A reactive power support-oriented far-sea wind power cluster multi-terminal flexible DC access system collaborative optimization planning method

Abstract

The application discloses a kind of far sea wind power cluster multi-terminal flexible DC access system collaborative optimization planning methods for reactive support, comprising: obtaining the planning basic data of far sea wind power cluster multi-terminal flexible DC access system;System level candidate access scheme is generated based on planning basic data;System level candidate access scheme is evaluated to receiving end power grid reactive support capability and grid connection point voltage deviation, and feasible access scheme of system level is obtained by screening in combination with line investment constraint;According to the capacity of land receiving end converter station, DC voltage grade and topological connection relationship in system level feasible access scheme, the equipment selection scheme of matching converter transformer, converter valve submodule, submodule capacitor and bridge arm reactor is determined;System level feasible access scheme and equipment selection scheme are evaluated and iterated and updated collaboratively, and collaborative optimization planning result is output.The application can improve the reactive support capability and voltage stability of receiving end power grid, and also considers project investment.

Description

Technical Field

[0001] This invention belongs to the technical field of offshore wind power grid-connected transmission system planning, specifically involving a collaborative optimization planning method for multi-terminal flexible DC access systems of offshore wind power clusters oriented towards reactive power support. Background Technology

[0002] As the scale of offshore wind power development continues to expand, connecting multiple offshore wind farms to the receiving-end power grid in a cluster manner has become an important development trend. Offshore wind farms are typically located far from shore and have large power outputs. Using flexible DC transmission can improve the controllability of power transmission and has a certain reactive power regulation capability, but it also brings the problem of high investment in converter stations, DC submarine cables, onshore lines, and key equipment within the stations.

[0003] In offshore wind power cluster integration scenarios, there is a strong coupling relationship between the selection of the access point, the capacity configuration of the receiving-end converter station, the DC voltage level, the topology of the DC submarine cable and onshore DC line, the line type, and the key equipment parameters of the converter station. If the design is based solely on local investment or a single access scheme during the planning stage, it can easily lead to problems such as high line construction costs, unreasonable converter station capacity configuration, mismatch between DC voltage level and line transmission capacity, or insufficient operational margin of the receiving-end AC grid.

[0004] Existing offshore wind power grid connection planning typically focuses on line investment, grid connection point selection, converter station capacity configuration, or onshore power grid expansion schemes. For example, CN120582217A discloses a joint optimization method for the offshore and onshore AC / DC electrical systems of offshore wind power clusters. This method constructs a three-layer joint optimization model consisting of a grid connection point optimization layer, an offshore electrical system planning layer, and an onshore electrical system operation and scheduling layer. It combines basic data of the offshore wind power cluster, wind speed probability density distribution data, and onshore power grid topology data to obtain offshore rectifier station schemes, optimal grid connection schemes, and onshore power grid expansion schemes. While this type of method can consider the grid connection schemes of offshore wind power clusters and the operational needs of the onshore power grid to some extent, its optimization focus is mainly on the overall grid connection of the offshore and onshore AC / DC systems, the planning configuration under typical wind conditions, and onshore power grid expansion. It does not adequately consider the reactive power support capacity, voltage stability margin, and mutual influences between multiple grid connection points when offshore wind power clusters are connected to the receiving-end AC grid via multi-terminal flexible DC systems.

[0005] Especially in receiving-end AC grids with multiple DC feeds, the grid connection points of multiple receiving-end converter stations are not independent of each other. The equivalent impedance, electrical distance, feed-in power, and reactive power regulation boundary of different grid connection points all affect the static voltage stability level of the receiving-end AC grid. Existing planning methods, when dealing with such problems, usually simplify voltage safety issues to node voltage upper and lower limits, power flow balance constraints, or line capacity constraints, lacking a quantitative evaluation of the voltage stability margin of the receiving-end AC grid under conditions of multiple flexible DC feeds. Therefore, if the planning scheme is determined solely based on investment costs, connection distance, wind conditions, or conventional power flow results, there may be risks such as increased voltage deviation at grid connection points, insufficient voltage support capacity at local nodes, low static voltage stability margin, and even the equivalent short-circuit ratio falling below the stability critical value.

[0006] Furthermore, in existing technologies, system-level network planning and equipment-level selection are often conducted separately. System-level planning typically focuses on the site, capacity, DC voltage level, submarine cables, and onshore line topology of the onshore receiving-end converter station. In contrast, equipment-level selection usually involves independently determining key equipment such as converter transformers, converter valve submodule power devices, submodule capacitors, and bridge arm reactors after the system scheme has been finalized. Due to the lack of a unified matching relationship between the two, it may result in the site selection, topology, and voltage level being determined, but the corresponding converter transformer capacity, power device withstand voltage and current capabilities, number of submodules, capacitor configuration, and bridge arm reactor parameters not being fully coordinated with the system's operational requirements. This can lead to equipment redundancy, increased investment, or insufficient safety margins.

[0007] The output of offshore wind power and the load of the receiving-end AC grid exhibit significant fluctuations. Under different operating scenarios, such as high wind power generation, low wind power generation, peak load, and low load, the voltage deviation at the grid connection point, the power flow distribution of the lines, and the active and reactive power output of the converter stations may all change considerably. Although existing planning methods can incorporate wind conditions or load scenarios for analysis, they are still insufficient in providing coordinated constraints on grid connection point voltage quality, power flow feasibility, and line transmission capacity under multiple typical operating scenarios. This makes it difficult to guarantee that offshore wind power clusters have good voltage stability and smooth operation under various operating conditions.

[0008] Therefore, the following technical issues still exist in the planning of multi-terminal flexible DC access systems for offshore wind power clusters: how to accurately reflect the voltage stability margin of the receiving-end AC grid while controlling line and equipment investment; how to evaluate the mutual influence and reactive power support capacity between different grid connection points under multi-terminal flexible DC feed-in conditions; how to avoid the disconnect between system-level grid planning and the selection of key equipment for converter stations; and how to balance power flow feasibility, line transmission capacity and grid connection point voltage deviation under multiple typical operating scenarios. Summary of the Invention

[0009] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters with reactive power support.

[0010] The objective of this invention can be achieved through the following technical solutions: This invention provides a collaborative optimization planning method for multi-terminal flexible DC access systems of offshore wind power clusters oriented towards reactive power support, comprising the following steps: Obtain the basic dataset for planning; A system-level optimization model is constructed based on the aforementioned planning dataset; Solve the system-level optimization model to select system-level feasible solutions that meet the requirements of converter station configuration, DC voltage level, receiving-end AC grid voltage stability, power flow, and line transmission capacity. The onshore receiving-end converter station capacity, DC voltage level, and line topology in the system-level feasible scheme are used as inputs to construct the equipment-level optimization model. The equipment-level optimization model is then used to select equipment such as converter transformers, converter valve submodule power devices, submodule capacitors, and bridge arm reactors to obtain an equipment-level selection scheme that matches the system-level feasible scheme. A comprehensive evaluation result is formed based on the system-level feasible solution and the equipment-level selection solution, and the system-level feasible solution is iteratively updated based on the comprehensive evaluation result until the convergence condition is met; The scheme that satisfies the convergence condition is output as the target planning scheme.

[0011] Furthermore, the planning basic dataset includes data on the sending-end converter stations of offshore wind power clusters, data on the receiving-end AC power grid, data on candidate onshore grid connection points, data on candidate DC voltage levels, data on candidate lines, data on typical operating scenarios, and data on candidate converter station equipment.

[0012] Furthermore, the data of the sending-end converter stations includes the location information, rated capacity, transmission power, corresponding offshore wind farm capacity, and DC transmission distance between each offshore sending-end converter station and the candidate onshore grid connection point. The receiving-end AC grid data includes the network topology, node parameters, branch parameters, node voltage levels, node voltage operating limits, node load data, AC line power flow limits, and node impedance admittance parameters used to calculate the voltage stability index of the receiving-end AC grid. The candidate onshore grid connection point data includes a set of candidate onshore grid connection points, the node number of each candidate onshore grid connection point in the receiving-end AC power grid, the grid connection point voltage level, the grid connection point's allowable access capacity, the electrical connection relationship between grid connection points, and the equivalent impedance parameters between grid connection points. The candidate DC voltage level data includes multiple selectable DC voltage levels and the corresponding line transmission capacity, insulation configuration requirements and converter station equipment adaptation requirements for each selectable DC voltage level. The candidate line data includes candidate DC submarine cable data and candidate onshore DC overhead line data. The candidate DC submarine cable data includes the candidate submarine cable model, cost per unit length, maximum transmission capacity, and submarine cable length from the offshore converter station to the candidate onshore grid connection point. The candidate onshore DC overhead line data includes the candidate onshore DC overhead line model, cost per unit length, maximum transmission capacity, and overhead line length between the candidate onshore grid connection points. The typical operating scenario data includes wind power output level, receiving-end AC grid load level, weighting coefficients corresponding to each typical operating scenario, active power output, reactive power output, node load and grid connection voltage reference value under each typical operating scenario. The candidate converter station equipment data includes candidate converter transformer data, candidate converter valve submodule power device data, candidate submodule capacitor data, and candidate bridge arm reactor data. Specifically, the candidate converter transformer data includes the candidate converter transformer model, rated capacity, compatible AC voltage level, compatible DC voltage level, and unit capacity cost. The candidate converter valve submodule power device data includes the candidate power device model, rated voltage, rated current, and cost per power device. The candidate submodule capacitor data includes the candidate submodule capacitor model, capacitance value, rated voltage, and cost per capacitor. The candidate bridge arm reactor data includes the candidate bridge arm reactor model, rated current, reactance parameters, and cost per bridge arm reactor.

[0013] Furthermore, the system-level optimization model takes the onshore receiving-end converter station construction scheme, DC voltage level scheme, line topology scheme and line selection scheme as system-level decision objects, and takes the line construction cost, the receiving-end AC grid voltage stability index used to characterize reactive power support capability and the voltage deviation of the grid connection point in multiple scenarios as system-level evaluation objects.

