DC bias traceability method and system based on MMC bridge arm parameter asymmetry

Abstract

The invention relates to the technical field of direct current power transmission, and discloses a direct current bias tracing method and system based on MMC bridge arm parameter asymmetry. The method comprises the following steps: S1, based on a bridge arm topological structure and an average switching function model of the MMC, establishing a direct current bias current model under asymmetry of bridge arm parameters through component disassembly and correlation derivation; s2, determining a primary bridge arm element causing direct current bias; s3, determining a first deviation degree of the primary bridge arm element; s4, determining a secondary bridge arm element causing direct current bias; s5, determining a second deviation degree of the secondary bridge arm element; and S6, repeatedly executing the steps S4-S5 until the transformer valve side direct current bias current calculated through the direct current bias current model is matched with the actually measured transformer valve side direct current bias current. According to the method, the effectiveness of an engineering direct current magnetic bias suppression scheme is improved, and a powerful guarantee is provided for safe and stable operation of a flexible direct current power transmission system.

Description

Technical Field

[0001] This invention relates to the field of DC power transmission technology, and in particular to a DC bias tracing method and system based on MMC arm parameter asymmetry. Background Technology

[0002] Flexible DC transmission technology, with its advantages of high controllability, good flexibility, and mature technology, has become the main choice for DC transmission projects at present. As a key device in flexible DC transmission systems, the modular multilevel converter (MMC) has a three-phase six-arm symmetrical topology. Under ideal conditions, the current in the upper and lower arms of any phase exhibits the characteristics that the DC component has the same amplitude and direction, while the AC component has the same amplitude but opposite direction.

[0003] However, in actual engineering, due to factors such as deviations in equipment manufacturing processes, differences in component supply channels, and parameter drift during operation, key parameters such as the number of converter valve submodules, arm reactance, submodule capacitance, and on-resistance inevitably exhibit asymmetry. This parameter asymmetry disrupts the original symmetrical operation assumption of the MMC, causing the DC component balance of the arm current to be broken, which in turn generates a DC bias current in the converter transformer. This current can cause transformer core saturation, resulting in DC bias magnetization, which leads to increased transformer vibration and noise. In severe cases, it can even cause winding overheating, insulation damage, and other faults, threatening the safe and stable operation of the system.

[0004] Existing research on the operation and control of MMC (Flexible Modular Control) systems is mostly based on the ideal assumption of symmetrical arm parameters. A clear understanding of the generation mechanism of DC bias under parameter asymmetry is lacking, especially regarding the quantitative relationship between the degree of arm parameter asymmetry and the magnitude of the DC bias current. Therefore, how to accurately calculate the DC bias current under parameter asymmetry scenarios and effectively trace the source of asymmetric parameters has become a key technical problem urgently needing to be solved in the current research field of flexible DC transmission systems. Summary of the Invention

[0005] To address the aforementioned problems in existing technologies, this invention provides a DC bias tracing method and system based on MMC arm parameter asymmetry. This method not only provides theoretical support for in-depth analysis of the influencing factors of DC bias, but also provides scientific guidance for the suppression and control of DC bias in engineering practice.

[0006] In a first aspect, embodiments of the present invention provide a DC bias tracing method based on MMC arm parameter asymmetry, comprising the following steps: S1. Based on the MMC-based bridge arm topology and average switching function model, a DC bias current model under bridge arm parameter asymmetry is established through component decomposition and correlation derivation. S2. Compare the measured DC bias current of the first bridge arm with the DC bias current of the second bridge arm under different single bridge arm parameter asymmetry calculated by the DC bias current model to determine the primary bridge arm element causing DC bias. S3. Compare the DC bias current of the third arm of the primary arm element under different degrees of asymmetry, calculated by the DC bias current model, with the DC bias current of the first arm element to determine the first degree of deviation of the primary arm element. S4. Based on the first deviation degree and the first bridge arm DC bias current, calculate the fourth bridge arm DC bias current under the parameter asymmetry of other bridge arm elements besides the primary bridge arm element through the DC bias current model, and determine the secondary bridge arm element that causes DC bias. S5. Compare the DC bias current of the fifth arm of the secondary arm element calculated by the DC bias current model under different degrees of asymmetry with the DC bias current of the first arm element to determine the second degree of deviation of the secondary arm element. S6. Repeat steps S4-S5 until the DC bias current on the transformer valve side calculated by the DC bias current model matches the actual measured DC bias current on the transformer valve side.

[0007] Preferably, the MMC-based bridge arm topology and average switching function model establishes a DC bias current model under bridge arm parameter asymmetry through component decomposition and correlation derivation, including: The switching function of the MMC bridge arm and the capacitor voltage of the submodule are decomposed into a first mathematical expression containing a DC component, a fundamental component and a second harmonic component, respectively. The bridge arm voltage and bridge arm current of the MMC bridge arm are decomposed into a second mathematical expression containing a DC component and a fundamental component, respectively. Based on the average switching function model, the first correlation between the converter valve output voltage and the submodule capacitor voltage and the switching function, and the second correlation between the bridge arm current and the submodule capacitor voltage and the switching function are established respectively. Based on the KVL equations, a third correlation between the converter valve output voltage and the bridge arm resistance and a fourth correlation between the converter valve output voltage and the bridge arm reactance are established respectively. By combining all mathematical expressions and all relationships, a fifth relationship is established between the bridge arm current and the bridge arm resistance, bridge arm reactance, submodule capacitance, and number of submodules.

