High harmonic resistance optimization method for converter transformer based on multi-physical field coupling

Abstract

The present application relates to the technical field of transformer design, and particularly relates to a high-order harmonic resistance optimization method for a converter transformer based on multi-physical field coupling. The present application obtains multi-physical field stress response data under high-frequency disturbance; secondly, the electric, thermal and mechanical stress optimization is carried out in different dimensions to respectively inhibit electric field distortion, control high-frequency temperature rise and avoid structure resonance, forming a preliminary design scheme considering single-field performance; then, a multi-physical field coupling mechanism under high-frequency disturbance is constructed based on the scheme, realizing quantitative analysis of mutual influence and superposition effect of each physical field stress; finally, relying on the coupling mechanism, a multi-dimensional stress collaborative regulation strategy is adopted to realize performance balance across physical fields, so that the converter transformer itself has the ability to resist high-order harmonics for a long time, without the need to configure an external AC filter, which not only solves the problem of large filter occupation and restricts the lightweight of the platform, but also overcomes the defect that decoupling design cannot adapt to multi-field coupling disturbance.

Description

Technical Field

[0001] This invention relates to the field of transformer design technology, and more specifically to an optimization method for high-order harmonic resistance of converter transformers based on multi-physics coupling. Background Technology

[0002] With the rapid development of low-cost offshore wind power transmission technology, diode uncontrolled rectifier transmission systems, with their advantages of low cost and simple structure, are gradually replacing traditional flexible DC transmission systems and becoming an important technical solution for deep-sea wind power transmission. However, this system continuously generates a large number of high-order harmonics and has reactive power deficits during operation, causing serious high-frequency disturbance problems. To suppress harmonics and compensate for reactive power, existing technologies must install multiple sets of bulky AC filters, occupying a large amount of space on the offshore platform and restricting the lightweight and compact construction of the platform. At the same time, existing converter transformers generally adopt a separate design approach that decouples electrical, thermal, and mechanical stresses, lacking systematic research and quantitative methods for the coupling effect of multiple physical fields under high-frequency and power frequency superposition conditions. Relying solely on traditional optimization methods such as thickened insulation, redundant cooling, and passive vibration reduction cannot effectively adapt to long-term high-frequency harmonic disturbance conditions, leading to transformers prone to excessive temperature rise, increased vibration, insulation aging and failure, and other faults, making it difficult to meet the long-term stable operation requirements of offshore wind power. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide an optimization method for high-order harmonic resistance of converter transformers based on multi-physics field coupling, in order to solve the problems that existing offshore wind power diode uncontrolled rectification and transmission systems require large-volume filters that restrict the platform's lightweight design, and that traditional converter transformer decoupling designs cannot adapt to high-frequency harmonic multi-field coupling disturbances, resulting in poor harmonic resistance and low reliability of the equipment.

[0004] In a first aspect, embodiments of the present invention provide a method for optimizing the high-harmonic resistance of converter transformers based on multi-physics coupling, the method comprising: Acquire multi-physics stress response data of converter transformers under high-frequency disturbances; The multi-physics stress response data were optimized in terms of electrical stress, thermal stress and mechanical stress dimensions to obtain a preliminary design scheme for performance adaptation in each dimension. Based on the preliminary design scheme, a multi-physics coupling mechanism under high-frequency disturbance is constructed. Based on the aforementioned multi-physics coupling mechanism, a multi-dimensional stress synergistic control strategy is adopted to optimize the transformer's operating characteristics, resulting in a target design scheme that can withstand long-term high-order harmonics.

[0005] Furthermore, the multiphysics stress response data includes: high-frequency potential distribution parameters, temperature rise aging characterization parameters, and structural vibration excitation parameters; The multi-physics stress response data is optimized for electrical stress, thermal stress, and mechanical stress dimensions to obtain preliminary design schemes for performance adaptation in each dimension, including: For the high-frequency potential distribution parameters, electrical stress analysis was carried out through potential gradient measurement and stepped pressure test to obtain initial optimization data for electrical stress control. The electric field distribution of the initial optimization data was then optimized to suppress the electric field amplitude, and design parameters for electrical stress dimension adaptation were obtained. A novel temperature rise-life evaluation model is constructed using empirical aging formulas and high-frequency correction coefficients. The temperature rise aging characterization parameters are then optimized in the thermal stress dimension to obtain design parameters adapted to the thermal stress dimension. By utilizing the vibration characteristics induced by the winding electrodynamics and magnetostrictive forces, and mechanical vibration reduction and control strategies, the vibration excitation parameters of the structure are optimized in the mechanical stress dimension to obtain design parameters adapted to the mechanical stress dimension. By integrating the design parameters for the electrical stress, thermal stress, and mechanical stress dimensions, a preliminary design scheme for performance adaptation in each dimension is obtained.

