Equivalent order reduction modeling method and system of offshore wind power flexible direct output system

Abstract

The invention relates to an equivalent reduced-order modeling method of an offshore wind power flexible direct output system. The method comprises the following steps: constructing an equivalent reduced-order model of a wind power plant; constructing an equivalent order reduction model of the modular multilevel converter; constructing a broadband equivalent reduced-order model of the receiving-end power grid; constructing an equivalent order reduction model of the offshore wind power flexible direct output system based on the equivalent order reduction model of the wind power plant, the equivalent order reduction model of the modular multilevel converter and the broadband equivalent order reduction model of the receiving end power grid; according to the method, the wind power plant, the MMC and the receiving-end power grid are subjected to order reduction and integration, the number of overall nodes and elements is reduced in a multiplied mode, the voltage-current transient consistency of grid-connected points is still kept, the CPU calculation amount is remarkably reduced, and a larger-scale fan group can be loaded on an HIL platform at a time.

Description

Technical Field

[0001] The present invention relates to an equivalent order reduction modeling method and system for a flexible DC transmission system for offshore wind power, belonging to the technical field of offshore wind power. Background Art

[0002] Since the flexible DC transmission technology has the ability to provide voltage support to a passive power grid, it has become the preferred solution for long-distance offshore wind power grid connection. After the wind farms are aggregated, they are sent out through the offshore flexible DC system. Both sides of the AC line show the characteristics of a power electronic controlled power supply. Compared with the traditional fan connected to the AC system, the fault characteristics have changed fundamentally, which will greatly affect the performance of traditional protection and pose a threat to the safe operation of wind turbine generators and the flexible DC transmission system.

[0003] During the fault on the sending-end AC side, the wind turbines and the flexible DC system of the wind power through the flexible DC transmission system will be equipped with different fault ride-through control strategies according to the regulations. The various strategies work in coordination to ensure the continuous non-disconnection operation of the flexible DC transmission system and the wind farm. The fault characteristics of the wind power through the flexible DC transmission system are closely related to the coordinated fault ride-through strategies of each converter. However, there are a variety of control strategies used by the converters, and the control parameters are mostly not equal. The combined action and mutual influence of the low voltage ride-through strategies of different converter devices result in characteristics such as phase angle control and amplitude limitation of the short-circuit current provided by the new energy flexible DC transmission system under the fault on the sending-end AC side. Its fault characteristics are significantly different from those of the traditional AC transmission system, making it lack a clear understanding of the fault characteristics of the transmission line of the wind power flexible DC transmission system currently.

[0004] When different types of faults occur in the offshore wind power flexible DC transmission system, the fault characteristics at the machine terminal of the wind turbine mainly include: three-phase voltage, three-phase current, positive sequence, negative sequence, and zero-sequence voltage and current components, phase angle jump, system frequency deviation, broadband oscillation, and the power output of the fan, etc.

[0005] Large-scale far-sea wind farms have significant clustering characteristics. Their typical configuration usually includes dozens of wind turbine generators. When carrying out simulation analysis of multiple control strategies, multiple parameter combinations, and multiple fault scenarios, the hardware-in-the-loop simulation test method is usually adopted. The actual hardware controller is used to control the converter in the system. The actual unit controller under test is exactly the same as the actual unit, which can further improve the consistency and fidelity between the simulation and the actual scenario. However, the use of a conventional full-order model has technical bottlenecks such as high demand for simulation computing resources and significant time consumption for feature extraction and condition traversal. Moreover, large-scale wind farm clusters and their flexible DC transmission systems occupy too much resources, seriously affecting the scale and efficiency of the hardware-in-the-loop (HIL) simulation test system. Summary of the Invention

[0006] To solve the problems existing in the above-mentioned prior art, the present invention proposes an equivalent order reduction modeling method and system for a flexible DC transmission system of offshore wind power.

[0007] The technical solution of the present invention is as follows: In a first aspect, the present invention provides an equivalent order reduction modeling method for a flexible DC transmission system of offshore wind power, including the following steps: Construct an equivalent order reduction model of a wind farm; Construct an equivalent order reduction model of a modular multilevel converter; Construct a broadband equivalent order reduction model of the receiving-end power grid; Based on the equivalent order reduction model of the wind farm, the equivalent order reduction model of the modular multilevel converter, and the broadband equivalent order reduction model of the receiving-end power grid, construct an equivalent order reduction model of the flexible DC transmission system of offshore wind power.

[0008] As a preferred embodiment, the equivalent order reduction model of the wind farm includes an equivalent order reduction model of the wind farm collector line, an equivalent order reduction model of the wind turbine generator set, and an equivalent order reduction model of the transformer at the generator terminal of the wind turbine generator set.

[0009] As a preferred embodiment, the equivalent order reduction model of the wind farm collector line is constructed by using the equal voltage loss method or the equal power loss method.

[0010] As a preferred embodiment, the equivalent order reduction model of the wind farm collector line is modeled as an equivalent impedance model of the wind farm collector line, including: Positive-sequence equivalent impedance model of the wind farm collector line, negative-sequence equivalent impedance model of the wind farm collector line, and zero-sequence equivalent impedance model of the wind farm collector line.

[0011] As a preferred embodiment, the equivalent order reduction model of the wind turbine generator set is constructed by using any one of the single-machine aggregation method, the parameter identification method, and the multi-machine equivalence method.

[0012] As a preferred embodiment, the construction method of the equivalent order reduction model of the transformer at the generator terminal of the wind turbine generator set is: Equivalent all the transformers at the generator terminals of the wind turbine generators in the wind farm to the capacity expansion of a single transformer, and calculate the parameters of the equivalent single transformer, including the capacity and impedance of the equivalent single transformer.

[0013] As a preferred embodiment, the equivalent order reduction model of the modular multilevel converter is constructed based on any one of the half-bridge modular multilevel converter arm average value model or the full-bridge modular multilevel converter arm average value model.

[0014] As a preferred embodiment, the broadband equivalent reduced-order model of the receiving-end power grid is constructed by using the RLC equivalent circuit modeling method based on the full-band equivalent impedance analysis.

[0015] In a second aspect, the present invention also provides an equivalent reduced-order modeling system for a flexible HVDC transmission system of offshore wind power, including: A wind farm model construction module for constructing an equivalent reduced-order model of a wind power farm; A converter model construction module for constructing an equivalent reduced-order model of a modular multilevel converter; A receiving-end power grid model construction module for constructing a broadband equivalent reduced-order model of the receiving-end power grid; An integration module for integrating the equivalent reduced-order model of the wind power farm, the equivalent reduced-order model of the modular multilevel converter, and the broadband equivalent reduced-order model of the receiving-end power grid to construct an equivalent reduced-order model of the flexible HVDC transmission system of offshore wind power.

[0016] In a third aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the program runs on the electronic device, it can implement the equivalent reduced-order modeling method of the flexible HVDC transmission system of offshore wind power as described in any embodiment of the present invention.

[0017] In a fourth aspect, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the equivalent reduced-order modeling method of the flexible HVDC transmission system of offshore wind power as described in any embodiment of the present invention.

[0018] In a fifth aspect, the present invention also provides a method for analyzing the fault characteristics of a flexible HVDC transmission system of offshore wind power, including the following steps: Establish an equivalent reduced-order model of the target flexible HVDC transmission system of offshore wind power by using the equivalent reduced-order modeling method of the flexible HVDC transmission system of offshore wind power as described in any embodiment of the present invention; When a fault occurs in the target flexible HVDC transmission system of offshore wind power, obtain the AC voltage at the fault point in the target flexible HVDC transmission system based on the equivalent reduced-order model of the target flexible HVDC transmission system of offshore wind power; Conduct fault characteristic analysis based on the obtained AC voltage at the fault point.