[0008] Preferably, the step of establishing a first correlation between the converter valve output voltage and the submodule capacitor voltage and the switching function, and a second correlation between the bridge arm current and the submodule capacitor voltage and the switching function, based on the average switching function model, includes: Based on the equivalent principle of MMC submodule switching, a first correlation is established whereby the output voltage of the converter valve is equal to the product of the submodule capacitor voltage and the switching function. A second correlation is established between the bridge arm current and the submodule capacitor voltage and the switching function based on the charging and discharging characteristics of the submodule capacitor.

[0009] Preferably, the step of establishing a third correlation between the converter valve output voltage and the bridge arm resistance and a fourth correlation between the converter valve output voltage and the bridge arm reactance based on the KVL equation includes: Based on the KVL equations, the third correlation is determined that the DC component of the converter valve output voltage is equal to the DC voltage drop component of the bridge arm resistance, and the fourth correlation is determined that the fundamental component of the converter valve output voltage is equal to the fundamental voltage drop component of the bridge arm reactance.

[0010] Preferably, the step of comparing the actually measured DC bias current of the first bridge arm with the DC bias current of the second bridge arm under different single bridge arm parameter asymmetries calculated by the DC bias current model to determine the primary bridge arm element causing the DC bias includes: Based on the actual measured DC bias current of the first arm of each MMC arm, the arm containing the primary component causing the DC bias is determined. The DC bias current of the second bridge arm under the condition of parameter asymmetry for each element on the bridge arm where the primary element is located is calculated using the DC bias current model. The DC bias current of each second bridge arm is compared with the DC bias current of the first bridge arm in the bridge arm where the primary element is located. The element corresponding to the DC bias current of the second bridge arm that is most similar to the DC bias current of the first bridge arm is determined as the primary bridge arm element that causes the DC bias.

[0011] Preferably, the step of comparing the DC bias current of the third arm of the primary arm element calculated by the DC bias current model under different degrees of asymmetry with the DC bias current of the first arm element to determine the first deviation degree of the primary arm element includes: The DC bias current of the third arm of the primary arm element calculated by the DC bias current model under different degrees of asymmetry is compared with the DC bias current of the first arm of the arm where the primary arm element is located. The degree of asymmetry corresponding to the DC bias current of the third arm element that is most similar to the DC bias current of the first arm element is determined as the first deviation degree of the primary arm element.

[0012] Preferably, the step of calculating the fourth arm DC bias current under parameter asymmetry of other arm elements besides the primary arm element based on the first deviation degree and the first arm DC bias current, and determining the secondary arm element causing the DC bias, includes: The DC bias current model, which has been substituted with the first deviation level, is used to sequentially calculate the DC bias current of the fourth bridge arm under the condition of asymmetry of the parameters of the other components in the bridge arm where the primary bridge arm component is located, and the DC bias current of the fourth bridge arm under the condition of asymmetry of the parameters of the components in other bridge arms besides the bridge arm where the primary bridge arm component is located. The element corresponding to the DC bias current of the fourth bridge arm that is most similar to the DC bias current of the first bridge arm in the bridge arm where the primary bridge arm element is located is identified as the secondary bridge arm element that causes the DC bias.

[0013] Preferably, the step of comparing the DC bias current of the fifth arm of the secondary arm element calculated by the DC bias current model under different degrees of asymmetry with the DC bias current of the first arm element to determine the second degree of deviation of the secondary arm element includes: The DC bias current of the fifth bridge arm of the secondary bridge arm element calculated by the DC bias current model under different degrees of asymmetry is compared with the DC bias current of the first bridge arm of the primary bridge arm element. The degree of asymmetry corresponding to the DC bias current of the fifth bridge arm element that is most similar to the DC bias current of the first bridge arm element is determined as the second deviation degree of the secondary bridge arm element.

[0014] Preferably, repeating steps S4-S5 until the DC bias current on the transformer valve side calculated by the DC bias current model matches the actually measured DC bias current on the transformer valve side includes: Repeat steps S4-S5 to determine the remaining bridge arm elements causing DC bias, and correct the deviation of all the bridge arm elements causing DC bias until the transformer valve side DC bias current calculated by the DC bias current model matches the actual measured transformer valve side DC bias current.

[0015] Secondly, embodiments of the present invention provide a DC bias tracing system based on MMC arm parameter asymmetry, comprising: The current model building module is used for MMC-based bridge arm topology and average switching function models. It establishes a DC bias current model under bridge arm parameter asymmetry through component decomposition and correlation derivation. The primary component determination module is used to compare the actual measured DC bias current of the first bridge arm with the DC bias current of the second bridge arm under different single bridge arm parameter asymmetry calculated by the DC bias current model, and to determine the primary bridge arm component that causes the DC bias. The first deviation determination module is used to compare the third arm DC bias current of the primary arm element under different degrees of asymmetry, calculated by the DC bias current model, with the first arm DC bias current to determine the first deviation degree of the primary arm element. The secondary component determination module is used to calculate the DC bias current of the fourth bridge arm under the condition of parameter asymmetry of other bridge arm components besides the primary bridge arm component based on the first deviation degree and the first bridge arm DC bias current, and to determine the secondary bridge arm component that causes DC bias. The second deviation determination module is used to compare the DC bias current of the fifth arm of the secondary arm element under different degrees of asymmetry, calculated by the DC bias current model, with the DC bias current of the first arm element to determine the second deviation degree of the secondary arm element.