[0006] Furthermore, for the high-frequency potential distribution parameters, electrical stress analysis is conducted through potential gradient measurement and stepped pressure testing to obtain initial optimization data for electrical stress control. The initial optimization data is then used to optimize the electric field distribution to suppress electric field amplitude, resulting in design parameters adapted to the electrical stress dimension, including: The high-frequency potential distribution parameters were used to measure the potential gradient in the key insulation area of ​​the converter transformer, and the measured potential distribution data of each area were obtained. Using the measured potential distribution data, a stepped voltage test was conducted on the converter transformer at different voltage levels to obtain electric field response data under multiple operating conditions. Based on the electric field response data under multiple operating conditions, the electric stress distribution characteristics of the converter transformer are analyzed to obtain the initial optimization data for electric stress regulation. Based on the initial optimization data of electric stress regulation, the electric field distribution of the converter transformer is optimized in a targeted manner to suppress the electric field amplitude, and design parameters adapted to the electric stress dimension are obtained.

[0007] Furthermore, a novel temperature rise-life evaluation model is constructed using empirical aging formulas and high-frequency correction coefficients. This model optimizes the temperature rise aging characterization parameters in the thermal stress dimension, yielding design parameters adapted to the thermal stress dimension, including: The temperature rise aging characterization parameters are fitted using empirical aging formulas to obtain a basic temperature rise aging calculation model. By iterating the model parameters of the basic temperature rise aging calculation model using the high-frequency correction coefficient, a temperature rise-life evaluation model adapted to high-frequency disturbances is obtained. Based on the temperature rise-life evaluation model, a global thermal stress quantification analysis is performed on the temperature rise aging characterization parameters to obtain thermal stress optimization benchmark data. Based on the aforementioned thermal stress optimization benchmark data, the thermal control parameters of the converter transformer are adapted and iteratively optimized to obtain design parameters adapted to the thermal stress dimension.

[0008] Furthermore, by utilizing the vibration characteristics induced by the winding electrodynamics and magnetostrictive forces, and employing mechanical vibration reduction and control strategies, the mechanical stress dimension of the structural vibration excitation parameters is optimized to obtain design parameters adapted to the mechanical stress dimension, including: By utilizing the interaction mechanism of winding electrodynamics and magnetostrictive force, the vibration excitation parameters of the structure are analyzed to decompose the vibration characteristics and obtain vibration characteristic data under high-frequency disturbance. Based on vibration characteristic data, the structural resonance risk and stress concentration points of the converter transformer are identified to obtain mechanical defect identification data. By utilizing mechanical vibration reduction and control strategies, targeted optimization analysis is performed on mechanical defect identification data to obtain benchmark data for mechanical stress control. Based on the benchmark data for mechanical stress regulation, the structural parameters of the transformer are iteratively optimized and adapted to obtain the design parameters adapted to the mechanical stress dimension.

[0009] Furthermore, based on the preliminary design scheme, the construction of a multi-physics coupling mechanism under high-frequency perturbation includes: Using the design parameters adapted to each dimension in the preliminary design scheme, an analysis model for each single physics field is constructed, resulting in a set of single physics field models. Based on the set of single-physics models, the mutual influence relationships between electro-thermal, thermo-mechanical, and electro-mechanical fields are analyzed to obtain multi-physics coupling correlation data; Based on multi-physics coupling correlation data, we establish coupling boundary conditions and parameter transfer rules between various physics fields to obtain an initial model of the coupling mechanism. The initial model of the coupling mechanism was verified and corrected under multiple operating conditions through simulation, and the multi-physics coupling mechanism under high-frequency disturbance was obtained.

[0010] Furthermore, based on the multi-physics coupling mechanism, a multi-dimensional stress synergistic control strategy is adopted to optimize the transformer's operating characteristics, resulting in a target design scheme that can withstand long-term high-order harmonics, including: By utilizing the coupling mechanism of multiple physical fields, a global simulation analysis of the electro-thermal-mechanical coupling stress response of the converter transformer is performed to obtain the coupling stress distribution data. Based on the coupled stress distribution data, weak links and stress amplification risk points under the synergistic effect of multiple physical fields are identified, and key target data for stress regulation are obtained. A multi-dimensional stress synergistic regulation strategy is adopted to perform cross-physics field synergistic optimization on key target data of stress regulation, and obtain the optimized design parameters after synergistic regulation. Based on the optimized design parameters after coordinated control, the overall design of the transformer is iteratively corrected and verified to obtain the target design scheme that can withstand long-term high-order harmonics.