[0014] Furthermore, the system-level optimization model aims to minimize line construction costs, maximize the voltage stability index of the receiving-end AC grid, and minimize the total voltage deviation at the grid connection point under multiple typical operating scenarios. The objective function of the system-level optimization model is expressed as: in, This represents the system-level optimization objective function; This indicates the construction cost of DC submarine cables and onshore DC overhead lines; This represents the minimum value of the hybrid feed-in equivalent short-circuit ratio index corresponding to the grid connection point of each receiving-end converter station in the receiving-end AC power grid. The hybrid feed-in equivalent short-circuit ratio index is determined based on the equivalent impedance, equivalent power, and reactive power boundary function influence term of the flexible DC converter station between the grid connection points of the receiving-end converter stations. This indicates the total voltage deviation at the grid connection point under multiple typical operating scenarios; The construction cost of the line and the total voltage deviation at the grid connection point under the multiple typical operating scenarios are respectively expressed as follows: in, This indicates a collection of offshore power transmission converter stations. This represents the set of candidate onshore grid connection sites; This represents the set of candidate DC submarine cable models; This represents the set of candidate onshore DC overhead line models; Indicates offshore power transmission station With candidate onshore grid connection points Whether to select a model For DC submarine cables, if selected, take 1; otherwise, take 0. Indicates offshore power transmission station With candidate onshore grid connection points The length of the DC submarine cable between them; Model number Cost per unit length of DC submarine cable; Indicating candidate onshore grid connection points With candidate onshore grid connection points Whether to select a model For onshore DC overhead lines, take 1 if selected, otherwise take 0; Indicating candidate onshore grid connection points With candidate onshore grid connection points The length of the onshore DC overhead line between them; Model number Cost per unit length of onshore DC overhead lines; Represents a set of typical operating scenarios; Indicates the first Weighting coefficients for a typical operating scenario; Indicates the first In the first typical operating scenario, the The actual voltage amplitude at each grid connection point; This indicates the reference value for the grid connection point voltage.

[0015] Furthermore, the decision variables of the system-level optimization model include the number of onshore receiving-end converter stations, the site selection of onshore receiving-end converter stations, the capacity configuration of onshore receiving-end converter stations, the DC voltage level selection, the DC submarine cable connection between the offshore sending-end converter station and the onshore receiving-end converter station, the onshore DC overhead line connection between candidate onshore grid connection points, the DC submarine cable model selection, and the onshore DC overhead line model selection. The number of onshore receiving-end converter stations, the site of the onshore receiving-end converter station, the capacity of the onshore receiving-end converter station, the DC voltage level, the DC submarine cable connection relationship, the onshore DC overhead line connection relationship, the DC submarine cable model, and the onshore DC overhead line model obtained from the solution are used as the system-level feasible solutions.

[0016] Furthermore, the constraints of the system-level optimization model include converter station configuration constraints, DC voltage level constraints, receiving-end AC grid voltage stability constraints, power flow constraints for typical operating scenarios, and line transmission capacity constraints. The converter station configuration constraints and the DC voltage level constraints are expressed as follows: in, This indicates the actual planned number of onshore receiving-end converter stations; Indicates the first If a candidate onshore grid connection site is to be built, an onshore receiving-end converter station is selected; if it is, a value of 1 is selected; otherwise, a value of 0 is selected. This indicates the maximum number of onshore receiving-end converter stations that can be planned. Indicates the first The planned capacity of the onshore receiving-end converter station at each candidate onshore grid connection point; They represent the first The minimum and maximum planarable capacity of the onshore receiving-end converter station at each candidate onshore grid connection point; This indicates the total power transmitted by the offshore power transmission system of the offshore wind power cluster; Represents the set of candidate DC voltage levels; Indicates the first Should the first candidate onshore grid connection site be selected? A candidate DC voltage level is selected; if selected, the value is 1, otherwise the value is 0. Indicates the first The DC voltage levels corresponding to the candidate onshore grid connection points; The receiving-end AC grid voltage stability constraint, typical operating scenario power flow constraint, and line transmission capacity constraint are expressed as follows: in, Indicates the first The equivalent short-circuit ratio index of the hybrid feed-in system is corresponding to the grid connection point of the constructed onshore receiving-end converter station. The equivalent short-circuit ratio index of the hybrid feed-in system is determined based on the equivalent impedance, equivalent power and reactive power of the receiving-end converter station grid connection point and the reactive power boundary function influence term of the flexible DC converter station. This represents the threshold value of the hybrid feed-in equivalent short-circuit ratio for the receiving-end AC grid to meet the static voltage stability requirements. Represents a set of typical operating scenarios; Represents the set of AC power grid nodes at the receiving end; Indicates the first In the first typical operating scenario, the Voltage amplitude at each node; , They represent the first The lower and upper limits of voltage operation for each node; , They represent the first In the first typical operating scenario, the The active and reactive power injected into the receiving-end AC grid by each onshore receiving-end converter station; , They represent the first In the first typical operating scenario, the Active and reactive loads of each node; This represents the set of candidate lines consisting of candidate submarine DC cable lines and candidate overhead DC terrestrial lines. , They represent the first In the first typical operating scenario, the The active and reactive power losses of each line; Indicates the first In the first typical operating scenario, the The active power transmitted by a DC submarine cable line or a land-based DC overhead line; Indicates the first The maximum allowable transmission power of the line under the selected line type and selected DC voltage level; The system-level planning scheme that simultaneously satisfies the converter station configuration constraints, DC voltage level constraints, receiving-end AC grid voltage stability constraints, typical operating scenario power flow constraints, and line transmission capacity constraints is determined as the system-level feasible scheme.

[0017] Furthermore, the equipment-level optimization model takes the onshore receiving-end converter station capacity, DC voltage level, and line topology from the aforementioned system-level feasible schemes as input, and aims to minimize the equipment investment cost of the receiving-end converter station. The optimization objective function of the equipment-level optimization model is expressed as: in, This represents the device-level optimization objective function; This indicates the total investment cost of the receiving-end converter station equipment; This represents the set of onshore receiving-end converter stations determined by the system-level feasible schemes. Indicates the first The cost of converter transformers at an onshore receiving-end converter station; Indicates the first Cost of converter valve submodule for an onshore receiving-end converter station; Indicates the first Cost of bridge arm reactors for an onshore receiving-end converter station; Among them, the The equipment cost composition of an onshore receiving-end converter station is expressed as follows: in, Indicates the first The unit capacity cost of the converter transformers selected for each onshore receiving-end converter station; Indicates the first The rated capacity of the converter transformers selected for each onshore receiving-end converter station; Indicates the first The number of converter valve sub-modules in each onshore receiving-end converter station; Indicates the first The individual cost of the power devices in the selected converter valve submodule of an onshore receiving-end converter station; Indicates the first The cost per capacitor in the selected submodule of an onshore receiving-end converter station; Indicates the first The number of bridge arm reactors in each onshore receiving-end converter station; Indicates the first Cost of a single bridge arm reactor selected for an onshore receiving-end converter station; The decision variables of the equipment-level optimization model include the following variables: converter transformer model selection, converter transformer rated capacity selection, converter valve submodule power device model selection, converter valve submodule quantity configuration, submodule capacitor model selection, submodule capacitor value selection, and bridge arm reactor model and quantity configuration for each onshore receiving-end converter station. The converter transformer model and capacity, converter valve submodule power device model, converter valve submodule quantity, submodule capacitor model and capacitance value, and bridge arm reactor model and quantity obtained from the solution for each onshore receiving-end converter station are used as the equipment-level selection schemes that match the system-level feasible scheme.

[0018] Furthermore, the constraints of the equipment-level optimization model include converter transformer capacity constraints, converter valve submodule voltage constraints, bridge arm current constraints, converter valve submodule power device current safety margin constraints, submodule capacitor candidate value constraints, and bridge arm reactor configuration constraints. The capacity constraint of the converter transformer and the voltage constraint of the converter valve submodule are expressed as follows: in, This represents the set of onshore receiving-end converter stations determined by the system-level feasible schemes. Indicates the first The rated capacity of the converter transformers selected for each onshore receiving-end converter station; The first feasible solution determined by the system-level feasible solution is... Capacity requirements for each onshore receiving-end converter station; Indicates the first The number of converter valve sub-modules in each onshore receiving-end converter station; Indicates the first The rated voltage of the selected sub-modules in each onshore receiving-end converter station; The first feasible solution determined by the system-level feasible solution is... The DC voltage level of each onshore receiving-end converter station; Indicates the first The rated voltage of the power devices in the selected converter valve submodule of each onshore receiving-end converter station; This represents the voltage safety margin factor; The bridge arm current constraint, the current safety margin constraint of the power device in the converter valve submodule, the candidate value constraint of the submodule capacitor, and the bridge arm reactor configuration constraint are expressed as follows: in, Indicates the first DC side current of an onshore receiving-end converter station; The first feasible solution determined by the system-level feasible solution is... Active power requirements of an onshore receiving-end converter station; Indicates the first AC side current of an onshore receiving-end converter station; Indicates the first The rated AC voltage of each onshore receiving-end converter station; Indicates the first The bridge arm current of an onshore receiving-end converter station; Indicates the first The rated current of the power devices of the selected converter valve submodules in each onshore receiving-end converter station; Indicates the current safety margin factor; Indicates the first The rated current of the selected bridge arm reactors at each onshore receiving-end converter station; Indicates the first The capacitance value of the selected submodule capacitors in each onshore receiving-end converter station; This represents the set of candidate submodule capacitance values; Indicates the first Reactance parameters of the selected bridge arm reactors at each onshore receiving-end converter station; This represents the set of parameters for candidate bridge arm reactors; The equipment selection results that simultaneously meet the constraints of converter transformer capacity, converter valve submodule voltage, bridge arm current, converter valve submodule power device current safety margin, submodule capacitor candidate value, and bridge arm reactor configuration are determined as the equipment-level selection scheme that matches the system-level feasible scheme.

[0019] Furthermore, the step of forming a comprehensive evaluation result based on the system-level feasible solution and the equipment-level selection solution, and iteratively updating the system-level feasible solution based on the comprehensive evaluation result until the convergence condition is met, specifically includes: Obtain the system-level optimization objective function value corresponding to the system-level feasible solution; Obtain the device-level optimization objective function value corresponding to the device-level selection scheme that matches the system-level feasible scheme; The system-level optimization objective function value and the device-level optimization objective function value are used as the corresponding evaluation results of the system-level feasible solution and the device-level selection solution, and the different system-level feasible solutions are ranked according to the corresponding evaluation results; Based on the ranking results, the system-level feasible solution that meets the requirements of AC grid voltage stability, power flow, line transmission capacity, and equipment selection matching at the receiving end is selected as the current preferred solution; The system-level planning scheme for the neighborhood is generated by perturbing at least one of the following system-level variables in the current preferred scheme: site of the onshore receiving-end converter station, capacity of the onshore receiving-end converter station, DC voltage level, DC submarine cable connection relationship, onshore DC overhead line connection relationship, and line type. The system-level optimization solution and equipment-level optimization solution are re-executed for the neighborhood system-level planning scheme to obtain the updated system-level feasible scheme and the matching equipment-level selection scheme, and the corresponding evaluation results are re-formed; When the change in the corresponding evaluation result during continuous iteration is less than the preset convergence threshold, or the number of iterations reaches the preset maximum number of iterations, the convergence condition is determined to be met; otherwise, the system-level feasible solution is iteratively updated based on the corresponding evaluation result.