[0019] As a preferred embodiment, the step of conducting fault characteristic analysis based on the obtained AC voltage at the fault point includes: Obtain the three-phase vector of the AC voltage at the fault point; Delay and rotate the three-phase vector of the AC voltage at the fault point by 90 degrees to obtain an orthogonal virtual phasor; Decoupling operation is performed based on the three-phase vector sum and orthogonal virtual phasor of the AC voltage at the fault point to obtain the positive-sequence, negative-sequence, and zero-sequence components of the AC voltage at the fault point; Fault characteristic analysis is carried out based on the positive-sequence, negative-sequence, and zero-sequence components of the AC voltage at the fault point.

[0020] In a sixth aspect, the present invention further provides a fault characteristic analysis system for a flexible HVDC transmission system of offshore wind farms, characterized by comprising: A modeling module that establishes an equivalent reduced-order model of the target flexible HVDC transmission system of offshore wind farms by using the equivalent reduced-order modeling method of the flexible HVDC transmission system of offshore wind farms according to any embodiment of the present invention; A fault monitoring module for monitoring whether a fault occurs in the target flexible HVDC transmission system of offshore wind farms, and when a fault occurs, obtaining the AC voltage at the fault point in the target flexible HVDC transmission system of offshore wind farms based on the equivalent reduced-order model of the target flexible HVDC transmission system of offshore wind farms; A fault characteristic analysis module that performs fault characteristic analysis based on the obtained AC voltage at the fault point.

[0021] In a seventh aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the program runs on the electronic device, it can implement the fault characteristic analysis method of the flexible HVDC transmission system of offshore wind farms according to any embodiment of the present invention.

[0022] In an eighth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the fault characteristic analysis method of the flexible HVDC transmission system of offshore wind farms according to any embodiment of the present invention.

[0023] On the other hand, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. It is characterized in that when the program runs on the electronic device, it can implement the steps of the method, model, and calculation described in the present invention.

[0024] In yet another aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the method described in the present invention.

[0025] The present invention has the following beneficial effects: 1. By reducing the order and integrating the wind farm, MMC, and receiving-end power grid respectively, the present invention significantly reduces the number of overall nodes and components by several times, still maintains the transient consistency of the grid-connected point voltage-current, significantly reduces the CPU operation amount, and enables the HIL platform to load a larger-scale wind turbine group at one time.

[0026] 2. The present invention subdivides a wind farm into three equivalent sub-models: a collector line, a wind turbine body, and a generator terminal transformer. Any sub-module can be flexibly replaced on the premise of ensuring the authenticity of internal electromagnetic coupling, realizing rapid reconstruction and comparative analysis for different wind farm layouts.

[0027] 3. The present invention uses the "equal voltage loss / equal power loss" method to equivalent the impedance of the collector line, making the simplified line fully match the original network in terms of two indicators: power flow and loss. This not only avoids voltage drop distortion but also eliminates energy balance errors.

[0028] 4. After the present invention performs positive-negative-zero sequence impedance separation modeling, the reduced-order model can still accurately reproduce the sequence component characteristics during asymmetrical faults such as single-phase grounding and two-phase short circuits, providing a high-fidelity basis for relay protection coordination and resonance analysis.

[0029] 5. The present invention adaptively selects the wind turbine equivalent strategy through the single-machine aggregation method / parameter identification method / multi-machine aggregation method, and can synchronously retain the cluster inertia and control dynamics with the least state variables, ensuring small-signal stability and the accuracy of oscillation mode evaluation.

[0030] 6. The present invention expands all generator terminal step-up transformers into one equivalent transformer and calculates the unified impedance, which not only simplifies the topology but also makes the equivalent short-circuit capacity and leakage reactance ratio consistent with the actual field, facilitating impedance-frequency scanning and inrush current research.

[0031] 7. Based on the bridge arm average value model, the present invention can reproduce the modulation, blocking, and freewheeling behaviors of the half-bridge / full-bridge MMC with only a small number of controlled sources, and can increase the simulation step size to the millisecond level while maintaining waveform accuracy, significantly accelerating transient calculations.

[0032] 8. The present invention fits the full-frequency band impedance of the receiving-end power grid into a multi-order RLC transfer function model, which can quickly switch between weak grid and strong grid scenarios while retaining the resonance peak position, providing an adjustable parameter platform for wide-frequency oscillation suppression design.

[0033] 9. The present invention proposes a method for analyzing the fault characteristics of a flexible DC transmission system for offshore wind power. By using the 90° delay rotation orthogonal projection algorithm, the positive, negative, and zero sequence components are instantaneously separated from the three-phase voltage. The calculation amount is reduced by about 60% compared with the traditional synchronous double dq transformation, and at the same time, the inter-sequence coupling problem caused by frequency drift is avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a schematic diagram of the wind farm modeling before equivalent order reduction; Figure 2 is a schematic diagram of the wind farm modeling after equivalent order reduction; Figure 3 is a schematic diagram of the comparison of voltage waveforms at the grid connection point of the wind farm modeling before and after equivalent order reduction; Figure 4 Schematic diagram for comparing the port voltage waveforms of the terminal wind turbines in the wind farm model before and after equivalent order reduction; Figure 5 Topological diagram of the improved average value model of the half-bridge MMC arm; Figure 6 Schematic diagram of the current flow direction after the improved average value model of the half-bridge MMC arm is blocked; Figure 7 Control flow chart of the improved average value model of the half-bridge MMC arm; Figure 8 Topological diagram of the improved average value model of the full-bridge MMC arm; Figure 9 Schematic diagram of the current flow direction after the improved average value model of the full-bridge MMC arm is blocked; Figure 10 Flow chart of the wide-frequency equivalent modeling of the receiving-end power grid; Figure 11 Vector schematic diagram of positive sequence, negative sequence, and zero sequence components; Figure 12 Schematic diagram of the projection relationship between positive sequence and negative sequence components. Specific implementation manners

[0035] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0036] It should be understood that the step numbers used in the text are only for convenient description and do not limit the execution order of the steps.

[0037] It should be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0038] The terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0039] The term " / and / " refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0040] The flexible DC transmission system for offshore wind power mainly consists of an offshore wind farm, a modular multilevel converter (MMC) converter station, and a receiving-end power grid. Using the traditional full-order model has technical bottlenecks such as high requirements for simulation computing resources, significant time consumption for feature extraction and condition traversal, etc. However, large-scale wind farm clusters and their flexible DC transmission systems occupy too much resources, seriously affecting the scale and efficiency of the hardware-in-the-loop (HIL) simulation test system. Compared with the traditional full-order modeling method, the embodiment of this application proposes an equivalent reduced-order modeling method for the flexible DC transmission system of offshore wind power to ensure that the established model can significantly improve the simulation speed, reduce the consumption of simulation computing resources, be compatible with offline simulation and HIL real-time simulation platforms, coincide with actual engineering parameters, meet the test requirements of the IEC 61400 series standards, and provide an accurate model for the simulation analysis of offshore wind turbines. The method specifically includes the following steps: S100. Construct an equivalent reduced-order model of the wind farm; replace a complex large-scale wind farm containing dozens to hundreds of wind turbines with a small number of equivalent units (such as a single or multiple equivalent wind turbines and their equivalent collector networks). The core is to significantly reduce the computational complexity of the grid connection simulation of large-scale wind turbines on the premise of ensuring simulation accuracy (such as power flow distribution, fault characteristics, or dynamic response).