[0011] Secondly, embodiments of the present invention provide a converter transformer high-harmonic resistance optimization device based on multi-physics field coupling, the device comprising: The acquisition module is used to acquire multi-physics stress response data of converter transformers under high-frequency disturbances; The optimization module is used to perform dimensional optimization of the multi-physics stress response data for electrical stress, thermal stress and mechanical stress respectively, so as to obtain a preliminary design scheme for performance adaptation in each dimension. A construction module is used to construct a multi-physics coupling mechanism under high-frequency disturbances based on the preliminary design scheme. The processing module is used to optimize the transformer's operating characteristics based on the multi-physics coupling mechanism and a multi-dimensional stress synergistic control strategy to obtain a target design scheme that can withstand long-term high-order harmonics.

[0012] Thirdly, embodiments of the present invention provide a computer device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method described in the first aspect or any corresponding embodiment thereof.

[0013] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that cause a computer to perform the method described in the first aspect or any of its corresponding embodiments.

[0014] This invention acquires multi-physics stress response data under high-frequency disturbances. Secondly, by optimizing electrical, thermal, and mechanical stresses in different dimensions, it suppresses electric field distortion, controls high-frequency temperature rise, and avoids structural resonance, forming a preliminary design scheme that balances single-field performance. Then, based on this scheme, it constructs a multi-physics coupling mechanism under high-frequency disturbances, realizing a quantitative analysis of the mutual influence and superposition effects of stresses in each physics field. Finally, relying on the coupling mechanism, it adopts a multi-dimensional stress synergistic control strategy to achieve performance balance across physics fields, enabling the converter transformer itself to withstand high-order harmonics for extended periods without the need for an external AC filter. This solves the problems of large filter footprint and limitations on platform lightweighting, while also overcoming the shortcomings of decoupled designs that cannot adapt to multi-field coupled disturbances. Attached Figure Description

[0015] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating an optimization method for high-harmonic resistance of converter transformers based on multi-physics coupling according to some embodiments of the present invention. Figure 2 This is a flowchart illustrating another optimization method for converter transformer high-order harmonic resistance based on multi-physics coupling according to some embodiments of the present invention. Figure 3 This is a schematic diagram of an optimization framework for converter transformers to withstand high harmonics based on multi-physics coupling according to some embodiments of the present invention; Figure 4 This is a structural block diagram of a converter transformer high-harmonic resistance optimization device based on multi-physics field coupling according to an embodiment of the present invention. Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] According to embodiments of the present invention, a method for optimizing the high-order harmonic resistance of converter transformers based on multi-physics coupling is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0019] This embodiment provides a method for optimizing the high-order harmonic resistance of converter transformers based on multi-physics coupling. Figure 1 This is a flowchart of a method for optimizing the high-harmonic resistance of a converter transformer based on multi-physics coupling according to an embodiment of the present invention, as shown below. Figure 1 As shown, the process includes the following steps: Step S101: Obtain multi-physics stress response data of the converter transformer under high-frequency disturbance.

[0020] In this embodiment, the multiphysics stress response data includes: high-frequency potential distribution parameters, temperature rise aging characterization parameters, and structural vibration excitation parameters; Specifically, high-frequency potential distribution parameters are collected through potential gradient measurement technology. Under high-frequency harmonic conditions, the potential gradient distribution of key insulation areas of the converter transformer (such as winding ends, lead and outgoing line devices, and near electrodes) is tested to obtain the potential change law, electric field concentration point location and field strength amplitude data of each area. At the same time, the electric field withstand capability under different voltage levels is verified by step-pressure test to ensure that the data covers high-frequency disturbance scenarios under all operating conditions.

[0021] Temperature rise aging characterization parameters were collected through temperature rise tests and accelerated aging tests under harmonic conditions. The temperature rise curves, hot spot temperature changes and aging rates of insulation materials of various parts of the transformer under different high-order harmonic contents were recorded, providing experimental basis for subsequent life assessment.

[0022] The structural vibration excitation parameters are obtained through vibration testing and mechanical analysis. The measurement of winding electrodynamic force, winding axial / radial vibration caused by magnetostrictive force of silicon steel sheet, and core lamination vibration response data under high frequency disturbance is used to identify the correspondence between vibration excitation frequency and structural natural frequency. The three types of data together constitute a complete multiphysics stress response dataset.

[0023] Step S102: Dimensional optimization of electrical stress, thermal stress and mechanical stress is performed on the multi-physics stress response data to obtain a preliminary design scheme for performance adaptation in each dimension.

