid characteristics and land-sea coupled operation characteristics of offshore wind power; The evaluation and decision-making module is used to calculate indicators for each candidate planning scheme from several preset evaluation dimensions based on the operation status data corresponding to each candidate planning scheme, evaluate and obtain multiple indicator values ​​for each candidate planning scheme, and sort the candidate planning schemes according to the multiple indicator values ​​of each candidate planning scheme to obtain the offshore wind power transmission system planning scheme for the area to be decided.

9. A computer device, characterized in that, include: processor; Memory; A computer program stored in the memory and configured to be executed by the processor; When the processor executes the computer program, it implements a planning and decision-making method for an offshore wind power transmission system as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a plurality of instructions adapted for loading by a processor to execute the offshore wind power transmission system planning and decision-making method according to any one of claims 1 to 7.

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