[0041] S200. Construct an equivalent reduced-order model of the modular multilevel converter; S300. Construct a broadband equivalent reduced-order model of the receiving-end power grid; S400. Based on the equivalent reduced-order model of the wind farm, the equivalent reduced-order model of the modular multilevel converter, and the broadband equivalent reduced-order model of the receiving-end power grid, construct an equivalent reduced-order model of the flexible DC transmission system for offshore wind power.

[0042] The equivalent reduced-order model of the flexible DC transmission system for offshore wind power constructed based on the embodiment of this application can effectively reduce the complexity of the system model and improve the modeling efficiency. The equivalent reduced-order model of the flexible DC transmission system for offshore wind power constructed based on the equivalent reduced-order models of these three parts, namely the wind farm, the modular multilevel converter, and the receiving-end power grid, can be used for subsequent performance analysis, fault diagnosis, etc. of the flexible DC transmission system for offshore wind power. In some embodiments, step S100 specifically includes: S101. Construct an equivalent reduced-order model of the collector line of the wind farm; S102. The equivalent reduced-order model of the wind turbine; S103. The equivalent reduced-order model of the generator-side transformer of the wind turbine.

[0043] For step S101: The collector line of a wind farm usually contains many branches. To simplify the system analysis model, an equivalent method is often used to simplify the complex radial or loop collector network into one or a few equivalent lines.

[0044] In some embodiments, an equivalent reduced-order model of the collector line of a wind farm can be constructed by using the equal voltage loss method or the equal power loss method.

[0045] Specifically, the equal voltage loss method means: keeping the voltage loss at the end of the collector line (usually the fan access point) the same before and after equivalence. By adjusting the impedance parameters (mainly reactance) of the equivalent line, under the condition of the same total output current or power, the voltage drop at the end of the equivalent line relative to the head end is made equal to the voltage drops at all fan access points in the original complex network.

[0046] The equal power loss method: keeping the total active power loss on the collector line the same before and after equivalence. By adjusting the resistance parameters of the equivalent line, under the condition of the same total output current or power, the total copper loss on the equivalent line is made equal to the sum of the copper losses of all branches in the original complex network.

[0047] In a specific embodiment, to help those skilled in the art quickly understand the technical principle of this application, taking the equal voltage loss method as an example, the construction of the equivalent reduced-order model of the collector line of a wind farm is as follows. The specific steps include: Construct an equivalent impedance model of the collector line of a wind farm, including a positive-sequence equivalent impedance model of the collector line of a wind farm, a negative-sequence equivalent impedance model of the collector line of a wind farm, and a zero-sequence equivalent impedance model of the collector line of a wind farm; After the collector line of the wind farm is equivalent to the corresponding positive-sequence, negative-sequence, and zero-sequence equivalent impedances through the above impedance model, an equivalent reduced-order modeling of the wind farm is carried out.

[0048] Specifically, for constructing the positive-sequence equivalent impedance model of the collector line of a wind farm, the specific steps for calculating the positive-sequence equivalent impedance of the collector line of a wind farm are as follows: Calculate the voltage difference between the terminal voltage of each wind turbine in the wind farm and the grid connection point voltage of the HVDC flexible transmission system for offshore wind power, as shown in the following formula: ; Where: represents the voltage difference between the terminal of the th wind turbine in the wind farm and the grid connection point of the HVDC flexible transmission system for offshore wind power; represents the impedance value of the line corresponding to the terminal of the th wind turbine in the wind farm; represents the total number of wind turbines in the wind farm; represents the active power of the th wind turbine in the wind farm; represents the voltage value at the grid connection point of the offshore HVDC transmission system for wind power; Calculate the total voltage loss of the wind farm based on the voltage difference between the terminals of each wind turbine and the grid connection point of the offshore HVDC transmission system for wind power, as shown in the following formula: ; where: represents the total voltage loss of the wind farm; represents the active power of the th wind turbine in the wind farm; Calculate the positive-sequence equivalent impedance of the wind farm collector line based on the total voltage loss of the wind farm, as shown in the following formula: ; where: represents the positive-sequence equivalent impedance of the wind farm collector line.

[0049] In a specific embodiment, assume that there are 5 wind turbines in the wind farm. Then the calculation steps for the positive-sequence equivalent impedance of the wind farm collector line are as follows: Calculate the voltage difference between the terminals of each wind turbine in the wind farm and the grid connection point of the offshore HVDC transmission system for wind power, as shown in the following formula: ; Calculate the total voltage loss of the wind farm based on the voltage difference between the terminals of each wind turbine and the grid connection point of the offshore HVDC transmission system for wind power, as shown in the following formula: ; where: represents the total voltage loss of the wind farm; represents the active power of the th wind turbine in the wind farm; Calculate the positive-sequence equivalent impedance of the wind farm collector line based on the total voltage loss of the wind farm, as shown in the following formula: ; where: represents the positive-sequence equivalent impedance of the wind farm collector line; In the above equivalent calculations, only resistive and inductive parameters are considered, capacitive parameters are calculated separately, voltage differences within the wind farm are ignored, and the capacitance value after equivalence is equal to the sum of the capacitance values of all lines before equivalence. At this time, the resistance effect is no longer considered repeatedly.

[0050] Since the collector line is a static component and the positive and negative sequence parameters of its resistance and reactance are the same, the negative sequence equivalent impedance model of the collector line of the wind farm is the same as the positive sequence equivalent impedance model of the collector line of the wind farm. However, under the action of the negative sequence current suppression module in the converter control, the negative sequence current component on the AC side of the grid-side converter is zero when a fault occurs. At this time, the negative sequence equivalent impedance of the collector line of the wind farm is infinite; Specifically, the steps for constructing the negative sequence equivalent impedance model of the collector line of the wind farm and calculating the negative sequence equivalent impedance of the collector line of the wind farm are as follows: Calculate the voltage difference between the machine terminals of each wind turbine in the wind farm and the grid connection point of the offshore HVDC transmission system, as shown in the following formula: ; Where: represents the voltage difference between the machine terminal of the th wind turbine in the wind farm and the grid connection point of the offshore HVDC transmission system; represents the impedance value of the line corresponding to the machine terminal of the th wind turbine in the wind farm; represents the total number of wind turbines in the wind farm; represents the active power of the th wind turbine in the wind farm; represents the voltage value of the grid connection point of the offshore HVDC transmission system.

[0051] Calculate the total voltage loss of the wind farm based on the voltage difference between the machine terminals of each wind turbine and the grid connection point of the offshore HVDC transmission system, as shown in the following formula: ; Where: represents the total voltage loss of the wind farm; represents the active power of the th wind turbine in the wind farm.

[0052] Calculate the negative sequence equivalent impedance of the collector line of the wind farm based on the total voltage loss of the wind farm, as shown in the following formula: ; Where: represents the negative sequence equivalent impedance of the collector line of the wind farm.