[0024] In this embodiment, regarding electrical stress regulation, based on high-frequency potential distribution parameters and stepped pressure test results, key areas of electric field concentration are located. The electric field distribution is optimized by suppressing electric field amplitude, rounding electrode shape, and locally reinforcing insulation structures, thereby reducing local field strength peaks and improving the transformer's insulation withstand capability under high-frequency disturbances, thus forming design parameters adapted to the electrical stress dimension. Regarding thermal stress regulation, for existing conventional power transformer thermal aging rules, high-frequency correction coefficients are introduced for electrothermal parameters such as electric field strength, field strength application speed, temperature, and vibration frequency, constructing a novel temperature rise regulation mechanism adapted to high-frequency disturbances. The lifespan assessment framework optimizes thermal control design based on temperature rise aging characterization parameters, controls the additional temperature rise caused by high-frequency harmonics, ensures the long-term lifespan of insulation materials, and forms design parameters adapted to the thermal stress dimension. In the mechanical stress control dimension, based on structural vibration excitation parameters, it analyzes the vibration characteristics caused by winding electrodynamics and magnetostriction under high-frequency disturbances. By controlling the core magnetic flux density, optimizing the lead and lead-out device structure, and improving the clamping device design, it avoids structural resonance under high-frequency excitation and reduces the vibration amplitude of the winding and core, forming design parameters adapted to the mechanical stress dimension. Finally, it integrates the adapted design parameters of the electrical, thermal, and mechanical dimensions to obtain a preliminary design scheme that takes into account insulation, temperature rise, and vibration performance.

[0025] Step S103: Based on the preliminary design scheme, construct the multi-physics coupling mechanism under high-frequency disturbance.

[0026] In this embodiment, based on the preliminary design scheme, a multi-physics coupling mechanism under high-frequency disturbance is constructed, including: using the design parameters adapted to each dimension in the preliminary design scheme to construct the analysis model of each single physics field, and obtain a set of single physics field models; based on the set of single physics field models, analyzing the mutual influence relationships between electro-thermal, thermo-mechanical, and electro-mechanical fields, and obtaining multi-physics field coupling correlation data; based on the multi-physics field coupling correlation data, establishing the coupling boundary conditions and parameter transfer rules between each physics field, and obtaining the initial model of the coupling mechanism; and performing simulation verification and correction of the initial model of the coupling mechanism under multiple operating conditions to obtain the multi-physics field coupling mechanism under high-frequency disturbance.

[0027] Specifically, for the electric stress dimension, an electric field analysis model under high-frequency harmonics is established using the optimized electric field distribution parameters, local reinforcement structure parameters, and electrode circularization design data as inputs. This model can simulate the potential gradient distribution, peak electric field strength, and electric field distortion of the key insulation area of ​​the converter transformer under different voltage levels and different harmonic content conditions, accurately reproducing the influence of high-frequency disturbances on the electric field distribution. For the thermal stress dimension, based on the thermal control parameters, high-frequency correction coefficients, and hot spot temperature control indicators of the new temperature rise-life evaluation framework, a thermal field analysis model is constructed. This model can simulate the temperature rise distribution, hot spot temperature changes, and thermal aging rate of insulation materials of windings, cores, and insulating oil under different harmonic currents, and quantify the impact of the additional temperature rise caused by high-frequency harmonics on insulation life. For the mechanical stress dimension, a mechanical vibration analysis model is established using the controlled core magnetic flux density, optimized structural design parameters, and vibration reduction structure configuration data as inputs. This model can simulate the winding axial / radial vibration and core lamination vibration response caused by the winding electrodynamic force and magnetostrictive force under high-frequency disturbances, analyze the matching relationship between the structure's natural frequency and the excitation frequency, and identify resonance risk points.

[0028] The three single-physics models are all built based on the adaptation parameters of the preliminary design scheme. Each model has its own independent analysis boundary and working condition adaptation capability, and together they form the basic model set for subsequent coupled analysis.