[0020] Compared with the prior art, the present invention has the following advantages: (1) Existing offshore wind power cluster access system planning usually only judges the safety of the receiving-end AC grid by node voltage limits, power flow balance or line capacity. It is difficult to reflect the electrical coupling between grid connection points and the changes in reactive power support capacity after multi-terminal flexible DC feed-in. It is easy to have the problem of seemingly feasible power flow but insufficient static voltage stability margin. This invention introduces the equivalent short-circuit ratio index DPHSCR of hybrid feed-in into the system-level optimization objective and stability constraint. This enables the planning scheme to identify and eliminate low-cost schemes with insufficient voltage stability while meeting the conventional operation constraints, thereby improving the static voltage stability margin of the receiving-end grid after multi-terminal flexible DC feed-in of offshore wind power clusters.

[0021] (2) Existing technologies usually focus on the selection of access points, line investment or expansion of onshore power grids, and easily overlook the coordination relationship between construction costs, voltage stability and voltage deviation at the grid connection point. This invention uses line construction costs, AC grid voltage stability indicators at the receiving end and voltage deviation at the grid connection point in multiple scenarios as system-level evaluation objects, which can avoid the decline in voltage quality caused by simply pursuing low investment, and also avoid the waste of construction costs caused by excessively increasing the configuration.

[0022] (3) In the past, the planning of the existing system-level grid structure and the selection of key equipment for converter stations were often carried out separately. This may result in the difficulty of matching the determined site, capacity, topology and DC voltage level with the equipment parameters such as converter transformers, converter valve submodule power devices, submodule capacitors and bridge arm reactors. The present invention uses the onshore receiving-end converter station capacity, DC voltage level and line topology in the system-level feasible scheme as input to the equipment-level optimization model, so that the equipment selection is determined in correspondence with the system planning results. This reduces the investment increase caused by capacity redundancy, repeated equipment verification and parameter mismatch, and improves the engineering feasibility of the planning scheme.

[0023] (4) Existing planning methods do not adequately consider voltage deviations under different operating scenarios such as high wind power generation, low wind power generation, peak load, and low load, which may result in the scheme being applicable only to local operating conditions. This invention evaluates the total voltage deviation at the grid connection point under multiple typical operating scenarios, enabling the target planning scheme to adapt to changes in wind power output and load levels, and reducing voltage fluctuations at the grid connection point during operation.

[0024] (5) For receiving-end AC grids with multiple DC feeds, if offshore wind power is concentrated at a single grid connection point, it can easily cause excessive local voltage support pressure. Existing technologies focus more on connection distance or expansion costs, and do not adequately consider the role of decentralized connection of receiving-end converter stations and DC-side interconnection between stations. This invention incorporates the site, capacity, and DC line topology of onshore receiving-end converter stations into the system-level planning, enabling decentralized connection of receiving-end converter stations and achieving power mutual assistance and coordinated voltage regulation through DC-side interconnection. While controlling the increase in line investment, it improves the system stability margin and reduces voltage deviation in multiple scenarios.

[0025] (6) In existing schemes, the line type and DC voltage level are sometimes only used as subsequent verification objects, which can easily lead to inconsistencies between the planning results and the actual transmission capacity. This invention determines the DC voltage level, submarine cable type, onshore DC overhead line type and line topology simultaneously in system-level optimization, thereby improving the completeness of the line construction scheme. Attached Figure Description

[0026] Figure 1 This is a flowchart of the collaborative optimization planning method according to an embodiment of the present invention; Figure 2 This is an initial planning scenario diagram of the offshore wind power cluster access 118-node system according to an embodiment of the present invention; Figure 3 This is a topology diagram of the optimal planning scheme in an embodiment of the present invention; Figure 4 This is a topology diagram comparing the site selection schemes of single-station and dual-station receiving-end converter stations according to an embodiment of the present invention; Figure 5 This is a topology diagram of a comparative scheme considering only cost objectives in an embodiment of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] Example 1: like Figure 1 As shown in this embodiment, a collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters, oriented towards reactive power support, can be applied to planning scenarios where multiple offshore wind farms transmit power through multiple offshore sending-end converter stations and connect to the receiving-end AC grid through one or more onshore receiving-end converter stations. The multi-terminal flexible DC access system may include an offshore sending-end converter station, an onshore receiving-end converter station, a DC submarine cable connecting the offshore sending-end converter station and the onshore receiving-end converter station, an onshore DC overhead line connecting different onshore receiving-end converter stations, and converter transformers, converter valve submodule power devices, submodule capacitors, and bridge arm reactors within the onshore receiving-end converter station. The onshore receiving-end converter station can directly connect to a candidate onshore grid connection point of the receiving-end AC grid, or it can achieve power mutual support between different receiving-end converter stations through inter-station DC side interconnection. This structure allows the transmitted power of the offshore wind power cluster to avoid being concentrated into a single grid connection point, thereby reducing the voltage support pressure on the local receiving-end AC grid.

[0029] The method in this embodiment can be implemented according to the following process.

[0030] S1. Obtain the basic dataset for planning.

[0031] In this embodiment, the planning dataset can be formed by combining offshore wind farm planning data, submarine cable route survey data, onshore power grid flow calculation models, equipment manufacturer sample libraries, and typical operation mode data. Specifically, the offshore sending-end converter station data can be obtained from offshore wind farm cluster planning data, including the location, rated capacity, transmission power, and corresponding wind farm capacity of each offshore sending-end converter station; the DC transmission distance between each offshore sending-end converter station and the candidate onshore grid connection point can be obtained after route planning based on geographical coordinates, submarine cable corridor constraints, landing point location, and avoidance areas, or the initial distance can be determined first based on the geographical straight-line distance, and then multiplied by the path correction factor to obtain the usable distance for the project. For projects where submarine cable route surveys have been completed, the submarine cable route length obtained from the survey can also be used directly.

[0032] Data on the receiving-end AC grid can be obtained from grid planning models or power flow calculation models, including the receiving-end AC grid topology, node parameters, branch parameters, node voltage levels, load data, AC line power flow limits, and node voltage upper and lower limits. The node impedance admittance parameters used to calculate the voltage stability index of the receiving-end AC grid can be obtained by inverting the node admittance matrix of the receiving-end AC grid. When considering an external equivalent grid, the external grid can also be first equivalentd using Thevenin's method to form the equivalent impedance parameters between candidate grid connection points. Therefore, the candidate onshore grid connection points not only have geographical distances but also electrical distances used to evaluate the mutual influence of multiple DC feeders.

[0033] Candidate onshore grid connection point data may include a set of candidate onshore grid connection points, the node number of each candidate onshore grid connection point in the receiving-end AC grid, the voltage level of the grid connection point, the allowable access capacity, the equivalent impedance parameters between grid connection points, and whether onshore DC overhead interconnections are permitted between grid connection points. Candidate onshore grid connection points can be pre-defined by grid planners or selected based on node voltage level, short-circuit capacity, load center distance, and available site conditions. Nodes lacking land for construction, failing to meet access capacity requirements, or not permitted to add new DC line channels may be excluded from the candidate onshore grid connection point set.

[0034] Candidate DC voltage level data can include multiple selectable DC voltage levels such as ±320kV, ±400kV, and ±500kV. Each candidate DC voltage level corresponds to a set of line transmission capacity, insulation configuration requirements, and converter station equipment adaptation requirements. Candidate line data can be generated from a line sample library. Candidate DC submarine cable data includes cable type, cost per unit length, rated current, maximum transmission capacity, and compatible DC voltage level; candidate onshore DC overhead line data includes onshore DC overhead line type, cost per unit length, rated current, number of conductor splits, maximum transmission capacity, and the length of the overhead line between candidate onshore grid connection points. The maximum transmission capacity of the line can be directly provided from the equipment sample library or calculated based on the selected DC voltage level and the line's rated current. For example, for a bipolar flexible DC line, the maximum allowable transmission power of the line can be determined in the following manner: in, Indicates the first The maximum allowable transmission power of a single DC submarine cable line or a land-based DC overhead line; Indicates the first The single-pole DC voltage corresponding to each line; Indicates the first The rated current of the selected circuit model; Indicates the first The transmission margin factor or reduction factor for each line. For single-pole connections or other DC connection methods, the coefficient 2 in the formula can be removed or adjusted accordingly. This processing method establishes a correspondence between line type, voltage level, and transmission capacity, rather than checking the usability of the line separately after system optimization.

[0035] Typical operating scenario data can be obtained by combining wind power output levels and receiving-end AC grid load levels. In one specific implementation, typical operating scenarios include four types of conditions: high wind power generation and peak load, low wind power generation and peak load, high wind power generation and low load, and low wind power generation and low load. In another specific implementation, clustering can be performed based on the annual wind power output and load curves to obtain several representative typical operating scenarios, and a weight coefficient can be assigned to each typical operating scenario. The scenario weight can be determined by the probability of the scenario occurring throughout the year, or the weight of high-risk scenarios can be artificially increased based on the safety requirements of the planners. This avoids the planning results being applicable only to a single high-incidence condition or a single peak load condition.

[0036] Candidate converter station equipment data can be obtained from equipment manufacturer sample libraries or engineering cost databases. This includes candidate converter transformer models, rated capacities, compatible AC voltage levels, compatible DC voltage levels, and unit capacity costs; candidate converter valve submodule power device models, rated voltages, rated currents, and individual power device costs; candidate submodule capacitor models, capacitance values, rated voltages, and individual capacitor costs; and candidate bridge arm reactor models, rated currents, reactance parameters, and individual bridge arm reactor costs. Candidate equipment data can be initially screened based on the DC voltage levels determined by the system-level feasible solutions and the onshore receiving-end converter station capacity before entering the equipment-level optimization model. This approach reduces the number of incompatible equipment models entering the optimization process, improving equipment-level selection efficiency.

[0037] S2. Construct a system-level optimization model based on the planning dataset.

[0038] In this embodiment, a system-level planning scheme can be represented as a set of schemes composed of multiple system-level variables, including at least: whether each candidate onshore grid connection point constructs an onshore receiving-end converter station, the planned capacity of each onshore receiving-end converter station, the DC voltage level adopted by each onshore receiving-end converter station, which onshore receiving-end converter station each offshore sending-end converter station is connected to, whether the corresponding DC submarine cable is constructed and its model, whether onshore DC overhead connection lines are set up between different onshore receiving-end converter stations, the model of the onshore DC overhead line, and the transmission power of each line under different typical operating scenarios.

[0039] As a specific representation, a system-level scheme can be written as: in, This represents a system-level planning scheme; Indicates the first Whether to construct onshore receiving-end converter stations at each candidate onshore grid connection site; Indicates the first The planned capacity of the onshore receiving-end converter station at each candidate onshore grid connection point; Indicates the first Should the first candidate onshore grid connection site be selected? One candidate DC voltage level; Indicates the first The first offshore power transmission converter station and the first Should a model be selected among the candidate onshore grid connection sites? DC submarine cable; Indicates the first The first candidate onshore grid connection point and the first Should a model be selected among the candidate onshore grid connection sites? Overhead DC power lines on land; Indicates the first In the first typical operating scenario, the The active power transmitted by a DC line.