[0053] Specifically, the steps for constructing the zero sequence equivalent impedance model of the collector line of the wind farm and calculating the zero sequence equivalent impedance of the collector line of the wind farm are as follows: Calculate the fundamental zero-sequence components of the terminal voltage phasor and current phasor of each wind turbine in the wind farm, and calculate the active power of the fundamental zero-sequence component based on the fundamental zero-sequence components of the voltage phasor and current phasor, as shown in the following formula: ; Where: represents the active power of the fundamental zero-sequence component at the terminal of the th wind turbine; represents the real part of the impedance of the fundamental zero-sequence component of the terminal voltage phasor of the th wind turbine; represents the real part of the impedance of the fundamental zero-sequence component of the terminal current phasor of the th wind turbine; represents the imaginary part of the impedance of the fundamental zero-sequence component of the terminal voltage phasor of the th wind turbine; represents the imaginary part of the impedance of the fundamental zero-sequence component of the terminal current phasor of the th wind turbine.

[0054] Calculate the effective value of the phase voltage of the fundamental zero-sequence component based on the fundamental zero-sequence component of the voltage phasor, as shown in the following formula: ; Where: represents the effective value of the phase voltage of the fundamental zero-sequence component at the terminal of the th wind turbine.

[0055] Calculate the zero-sequence equivalent impedance of the collector line of the wind farm according to the active power and the effective value of the phase voltage of the fundamental zero-sequence component at the terminal of each wind turbine, as shown in the following formula: ; Where: represents the zero-sequence equivalent impedance of the collector line of the wind farm; represents the fundamental zero-sequence component of the voltage phasor at the grid connection point of the HVDC transmission system for offshore wind power; represents the active power of the fundamental zero-sequence component at the terminal of the th wind turbine in the wind farm; represents the voltage difference between the effective value of the phase voltage of the fundamental zero-sequence component at the terminal of the th wind turbine in the wind farm and .

[0056] For step S102: The dynamic equivalent method of wind turbines is a key research object that has received extensive attention currently.

[0057] In some embodiments, for the equivalent reduced-order model of a wind turbine generator set, any one of the single-machine aggregation method, parameter identification method, and multi-machine equivalence method is used for construction.

[0058] In a specific embodiment, the equivalent reduced-order model of a wind turbine generator set is constructed by using the single-machine aggregation method based on capacity weighted average. The specific steps include: The wind farm composed of wind turbine generator sets of the same model, capacity, and similar control parameters is equivalently regarded as the expansion of a single wind turbine generator set (reference [1]).

[0059] The capacity of the single unit after expansion is the same as the overall capacity of the wind farm. The weight of each unit is obtained by calculating the ratio of the capacity of each wind turbine generator set to the total capacity of the wind farm.

[0060] The parameters of the equivalent wind turbine generator set are determined according to the weighted average value of all wind turbine generator set parameters (reference [2]). Taking the doubly-fed wind turbine as an example, reference [3] provides a method for equivalent reduced-order modeling of wind turbine generator sets by using the single-machine aggregation method based on capacity weighted average; It can be seen from the above analysis that the capacity weighted average method calculates the physical parameters of the equivalent wind turbine generator set according to the capacity weight, and the calculation process is simple, which is more suitable for the study of the steady-state output of the wind farm.

[0061] In a specific embodiment, the equivalent reduced-order model of a wind turbine generator set is constructed by using the simplified model parameter identification method that matches the dynamic response. Specifically: The parameter identification method regards the equivalent wind farm (selecting one wind turbine generator set for expansion) as a gray-box model, but some parameters are unknown. The parameters of the equivalent wind field in the gray-box model are identified by comparing the measured data or simulation data at the grid connection point of the equivalent wind farm and the original wind farm (references [4-5]).

[0062] The process of parameter identification is essentially an optimization problem. The optimization objective is that the dynamic response variance of the equivalent wind field and the original wind field at the grid connection point within a certain time is the smallest, and the quantity to be solved is the physical parameters of the equivalent wind turbine generator set. Nonlinear calculations and the solution of differential equations are involved in the optimization process, and generally, intelligent optimization algorithms are required (reference [6]).

[0063] In a specific embodiment, the equivalent reduced-order model of a wind turbine generator set is constructed by using the multi-machine equivalence method based on the characteristics or operating status clustering of wind turbine generator sets. Specifically: Multi-machine equivalence mainly includes two steps: clustering and equivalent parameter calculation.

[0064] Regarding the research on the clustering method, References [7-8] proposed to divide the wind turbine group according to the wind speed, wake effect influence factor, etc. Reference [9] used the multi-scale entropy of active power, reactive power, voltage and current as the clustering index, and further combined with the multi-perspective transfer fuzzy C-means algorithm to achieve clustering. Reference

[10] proposed to use the wind turbine operating state variables after dimensionality reduction by the principal component analysis method as the clustering index. References [11-12] started from the similarity of the dynamic response trajectories of wind turbines for clustering, and used the short-circuit current envelope trajectory and active power time series data as the clustering index respectively.

[0065] In terms of equivalent parameter calculation, the existing research often uses the capacity weighting method (Reference

[13] ). Reference

[14] used an improved genetic learning particle swarm hybrid algorithm to identify the parameters of the single-machine equivalent model of a direct-drive wind farm. Reference

[15] proposed a classification and key identification strategy for the double-fed wind farm model with different control strategies.

[0066] For step S103, in some embodiments, the machine-side transformers of all wind turbines in the wind farm are equivalent to the capacity expansion of a single transformer, and the parameters of the equivalent single transformer are calculated, including the capacity and impedance of the equivalent single transformer.

[0067] In a specific embodiment, the specific steps of the equivalent order reduction modeling of the machine-side transformer of the wind turbine are as follows: The machine-side transformers of all wind turbines in the wind farm are equivalent to the capacity expansion of a single transformer, and the parameters of the equivalent single transformer are calculated. The parameters include the capacity and impedance of the equivalent single transformer, and the specific calculation formulas are: ; ; Among them, and are the capacity and impedance of the equivalent single transformer respectively; and are the capacity and impedance of the th wind turbine in the wind farm respectively.

[0068] Figure 1 and Figure 2 are example models built based on MATLAB / Simulink, which respectively represent the voltage comparison at the point of common coupling PCC of the wind farm modeling before and after equivalent order reduction. As Figure 3 shown, V2 and V5 represent the port voltages of the end wind turbines before and after equivalent order reduction respectively, and their comparison waveforms are as Figure 4As shown, it can be seen that within the allowable error range, this equivalent method is effective and feasible. To verify the accuracy of the model, the same simulation system was built on PSCAD, and the equivalent comparison results were consistent with those of Simulink. The equivalent order reduction modeling of the wind farm in this embodiment can significantly reduce the simulation calculation amount, significantly reduce the simulation resources without reducing the simulation accuracy, and improve the simulation efficiency.

[0069] In some embodiments, the equivalent order reduction model of the modular multilevel converter in S200 is constructed based on either the half-bridge modular multilevel converter arm average value model or the full-bridge modular multilevel converter arm average value model.