[0029] Then, in terms of the analysis of the electro-thermal coupling relationship, the loss changes of the insulating medium under different high-frequency electric field distributions are simulated by the electric field model. The influence of the additional heat generated by the loss on the temperature rise distribution is analyzed by the thermal field model. At the same time, the changes of the dielectric constant and conductivity of the insulating material under different temperature rise conditions are simulated by the thermal field model. The influence of these changes on the distortion of the electric field distribution is analyzed in reverse. The mutual influence coefficient between electric field and temperature rise is quantified to obtain the electro-thermal coupling correlation data. In terms of thermo-mechanical coupling analysis, the thermal expansion and contraction effects of winding conductors, core silicon steel sheets and insulating materials under different temperature rise conditions are simulated by thermal field model. Combined with mechanical vibration model, the influence of structural stress changes caused by thermal deformation on vibration response is analyzed. At the same time, the changes of core magnetic circuit and winding contact state under different vibration amplitudes are simulated by mechanical model to analyze their influence on magnetostrictive force and winding electrodynamic force, which in turn affects temperature rise distribution. The coupling law between temperature rise and mechanical stress is quantified to obtain thermo-mechanical coupling correlation data. In the analysis of electromechanical coupling, the changes in electrode spacing and insulation gap under different vibration displacements were simulated using an electric field model to analyze their impact on the electric field distribution and peak field strength. Simultaneously, the micro-vibrations induced by polarization and electrostriction of the insulating medium under different electric field distributions were simulated using a mechanical model to analyze their superposition effect on the structural vibration response, quantifying the mutual influence between the electric field and mechanical stress, and obtaining electromechanical coupling correlation data. These three types of coupling correlation data comprehensively reveal the bidirectional influence mechanism between the individual physical fields, providing a quantitative basis for the subsequent establishment of coupling boundary conditions.

[0030] For the electro-thermal coupling boundary, based on the electro-thermal coupling correlation data, the heat transfer boundary from electric field loss to thermal field is defined, the loss-heat conversion coefficient under different electric field strengths and frequencies is clarified, and the material property transfer boundary from thermal field temperature change to electric field is defined. The mapping relationship between temperature-dielectric constant and temperature-conductivity is established to realize the bidirectional parameter transfer between electric field and thermal field. For the thermo-mechanical coupling boundary, based on the thermo-mechanical coupling correlation data, the thermal deformation transfer boundary from the temperature rise change of the thermal field to the mechanical field is defined, and the mapping relationship between temperature and structural stress and temperature and elastic modulus is established. At the same time, the friction loss transfer boundary from the vibration displacement of the mechanical field to the thermal field is defined, and the mechanical loss-heat conversion coefficient under different vibration amplitudes is clarified, so as to realize the bidirectional parameter transfer between the thermal field and the mechanical field. For electromechanical coupling boundaries, based on electromechanical coupling correlation data, we define the geometric boundary change transmission rules from mechanical field vibration displacement to electric field, establish the mapping relationship between vibration displacement and electrode spacing and vibration displacement and insulation gap, define the electrostrictive force transmission rules from electric field distribution to mechanical field, clarify the electrostrictive force-vibration response conversion coefficient under different electric field intensities, and realize bidirectional parameter transmission between electric field and mechanical field.

[0031] Based on this, the individual physics models are integrated with the coupled boundary conditions and parameter transfer rules to construct an initial coupled model that includes three physical fields—electric, thermal, and mechanical—and their mutual coupling relationships. This model can initially reflect the interaction and transmission path of stress in each physical field under high-frequency disturbances, providing a basic framework for subsequent simulation verification and correction.

[0032] Finally, multiple sets of typical high-frequency disturbance conditions were acquired, covering combinations of different harmonic orders, harmonic content, voltage levels, and load levels. Simultaneously, actual operating data of the offshore wind power diode uncontrolled rectifier system were introduced as input to conduct multi-condition simulation analysis of the initial coupled model, obtaining coupled simulation results of electric field distribution, temperature rise variation, and vibration response under different conditions. Secondly, the simulation results were compared and analyzed with the acquired multi-physics stress response measured data to identify deviations between the initial model's coupled boundary conditions and parameter transfer rules and actual operating conditions, such as deviations in electric field loss calculation, errors in thermal deformation coefficients, and distortions in vibration response transmission. Subsequently, based on the deviation analysis results, the coupled model was iteratively corrected, adjusting the conversion coefficients, mapping relationships, and parameter transfer rules of the electro-thermal, thermo-mechanical, and electro-mechanical coupling boundaries, optimizing the operating condition adaptation parameters of each single-physics field model, and controlling the error between the simulation results and the measured data within the allowable range. Finally, the coupled model after multi-condition verification and correction was completed, which can accurately reflect the dynamic coupling effect between the electric field, thermal field, and mechanical field inside the converter transformer under high-frequency disturbances, quantify the coupling amplification factor and failure threshold of each physical field stress, clarify the synergistic effect law and mutual influence mechanism of electro-thermal-mechanical stress under high-frequency harmonic conditions, and form a complete multi-physics field coupling mechanism under high-frequency disturbances.