[0040] In this embodiment, the system-level optimization model takes minimizing line construction cost, maximizing the AC grid voltage stability index at the receiving end, and minimizing the total voltage deviation at the grid connection point under multiple typical operating scenarios as its optimization objectives. These multiple objectives can be solved directly as vector objectives, or they can be normalized during implementation to form a system-level comprehensive objective value. As a specific implementation method, the system-level optimization objective can be expressed as: in, This represents the system-level optimization objective function; This indicates the construction cost of DC submarine cables and onshore DC overhead lines; This represents the minimum value of the hybrid feed-in equivalent short-circuit ratio index corresponding to the grid connection point of each receiving-end converter station in the receiving-end AC power grid. The hybrid feed-in equivalent short-circuit ratio index is determined based on the equivalent impedance, equivalent power, and reactive power boundary function influence term of the flexible DC converter station between the grid connection points of the receiving-end converter stations. This is used to transform the goal of maximizing voltage stability into the goal of minimizing it. This indicates the total voltage deviation at the grid connection point under multiple typical operating scenarios.

[0041] In another specific implementation, to facilitate the subsequent formation of a comprehensive evaluation result together with the device-level optimization objective function value, the system-level objectives can be normalized to form system-level evaluation values: in, This represents the normalized system-level evaluation value; , , These represent the weighting coefficients corresponding to line construction costs, voltage deviation at grid connection points in multiple scenarios, and voltage stability indicators, respectively. , , These represent the reference values ​​for the corresponding targets. In this method, The larger, The smaller the value, the better it reflects the optimization direction of improving voltage stability margin. It should be noted that the above normalization method is only one implementation method; in other implementations, Pareto sorting, hierarchical optimization, or a priority rule of stability first and then economy can also be used.

[0042] The construction cost of the line can be calculated based on the line length, unit length cost, and line selection variables of the DC submarine cable and the onshore DC overhead line.

[0043] in, This indicates a collection of offshore power transmission converter stations. This represents the set of candidate onshore grid connection sites; This represents the set of candidate DC submarine cable models; This represents the set of candidate onshore DC overhead line models; Indicates the first The first offshore power transmission converter station and the first Should a model be selected among the candidate onshore grid connection sites? DC submarine cable; Indicates the first The first offshore power transmission converter station and the first The length of the DC submarine cable between the candidate onshore grid connection points; Model number Cost per unit length of DC submarine cable; Indicates the first The first candidate onshore grid connection point and the first Should a model be selected among the candidate onshore grid connection sites? Overhead DC power lines on land; Indicates the first The first candidate onshore grid connection point and the first The length of the onshore DC overhead line between the candidate onshore grid connection points; Model number The unit length cost of terrestrial DC overhead lines.

[0044] The total voltage deviation at the grid connection point under multiple typical operating scenarios can be expressed as: in, Represents a set of typical operating scenarios; Indicates the first Weighting coefficients for a typical operating scenario; Indicates the first Whether to construct onshore receiving-end converter stations at each candidate onshore grid connection site; Indicates the first In the first typical operating scenario, the The actual voltage amplitude at each grid connection point; This represents the reference value for the grid connection point voltage, which is taken as follows in one specific implementation: By introducing This allows the voltage deviation evaluation to correspond to the actual onshore receiving-end converter station grid connection point, rather than evaluating all candidate points indiscriminately.

[0045] S3. Determine the voltage stability index of the AC power grid at the receiving end.

[0046] In this embodiment, the voltage stability index of the receiving-end AC grid is characterized by the Hybrid Infeed Equivalent Short-Circuit Ratio (DPHSCR). This index reflects the impact of equivalent impedance, equivalent power, and reactive power boundary of the flexible DC converter station on the static voltage stability margin after multi-terminal flexible DC access. Compared with simply judging whether the node voltage exceeds the limit, DPHSCR can further reflect the stability margin of the receiving-end AC grid when subjected to power disturbances or changes in reactive power support demand.

[0047] In one specific implementation, the equivalent impedance matrix between candidate onshore grid-connected points can be obtained first based on the nodal admittance matrix of the receiving-end AC grid. For the set of candidate onshore grid-connected points... Its corresponding equivalent impedance matrix can be expressed as: in, This represents the equivalent impedance matrix between candidate onshore grid connection points; This represents the equivalent admittance matrix of the candidate onshore grid connection point, extracted from the admittance matrix of the receiving-end AC grid node. For receiving-end AC grids containing external equivalent systems, this can also be achieved by forming... Previously, the external network was processed using equivalence.

[0048] The reactive power boundary function of a flexible DC converter station can be expressed as the boundary of reactive power that the converter station can provide or absorb under given active power, AC-side voltage, and DC-side voltage conditions. As a specific implementation method, the first... The reactive power boundary function of an onshore receiving-end converter station can be denoted as: in, Indicates the first The reactive power boundary of an onshore receiving-end converter station; Indicates the first The active power of each onshore receiving-end converter station; Indicates the first AC side voltage of each onshore receiving-end converter station; Indicates the first The reactive power boundary of a land-based receiving-end converter station is determined by the DC side voltage. This reactive power boundary can be determined by the converter valve capacity, arm current limit, control strategy constraints, or the PQ operating capability curve provided by the manufacturer. Its partial derivative term is used to characterize the changing trend of the reactive power boundary of the converter station when the AC side voltage changes, that is, the change in the reactive power support capability that the flexible DC converter station can provide under voltage disturbances.

[0049] In one specific implementation, the first The DPHSCR corresponding to each existing onshore receiving-end converter station connected to the grid can be calculated in the following form: in, Indicates the first The equivalent short-circuit ratio of hybrid feed-in corresponding to the grid connection point of the already constructed onshore receiving-end converter station; Indicates the rated voltage of the AC system at the receiving end; This represents the set of onshore receiving-end converter stations determined by system-level feasible solutions; Indicates consideration of the first After the reactive power boundary of the first onshore receiving-end converter station is affected, the first The first grid connection point for the first The effect of equivalent impedance at each grid connection point; Indicates the first The equivalent power of each onshore receiving-end converter station. Specifically, It can be by the first The equivalent active power and equivalent reactive power of each onshore receiving-end converter station are determined. The DPHSCR can be determined by the equivalent impedance between candidate grid connection points, the electrical distance between nodes, and the partial derivative of the reactive power boundary function. This expression means that when the electrical distance between a grid connection point is long, the receiving-end AC grid is weak, the feed-in power is large, or the reactive power support boundary of the converter station is insufficient, the denominator increases, and the DPHSCR decreases, indicating that the static voltage stability margin of that grid connection point decreases.

[0050] in, The first is represented by the equivalent impedance matrix of the receiving-end AC power grid. The first grid connection point and the first Equivalent impedance between grid connection points; Indicates the first The reactive power boundary change of the converter station affects the first... The conversion factor for the impact of voltage stability at each grid connection point; Indicates the first The partial derivative of the reactive power boundary function of an onshore receiving-end converter station with respect to the AC side voltage. It should be noted that... The reactive power support capability can be determined based on the power flow sensitivity of the receiving-end AC grid, the node voltage sensitivity, or offline simulation results. In a simplified implementation, a uniform engineering experience coefficient can also be used for different grid connection points. This approach ensures that reactive power support capability is not an isolated equipment capability, but rather participates in the calculation of the voltage stability index of the receiving-end AC grid.

[0051] The voltage stability constraint of the AC grid at the receiving end can be expressed as: in, This represents the DPHSCR threshold indicating whether the receiving-end AC grid meets the static voltage stability requirements. In one specific implementation, The value can be preset based on the strength of the AC grid at the receiving end, the scale of the DC feed-in, and engineering experience, for example, 1.0, 1.1, or 1.2; in another specific implementation, The voltage stability margin can be determined through offline continuous power flow simulation, N-1 verification, or voltage stability margin simulation. For receiving-end AC grids with weak grid structures or a high proportion of multiple DC feeds, the voltage stability margin can be appropriately increased. This is to improve the safety margin of the planning scheme.

[0052] S4. Establish system-level constraints and screen system-level feasible solutions.

[0053] In this embodiment, the system-level optimization model needs to simultaneously satisfy converter station configuration constraints, DC voltage level constraints, receiving-end AC grid voltage stability constraints, power flow constraints for typical operating scenarios, and line transmission capacity constraints. Converter station configuration constraints ensure that the number of onshore receiving-end converter stations does not exceed the number of candidate onshore grid-connected points, and that the capacity of the receiving-end converter stations can cover the power transmitted by the offshore sending-end system. DC voltage level constraints ensure that each existing onshore receiving-end converter station can only select one DC voltage level from the candidate DC voltage level set, and that the corresponding lines and equipment meet the adaptation requirements under that voltage level.

[0054] Power flow constraints in typical operating scenarios can be implemented at the receiving-end AC grid node level, or the power transmitted via DC lines can be considered simultaneously. As a specific implementation method, in each typical operating scenario, the output power of each offshore sending-end converter station is first determined based on the offshore wind power output level. Then, according to the sending-end-receiving-end connection relationship in the system-level scheme, the output power is allocated to the corresponding onshore receiving-end converter stations. Subsequently, power flow calculations are performed on the receiving-end AC grid to obtain the voltage at each node, the power flow of each line, and the active and reactive power outputs of each onshore receiving-end converter station. The reactive power output of the converter stations can be used as a power flow optimization variable, adjusted within the reactive power boundary range of the converter stations to reduce the voltage deviation at the grid connection point and improve the voltage support capacity of the receiving-end AC grid. For simplified implementation methods that do not require complete AC power flow calculations, linearized power flow or sensitivity power flow models can also be used, but the upper and lower limits of node voltages, line power flow limits, and DC line capacity constraints should still be retained.

[0055] In one specific implementation, the node voltage constraint can be expressed as: in, and They represent the first The lower and upper limits of voltage operation for each receiving-end AC grid node; Indicates the first In the first typical operating scenario, the Voltage amplitude at each node; This represents the set of AC grid nodes at the receiving end. As an example, the upper and lower limits of the AC grid node voltage at the receiving end can be between 0.95 pu and 1.05 pu, or can be determined according to specific grid operation procedures.

[0056] The line transmission capacity constraint can be expressed as: in, Indicates the first In the first typical operating scenario, the The active power transmitted by a DC submarine cable or a DC overhead line on land; Indicates the first The maximum allowable transmission power of the line under the selected line type and selected DC voltage level; This represents the set of candidate DC submarine cable lines and candidate onshore DC overhead lines. This constraint ensures that the system-level planning scheme takes into account the actual transmission capacity when selecting the line type, avoiding schemes that cannot meet the transmission power requirements based solely on line cost.

[0057] A system-level planning scheme is considered a system-level feasible scheme when it simultaneously meets the requirements for converter station configuration, DC voltage level, receiving-end AC grid voltage stability, power flow, and line transmission capacity. If a scheme has a lower line cost but... Even if its conventional power flow calculations meet the upper and lower limits of node voltage, it will not be output as a system-level feasible solution. This approach can exclude low-cost solutions with insufficient static voltage stability margin during the planning stage.