[0070] In a specific embodiment, constructing the equivalent order reduction model of the modular multilevel converter based on the half-bridge modular multilevel converter arm average value model is specifically as follows: See Figure 5 , in the AC side equivalent circuit of the half-bridge modular multilevel converter arm average value model, a equivalent resistor is connected in series with the controlled voltage source, and three controllable unidirectional conductive power electronic devices are added at the shown position to connect the DC side equivalent loop, which is used to equivalent the IGBT anti-parallel diode in the MMC arm blocking state. The specific construction steps are as follows: The controlled voltage source in the AC side equivalent circuit of the original modular multilevel converter arm average value model The negative pole is connected to one end of the equivalent resistor ; The positive pole of the controlled voltage source is connected to the input terminal of the controllable unidirectional conductive power electronic device , the output terminal of the controllable unidirectional conductive power electronic device is connected to one end of the arm equivalent capacitor ; The other end of the arm equivalent capacitor is connected to the input terminal of the controllable unidirectional conductive power electronic device , the output terminal of the controllable unidirectional conductive power electronic device is connected to the other end of the equivalent resistor ; The output terminal of the controllable unidirectional conductive power electronic device is connected to the input terminal of the controllable unidirectional conductive power electronic device , the output terminal of the controllable unidirectional conductive power electronic device is connected to the input terminal of the controllable unidirectional conductive power electronic device ; The arm equivalent capacitor It is obtained by simplifying the equivalent relationship of the series sub-module capacitors of the MMC, representing the average value of the capacitor characteristics of the entire bridge arm, and taking the value of the total equivalent capacitance , represents the total number of sub-modules; It is an equivalent current source reflecting the dynamic of the bridge arm capacitor current, and its value is related to the ratio of the conducting sub-modules and the bridge arm current; In the normal operation state, the controlled voltage source is calculated from the capacitor voltage of the DC side accompanying circuit and the number of conducting sub-modules from the modulation module. At the same time, the equivalent resistance is set to the on-resistance of the switch (approximately 0), and the current of the controlled current source of the accompanying circuit is calculated from the bridge arm current and the number of conducting sub-modules; In the blocked state, the controller sets the number of conducting sub-modules to 0, and the equivalent resistance is set to the off-resistance of the switch (MΩ level). At the same time, continuous conduction signals are given to the three controllable unidirectional conductive power electronic devices , , At this time, the voltage of the controlled voltage source and the current of the controlled current source are both calculated to be 0, and the bridge arm current can flow through the controllable unidirectional conductive power electronic devices , , and the equivalent resistance to realize the freewheeling process to simulate the transient process of the MMC bridge arm detailed model after blocking; Since the direction of the current flowing into the sub-module is uncertain when the MMC is blocked, this leads to an uncertain current loop in the improved half-bridge modular multilevel converter bridge arm average value model. There are two cases in total. If the current flowing into the sub-module at the blocking moment is greater than zero, then the current flows as shown in Figure 6 (a). During the blocked period, the current will charge the capacitor through the upper and lower controllable unidirectional conductive power electronic devices; if the current flowing into the sub-module at the blocking moment is less than zero, the current will freewheel through the middle controllable unidirectional conductive power electronic device, and the current flow direction is as shown in 6(b), where represents the switch current of the th phase bridge arm.

[0071] In a specific embodiment, referring to Figure 7 , the overall control flow of the equivalent reduced-order model of the modular multilevel converter constructed based on the half-bridge modular multilevel converter bridge arm average value model is as follows: Step 1, initialize the data and detect whether the MMC is operating normally; Step 2, if the MMC is operating normally, then control the controllable unidirectional conductive power electronic device , , Turn off, the equivalent resistance of the arm is 0, calculate the number of conducting sub-modules in each arm and the equivalent controlled voltage source and current source. If the MMC operates abnormally, send a blocking signal to control the controllable unidirectional conducting power electronic device , , Conduct, the equivalent resistance of the arm is infinite, calculate the equivalent conduction resistance of the anti-parallel diode and the equivalent controlled voltage source and current source; Step 3: Solve the system network equation through the electromagnetic transient simulation program according to the data obtained in Step 2; Step 4: Judge whether the MMC operates normally at the next moment according to the solution of the network equation, and repeat Steps 1 to 3 until the simulation ends.

[0072] In a specific embodiment, an equivalent reduced-order model of the modular multilevel converter is constructed based on the arm average value model of the half-bridge modular multilevel converter, specifically: Refer to Figure 8 , in the equivalent circuit on the AC side of the full-bridge modular multilevel converter arm average value model, connect an equivalent resistance in series with the controlled voltage source, and add four controllable unidirectional conducting power electronic devices at the positions shown in the figure to connect the equivalent loop on the DC side, which is used to equivalent the IGBT anti-parallel diode in the locked state of the full-bridge MMC arm. The specific construction steps are as follows: Connect the negative pole of the controlled voltage source in the equivalent circuit on the AC side of the original modular multilevel converter arm average value model to one end of the equivalent resistance ; Connect the positive pole of the controlled voltage source to the input end of the controllable unidirectional conducting power electronic device and the output end of the controllable unidirectional conducting power electronic device respectively; Connect the output end of the controllable unidirectional conducting power electronic device to one end of the arm equivalent capacitor and the output end of the controllable unidirectional conducting power electronic device respectively; Connect the input end of the controllable unidirectional conducting power electronic device to the other end of the arm equivalent capacitor and the input end of the controllable unidirectional conducting power electronic device respectively. Connect the output end of the controllable unidirectional conducting power electronic device to the input end of the controllable unidirectional conducting power electronic device and the other end of the equivalent resistance respectively; Under the normal operating state of the full-bridge MMC, all controllable unidirectional-conducting power electronic devices will remain in the off state, there is no connection between the capacitor circuit and the arm circuit, and the equivalent resistance has a value of zero. At this time, the average value model of the arm of the improved full-bridge modular multilevel converter is exactly the same as the traditional model in function; when the full-bridge MMC switches to the locked state, all controllable unidirectional-conducting power electronic devices will conduct, and the capacitor circuit and the arm circuit are connected through the corresponding controllable unidirectional-conducting power electronic devices, and the equivalent resistance is set to infinity, and the voltage of the controlled voltage source and the current of the controlled current source are controlled to zero, which is equivalent to inserting zero sub-modules in the traditional model. In the locked state, the actual current flow direction in the average value model of the arm of the improved full-bridge modular multilevel converter is as Figure 9 shown. When the arm current direction is from bottom to top, as Figure 9 (a) shows, the equivalent capacitor of the arm is charged through the controllable unidirectional-conducting power electronic devices and ; when the arm current direction is from top to bottom, as Figure 9 (b) shows, the equivalent capacitor of the arm is charged through and ; The full-bridge type is slightly less economical than the half-bridge type, but it can isolate DC faults without an additional DC circuit breaker; Through the above improvements and control strategies, the improved arm average value model proposed by the present invention for the MMC flexible DC can accurately reflect the locking process characteristics of the flexible DC under disturbances, and realizes the accurate extraction of fault characteristics.

[0073] In some embodiments, the wide-frequency equivalent reduced-order model of the receiving-end power grid in S300 is constructed by using the RLC equivalent circuit modeling method based on the full-frequency band equivalent impedance analysis.