[0033] Step S104: Based on the multi-physics coupling mechanism, a multi-dimensional stress synergistic control strategy is adopted to optimize the transformer operation characteristics and obtain a target design scheme that can withstand long-term high-order harmonics.

[0034] In this embodiment, based on the multi-physics coupling mechanism, a multi-dimensional stress synergistic control strategy is adopted to optimize the transformer's operating characteristics, resulting in a target design scheme that can withstand long-term high-order harmonics. This includes: utilizing the multi-physics coupling mechanism to perform a full-domain simulation analysis of the electro-thermal-mechanical coupled stress response of the converter transformer, obtaining coupled stress distribution data; identifying weak points and stress amplification risk points under the synergistic effect of multi-physics fields based on the coupled stress distribution data, obtaining key target data for stress control; employing a multi-dimensional stress synergistic control strategy to perform cross-physics synergistic optimization of the key target data for stress control, obtaining optimized design parameters after synergistic control; and iteratively correcting and verifying the overall transformer design based on the optimized design parameters after synergistic control, thus obtaining a target design scheme that can withstand long-term high-order harmonics.

[0035] Specifically, by utilizing the established rules for the transfer of electrical, thermal, and mechanical physical field parameters and coupling boundary conditions, the limitations of the single analysis in traditional decoupling simulation are abandoned. Combined with the long-standing high-frequency harmonic superposition power frequency operation condition of offshore wind power diode uncontrolled rectifier transmission system, high-order harmonic disturbances of different numbers and amplitudes are used as excitation sources, comprehensively covering components such as transformer windings, iron cores, insulating media, lead wire structures, and clamping and fixing devices.

[0036] During the simulation, the localized electric stress concentration effect caused by high-frequency electric field distortion, the thermal stress effect caused by the accumulation of harmonic losses, and the mechanical vibration stress effect generated by the excitation of winding electrodynamics and magnetostrictive forces are calculated simultaneously. The dynamic coupling, superposition, mutual influence, and stress amplification process among these three factors are accurately depicted. Through full-domain refined simulation, the electric field distribution, temperature rise gradient, vibration amplitude, stress magnitude, and spatiotemporal distribution patterns at various locations of the transformer are fully obtained, forming a coupled stress distribution dataset containing multiple operating conditions, multiple locations, and multiple dimensions. This provides a comprehensive, realistic, and quantitative data foundation for subsequent risk identification and precise control.

[0037] Based on the electro-thermal-mechanical coupled stress distribution data obtained from the full-domain simulation, weak areas and stress amplification risk points of the equipment under the synergistic effect of multiple physical fields are identified, and key target data for stress regulation are accurately extracted. Due to the coupling superposition and linkage degradation characteristics of various physical fields of the transformer under high-frequency harmonic conditions, areas that meet the standards of a single physical field are prone to problems such as stress exceeding the standard and performance degradation due to the coupling effect of multiple fields. Therefore, this step conducts a detailed analysis of the coupled stress distribution data in layers, regions, and items.

[0038] First, the coupled stress values ​​of each region were compared and verified with design standards such as allowable field strength of transformer insulation, thermal aging tolerance temperature, and structural vibration safety threshold to identify weak structural areas with insufficient stress margin and local exceedances. Second, a deep analysis of the multi-field cascading failure mechanism of electrothermal, thermal vibration, and vibration-induced field distortion was conducted to accurately identify key risk points where stress superimposed and amplified under high-frequency disturbances, distinguishing between independent stress risks and coupled-derived risks. Finally, considering the long-term continuous operation characteristics of offshore wind power, potential hazards such as insulation aging, structural loosening, and overheating failure under long-term harmonic accumulation were predicted. All risk points were quantified, classified, and ranked to clarify the structural parts, stress types, and performance indicators that require key optimization and control. Ultimately, clear and hierarchical key target data for stress control were formed, providing clear optimization targets for cross-physics field collaborative optimization.