[0016] This invention, based on an MMC arm parameter asymmetry tracing method and system, offers several advantages over existing technologies. Firstly, it constructs a DC bias current model with asymmetric coupling of multiple MMC arm parameters (arm resistance, arm reactance, submodule capacitance, and number of submodules). Through component decomposition and correlation derivation, it achieves full-process quantitative calculation of arm parameter deviations, arm DC bias current, and transformer valve-side DC bias current. Secondly, it proposes a tracing approach for arm asymmetry parameters, involving primary component location, deviation degree quantification, secondary component investigation, and iterative verification. This approach not only quickly identifies the primary deviation component causing DC bias but also accurately identifies secondary components and their specific deviation degrees, providing direct and accurate technical support for on-site equipment parameter investigation and fault location. This invention enhances the pertinence and effectiveness of engineering DC bias suppression schemes, providing strong technical support for the safe and stable operation and optimized design of flexible DC transmission systems. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a DC bias tracing method based on MMC arm parameter asymmetry according to an embodiment of the present invention. Figure 2 This is a schematic diagram showing the relationship between the DC bias voltage and current of the MMC in an embodiment of the present invention; Figure 3 This is a schematic diagram of a DC bias tracing system based on MMC arm parameter asymmetry according to an embodiment of the present invention; Figure label: SM1, the first submodule; SMn, the nth submodule; 01, current model construction module; 02, primary component determination module; 03, first deviation determination module; 04, secondary component determination module; 05, second deviation determination module. Detailed Implementation

[0018] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0019] In the description of this invention, it should be understood that the terms "first" and "second," etc., are used to distinguish different objects, rather than to describe a specific order.

[0020] In the description of this invention, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by those skilled in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0021] In flexible DC transmission systems, the MMC (Multi-Module Converter) serves as the core converter unit, with its output directly connected to the transformer valve side, forming a crucial link for energy conversion and transmission. If there are asymmetrical deviations in parameters such as the resistance, reactance, submodule capacitance, and number of submodules in the MMC arms, a DC bias current will be generated in the arms. This current will further inject into the transformer valve side, creating a DC bias and ultimately leading to DC magnetization in the transformer, severely impacting the safe and stable operation of the system. Therefore, this invention was developed to accurately locate the aforementioned asymmetrical deviation parameters and clarify the root cause of DC magnetization.

[0022] like Figure 1 The diagram shown is a flowchart illustrating a DC bias tracing method based on MMC arm parameter asymmetry according to an embodiment of the present invention. (Refer to...) Figure 1 This invention provides a DC bias tracing method based on MMC arm parameter asymmetry, comprising the following steps: S1. Based on the MMC-based bridge arm topology and average switching function model, a DC bias current model under bridge arm parameter asymmetry is established through component decomposition and correlation derivation. In the three-phase six-arm topology of MMC, each arm mainly consists of arm reactance and converter valve submodules. AC / DC conversion is achieved by controlling the on / off state of the converter valves. When there are deviations in the equipment parameters of each arm, the original symmetry assumptions and modeling methods no longer hold. This step will establish a DC bias current model under scenarios of asymmetrical arm parameters such as resistance, reactance, capacitance, and the number of submodules, and analyze the DC bias situation under different influencing factors.

[0023] Specifically, step S1 includes: 11) Decompose the switching function of the MMC bridge arm and the capacitor voltage of the submodule into a first mathematical expression containing a DC component, a fundamental component and a second harmonic component, respectively; and decompose the bridge arm voltage and bridge arm current of the MMC bridge arm into a second mathematical expression containing a DC component and a fundamental component, respectively. 12) Based on the average switching function model, establish the first correlation between the converter valve output voltage and the submodule capacitor voltage and the switching function, and the second correlation between the bridge arm current and the submodule capacitor voltage and the switching function. Based on the equivalent principle of MMC submodule switching, a first correlation is established whereby the output voltage of the converter valve is equal to the product of the submodule capacitor voltage and the switching function. A second correlation is established between the bridge arm current and the submodule capacitor voltage and the switching function based on the charging and discharging characteristics of the submodule capacitor.

[0024] 13) Based on the KVL equation, establish the third correlation between the output voltage of the converter valve and the arm resistance, and the fourth correlation between the output voltage of the converter valve and the arm reactance. Based on the KVL equations, a third correlation is established where the DC component of the converter valve output voltage is equal to the DC voltage drop component of the bridge arm resistance, and a fourth correlation is established where the fundamental component of the converter valve output voltage is equal to the fundamental voltage drop component of the bridge arm reactance. The DC voltage drop component is determined by the product of the DC component of the bridge arm current and the bridge arm resistance, while the fundamental voltage drop component is determined by the product of the fundamental component of the bridge arm current and the fundamental frequency reactance of the bridge arm.

[0025] 14) Combining all mathematical expressions and all relationships, establish the fifth relationship between bridge arm current and bridge arm resistance, bridge arm reactance, submodule capacitance, and number of submodules.