[0074] In a specific embodiment, the wide-frequency equivalent reduced-order modeling of the receiving-end power grid of the offshore wind power flexible DC transmission system is carried out by using the RLC equivalent circuit modeling method based on the full-frequency band equivalent impedance analysis. Specifically: Collect the full-frequency band equivalent impedance (DQ axis) of the receiving-end power grid, and perform averaging processing on the full-frequency band equivalent impedance and extract the equivalent impedance of the single-input single-output (SISO) of the receiving-end power grid and the corresponding resonance frequency; Intercept the equivalent impedance of the single-input single-output and the corresponding resonance frequency within the preset frequency band width and fit them into a multi-order transfer function, and optimize the parameters of the multi-order transfer function through an optimization algorithm (such as the least squares method, genetic algorithm, etc.) until the fitting accuracy of the multi-order transfer function reaches the preset fitting accuracy threshold and then stop the optimization to obtain a successfully fitted multi-order transfer function; Optionally, the equivalent impedance of a single-input single-output and its corresponding resonant frequency are fitted by a direct impedance fitting method; After extracting the parameters of the RLC components (resistance R, inductance L, capacitance C) in the RLC circuit from the denominator coefficients and numerator coefficients of the successfully fitted multi-order transfer function respectively, a corresponding RLC equivalent circuit is constructed; Generally, by analyzing the pole and zero formulas of the transfer function, the corresponding resistance R, inductance L, and capacitance C of each order are deduced and combined in series or parallel with an ideal voltage source to form a broadband equivalent reduced-order modeling of the receiving-end power grid; The obtained RLC circuit presents an equivalent short-circuit capacity (reflected by the real part of the equivalent impedance) at power frequency and reproduces the resonance characteristics of the power grid at high frequencies. Therefore, it is more accurate than a simple ideal voltage source + fixed impedance model. By adjusting the parameters of the RLC components, the situations of a weak power grid (large impedance, low short-circuit ratio) or a strong power grid (small impedance, high short-circuit ratio) can be conveniently simulated.

[0075] When the dynamic characteristics of the receiving-end power grid are relatively complex, including multiple resonant frequencies and dynamic processes with different time constants, the multi-order transfer function can more accurately describe the full-frequency characteristics of the system. In some occasions with high requirements for computational complexity or only requiring a preliminary analysis and design of the main dynamic characteristics of the system, reducing the multi-order transfer function to a second-order transfer function can greatly simplify the calculation process and improve the analysis efficiency.

[0076] In a specific embodiment, the equivalent reduced-order modeling of the receiving-end power grid of the HVDC transmission system for offshore wind power is carried out by the ideal power grid equivalent method, specifically: The receiving-end power grid is equivalent to an ideal voltage source and an infinite bus, ignoring the impedance and dynamic characteristics inside the power grid.

[0077] In a specific embodiment, the equivalent reduced-order modeling of the receiving-end power grid of the HVDC transmission system for offshore wind power is carried out by the RL power grid equivalent method (equivalent based on the short-circuit ratio), specifically: According to the short-circuit ratio of the receiving-end power grid, the receiving-end power grid is equivalent to a resistor or an inductor.

[0078] The embodiment of the present application also proposes an equivalent reduced-order modeling system for the HVDC transmission system for offshore wind power, which is constructed based on the equivalent reduced-order modeling method for the HVDC transmission system for offshore wind power proposed in the embodiment of the present invention. The equivalent reduced-order modeling system for the HVDC transmission system for offshore wind power includes: A wind farm model construction module for constructing an equivalent reduced-order model of a wind farm; A converter model construction module for constructing an equivalent reduced-order model of a modular multilevel converter; A receiving-end power grid model building module is used to build a broadband equivalent reduced-order model of the receiving-end power grid; The integrated module is used to integrate the equivalent reduced-order model of the wind farm, the equivalent reduced-order model of the modular multilevel converter and the broadband equivalent reduced-order model of the receiving power grid to construct an equivalent reduced-order model of the offshore wind power flexible direct current transmission system.

[0079] In the offshore wind power flexible direct current transmission system, the accurate separation and solution of the positive sequence, negative sequence and zero sequence components of each electrical quantity is crucial for the analysis and control of system fault characteristics. Affected by factors such as the nonlinearity of the zero sequence path caused by the frequency-variable parameters of the submarine cable, the transient overcurrent of the converter under the bipolar short circuit fault, and the background harmonic interference of the weak power grid and wind farm, it is necessary to adopt a reasonable and effective method for separating the sequence components to accurately obtain the phase and amplitude characteristics of the transient sequence components of the fault, and provide key data support for relay protection setting, fault ride-through control, oscillation suppression strategy and accurate simulation of test conditions.

[0080] The zero-sequence component is directly calculated by the algebraic sum of the three-phase quantities in the three-phase four-wire system. It is always zero in the three-phase three-wire system, so the zero-sequence is usually processed independently, and the separate solution of the positive-sequence and negative-sequence components becomes the key and difficulty.

[0081] The traditional symmetrical component method is based on the assumption of a linear time-invariant system. It decouples the three-phase asymmetric quantity into mutually orthogonal positive-sequence, negative-sequence, and zero-sequence components through a complex transformation matrix. The core of the method is to construct an orthogonal rotating basis vector based on the power frequency fundamental wave to achieve frequency domain decoupling. This method has significant limitations in the offshore wind power flexible direct current grid-connected system. The transient process caused by the modular multilevel converter under a bipolar short-circuit fault has strong nonlinear and time-varying characteristics, which destroys the applicable conditions of the linear superposition principle.

[0082] The traditional symmetrical component method is based on the assumption of a linear time-invariant system. It decouples the three-phase asymmetric quantity into mutually orthogonal positive-sequence, negative-sequence, and zero-sequence components through a complex transformation matrix. The core of the method is to construct an orthogonal rotating basis vector based on the power frequency fundamental wave to achieve frequency domain decoupling. This method has significant limitations in the offshore wind power flexible direct current grid-connected system. The transient process caused by the modular multilevel converter under a bipolar short-circuit fault has strong nonlinear and time-varying characteristics, which destroys the applicable conditions of the linear superposition principle.

[0083] The transformation first projects the three-phase quantity into a stationary orthogonal coordinate system to decouple and obtain the zero-sequence component, and then converts the fundamental positive / negative sequence components into DC quantities through positive / negative synchronous rotating dq transformation to achieve separation. This combined method has essential defects in the offshore wind power flexible DC system. The double dq transformation structure causes positive and negative sequence cross-coupling oscillation due to rotation angle mismatch when the grid frequency fluctuates, and The transformation lacks the ability to suppress the high - order harmonics introduced by the converter switches, resulting in spectrum pollution of the sequence components. More critically, the frequency - varying parameters of the submarine cable make the zero - sequence path exhibit non - linear impedance characteristics, invalidating the zero - sequence decoupling assumption in the stationary coordinate system. The combined transformation cannot characterize its dynamic coupling mechanism, and amplitude - phase calculation deviation will occur during bipolar faults, seriously affecting the reliability of transient protection.

[0084] The discrete Fourier transform extracts the amplitude - phase information of the fundamental positive - sequence, negative - sequence, and zero - sequence components through the spectral analysis of the time - domain sampling sequence. Its essence is to use orthogonal basis vectors to project the signal in the frequency domain to achieve decoupling. This method has fundamental defects in the MMC - based HVDC grid - connected system of offshore wind power. The requirement of full - cycle sampling leads to a dynamic response delay, which cannot meet the fast sequence separation demand for converter transient faults. The spectral leakage effect under non - synchronous sampling spreads the fundamental wave energy to the sidebands, causing amplitude - phase calculation deviation of the positive and negative sequences. The high - order characteristic harmonics generated during the switching process of the modular multilevel converter further lead to spectral aliasing, resulting in cross - contamination of the sequence components. More critically, the non - linear characteristics of the zero - sequence path caused by the frequency - varying parameters of the submarine cable cannot be accurately modeled by fixed - frequency - domain basis vectors, and the decoupling of transient sequence components will fail during bipolar short - circuit faults, severely restricting the reliability of protection actions and the accuracy of fault - ride - through control.