[0039] Traditional transformer design often employs independent optimization models for electrical, thermal, and mechanical stresses, which easily leads to single-dimensional performance optimization followed by performance imbalance after multi-field coupling. Therefore, this paper utilizes the laws governing multi-physics field coupling to conduct overall optimization with the core objective of "multi-stress synergistic balance and optimal global performance." To address the issue of excessive insulation electrical stress caused by concentrated electric fields, while optimizing electrical parameters through electrode rounding, local insulation reinforcement, and electric field amplitude suppression, heat dissipation structures and mechanical vibration reduction parameters are simultaneously matched to avoid loss accumulation and increased vibration after insulation optimization. For the thermal stress aging problem caused by harmonic losses, thermal control parameters are corrected based on a high-frequency temperature rise-life evaluation framework to reduce the high-frequency temperature rise increment. Simultaneously, the impact of temperature changes on structural deformation and electric field distribution is checked to avoid thermal coupling risks. For the mechanical vibration and resonance problems caused by high-frequency excitation, vibration reduction optimization is achieved by adjusting the core magnetic flux density, optimizing the structural layout and clamping devices, and the electric field and temperature rise characteristics after vibration improvement are checked in reverse. Through multiple rounds of cross-physics field iterative adaptation and parameter linkage correction, the shortcomings and coupling side effects of single-dimensional optimization are completely eliminated, and finally, synergistic control and optimization design parameters that take into account insulation tolerance, thermal aging life and structural vibration resistance are obtained.

[0040] Based on the optimized design parameters after multi-dimensional coordinated regulation, the overall structure and electrical parameters of the converter transformer are comprehensively iterated and corrected, and multi-condition simulation verification is performed to obtain a target design scheme for the transformer that can withstand long-term high-order harmonic disturbances.

[0041] It should be noted that, based on the core principle of collaborative optimization parameters, a systematic iterative update was conducted on the entire design, including transformer insulation structure design, electrode shape parameters, heat dissipation system configuration, core magnetic flux density parameters, winding clamping structure, and lead wire output device. This replaced the conservative and poorly adaptable outdated parameters from the traditional decoupled design, achieving full structural and parameter adaptation to high-frequency harmonic operation conditions. After the design iteration was completed, multiple extreme simulation conditions with different harmonic contents, load ratios, and operating durations were set up for the extreme operating scenario of offshore wind power diode uncontrolled rectifier systems without filters and with long-term harmonic superposition. These simulations comprehensively verified and validated the optimized transformer's electric field tolerance, temperature rise aging life, and structural vibration stability.

[0042] Simultaneously, the stress levels of multi-physics fields and the durability performance of the equipment before and after optimization were compared, the stress suppression effect and performance margin under multi-field coupling were verified, local design defects and parameter adaptation errors were eliminated, and multiple iterative corrections and performance closed-loop verifications were completed. Finally, a high-performance converter transformer target design scheme that can withstand high-order harmonic disturbances for a long time, eliminate insulation failure and aging acceleration problems, and adapt to low-cost, unfiltered transmission systems at sea was formed.

[0043] In this embodiment, the electrical stress, thermal stress, and mechanical stress dimensions are optimized for the multiphysics stress response data to obtain preliminary design schemes with performance adaptation in each dimension, such as... Figure 2 As shown, it includes: Step S201: For the high-frequency potential distribution parameters, conduct electric stress analysis through potential gradient measurement and stepped pressure test to obtain initial optimization data for electric stress control, and optimize the electric field distribution of the initial optimization data to suppress the electric field amplitude, thereby obtaining design parameters for electric stress dimension adaptation.

[0044] In this embodiment, for high-frequency potential distribution parameters, electrical stress analysis is conducted through potential gradient measurement and stepped pressure test to obtain initial optimized data for electrical stress control. The initial optimized data is then used to optimize the electric field distribution to suppress electric field amplitude, resulting in design parameters adapted to the electrical stress dimension, including: Step A1: Measure the potential gradient in the key insulation area of ​​the converter transformer using high-frequency potential distribution parameters to obtain measured potential distribution data for each area.

[0045] Specifically, based on the acquired high-frequency potential distribution parameters, key insulation areas prone to electric field concentration, such as winding ends, electrode connections, and the periphery of leads, were selected as the detection targets, and potential gradient measurements were systematically carried out. The measurement process was matched to the high-frequency harmonic operation conditions of offshore wind power, simulating a high-frequency disturbance environment throughout. Potential values ​​and gradient changes at different locations were collected point by point, and the high and low potential distribution, trends, and local extreme points of each insulation area were fully recorded. Through standardized on-site testing and data acquisition procedures, the core insulation structure of the transformer was comprehensively covered. Finally, all measurement point information was compiled and summarized to form complete, accurate, and usable measured data of potential distribution in each area for subsequent analysis, laying a solid data foundation for subsequent pressure testing and electrical stress analysis.

[0046] Step A2: Using the measured potential distribution data, conduct stepped voltage tests on the converter transformer at different voltage levels to obtain electric field response data under multiple operating conditions.