[0026] like Figure 2 As shown, this is a schematic diagram illustrating the DC bias voltage and current relationship of the MMC in an embodiment of the present invention. (Refer to...) Figure 2 Taking the deviation in the parameters of the upper bridge arm equipment in phase A as an example, Indicates the voltage of the AC system. , , This represents the DC component of the valve-side voltage of the converter transformer. , , This represents the three-phase current on the grid side of the converter transformer. , , This represents the DC component of the valve-side current of the converter transformer. , This indicates the output voltage of the upper and lower bridge arms of the converter valve. , This represents the DC component of the current in the upper and lower bridge arms. This indicates DC voltage.

[0027] To simplify the derivation, only the DC, fundamental, and second harmonic components of the switching function are considered. The average switching function of the bridge arm is shown below: (1) in, , Indicates the first of the upper and lower bridge arms The switch functions for each submodule Indicates the fundamental frequency modulation ratio. Indicates the second harmonic component modulation ratio. This represents the initial phase of the second harmonic component of the switching function. This indicates the number of submodules in a single bridge arm (excluding redundancy). Indicates the fundamental angular frequency. Indicates time.

[0028] Considering only the DC, fundamental, and second harmonic components of the submodule capacitor voltage, assume the voltage of a single submodule capacitor is as follows: (2) in, , These represent the DC components of the capacitor voltages of the upper and lower bridge arm submodules, respectively. , Indicates the amplitude of the fundamental component. , This represents the amplitude of the second harmonic component. , These represent the phases of the fundamental component and the second harmonic component, respectively.

[0029] It should be noted that formula (1) can be understood as decomposing the switching function of the MMC bridge arm into a first mathematical expression containing DC component, fundamental component and second harmonic component, and formula (2) can be understood as decomposing the submodule capacitor voltage of the MMC bridge arm into a first mathematical expression containing DC component, fundamental component and second harmonic component.

[0030] Assume the voltages of the upper and lower bridge arms are , The currents of the upper and lower bridge arms are , The expression is as follows: (3) in, , This represents the DC component of the output voltage of the upper and lower bridge arm converter valves. , This represents the amplitude of the fundamental component of the output voltage of the upper and lower bridge arm converter valves. Indicates the phase of the fundamental voltage. , This represents the DC component of the current in the upper and lower bridge arms. , This represents the amplitude of the fundamental component of the current in the upper and lower bridge arms. This indicates the phase of the fundamental current.

[0031] It should be noted that formula (3) can be understood as decomposing the arm voltage and arm current of the MMC arm into a second mathematical expression containing DC component and fundamental component respectively.

[0032] Based on the average switching function model, the correspondence between the converter valve output voltage, the submodule capacitor voltage, and the switching function is shown below: (4) It should be noted that formula (4) can be understood as the first correlation between the output voltage of the converter valve and the product of the submodule capacitor voltage and the switching function, established based on the physical basis of the average switching function model, namely the MMC submodule switching equivalent principle. Here, the MMC submodule switching equivalent principle refers to the working principle of the submodule, through the action of putting on or cutting off, equivalently realizing the connection or disconnection of its capacitor voltage to or from the bridge arm circuit, thereby outputting a discrete voltage.

[0033] Substituting equations (1) and (2) into equation (4), the second harmonic component of the converter valve output voltage can be obtained as follows: (5) According to formula (5), the amplitudes of the fundamental component and the second harmonic component of the submodule capacitor voltage are in a one-to-one correspondence with the DC component. When the DC component of the submodule capacitor voltage changes, the fundamental component and the second harmonic component will also change accordingly.

[0034] Substituting formula (5) into formula (4), the DC component of the output voltage of the upper and lower bridge arm converter valves is... , and fundamental component amplitude , for: (6) Among them are: (7) Furthermore, based on the average switching function model, the corresponding relationships between the bridge arm current, submodule capacitor voltage, and switching function are as follows: (8) in, , This represents the average number of submodules deployed in any given period. , These represent the capacitors of individual submodules in the upper and lower bridge arms, respectively.

[0035] It should be noted that formula (8) can be understood as the second correlation between the bridge arm current, submodule capacitor voltage, and switching function established based on the electrical constraints of the average switching function model, namely the charging and discharging characteristics of the submodule capacitor. Here, the charging and discharging characteristics of the submodule capacitor refer to the electrical characteristic where the current of the submodule capacitor is equal to the product of the capacitance value and the rate of change of the capacitor voltage.

[0036] Substituting formulas (1)-(3) into formula (8), the corresponding relationship between the DC component and the fundamental frequency component of the bridge arm current is as follows: (9) Substituting formula (9) into the expansion of formula (8), we can obtain the expression for the fundamental component amplitude of the capacitor voltage of a single submodule in the upper and lower bridge arms: (10) Among them are: (11) Based on the KVL equations, the expressions for the DC component and the fundamental frequency component are: (12) in, , This represents the bridge arm resistance of the upper and lower bridge arms.

[0037] It should be noted that formula (12) can be understood as the third correlation between the output voltage of the converter valve and the resistance of the bridge arm, and the fourth correlation between the output voltage of the converter valve and the reactance of the bridge arm, respectively, established based on the KVL equation.

[0038] Substituting formulas (6), (7), (9), and (10) into formula (12) yields: (13) Among them are: (14) It should be noted that formula (14) can be understood as the fifth relationship between the bridge arm current and the bridge arm resistance, bridge arm reactance, submodule capacitance, and number of submodules, which is established by combining all mathematical expressions and all relationships.