[0085] To solve the above problems, the embodiment of the present application proposes a method for analyzing the fault characteristics of an MMC - based HVDC transmission system for offshore wind power, which specifically includes the following steps: S01: Establish an equivalent reduced - order model of the target MMC - based HVDC transmission system for offshore wind power by using the equivalent reduced - order modeling method of the MMC - based HVDC transmission system for offshore wind power proposed in the above - mentioned embodiment; S02: When a fault occurs in the target MMC - based HVDC transmission system for offshore wind power, obtain the AC voltage at the fault point in the target MMC - based HVDC transmission system for offshore wind power based on the equivalent reduced - order model of the target MMC - based HVDC transmission system for offshore wind power; S03: Conduct fault - characteristic analysis based on the obtained AC voltage at the fault point.

[0086] In some embodiments, the specific steps of S03 are as follows: Obtain the three - phase vector of the AC voltage at the fault point; Delay and rotate the three - phase vector of the AC voltage at the fault point by 90 degrees to obtain an orthogonal virtual phasor; Conduct decoupling operation based on the three - phase vector and the orthogonal virtual phasor of the AC voltage at the fault point to obtain the positive - sequence, negative - sequence, and zero - sequence components of the AC voltage at the fault point; Conduct fault - characteristic analysis based on the positive - sequence, negative - sequence, and zero - sequence components of the AC voltage at the fault point.

[0087] In a specific embodiment, the steps of conducting fault - characteristic analysis based on the obtained AC voltage at the fault point include: Obtain the three-phase vectors of the AC voltage at the fault point; Eliminate the zero-sequence component of the AC voltage at the fault point, as shown in the following formula: ; ; Where: represents the A-phase vector of the AC voltage at the fault point; represents the B-phase vector of the AC voltage at the fault point; represents the C-phase vector of the AC voltage at the fault point; represents the three-phase zero-sequence component at the fault point; and respectively represent the positive-sequence and negative-sequence components of the A-phase vector of the AC voltage at the fault point; and respectively represent the positive-sequence and negative-sequence components of the B-phase vector of the AC voltage at the fault point; and respectively represent the positive-sequence and negative-sequence components of the C-phase vector of the AC voltage at the fault point; Delay the rotation of the three-phase vectors of the AC voltage at the fault point by 90 degrees, as Figure 11 shown, to obtain new three-phase vectors, and then eliminate the zero-sequence component of the new three-phase vectors, as shown in the following formula: ; ; Where: 、 、 respectively represent the new A-phase vector, new B-phase vector, and new C-phase vector of the AC voltage at the fault point; represents the three-phase zero-sequence component after delaying the rotation of the three-phase vectors of the AC voltage at the fault point by 90 degrees; and respectively represent the positive-sequence and negative-sequence components of the new A-phase vector of the AC voltage at the fault point; and respectively represent the positive-sequence and negative-sequence components of the new B-phase vector of the AC voltage at the fault point; and respectively represent the positive-sequence and negative-sequence components of the new C-phase vector of the AC voltage at the fault point; As Figure 12 shown, at this time, the direction of is the same as the direction of and the amplitude is times that of the direction of is the same as the direction of and the amplitude is times that of; Eliminate the negative sequence component in the above formula and extract the positive sequence component of the three-phase vector of the AC voltage at the fault point, as shown in the following formula: ; ; ; Similarly, after eliminating the positive sequence component, the negative sequence component of the three-phase vector of the AC voltage at the fault point is obtained, as shown in the following formula: ; ; ; The zero sequence component of the three-phase vector of the AC voltage at the fault point is directly calculated by the algebraic sum of the three quantities in the three-phase four-wire system, as shown in the following formula: ; Where: , , respectively represent the zero sequence components of the vectors of phases A, B, and C of the AC voltage at the fault point.

[0088] The extraction method of the positive sequence, negative sequence, and zero sequence components of the AC voltage simplifies the matrix operation with complex numbers in the symmetrical component method into algebraic operations, simplifies the calculation method, and greatly improves the efficiency of fault feature extraction in the case of faults in wind turbine generators.

[0089] The embodiment of the present application also proposes a fault characteristic analysis system for a flexible DC transmission system for offshore wind power, which is constructed based on the fault characteristic analysis method for a flexible DC transmission system for offshore wind power proposed in the embodiment of the present invention. The fault characteristic analysis system for a flexible DC transmission system for offshore wind power includes: A modeling module that establishes an equivalent reduced-order model of the target flexible DC transmission system for offshore wind power by using the equivalent reduced-order modeling method of the flexible DC transmission system for offshore wind power described in the embodiment; A fault monitoring module that is used to monitor whether a fault occurs in the target flexible DC transmission system for offshore wind power, and when a fault occurs, obtains the AC voltage at the fault point in the target flexible DC transmission system for offshore wind power based on the equivalent reduced-order model of the target flexible DC transmission system for offshore wind power; A fault characteristic analysis module that performs fault characteristic analysis based on the obtained AC voltage at the fault point.

[0090] The embodiment of the present application also proposes an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the method described in any embodiment of the present invention.

[0091] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method described in any embodiment of the present invention is implemented.

[0092] References: [1] Huang P H, Moursi M E, Xiao W, et al. Subsynchronous Resonance Mitigation for Series-Compensated DFIG-Based Wind Farm by Using Two-Degree-of-Freedom Control Strategy[J]. IEEE Transactions on Power Systems, 2015, 30(3): 1442-1454. [2] Chao Pupu, Li Weixing, Jin Xiaoming, et al. Practical Equivalent Method for Doubly Fed Induction Generator-Based Wind Farms Based on Active Power Response[J]. Proceedings of the CSEE, 2018, 38(6): 8. [3] Fang R, Shang R, Wu M, et al. Application of gray relational analysis to k-means clustering for dynamic equivalent modeling of wind farm[J]. International Journal of Hydrogen Energy, 2017, 42(31). [4] Du Xiaoyan, Yin Huajie, Ye Chao, et al. Research on Wind Farm Equivalent Based on Improved Fuzzy C-Means Clustering and MPSO[J]. Guangdong Electric Power, 2016, 9(8): 7. [5] Zhan Z, Jie C, Jing H, et al. Wind farm modeling based on running data and SVM algorithm[J]. Renewable Energy Resources, 2015. [6] Zhou Y, Zhao L, Lee WJ. Robustness Analysis of Dynamic Equivalent Model of DFIG Wind Farm for Stability Study[J]. IEEE Transactions on Industry Applications, 2018, 54(6): 5682 - 5690. [7] ALI M, ILIE I, MILANOVIC JV, et al. Wind farm model aggregation using probabilistic clustering[J]. IEEE Transactions on Power Systems, 2013, 28(1): 309 - 316. [8] Yu Hao, Li Canbing, Ye Zhiliang, et al. Dynamic equivalent modeling of short - circuit faults in wind farms considering wake effect[J]. Journal of Shanghai Jiao Tong University, 2024, 58(6): 798 - 805. [9] Han Ji, Miao Shihong, Li Lixing, et al. Cluster division of internal generators in wind farms and comprehensive optimization of equivalent wind farm parameters based on multi - perspective transfer learning[J]. Proceedings of the CSEE, 2020, 40(15): 4866 - 4881.

[10] Yan Xiangwu, Li Junyan. Cluster - division method of direct - drive wind farms based on principal component analysis[J]. Power System Protection and Control, 2020, 48(5): 127 - 133.

[11] Ouyang Jinxin, Diao Yanbo, Zheng Di, et al. Electromagnetic transient homology - based clustering method for DFIG wind turbine groups using current trajectory similarity[J]. Proceedings of the CSEE, 2017, 37(10): 2896 - 2904.