[0058] S5. Map the system-level feasible solution to the device-level optimization model input.

[0059] In this embodiment, after the system-level feasible solution is determined, the capacity of the onshore receiving-end converter stations, the DC voltage level, the line topology, and the active power demand undertaken by each onshore receiving-end converter station are transferred to the equipment-level optimization model. Specifically, if the system-level feasible solution is determined to be... The capacity of each onshore receiving-end converter station is DC voltage level is The AC side voltage level is The equipment-level optimization model then needs to select from candidate converter transformers, candidate converter valve submodule power devices, candidate submodule capacitors, and candidate bridge arm reactors that can be compatible with... , and A matching combination of equipment.

[0060] In one specific implementation, equipment can be initially screened based on system-level feasible solutions. For converter transformers, candidate models that are compatible with both AC and DC voltage levels and have a rated capacity not less than the capacity requirement of the onshore receiving-end converter station are retained. For converter valve submodule power devices, candidate models whose rated voltage and rated current meet safety margin requirements are retained. For submodule capacitors, models whose rated voltage and capacitance values ​​are within the candidate range are retained. For bridge arm reactors, models whose rated current is not less than the bridge arm current requirement and whose reactance parameters meet the candidate configuration requirements are retained. This screening mechanism can reduce invalid combinations in equipment-level optimization and ensure that equipment-level selection always corresponds to system-level feasible solutions.

[0061] S6. Construct a device-level optimization model.

[0062] In this embodiment, the equipment-level optimization model aims to minimize the equipment investment cost of the receiving-end converter station. The equipment investment cost includes the cost of the converter transformer, the converter valve submodule, and the bridge arm reactor. The cost of the converter valve submodule can be determined by the number of submodules, the cost of a single power device, and the cost of a single capacitor. The equipment-level optimization objective function can be expressed as: in, This represents the device-level optimization objective function; This indicates the total investment cost of the receiving-end converter station equipment; This represents the set of onshore receiving-end converter stations determined by the system-level feasible schemes. Indicates the first The cost of converter transformers at an onshore receiving-end converter station; Indicates the first Cost of converter valve submodule for an onshore receiving-end converter station; Indicates the first Cost of bridge arm reactors for an onshore receiving-end converter station; In one specific implementation, the first The equipment cost of an onshore receiving-end converter station can be expressed as: in, Indicates the first The unit capacity cost of the converter transformers selected for each onshore receiving-end converter station; Indicates the first The rated capacity of the converter transformers selected for each onshore receiving-end converter station; Indicates the first The number of converter valve sub-modules in each onshore receiving-end converter station; Indicates the first The individual cost of the power devices in the selected converter valve submodule of an onshore receiving-end converter station; Indicates the first The cost per capacitor in the selected submodule of an onshore receiving-end converter station; Indicates the first The number of bridge arm reactors in each onshore receiving-end converter station; Indicates the first Cost of a single bridge arm reactor selected for an onshore receiving-end converter station.

[0063] The capacity constraint of the converter transformer can be expressed as: in, The first option determined by the system-level feasible solution Capacity requirements for each onshore receiving-end converter station; Indicates the first The rated capacity of the converter transformers selected for each onshore receiving-end converter station. This constraint ensures that the converter transformer capacity is not less than the system-level planned capacity requirement, avoiding a situation where the system-level scheme is feasible but the converter transformer capacity is insufficient.

[0064] The number of converter valve submodules can be determined based on the DC voltage level, the submodule's rated voltage, and the voltage safety margin. As a specific implementation method, it can take the following form: in, Indicates the first The number of converter valve submodules for each onshore receiving-end converter station, rounded to a positive integer; This represents the voltage safety margin factor; The first option determined by the system-level feasible solution DC voltage level of each onshore receiving-end converter station; Indicates the first The rated voltage of the selected submodules in each onshore receiving-end converter station. This calculation allows the DC voltage level selected at the system level to directly affect the number of submodules at the equipment level; in actual selection, the minimum value among positive integers that meet this constraint can be selected as the number of submodules, avoiding a disconnect between the voltage level and the converter valve configuration.

[0065] In another specific implementation, when the equipment manufacturer's sample library already provides a recommended number of submodules for a certain voltage level, the manufacturer's recommended number can be used first, and the above formula can be used for safety verification. This method is suitable for scenarios where mature equipment solutions are already available in the engineering design phase. Its advantage lies in reducing computational complexity and improving the consistency between equipment selection and the manufacturer's supply plan.

[0066] The arm current can be determined based on the converter station capacity, DC-side current, and AC-side current. As a specific implementation, the DC-side current and AC-side current can be expressed as: in, Indicates the first DC side current of an onshore receiving-end converter station; The first option determined by the system-level feasible solution Active power requirements of an onshore receiving-end converter station; Indicates the first The single-pole DC voltage of an onshore receiving-end converter station; Indicates the first AC side current of an onshore receiving-end converter station; Indicates the first Capacity requirements for each onshore receiving-end converter station; Indicates the first The rated voltage of the AC side of the onshore receiving-end converter station. For other DC connection methods, the voltage can be adjusted according to the DC side connection structure. The calculation method.

[0067] The bridge arm current can be further expressed as: in, Indicates the first The expression represents the arm current of an onshore receiving-end converter station. This expression is used to estimate the current carrying capacity requirements of the converter valve arms during the equipment selection phase. This further limits the rated current of the power devices in the converter valve submodules and the rated current of the arm reactors. For example: in, Indicates the first The rated current of the power devices selected for each onshore receiving-end converter station; Indicates the current safety margin factor; Indicates the first The rated current of the bridge arm reactors selected for the onshore receiving-end converter station. This constraint avoids selecting power devices or bridge arm reactors with insufficient rated current based solely on cost.

[0068] The submodule capacitance value can be selected from a set of candidate submodule capacitance values. In one specific implementation, the submodule capacitance value only needs to satisfy the candidate set constraint: in, Indicates the first The capacitance value of the selected submodule capacitors in each onshore receiving-end converter station; This represents the set of candidate submodule capacitance values. This method is suitable for scenarios where the equipment manufacturer has already completed the standardized design of submodule capacitance parameters.

[0069] In another specific implementation, candidate capacitors can be screened in conjunction with submodule voltage fluctuation constraints. For example, based on the allowable submodule voltage fluctuation range, converter station power requirements, and submodule energy buffering requirements, candidate models with excessively small capacitor values ​​can be eliminated first, and then cost optimization can be performed on the remaining candidate models. The advantage of this approach is that it avoids selecting submodule capacitors with insufficient energy buffering capacity simply because of their low cost, thereby improving the operational stability of the converter station during active power fluctuations and reactive power regulation.

[0070] The bridge arm reactor can be selected from a set of candidate bridge arm reactors based on its rated current and reactance parameters. The rated current of the bridge arm reactor ensures that it does not experience thermal stability issues under normal operation and overload verification conditions, while the reactance parameters affect bridge arm current fluctuations, fault current rise rates, and the dynamic operational stability of the converter station. In one specific implementation, the reactance parameters of the bridge arm reactor can be directly selected from the set of candidate bridge arm reactor parameters; in another specific implementation, the lower limit of the reactance parameters can be determined first based on fault current limitation requirements, and then a model that meets the conditions and has a lower cost can be selected from the candidate set. This approach can balance normal operation economy and fault condition safety.

[0071] S7. Develop equipment-level selection schemes.

[0072] After solving the equipment-level optimization model, an equipment-level selection scheme matching the system-level feasible solution can be obtained. This equipment-level selection scheme includes the converter transformer model and rated capacity, converter valve submodule power device model, converter valve submodule quantity, submodule capacitor model and capacitance value, and bridge arm reactor model and quantity for each onshore receiving-end converter station. It should be noted that matching in this embodiment not only means that the equipment model can be installed in the converter station, but also that the equipment capacity, voltage level, withstand voltage and current capacity, submodule quantity, and reactor parameters all correspond to the capacity, voltage level, and operating power determined by the system-level feasible solution.

[0073] In one specific implementation, if the system-level feasible solution determines that a certain onshore receiving-end converter station adopts a ±400kV DC voltage level and has a capacity requirement of 400MW, the equipment-level optimization model can first screen converter transformer models from candidate converter transformers that are compatible with both the 220kV AC side voltage and the ±400kV DC side voltage. Then, it can screen IGBT models from 6.5kV-level power devices that meet the voltage and current margin requirements, and determine the number of submodules based on the DC voltage level. This approach can reduce iterative adjustments between system-level planning and equipment-level selection.

[0074] S8. A comprehensive evaluation result is formed based on the system-level optimization objective function value and the device-level optimization objective function value.

[0075] In this embodiment, for each system-level feasible solution, a corresponding system-level optimization objective function value can be obtained; after inputting this system-level feasible solution into the equipment-level optimization model, a corresponding equipment-level optimization objective function value can also be obtained. The comprehensive evaluation result can be formed by the system-level optimization objective function value and the equipment-level optimization objective function value. The system-level optimization objective function value may include line construction cost, minimum DPHSCR, and total voltage deviation at grid connection points in multiple scenarios; the equipment-level optimization objective function value may include converter transformer cost, converter valve submodule cost, and bridge arm reactor cost.

[0076] As a specific implementation method, the system-level evaluation value and the equipment-level evaluation value can be normalized to form a comprehensive evaluation value: in, This represents the overall evaluation value; This represents the normalized system-level evaluation value; This represents the device-level optimization objective function value; This indicates a reference value for equipment-level costs; and These represent the weighting coefficients for system-level and equipment-level objectives, respectively. The smaller the comprehensive evaluation value, the better the overall performance of the scheme in terms of line investment, voltage stability, voltage deviation, and equipment investment.

[0077] In another specific implementation, instead of forming a single comprehensive evaluation value, a tiered screening approach can be adopted: first, schemes that do not meet the DPHSCR threshold and multi-scenario voltage deviation requirements are eliminated; then, the remaining schemes are ranked according to line construction cost and total equipment investment cost. This approach is suitable for receiving-end AC power grids with high voltage stability requirements. Its advantage is that it can prevent schemes with poor stability but low investment from being mistakenly selected as the target planning scheme.

[0078] S9. Iteratively update the system-level feasible solutions based on the comprehensive evaluation results.

[0079] In this embodiment, the iterative update is not an unconstrained random search of all variables, but rather generates neighborhood system-level planning schemes that satisfy the candidate set and basic engineering constraints near the current system-level feasible solutions. The disturbance objects may include at least one of the following: the site of the onshore receiving-end converter station, the capacity of the onshore receiving-end converter station, the DC voltage level, the connection relationship between the offshore sending-end converter station and the onshore receiving-end converter station, whether an inter-station DC tie line is installed, the type of DC submarine cable, and the type of onshore DC overhead line.