[0039] Depend on Figure 1 It can be seen that the DC component of the AC side current of the converter valve is: (15) Substituting formula (14) into formula (15), the DC component of the transformer valve side current under bridge arm parameter asymmetry can be obtained.

[0040] It should be noted that the DC bias current model under asymmetrical bridge arm parameters is not a single formula, but a derivation system of formulas (1) to (15). That is to say, the DC bias current model is constructed by decomposing electrical quantity components, deriving the average switching function model, and introducing the KVL law to build a quantitative mapping derivation system between asymmetrical parameters such as bridge arm resistance, reactance, submodule capacitance and number, and the DC bias current of the bridge arm and transformer valve side.

[0041] S2. Compare the measured DC bias current of the first bridge arm with the DC bias current of the second bridge arm under different single bridge arm parameter asymmetry calculated by the DC bias current model to determine the primary bridge arm element causing DC bias. Specifically, step S2 includes: 21) Based on the actual measured DC bias current of the first arm of each MMC arm, determine the arm where the primary component causing the DC bias is located. By actually measuring the DC bias current of the first bridge arm of each MMC bridge arm, it can be determined which bridge arm has a significant current anomaly, thereby pinpointing the bridge arm where the primary component is located.

[0042] 22) Calculate the DC bias current of the second bridge arm under the condition of parameter asymmetry for each component on the bridge arm where the primary component is located using the DC bias current model; Based on the DC bias current model, the bridge arm resistance, bridge arm reactance, submodule capacitance, and number of submodules are selected as independent variables for the bridge arm containing the primary component. The scenarios in which each variable has asymmetric parameters are simulated one by one, and the corresponding second bridge arm DC bias current under each scenario is calculated.

[0043] 23) Compare the DC bias current of each second bridge arm with the DC bias current of the first bridge arm in which the primary element is located, and determine the element corresponding to the DC bias current of the second bridge arm that is most similar to the DC bias current of the first bridge arm as the primary bridge arm element that causes DC bias.

[0044] When the DC bias current of the second bridge arm corresponding to a certain component has the highest similarity to the measured DC bias current of the first bridge arm, it indicates that the parameter asymmetry of that component is the primary factor causing DC bias, and based on this, it is determined to be the primary bridge arm component. The bias characteristics include the current amplitude and its trend with system power or operating mode.

[0045] S3. Compare the DC bias current of the third arm of the primary arm element calculated by the DC bias current model under different degrees of asymmetry with the DC bias current of the first arm element to determine the first degree of deviation of the primary arm element. The DC bias current of the third arm of the primary arm element, calculated by the DC bias current model under different degrees of asymmetry, is compared with the DC bias current of the first arm of the arm where the primary arm element is located. The degree of asymmetry corresponding to the DC bias current of the third arm element that is most similar to the DC bias current of the first arm element is determined as the first deviation degree of the primary arm element.

[0046] Specifically, based on the primary bridge arm element and the bridge arm it belongs to, multiple different asymmetry gradients are set with reference to the allowable manufacturing tolerances or deviation ranges of such elements. The DC bias current of the third bridge arm under each gradient is calculated one by one through the DC bias current model. Then, based on the bias characteristics, the DC bias current of the third bridge arm with the highest similarity to the bias characteristics of the measured DC bias current of the first bridge arm is selected. The corresponding asymmetry degree is the first deviation degree of the primary bridge arm element.

[0047] S4. Based on the first deviation degree and the first bridge arm DC bias current, calculate the fourth bridge arm DC bias current under the parameter asymmetry of other bridge arm elements besides the primary bridge arm element through the DC bias current model, and determine the secondary bridge arm element that causes DC bias. Specifically, step S4 includes: 41) Calculate the DC bias current of the fourth bridge arm under the condition of asymmetric parameters of other components in the bridge arm where the primary bridge arm component is located, and the DC bias current of the fourth bridge arm under the condition of asymmetric parameters of components in other bridge arms besides the bridge arm where the primary bridge arm component is located, by substituting the DC bias current model with the first deviation degree. Substitute the first deviation degree of the primary bridge arm element into the DC bias current model, fix the parameter deviation state of the element to eliminate its individual interference; first, take the other elements in the bridge arm where the primary bridge arm element is located as independent variables, and then take all the elements in other bridge arms as independent variables, simulate the scenario where each variable has parameter asymmetry individually, and calculate the corresponding fourth bridge arm DC bias current under each scenario through the DC bias current model.

[0048] 42) Identify the element corresponding to the DC bias current of the fourth arm that is most similar to the DC bias current of the first arm of the arm containing the primary arm element as the secondary arm element that causes the DC bias.

[0049] When the DC bias current of the fourth bridge arm corresponding to a certain component has the highest similarity to the measured DC bias current of the first bridge arm, it indicates that the parameter asymmetry of the component is a secondary factor causing DC bias, other than the primary bridge arm component. Based on this, it is determined to be a secondary bridge arm component.