[12] Li Longyuan. Research on dynamic equivalent modeling method of direct - drive wind farms[D]. Chengdu: Southwest Jiaotong University, 2022.

[13] Sun Huadong, Li Jiahao, Li Wenfeng, et al. Research on the model structure and modeling method of new - energy power stations for large - scale power system simulation (Part II): electromechanical transient model[J]. Proceedings of the CSEE, 2023, 43(6): 2190 - 2202.

[14] Zhang Jian, He Yigang. Parameter identification of equivalent model for permanent - magnet direct - drive wind farms based on trajectory sensitivity analysis[J]. Transactions of China Electrotechnical Society, 2020, 35(15): 3303 - 3313.

[15] Pan Xueping, Qi Xiangwei, Liang Wei, et al. Multi-machine equivalent and overall parameter identification of wind farms by integrating model aggregation and parameter identification [J]. Electric Power Automation Equipment, 2022, 42(1): 124-132. In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent the cases of A existing alone, A and B existing simultaneously, and B existing alone. Where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one of the following" and its similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0093] Those of ordinary skill in the art can realize that the units and algorithm steps described in the embodiments disclosed herein can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0094] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0095] In several embodiments provided by the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or a part of this 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 for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (hereinafter referred to as ROM), random access memories (hereinafter referred to as RAM), magnetic disks, or optical discs that can store program codes.

[0096] The above are only embodiments of the present invention, and thus do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall similarly be included within the patent protection scope of the present invention.

Claims

1. An equivalent order reduction modeling method for a flexible DC transmission system of offshore wind power, characterized in that Including the following steps: Construct an equivalent reduced-order model of a wind farm; Construct an equivalent reduced-order model of a modular multilevel converter; Construct a broadband equivalent reduced-order model of the receiving-end power grid; Based on the equivalent reduced-order model of the wind farm, the equivalent reduced-order model of the modular multilevel converter, and the broadband equivalent reduced-order model of the receiving-end power grid, construct an equivalent reduced-order model of the HVDC flexible transmission system for offshore wind power.

2. The equivalent order reduction modeling method of an HVDC flexible transmission system for offshore wind power according to claim 1, wherein The equivalent reduced-order model of the wind farm includes an equivalent reduced-order model of the wind farm collector line, an equivalent reduced-order model of the wind turbine generator set, and an equivalent reduced-order model of the step-up transformer at the generator terminal of the wind turbine generator set.

3. The equivalent reduced-order modeling method of an HVDC flexible transmission system for offshore wind power according to claim 2, wherein: The equivalent reduced-order model of the wind farm collector line is constructed by using the equal voltage loss method or the equal power loss method.

4. The equivalent order reduction modeling method of an HVDC flexible transmission system for offshore wind power according to claim 3, characterized in that: The equivalent reduced-order model of the wind farm collector line is modeled as an equivalent impedance model of the wind farm collector line, including: The positive-sequence equivalent impedance model of the wind farm collector line, the negative-sequence equivalent impedance model of the wind farm collector line, and the zero-sequence equivalent impedance model of the wind farm collector line.

5. The equivalent reduced-order modeling method of an HVDC flexible transmission system for offshore wind power according to claim 2, wherein: The equivalent reduced-order model of the wind turbine generator set is constructed by using any one of the single-machine aggregation method, the parameter identification method, and the multi-machine equivalence method.

6. The equivalent order reduction modeling method for a flexible DC transmission system of offshore wind power according to claim 2, wherein The construction method of the equivalent reduced-order model of the step-up transformer at the generator terminal of the wind turbine generator set is: Equivalent all the step-up transformers at the generator terminals of the wind turbines in the wind farm to the capacity expansion of a single transformer, and calculate the parameters of the equivalent single transformer, including the capacity and impedance of the equivalent single transformer.

7. The equivalent reduced-order modeling method of an HVDC flexible transmission system for offshore wind power according to claim 1, wherein: The equivalent reduced-order model of the modular multilevel converter is constructed based on any one of the half-bridge modular multilevel converter arm average value model or the full-bridge modular multilevel converter arm average value model.

8. The equivalent reduced-order modeling method of an HVDC flexible transmission system for offshore wind power according to claim 1, wherein: The broadband equivalent reduced-order model of the receiving-end power grid is constructed by using the RLC equivalent circuit modeling method based on the full-frequency band equivalent impedance analysis.

9. An equivalent order reduction modeling system for a flexible DC transmission system of offshore wind power, characterized in that, Including: A wind farm model construction module for constructing an equivalent reduced-order model of a wind farm; A converter model construction module for constructing an equivalent reduced-order model of a modular multilevel converter; A receiving-end power grid model construction module for constructing a broadband equivalent reduced-order model of the receiving-end power grid; An integration module for integrating the equivalent reduced-order model of the wind farm, the equivalent reduced-order model of the modular multilevel converter, and the broadband equivalent reduced-order model of the receiving-end power grid to construct an equivalent reduced-order model of the HVDC flexible transmission system for offshore wind power.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the program runs on the electronic device, it can implement the equivalent reduced-order modeling method of the HVDC flexible transmission system for offshore wind power according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the equivalent reduced-order modeling method of the HVDC flexible transmission system for offshore wind power according to any one of claims 1 to 8.

12. A method for analyzing the fault characteristics of a flexible DC transmission system for offshore wind power, characterized in that, Including the following steps: An equivalent reduced-order model of the target HVDC offshore wind power transmission system is established by using the equivalent reduced-order modeling method of the HVDC offshore wind power transmission system described in any one of claims 1 to 8; When a fault occurs in the target HVDC offshore wind power transmission system, the AC voltage at the fault point in the target HVDC offshore wind power transmission system is obtained based on the equivalent reduced-order model of the target HVDC offshore wind power transmission system; Fault characteristic analysis is performed based on the obtained AC voltage at the fault point.

13. A method for analyzing the fault characteristics of a flexible HVDC transmission system for offshore wind power according to claim 12, characterized in that, The step of performing fault characteristic analysis based on the obtained AC voltage at the fault point includes: Obtaining the three-phase vector of the AC voltage at the fault point; Delaying and rotating the three-phase vector of the AC voltage at the fault point by 90 degrees to obtain an orthogonal virtual phasor; Performing decoupling operation based on the three-phase vector and the orthogonal virtual phasor of the AC voltage at the fault point to obtain the positive-sequence, negative-sequence, and zero-sequence components of the AC voltage at the fault point; Performing fault characteristic analysis based on the positive-sequence, negative-sequence, and zero-sequence components of the AC voltage at the fault point.

14. A fault characteristic analysis system for a flexible DC transmission system of offshore wind power, characterized in that, Including: A modeling module that establishes an equivalent reduced-order model of the target HVDC offshore wind power transmission system by using the equivalent reduced-order modeling method of the HVDC offshore wind power transmission system described in any one of claims 1 to 8; A fault monitoring module for monitoring whether a fault occurs in the target HVDC offshore wind power transmission system, and when a fault occurs, obtaining the AC voltage at the fault point in the target HVDC offshore wind power transmission system based on the equivalent reduced-order model of the target HVDC offshore wind power transmission system; A fault characteristic analysis module that performs fault characteristic analysis based on the obtained AC voltage at the fault point.

15. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the program runs on the electronic device, it can implement the fault characteristic analysis method of the HVDC offshore wind power transmission system described in any one of claims 12 to 13.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the fault characteristic analysis method of the HVDC offshore wind power transmission system described in any one of claims 12 to 13.

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