[0080] For example, in one specific implementation, the number of onshore receiving-end converter stations can remain unchanged, with only one receiving-end converter station site being replaced, and the submarine cable length, equivalent impedance, line cost, and DPHSCR recalculated; this method is suitable for scenarios with many candidate grid connection points but a basically determined number of stations. In another specific implementation, the receiving-end station site can remain unchanged, with only the DC voltage level or line type changed, to compare the differences in investment, line capacity, and equipment cost between ±320kV, ±400kV, and ±500kV schemes. In yet another specific implementation, an onshore DC overhead interconnection line can be added or removed between two existing onshore receiving-end converter stations to evaluate the impact of inter-station DC side interconnection on power balance, grid connection point voltage deviation, and DPHSCR.

[0081] For each neighborhood system-level planning scheme, the system-level optimization and equipment-level optimization solutions are re-executed to obtain updated system-level feasible schemes and their corresponding equipment-level selection schemes, and the comprehensive evaluation results are recalculated. If the comprehensive evaluation result of the updated scheme is better than the current scheme, the scheme is retained as the current preferred scheme; if it is not better than the current scheme, the scheme can be discarded, or retained according to a preset probability to avoid getting trapped in local optima. Specific solution methods can include mixed-integer linear programming, mixed-integer nonlinear programming, heuristic search, genetic algorithms, neighborhood search, or a combination of the above methods. In engineering applications, if the system-level model contains many 0-1 variables, mixed-integer linear programming or constrained neighborhood search is preferred for solving the problem.

[0082] Convergence criteria can be determined based on the change in the comprehensive evaluation results, the number of iterations, or the number of consecutive periods without improvement. As a specific implementation method, the following convergence judgment can be used: in, Indicates the first The comprehensive evaluation value obtained from the next iteration; Indicates the first The comprehensive evaluation value obtained from the next iteration; This indicates a preset convergence threshold. In one implementation, the comprehensive evaluation result is considered to have reached stable convergence when the above conditions are met consecutively for a preset number of times. In another implementation, the convergence condition can also be determined to be met when the number of iterations reaches a preset maximum number of iterations, or when no better system-level feasible solution is obtained after several consecutive iterations. Through the above processing, infinite iteration of the optimization process can be avoided, while ensuring that the final solution has been jointly evaluated at the system and device levels.

[0083] S10, Output the target planning scheme.

[0084] Once the convergence condition is met, the current optimal solution is output as the target planning scheme. The target planning scheme may include the number of onshore receiving-end converter stations, their locations, capacity, DC voltage level, DC submarine cable connections from the offshore sending-end converter station to the onshore receiving-end converter station, DC overhead tie line connections between onshore receiving-end converter stations, DC submarine cable type, onshore DC overhead line type, converter transformer type and capacity, converter valve submodule power device type, number of submodules, submodule capacitor type and capacitance value, and bridge arm reactor type and quantity. Furthermore, the target planning scheme can also output the total system investment, total voltage deviation at the grid connection point under multiple typical operating scenarios, minimum DPHSCR index, and power flow verification results under each typical operating scenario.

[0085] To ensure the output becomes a complete engineering solution, this embodiment outputs a corresponding mapping between each offshore sending-end converter station and its corresponding onshore receiving-end converter station, each DC submarine cable and its model, and each onshore receiving-end converter station and its equipment-level selection scheme. For example, a complete chain can be output: "Sending-end station 1 - PCC3 - DC submarine cable model - DC voltage level - Receiving-end converter station capacity - Converter transformer model - Converter valve submodule model". This avoids the target planning scheme being merely a collection of isolated parameters, improving the feasibility of subsequent topology design, construction design, and equipment procurement.

[0086] In a specific application example, the total installed capacity of the offshore wind power cluster is 2400MW. The location and capacity of the offshore sending-end converter stations are predetermined, and each offshore sending-end converter station transmits power via a single circuit. The receiving-end AC grid adopts the IEEE 118-node system model with DC feeds, selecting six onshore nodes as candidate onshore grid connection points. The candidate DC voltage levels include ±320kV, ±400kV, and ±500kV, while the onshore AC system voltage level is 220kV. The candidate line data includes the DC submarine cable model and the onshore DC overhead line model, and the candidate equipment data includes the converter transformer model, IGBT model, submodule capacitor model, and bridge arm reactor parameters.

[0087] In this application example, the system-level optimization process compares single-receiving-end converter station schemes, dual-receiving-end converter station schemes, and schemes with different DC voltage levels. If a ±320kV single-station or dual-station scheme is used, the line investment is lower, but the minimum DPHSCR may be lower than the stability critical value, indicating that this scheme has insufficient static voltage stability margin. If a ±500kV scheme is used, the DPHSCR is higher, but the line and equipment investment increases significantly. Considering line cost, DPHSCR, and voltage deviations in multiple scenarios, two onshore receiving-end converter stations can be constructed at PCC3 and PCC4, with a ±400kV DC voltage level as the optimal system-level scheme. In this scheme, sending-end station 1 is connected to PCC3, sending-end station 2 is connected to PCC4, and an onshore DC overhead tie line can be set between PCC3 and PCC4. Although setting up the DC tie line between the stations will increase the investment in the line, it will enable the two onshore receiving-end converter stations to have DC power mutual assistance capability, thereby reducing the voltage deviation at the grid connection point under many typical operating scenarios and improving the minimum DPHSCR.

[0088] Regarding equipment-level selection, for a ±400kV dual-receiving-end converter station system, a converter transformer model that meets the capacity and voltage compatibility requirements can be selected from the candidate converter transformers. For example, the ZRDFPZ-400000 / 220 / 400 converter transformer can be chosen. For the power devices of the converter valve submodule, the FZ750R65KE3 IGBT with a withstand voltage of 6.5kV can be selected to ensure that the number of submodules connected in series meets the DC voltage level and voltage safety margin requirements. For the submodule capacitor, the MKKDC16.4mF6.5kV capacitor can be selected to balance submodule cost, energy buffering capacity, and reactive power support requirements. The above models are only examples in one specific implementation. In other implementations, other equipment models with the same capacity, voltage, current, and cost compatibility can be selected from the candidate equipment library.

[0089] In another specific implementation, if the receiving-end AC grid is strong, the electrical distance between candidate grid connection points is small, and the DPHSCR is already significantly higher than the threshold under the single receiving-end converter station scheme, then a single onshore receiving-end converter station scheme can be selected to reduce investment in inter-station DC overhead lines and the number of converter stations required. The advantages of this approach are simple engineering structure and low construction cost, making it suitable for scenarios with a large short-circuit capacity in the receiving-end grid and a relatively small scale of wind power integration. However, when the receiving-end AC grid is weak or the offshore wind power transmission capacity is large, the single receiving-end converter station scheme may lead to concentrated power injection, increasing the pressure on local voltage support.

[0090] In another specific implementation, if the planned area allows for the construction of multiple onshore receiving-end converter stations, and the receiving-end AC grid has multiple strong nodes with access conditions, a distributed access scheme for multiple receiving-end converter stations can be prioritized, and candidate optimization can be performed on the onshore DC overhead interconnection lines between adjacent receiving-end converter stations. This approach can utilize the electrical complementarity between different grid connection points and alleviate the problem of insufficient voltage support at a single grid connection point through DC-side interconnection. Its advantage is that it can reduce grid connection point voltage deviation and improve operational stability in voltage-sensitive scenarios such as high wind power generation and low load periods; its disadvantage is that it increases certain line investment, therefore it needs to be evaluated through both system-level and equipment-level objectives.

[0091] In another specific implementation, for engineering projects with a relatively complete sample library of equipment manufacturers, the equipment-level optimization model can be implemented using a filtering-then-sorting approach. That is, first, based on the capacity, voltage level, and bridge arm current requirements determined by the system-level feasible solutions, equipment combinations that do not meet the requirements for rated capacity, withstand voltage, withstand current, and capacitor candidate values ​​are eliminated; then, the remaining equipment combinations are sorted according to equipment investment cost. This method involves less computation and is suitable for rapid comparison during the engineering design phase. For projects with many candidate equipment models, significant differences in equipment costs, or requiring a refined number of submodules, a mixed integer programming approach can also be used to simultaneously optimize the converter transformer model, IGBT model, number of submodules, submodule capacitor model, and bridge arm reactor model. Its advantage is that it can obtain a more refined optimal combination of equipment costs.

[0092] It should be noted that the DPHSCR threshold, typical operating scenario weight, system-level target weight, equipment-level target weight, voltage safety margin coefficient, current safety margin coefficient, and convergence threshold in this embodiment can all be set according to the grid strength, wind power integration scale, equipment sample library, and planning safety level of the project. As long as it enables the selection of system-level feasible solutions, equipment-level selection, and comprehensive evaluation iteration to be executed according to the above logic, the collaborative optimization planning method described in this embodiment can be realized.

[0093] Through the above implementation methods, this embodiment can not only output the site selection and capacity determination of the onshore receiving-end converter station, DC voltage level and line topology, but also output the equipment-level selection results of converter transformers, converter valve submodule power devices, submodule capacitors and bridge arm reactors that match the system-level scheme. At the same time, through DPHSCR, voltage deviation and power flow verification of multiple typical operating scenarios, schemes with low investment but insufficient static voltage stability margin of the receiving-end AC grid can be eliminated in the planning stage. This enables the offshore wind power cluster multi-terminal flexible DC access system to meet the transmission requirements while improving the voltage support capacity of the receiving-end AC grid and the feasibility of project implementation.

[0094] Example 2: like Figure 2 , Figure 3 , Figure 4 , Figure 5 As shown, this embodiment takes a flexible DC access system for an offshore wind farm cluster with a total installed capacity of 2400MW as an example to illustrate the specific application process and optimization results of the collaborative optimization planning method described in this invention. This offshore wind farm cluster includes multiple offshore wind farms, each transmitting power via an offshore converter station, the location and capacity of which are predetermined. In this embodiment, each offshore converter station uses a single-circuit DC line for transmission, the receiving-end AC grid adopts an IEEE 118-node system model with LCC-HVDC feed, the onshore AC system voltage level is 220kV, and six onshore nodes are selected from the receiving-end AC grid as candidate points of common coupling (PCCs).

[0095] In this embodiment, candidate DC voltage levels include ±320kV, ±400kV, and ±500kV; candidate lines include DC submarine cables and onshore DC overhead lines; candidate equipment includes converter transformers, converter valve submodule power devices, submodule capacitors, and bridge arm reactors. Based on the distance between the offshore sending-end converter station and each candidate onshore grid connection point, the onshore line distance between candidate onshore grid connection points, the unit length cost of the candidate line models, and the maximum transmission capacity, a set of candidate lines required for system-level optimization is formed. Based on the node number, node impedance admittance parameters, voltage level, and operating constraints of the candidate onshore grid connection points, receiving-end AC grid data for calculating DPHSCR indicators and voltage deviations in multiple scenarios is formed. Based on the equipment manufacturer sample library and engineering cost data, candidate converter station equipment data is formed.