[0050] S5. Compare the DC bias current of the fifth arm of the secondary arm element calculated by the DC bias current model under different degrees of asymmetry with the DC bias current of the first arm element to determine the second degree of deviation of the secondary arm element. The DC bias current of the fifth arm of the secondary arm element, calculated by the DC bias current model under different degrees of asymmetry, is compared with the DC bias current of the first arm of the primary arm element. The degree of asymmetry corresponding to the DC bias current of the fifth arm element that is most similar to the DC bias current of the first arm element is determined as the second deviation degree of the secondary arm element.

[0051] Specifically, the first deviation degree is first substituted into the DC bias current model to fix the deviation influence of the primary bridge arm element. Then, referring to the allowable manufacturing tolerance or deviation range of this type of secondary bridge arm element, multiple different asymmetry degree gradients are set. The DC bias current of the fifth bridge arm under each gradient is calculated one by one through the DC bias current model. Based on the bias characteristics, the measured DC bias current of the first bridge arm is compared with the bias characteristics. The DC bias current of the fifth bridge arm with the highest similarity to the bias characteristics is selected. The corresponding asymmetry degree is the second deviation degree of the secondary bridge arm element.

[0052] S6. Repeat steps S4-S5 until the DC bias current on the transformer valve side calculated by the DC bias current model matches the actual measured DC bias current on the transformer valve side.

[0053] Repeat steps S4-S5 to determine the remaining bridge arm components causing DC bias, and correct the deviation of all bridge arm components causing DC bias until the transformer valve-side DC bias current calculated by the DC bias current model matches the actual measured transformer valve-side DC bias current.

[0054] Specifically, based on all the identified deviation bridge arm elements and their current deviation levels, the process of steps S4 to S5 is repeatedly executed to iteratively correct the deviation levels of all deviation bridge arm elements until the DC bias current calculated by the DC bias current model accurately matches the actual measured DC bias current on the transformer valve side.

[0055] To verify the effectiveness of the DC bias tracing method based on MMC arm parameter asymmetry in this embodiment of the invention, in another embodiment, the MMC arm reactance is 50mH, the arm resistance is 0.3Ω, the rated number of arm sub-modules is 226, the capacitance is 18mF, the reactance manufacturing tolerance is 0%~5%, the resistance deviation range is 0-0.3Ω, the deviation range of the number of redundant sub-modules is 0-16, and the allowable manufacturing tolerance of the sub-module capacitor is 0~5%.

[0056] Specifically, based on the above MMC bridge arm reference parameters and the deviation range of each component, a DC bias current model under the scenario of asymmetrical bridge arm parameters is constructed to clarify the DC bias characteristics when a single bridge arm parameter (bridge arm resistance, reactance, submodule capacitance and number of submodules) is asymmetrical.

[0057] Furthermore, the measured DC bias current of the bridge arm is compared with the simulated bias characteristics of each single-parameter asymmetric scenario. The corresponding element with the highest similarity of bias characteristics is determined as the primary bridge arm element causing DC bias. In this embodiment, the primary bridge arm element is the bridge arm reactance.

[0058] Furthermore, different deviation gradients were set within the range of 0% to 5% for the bridge arm reactance. The DC bias current under each gradient was calculated by the DC bias current model. After comparison with the measured current, the first deviation degree was determined to be about 1.67%.

[0059] Furthermore, the aforementioned 1.67% reactance deviation was substituted into the DC bias current model to fix its influence, and then the simulation bias characteristics of the other components (bridge arm resistor, submodule capacitor, number of submodules) in the asymmetrical scenario were compared one by one to clarify that the bridge arm resistor is a secondary bridge arm component.

[0060] Finally, a gradient was set within the resistance deviation range of 0~0.3Ω and the corresponding bias current was calculated. The second deviation was determined to be approximately 0.08Ω by comparing it with the measured current. After repeating the above iterative correction process, the DC bias current on the transformer valve side calculated by the DC bias current model accurately fits the actual measured DC bias current on the transformer valve side, which fully verifies the effectiveness of the DC bias tracing method based on MMC arm parameter asymmetry in this embodiment of the invention.

[0061] This invention presents a DC bias tracing method based on MMC arm parameter asymmetry. It constructs a DC bias current model with asymmetric coupling of multiple MMC arm parameters (arm resistance, arm reactance, submodule capacitance, and number of submodules). Through component decomposition and correlation derivation, it achieves full-process quantitative calculation of arm parameter deviation, arm DC bias current, and transformer valve-side DC bias current. The invention proposes a tracing approach for asymmetric arm parameters, including primary component location, deviation degree quantification, secondary component investigation, and iterative verification. This approach not only quickly identifies the primary deviation component causing DC bias but also accurately identifies secondary components and the specific deviation degree of each component, providing direct and accurate technical basis for on-site equipment parameter investigation and fault location. This invention improves the pertinence and effectiveness of engineering DC bias suppression schemes, providing strong technical support for the safe and stable operation and optimized design of flexible DC transmission systems.