[0096] The main input data and optimization results of this embodiment are shown in Table 1 below: Table 1 During the system-level optimization process, calculations were performed for schemes with different DC voltage levels and different numbers of onshore receiving-end converter stations. For each candidate scheme, the investment cost of DC submarine cables, the investment cost of onshore DC overhead lines, the DPHSCR index corresponding to each receiving-end converter station's grid connection point in the receiving-end AC power grid, and the weighted total voltage deviation of the grid connection point under multiple typical operating scenarios were calculated. Typical operating scenarios include peak wind power generation and load, peak wind power generation and load, low wind power generation and load, and low wind power generation and load, with corresponding weighting coefficients set for each operating scenario.

[0097] The comparison results of different system-level solutions are shown in Table 2 below: Table 2 The comparison results above show that the ±320kV scheme has lower submarine cable investment, but the minimum DPHSCR of both Schemes A and B is below the stability critical requirement. This indicates that although this type of scheme has advantages in construction cost, the static voltage stability margin of the receiving-end AC grid is insufficient, making it unsuitable as the target planning scheme. The ±500kV scheme can achieve a higher minimum DPHSCR and relatively low voltage deviation in multiple scenarios, but its submarine cable cost is significantly increased, resulting in poor overall economic efficiency. In contrast, the ±400kV dual onshore receiving-end converter station scheme achieves a better balance between submarine cable cost, minimum DPHSCR, and voltage deviation in multiple scenarios. Therefore, Scheme D is selected as the preferred system-level scheme in this embodiment.

[0098] Based on system-level optimization results, onshore receiving-end converter stations were selected at PCC3 and PCC4 on the land side. Sending-end station 1 is connected to PCC3 via a DC submarine cable, and sending-end station 2 is connected to PCC4 via a DC submarine cable. Both PCC3 and PCC4 are candidate grid connection points that are relatively close to the offshore sending-end converter stations and have the conditions for grid connection. This arrangement can shorten the length of the DC submarine cable and reduce the construction cost of the line. At the same time, the two onshore receiving-end converter stations are distributed and connected to the receiving-end AC grid, which can reduce the local voltage support pressure caused by the concentrated injection of offshore wind power into a single node, thereby improving the operational flexibility and stability margin of the receiving-end AC grid.

[0099] Based on the above ±400kV dual-receiving-end converter station scheme, a further comparison was made regarding whether to install an overhead DC tie line between PCC3 and PCC4. The comparison results are shown in Table 3 below: Table 3 The comparison results show that although setting up an onshore DC overhead interconnection line between PCC3 and PCC4 increases the line investment by 10.5 million yuan, the weighted total voltage deviation across multiple scenarios decreases from 0.132 pu to 0.121 pu, and the minimum DPHSCR increases from 1.15 to 1.36. This indicates that the inter-station DC side interconnection enables a certain degree of power mutual assistance between the two onshore receiving-end converter stations and enhances the coordinated voltage regulation effect between different grid connection points. Under voltage-sensitive conditions such as high offshore wind power generation or low receiving-end load, this interconnection structure can reduce the grid connection point voltage deviation and improve the static voltage stability margin of the receiving-end AC grid.

[0100] During the equipment-level optimization process, the onshore receiving-end converter station capacity, ±400kV DC voltage level, and line topology from the aforementioned system-level feasible solutions are used as inputs to the equipment-level optimization model. The equipment-level optimization model screens and compares the costs of candidate equipment combinations based on constraints such as converter transformer capacity, converter valve submodule voltage, bridge arm current, power device current safety margin, submodule capacitor candidate values, and bridge arm reactor configuration.

[0101] For the converter transformer, the candidate models need to simultaneously meet the 220kV voltage level on the onshore AC side, the ±400kV DC side adaptation requirements, and the corresponding onshore receiving-end converter station capacity requirements. After comparison, the ZRDFPZ-400000 / 220 / 400 converter transformer meets both capacity and voltage adaptation requirements and has a lower overall cost; therefore, it is the preferred converter transformer option in this embodiment.

[0102] For the power devices in the converter valve submodule, the equipment-level optimization model determines the power device models that meet the voltage and current withstand requirements based on the ±400kV DC voltage level, the submodule's rated voltage, the voltage safety margin factor, and the bridge arm current requirements. After comparing candidate combinations, the FZ750R65KE3 IGBT with a voltage withstand rating of 6.5kV reduces the number of submodules connected in series while meeting the rated current safety margin requirements of the power devices. For the submodule capacitor, the MKKDC16.4mF6.5kV capacitor matches the selected IGBT's voltage withstand rating and achieves a better balance between submodule cost and energy buffering capacity. In this embodiment, when the FZ750R65KE3 IGBT is combined with the MKKDC16.4mF6.5kV submodule capacitor, the total number of submodules is 820, which meets the converter valve configuration requirements of the ±400kV system.

[0103] To illustrate the impact of DPHSCR index, multi-scenario voltage deviation, and equipment-level collaborative selection on the target planning scheme in this invention, a scheme that takes into account reactive power support capability is compared with a scheme that only considers cost. The results are shown in Table 4 below: Table 4 The results show that while the cost-only approach reduces the total system investment, its weighted total voltage deviation across multiple scenarios reaches 0.168 pu, and the minimum DPHSCR is only 0.78, which is below the critical requirement for static voltage stability. This indicates that the approach suffers from insufficient voltage stability margin in the receiving-end AC grid. In contrast, although the approach that also considers reactive power support increases investment, it improves the minimum DPHSCR to 1.36 and reduces the weighted total voltage deviation across multiple scenarios to 0.121 pu through decentralized access of onshore receiving-end converter stations, inter-station DC-side interconnection, and coordinated selection of key equipment. This allows the approach to maintain good voltage quality and stability margin under various operating conditions in offshore wind power clusters.

[0104] This embodiment demonstrates that in scenarios involving large-capacity offshore wind power clusters connected to the receiving-end AC grid, determining the planning scheme solely based on line cost or access distance may result in a scheme with lower construction costs but insufficient voltage stability. By incorporating DPHSCR indicators, voltage deviations in multiple typical operating scenarios, line construction costs, and equipment-level investment costs into a collaborative optimization process, schemes with insufficient static voltage stability margins can be eliminated during the planning stage, yielding a complete target planning scheme that includes the site, capacity, DC voltage level, line topology, line type, and key equipment types for the onshore receiving-end converter station. This target planning scheme can provide a basis for engineering planning, topology design, and equipment procurement for multi-terminal flexible DC access systems of offshore wind power clusters.

[0105] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters with reactive power support, characterized in that, Includes the following steps: Obtain the basic dataset for planning; A system-level optimization model is constructed based on the aforementioned planning dataset; Solve the system-level optimization model to select system-level feasible solutions that meet the requirements of converter station configuration, DC voltage level, receiving-end AC grid voltage stability, power flow, and line transmission capacity. The onshore receiving-end converter station capacity, DC voltage level, and line topology in the system-level feasible scheme are used as inputs to construct the equipment-level optimization model. The equipment-level optimization model is then used to select equipment such as converter transformers, converter valve submodule power devices, submodule capacitors, and bridge arm reactors to obtain an equipment-level selection scheme that matches the system-level feasible scheme. A comprehensive evaluation result is formed based on the system-level feasible solution and the equipment-level selection solution, and the system-level feasible solution is iteratively updated based on the comprehensive evaluation result until the convergence condition is met; The scheme that satisfies the convergence condition is output as the target planning scheme.

2. The collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 1, is characterized in that... The planning basic dataset includes data on the sending-end converter stations of offshore wind power clusters, data on the receiving-end AC power grids, data on candidate onshore grid connection points, data on candidate DC voltage levels, data on candidate lines, data on typical operating scenarios, and data on candidate converter station equipment.

3. The collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 2, is characterized in that... The data of the sending-end converter stations includes the location information, rated capacity, transmission power, corresponding offshore wind farm capacity, and DC transmission distance between each offshore sending-end converter station and the candidate onshore grid connection point. The receiving-end AC grid data includes the network topology, node parameters, branch parameters, node voltage levels, node voltage operating limits, node load data, AC line power flow limits, and node impedance admittance parameters used to calculate the voltage stability index of the receiving-end AC grid. The candidate onshore grid connection point data includes a set of candidate onshore grid connection points, the node number of each candidate onshore grid connection point in the receiving-end AC power grid, the grid connection point voltage level, the grid connection point's allowable access capacity, the electrical connection relationship between grid connection points, and the equivalent impedance parameters between grid connection points. The candidate DC voltage level data includes multiple selectable DC voltage levels and the corresponding line transmission capacity, insulation configuration requirements and converter station equipment adaptation requirements for each selectable DC voltage level. The candidate line data includes candidate DC submarine cable data and candidate onshore DC overhead line data. The candidate DC submarine cable data includes the candidate submarine cable model, cost per unit length, maximum transmission capacity, and submarine cable length from the offshore converter station to the candidate onshore grid connection point. The candidate onshore DC overhead line data includes the candidate onshore DC overhead line model, cost per unit length, maximum transmission capacity, and overhead line length between the candidate onshore grid connection points. The typical operating scenario data includes wind power output level, receiving-end AC grid load level, weighting coefficients corresponding to each typical operating scenario, active power output, reactive power output, node load and grid connection voltage reference value under each typical operating scenario. The candidate converter station equipment data includes candidate converter transformer data, candidate converter valve submodule power device data, candidate submodule capacitor data, and candidate bridge arm reactor data. Specifically, the candidate converter transformer data includes the candidate converter transformer model, rated capacity, compatible AC voltage level, compatible DC voltage level, and unit capacity cost. The candidate converter valve submodule power device data includes the candidate power device model, rated voltage, rated current, and cost per power device. The candidate submodule capacitor data includes the candidate submodule capacitor model, capacitance value, rated voltage, and cost per capacitor. The candidate bridge arm reactor data includes the candidate bridge arm reactor model, rated current, reactance parameters, and cost per bridge arm reactor.

4. The collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 1, is characterized in that... The system-level optimization model takes the onshore receiving-end converter station construction scheme, DC voltage level scheme, line topology scheme, and line selection scheme as system-level decision objects, and takes line construction cost, receiving-end AC grid voltage stability index used to characterize reactive power support capability, and voltage deviation at grid connection points in multiple scenarios as system-level evaluation objects.

5. The collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 4, is characterized in that... The system-level optimization model aims to minimize line construction costs, maximize the voltage stability index of the receiving-end AC grid, and minimize the total voltage deviation at the grid connection point under multiple typical operating scenarios. The objective function of the system-level optimization model is expressed as: in, This represents the system-level optimization objective function; This indicates the construction cost of DC submarine cables and onshore DC overhead lines; This represents the minimum value of the hybrid feed-in equivalent short-circuit ratio index corresponding to the grid connection point of each receiving-end converter station in the receiving-end AC power grid. The hybrid feed-in equivalent short-circuit ratio index is determined based on the equivalent impedance, equivalent power, and reactive power boundary function influence term of the flexible DC converter station between the grid connection points of the receiving-end converter stations. This indicates the total voltage deviation at the grid connection point under multiple typical operating scenarios; The construction cost of the line and the total voltage deviation at the grid connection point under the multiple typical operating scenarios are respectively expressed as follows: in, This indicates a collection of offshore power transmission converter stations. This represents the set of candidate onshore grid connection sites; This represents the set of candidate DC submarine cable models; This represents the set of candidate onshore DC overhead line models; Indicates offshore power transmission station With candidate onshore grid connection points Whether to select a model For DC submarine cables, if selected, take 1; otherwise, take 0. Indicates offshore power transmission station With candidate onshore grid connection points The length of the DC submarine cable between them; Model number Cost per unit length of DC submarine cable; Indicating candidate onshore grid connection points With candidate onshore grid connection points Whether to select a model For onshore DC overhead lines, take 1 if selected, otherwise take 0; Indicating candidate onshore grid connection points With candidate onshore grid connection points The length of the onshore DC overhead line between them; Model number Cost per unit length of onshore DC overhead lines; Represents a set of typical operating scenarios; Indicates the first Weighting coefficients for a typical operating scenario; Indicates the first In the first typical operating scenario, the The actual voltage amplitude at each grid connection point; This indicates the reference value for the grid connection point voltage.

6. The collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 5, is characterized in that... The decision variables of the system-level optimization model include the number of onshore receiving-end converter stations, the site selection of onshore receiving-end converter stations, the capacity configuration of onshore receiving-end converter stations, the DC voltage level selection, the DC submarine cable connection between the offshore sending-end converter station and the onshore receiving-end converter station, the onshore DC overhead line connection between candidate onshore grid connection points, the DC submarine cable model selection, and the onshore DC overhead line model selection. The number of onshore receiving-end converter stations, the site of the onshore receiving-end converter station, the capacity of the onshore receiving-end converter station, the DC voltage level, the DC submarine cable connection relationship, the onshore DC overhead line connection relationship, the DC submarine cable model, and the onshore DC overhead line model obtained from the solution are used as the system-level feasible solutions.

7. The collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 5, is characterized in that... The constraints of the system-level optimization model include converter station configuration constraints, DC voltage level constraints, receiving-end AC grid voltage stability constraints, power flow constraints for typical operating scenarios, and line transmission capacity constraints. The converter station configuration constraints and the DC voltage level constraints are expressed as follows: in, This indicates the actual planned number of onshore receiving-end converter stations; Indicates the first If a candidate onshore grid connection site is to be built, an onshore receiving-end converter station is selected; if it is, a value of 1 is selected; otherwise, a value of 0 is selected. This indicates the maximum number of onshore receiving-end converter stations that can be planned. Indicates the first The planned capacity of the onshore receiving-end converter station at each candidate onshore grid connection point; They represent the first The minimum and maximum planarable capacity of the onshore receiving-end converter station at each candidate onshore grid connection point; This indicates the total power transmitted by the offshore power transmission system of the offshore wind power cluster; Represents the set of candidate DC voltage levels; Indicates the first Should the first candidate onshore grid connection site be selected? A candidate DC voltage level is selected; if selected, the value is 1, otherwise the value is 0. Indicates the first The DC voltage levels corresponding to the candidate onshore grid connection points; The receiving-end AC grid voltage stability constraint, typical operating scenario power flow constraint, and line transmission capacity constraint are expressed as follows: in, Indicates the first The equivalent short-circuit ratio index of the hybrid feed-in system is corresponding to the grid connection point of the constructed onshore receiving-end converter station. The equivalent short-circuit ratio index of the hybrid feed-in system is determined based on the equivalent impedance, equivalent power and reactive power of the receiving-end converter station grid connection point and the reactive power boundary function influence term of the flexible DC converter station. This represents the threshold value of the hybrid feed-in equivalent short-circuit ratio for the receiving-end AC grid to meet the static voltage stability requirements. Represents a set of typical operating scenarios; Represents the set of AC power grid nodes at the receiving end; Indicates the first In the first typical operating scenario, the Voltage amplitude at each node; , They represent the first The lower and upper limits of voltage operation for each node; , They represent the first In the first typical operating scenario, the The active and reactive power injected into the receiving-end AC grid by each onshore receiving-end converter station; , They represent the first In the first typical operating scenario, the Active and reactive loads of each node; This represents the set of candidate lines consisting of candidate submarine DC cable lines and candidate overhead DC terrestrial lines. , They represent the first In the first typical operating scenario, the The active and reactive power losses of each line; Indicates the first In the first typical operating scenario, the The active power transmitted by a DC submarine cable line or a land-based DC overhead line; Indicates the first The maximum allowable transmission power of the line under the selected line type and selected DC voltage level; The system-level planning scheme that simultaneously satisfies the converter station configuration constraints, DC voltage level constraints, receiving-end AC grid voltage stability constraints, typical operating scenario power flow constraints, and line transmission capacity constraints is determined as the system-level feasible scheme.

8. The collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 1, is characterized in that... The equipment-level optimization model takes the onshore receiving-end converter station capacity, DC voltage level, and line topology from the aforementioned system-level feasible schemes as input, and aims to minimize the equipment investment cost of the receiving-end converter station. The objective function of the equipment-level optimization model is expressed as: in, This represents the device-level optimization objective function; This indicates the total investment cost of the receiving-end converter station equipment; This represents the set of onshore receiving-end converter stations determined by the system-level feasible schemes. Indicates the first The cost of converter transformers at an onshore receiving-end converter station; Indicates the first Cost of converter valve submodule for an onshore receiving-end converter station; Indicates the first Cost of bridge arm reactors for an onshore receiving-end converter station; Among them, the The equipment cost composition of an onshore receiving-end converter station is expressed as follows: in, Indicates the first The unit capacity cost of the converter transformers selected for each onshore receiving-end converter station; Indicates the first The rated capacity of the converter transformers selected for each onshore receiving-end converter station; Indicates the first The number of converter valve sub-modules in each onshore receiving-end converter station; Indicates the first The individual cost of the power devices in the selected converter valve submodule of an onshore receiving-end converter station; Indicates the first The cost per capacitor in the selected submodule of an onshore receiving-end converter station; Indicates the first The number of bridge arm reactors in each onshore receiving-end converter station; Indicates the first Cost of a single bridge arm reactor selected for an onshore receiving-end converter station; The decision variables of the equipment-level optimization model include the following variables: converter transformer model selection, converter transformer rated capacity selection, converter valve submodule power device model selection, converter valve submodule quantity configuration, submodule capacitor model selection, submodule capacitor value selection, and bridge arm reactor model and quantity configuration for each onshore receiving-end converter station. The converter transformer model and capacity, converter valve submodule power device model, converter valve submodule quantity, submodule capacitor model and capacitance value, and bridge arm reactor model and quantity obtained from the solution for each onshore receiving-end converter station are used as the equipment-level selection schemes that match the system-level feasible scheme.

9. A collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 8, is characterized in that... The constraints of the equipment-level optimization model include converter transformer capacity constraints, converter valve submodule voltage constraints, bridge arm current constraints, converter valve submodule power device current safety margin constraints, submodule capacitor candidate value constraints, and bridge arm reactor configuration constraints. The capacity constraint of the converter transformer and the voltage constraint of the converter valve submodule are expressed as follows: in, This represents the set of onshore receiving-end converter stations determined by the system-level feasible schemes. Indicates the first The rated capacity of the converter transformers selected for each onshore receiving-end converter station; The first feasible solution determined by the system-level feasible solution is... Capacity requirements for each onshore receiving-end converter station; Indicates the first The number of converter valve sub-modules in each onshore receiving-end converter station; Indicates the first The rated voltage of the selected sub-modules in each onshore receiving-end converter station; The first feasible solution determined by the system-level feasible solution is... The DC voltage level of each onshore receiving-end converter station; Indicates the first The rated voltage of the power devices in the selected converter valve submodule of each onshore receiving-end converter station; This represents the voltage safety margin factor; The bridge arm current constraint, the current safety margin constraint of the power device in the converter valve submodule, the candidate value constraint of the submodule capacitor, and the bridge arm reactor configuration constraint are expressed as follows: in, Indicates the first DC side current of an onshore receiving-end converter station; The first feasible solution determined by the system-level feasible solution is... Active power requirements of an onshore receiving-end converter station; Indicates the first AC side current of an onshore receiving-end converter station; Indicates the first The rated AC voltage of each onshore receiving-end converter station; Indicates the first The bridge arm current of an onshore receiving-end converter station; Indicates the first The rated current of the power devices of the selected converter valve submodules in each onshore receiving-end converter station; Indicates the current safety margin factor; Indicates the first The rated current of the selected bridge arm reactors at each onshore receiving-end converter station; Indicates the first The capacitance value of the selected submodule capacitors in each onshore receiving-end converter station; This represents the set of candidate submodule capacitance values; Indicates the first Reactance parameters of the selected bridge arm reactors at each onshore receiving-end converter station; This represents the set of parameters for candidate bridge arm reactors; The equipment selection results that simultaneously meet the constraints of converter transformer capacity, converter valve submodule voltage, bridge arm current, converter valve submodule power device current safety margin, submodule capacitor candidate value, and bridge arm reactor configuration are determined as the equipment-level selection scheme that matches the system-level feasible scheme.

10. The collaborative optimization planning method for a multi-terminal flexible DC access system for offshore wind power clusters oriented towards reactive power support, as described in claim 1, is characterized in that... The process of forming a comprehensive evaluation result based on the system-level feasible solutions and the equipment-level selection solutions, and iteratively updating the system-level feasible solutions based on the comprehensive evaluation results until the convergence condition is met, specifically includes: Obtain the system-level optimization objective function value corresponding to the system-level feasible solution; Obtain the device-level optimization objective function value corresponding to the device-level selection scheme that matches the system-level feasible scheme; The system-level optimization objective function value and the device-level optimization objective function value are used as the corresponding evaluation results of the system-level feasible solution and the device-level selection solution, and the different system-level feasible solutions are ranked according to the corresponding evaluation results; Based on the ranking results, the system-level feasible solution that meets the requirements of AC grid voltage stability, power flow, line transmission capacity, and equipment selection matching at the receiving end is selected as the current preferred solution; The system-level planning scheme for the neighborhood is generated by perturbing at least one of the following system-level variables in the current preferred scheme: site of the onshore receiving-end converter station, capacity of the onshore receiving-end converter station, DC voltage level, DC submarine cable connection relationship, onshore DC overhead line connection relationship, and line type. The system-level optimization solution and equipment-level optimization solution are re-executed for the neighborhood system-level planning scheme to obtain the updated system-level feasible scheme and the matching equipment-level selection scheme, and the corresponding evaluation results are re-formed; When the change in the corresponding evaluation result during continuous iteration is less than the preset convergence threshold, or the number of iterations reaches the preset maximum number of iterations, the convergence condition is determined to be met; otherwise, the system-level feasible solution is iteratively updated based on the corresponding evaluation result.

Images