[0062] like Figure 3The diagram shown is a structural schematic of a DC bias tracing system based on MMC arm parameter asymmetry according to an embodiment of the present invention. (Refer to...) Figure 3 An embodiment of the present invention provides a DC bias tracing system based on MMC arm parameter asymmetry, comprising: The current model construction module 01 is used for the bridge arm topology and average switching function model based on MMC. It establishes the DC bias current model under bridge arm parameter asymmetry through component decomposition and correlation derivation. The primary component determination module 02 is used to compare the actual measured DC bias current of the first bridge arm with the DC bias current of the second bridge arm under different single bridge arm parameter asymmetry calculated by the DC bias current model, and to determine the primary bridge arm component that causes DC bias. The first deviation determination module 03 is used to compare the DC bias current of the third arm of the primary arm element under different degrees of asymmetry, calculated by the DC bias current model, with the DC bias current of the first arm element to determine the first deviation degree of the primary arm element. Secondary component determination module 04 is used to calculate the DC bias current of the fourth bridge arm under the parameter asymmetry of other bridge arm components besides the primary bridge arm component based on the first deviation degree and the first bridge arm DC bias current, and to determine the secondary bridge arm component that causes DC bias. The second deviation determination module 05 is used to compare the DC bias current of the fifth bridge arm under different degrees of asymmetry of the secondary bridge arm element calculated by the DC bias current model with the DC bias current of the first bridge arm element to determine the second deviation degree of the secondary bridge arm element.

[0063] It should be noted that each module in the aforementioned DC bias tracing system based on MMC arm parameter asymmetry can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module. For specific limitations regarding the DC bias tracing system based on MMC arm parameter asymmetry, please refer to the limitations of the DC bias tracing method based on MMC arm parameter asymmetry mentioned above; both have the same function and role, and will not be repeated here.

[0064] In summary, this invention provides a DC bias tracing method and system based on MMC arm parameter asymmetry. It constructs a DC bias current model with asymmetric coupling of multiple MMC arm parameters (arm resistance, arm reactance, submodule capacitance, and number of submodules). Through component decomposition and correlation derivation, it achieves full-process quantitative calculation of arm parameter deviation, arm DC bias current, and transformer valve-side DC bias current. The invention proposes a tracing approach for asymmetric arm parameters, including primary component location, deviation degree quantification, secondary component investigation, and iterative verification. This approach not only quickly identifies the primary deviation component causing DC bias but also accurately identifies secondary components and the specific deviation degree of each component, providing direct and accurate technical basis for on-site equipment parameter investigation and fault location. This invention improves the pertinence and effectiveness of engineering DC bias suppression schemes, providing strong technical support for the safe and stable operation and optimized design of flexible DC transmission systems.

[0065] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on its differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0066] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention.

Claims

1. A DC bias tracing method based on MMC arm parameter asymmetry, characterized in that, Including the following steps: S1. Based on the MMC-based bridge arm topology and average switching function model, a DC bias current model under bridge arm parameter asymmetry is established through component decomposition and correlation derivation. S2. Compare the measured DC bias current of the first bridge arm with the DC bias current of the second bridge arm under different single bridge arm parameter asymmetry calculated by the DC bias current model to determine the primary bridge arm element causing DC bias. S3. Compare the DC bias current of the third arm of the primary arm element under different degrees of asymmetry, calculated by the DC bias current model, with the DC bias current of the first arm element to determine the first degree of deviation of the primary arm element. S4. Based on the first deviation degree and the first bridge arm DC bias current, calculate the fourth bridge arm DC bias current under the parameter asymmetry of other bridge arm elements besides the primary bridge arm element through the DC bias current model, and determine the secondary bridge arm element that causes DC bias. S5. Compare the DC bias current of the fifth arm of the secondary arm element calculated by the DC bias current model under different degrees of asymmetry with the DC bias current of the first arm element to determine the second degree of deviation of the secondary arm element. S6. Repeat steps S4-S5 until the DC bias current on the transformer valve side calculated by the DC bias current model matches the actual measured DC bias current on the transformer valve side.

2. The DC bias tracing method based on MMC arm parameter asymmetry according to claim 1, characterized in that, The MMC-based bridge arm topology and average switching function model establishes a DC bias current model under bridge arm parameter asymmetry through component decomposition and correlation derivation, including: The switching function of the MMC bridge arm and the capacitor voltage of the submodule are decomposed into a first mathematical expression containing a DC component, a fundamental component and a second harmonic component, respectively. The bridge arm voltage and bridge arm current of the MMC bridge arm are decomposed into a second mathematical expression containing a DC component and a fundamental component, respectively. Based on the average switching function model, the first correlation between the converter valve output voltage and the submodule capacitor voltage and the switching function, and the second correlation between the bridge arm current and the submodule capacitor voltage and the switching function are established respectively. Based on the KVL equations, a third correlation between the converter valve output voltage and the bridge arm resistance and a fourth correlation between the converter valve output voltage and the bridge arm reactance are established respectively. By combining all mathematical expressions and all relationships, a fifth relationship is established between the bridge arm current and the bridge arm resistance, bridge arm reactance, submodule capacitance, and number of submodules.

3. The DC bias tracing method based on MMC arm parameter asymmetry according to claim 2, characterized in that, The method, based on the average switching function model, establishes a first correlation between the converter valve output voltage and the submodule capacitor voltage and the switching function, and a second correlation between the bridge arm current and the submodule capacitor voltage and the switching function, including: Based on the equivalent principle of MMC submodule switching, a first correlation is established whereby the output voltage of the converter valve is equal to the product of the submodule capacitor voltage and the switching function. A second correlation is established between the bridge arm current and the submodule capacitor voltage and the switching function based on the charging and discharging characteristics of the submodule capacitor.

4. The DC bias tracing method based on MMC arm parameter asymmetry according to claim 2, characterized in that, The establishment of a third correlation between the converter valve output voltage and the bridge arm resistance, and a fourth correlation between the converter valve output voltage and the bridge arm reactance, based on the KVL equations, includes: Based on the KVL equations, the third correlation is determined that the DC component of the converter valve output voltage is equal to the DC voltage drop component of the bridge arm resistance, and the fourth correlation is determined that the fundamental component of the converter valve output voltage is equal to the fundamental voltage drop component of the bridge arm reactance.

5. The DC bias tracing method based on MMC arm parameter asymmetry according to claim 1, characterized in that, The step of comparing the actually measured DC bias current of the first bridge arm with the DC bias current of the second bridge arm under different single bridge arm parameter asymmetries calculated by the DC bias current model to determine the primary bridge arm element causing the DC bias includes: Based on the actual measured DC bias current of the first arm of each MMC arm, the arm containing the primary component causing the DC bias is determined. The DC bias current of the second bridge arm under the condition of parameter asymmetry for each element on the bridge arm where the primary element is located is calculated using the DC bias current model. The DC bias current of each second bridge arm is compared with the DC bias current of the first bridge arm in the bridge arm where the primary element is located. The element corresponding to the DC bias current of the second bridge arm that is most similar to the DC bias current of the first bridge arm is determined as the primary bridge arm element that causes the DC bias.

6. The DC bias tracing method based on MMC arm parameter asymmetry according to claim 1, characterized in that, The step of comparing the DC bias current of the third arm of the primary arm element calculated by the DC bias current model under different degrees of asymmetry with the DC bias current of the first arm element to determine the first degree of deviation of the primary arm element includes: The DC bias current of the third arm of the primary arm element calculated by the DC bias current model under different degrees of asymmetry is compared with the DC bias current of the first arm of the arm where the primary arm element is located. The degree of asymmetry corresponding to the DC bias current of the third arm element that is most similar to the DC bias current of the first arm element is determined as the first deviation degree of the primary arm element.

7. The DC bias tracing method based on MMC arm parameter asymmetry according to claim 1, characterized in that, The step of calculating the fourth bridge arm DC bias current under parameter asymmetry of other bridge arm elements besides the primary bridge arm element based on the first deviation degree and the first bridge arm DC bias current using the DC bias current model, and determining the secondary bridge arm elements causing DC bias, includes: The DC bias current model, which has been substituted with the first deviation level, is used to sequentially calculate the DC bias current of the fourth bridge arm under the condition of asymmetry of the parameters of the other components in the bridge arm where the primary bridge arm component is located, and the DC bias current of the fourth bridge arm under the condition of asymmetry of the parameters of the components in other bridge arms besides the bridge arm where the primary bridge arm component is located. The element corresponding to the DC bias current of the fourth bridge arm that is most similar to the DC bias current of the first bridge arm in the bridge arm where the primary bridge arm element is located is identified as the secondary bridge arm element that causes the DC bias.

8. The DC bias tracing method based on MMC arm parameter asymmetry according to claim 1, characterized in that, The step of comparing the DC bias current of the fifth bridge arm element calculated by the DC bias current model under different degrees of asymmetry with the DC bias current of the first bridge arm element to determine the second degree of deviation of the second bridge arm element includes: The DC bias current of the fifth bridge arm of the secondary bridge arm element calculated by the DC bias current model under different degrees of asymmetry is compared with the DC bias current of the first bridge arm of the primary bridge arm element. The degree of asymmetry corresponding to the DC bias current of the fifth bridge arm element that is most similar to the DC bias current of the first bridge arm element is determined as the second deviation degree of the secondary bridge arm element.

9. The DC bias tracing method based on MMC arm parameter asymmetry according to claim 1, characterized in that, The repeated execution of steps S4-S5 until the transformer valve-side DC bias current calculated by the DC bias current model matches the actually measured transformer valve-side DC bias current includes: Repeat steps S4-S5 to determine the remaining bridge arm elements causing DC bias, and correct the deviation of all the bridge arm elements causing DC bias until the transformer valve side DC bias current calculated by the DC bias current model matches the actual measured transformer valve side DC bias current.

10. A DC bias tracing system based on MMC arm parameter asymmetry, characterized in that, include: The current model building module is used for MMC-based bridge arm topology and average switching function models. It establishes a DC bias current model under bridge arm parameter asymmetry through component decomposition and correlation derivation. The primary component determination module is used to compare the actual measured DC bias current of the first bridge arm with the DC bias current of the second bridge arm under different single bridge arm parameter asymmetry calculated by the DC bias current model, and to determine the primary bridge arm component that causes the DC bias. The first deviation determination module is used to compare the third arm DC bias current of the primary arm element under different degrees of asymmetry, calculated by the DC bias current model, with the first arm DC bias current to determine the first deviation degree of the primary arm element. The secondary component determination module is used to calculate the DC bias current of the fourth bridge arm under the condition of parameter asymmetry of other bridge arm components besides the primary bridge arm component based on the first deviation degree and the first bridge arm DC bias current, and to determine the secondary bridge arm component that causes DC bias. The second deviation determination module is used to compare the DC bias current of the fifth arm of the secondary arm element under different degrees of asymmetry, calculated by the DC bias current model, with the DC bias current of the first arm element to determine the second deviation degree of the secondary arm element.

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