[0047] Specifically, multi-stage stepped voltage tests were conducted on the converter transformer using measured potential distribution data to comprehensively collect electric field response data under different operating conditions. Multiple gradient voltage levels were defined based on the actual operating voltage range of the system, gradually increasing from the normal operating voltage to the ultimate test voltage, maintaining a constant high-frequency disturbance environment throughout to simulate the real operating state of the diode uncontrolled rectifier system. During the stable operation phase of each voltage level, the electric field changes, potential fluctuations, and field strength amplitude of the transformer as a whole and in each insulation area were continuously monitored, recording the dynamic changes in the electric field during voltage rise and fall. Through stepped tests covering the entire voltage range, the electric field performance under different operating conditions was fully reproduced. All test results were integrated to form complete electric field response data under multiple operating conditions, providing comprehensive experimental basis for the analysis of electrical stress characteristics.

[0048] Step A3: Based on the multi-condition electric field response data, conduct an analysis of the electric stress distribution characteristics of the converter transformer to obtain the initial optimization data for electric stress regulation.

[0049] Specifically, an in-depth analysis of the electrical stress distribution characteristics across the entire converter transformer was conducted based on multi-condition electric field response data. First, the distribution patterns of the electric field under different voltages and high-frequency disturbance intensities were analyzed to locate stress concentration areas with excessively high electric field strength and significant potential abrupt changes. The specific forms and impact range of electric field distortion caused by high-frequency harmonics were determined. Simultaneously, the actual electrical stress levels in each region were calculated against the transformer insulation material tolerance standards to assess the insulation safety margin of the existing structure under high-frequency operating conditions and identify deficiencies and shortcomings in the current electric field design. Combining the correlation between potential, electric field strength, and voltage, various electrical stress indicators were quantified to identify the core issues of excessive electric field amplitude and localized exceeding of electric field strength limits. The comprehensive analysis results were then integrated and processed to finally output initial optimization data for electrical stress control that can guide optimization efforts.

[0050] Step A4: Based on the initial optimization data of electric stress control, the electric field distribution of the converter transformer is optimized in a targeted manner to suppress the electric field amplitude, and the design parameters adapted to the electric stress dimension are obtained.

[0051] Specifically, based on the initial optimization data for electric stress regulation, targeted optimization and modification were implemented on the internal electric field distribution of the converter transformer to suppress abnormal electric field amplitudes. For areas with concentrated electric fields and excessive amplitudes identified in the analysis, the electric field morphology was reconstructed by methods such as rounding the electrode contour, locally thickening the insulation layer, and adjusting the relative positions of components, thereby weakening local field strength peaks and improving the overall electric field uniformity. During the optimization process, the electric field operation status under high-frequency conditions was repeatedly verified to ensure that the electric field amplitude was controlled within the allowable insulation range, while also considering the coordination between structural layout and electrical performance. After multiple rounds of adjustments, simulations, and verifications, electric stress-related defects were resolved one by one, completing the comprehensive optimization of the electric field structure. Ultimately, design parameters were formed that met the requirements for high-frequency harmonic operation and were adapted to the electric stress dimension.

[0052] As an example, taking the 35kV commutation transformer supporting the uncontrolled rectifier system of offshore wind power diodes as the application object, first, set the high-frequency harmonic frequency of the system to 150Hz, select three key insulation regions including the winding end, main insulation, and lead insulation, carry out potential gradient measurement with a measurement point spacing of 5cm, measure the potentials at both ends of the winding end to be 34.8kV and 2.1kV respectively, calculate the potential gradient in this region to be 654kV / m, synchronously collect the potential values in other regions, and organize them to form complete measured data of the potential distribution; then, based on the previously measured data, divide five levels of stepped voltages of 0.6 times, 0.8 times, 1.0 times, 1.2 times, and 1.4 times the rated voltage, corresponding voltage values of 21kV, 28kV, 35kV, 42kV, 49kV, keep the 150Hz high-frequency harmonic disturbance unchanged throughout the process, each level of voltage runs stably for ten minutes and data is collected, measure the average field strength of the main insulation under the rated voltage to be 220kV / m and the electric field amplitude to be ±18kV / m, the peak value of the local field strength under the 1.4 times overvoltage condition reaches 360kV / m and the electric field amplitude is ±32kV / m, summarize to obtain the electric field response data under multiple conditions; then, conduct a comparison and analysis in combination with two thresholds of the allowable field strength of 280kV / m and the allowable electric field amplitude of ±20kV / m of the transformer insulation material, determine that the field strength and electric field amplitude at the winding end exceed the standard under the voltage conditions of 1.2 times and above, clarify that the distortion is concentrated at the winding corner and the lead corner, and accordingly determine the optimization goal of controlling the local field strength within 280kV / m and reducing the electric field amplitude to within ±20kV / m and the key area, forming the initial optimized data for electric stress regulation; finally, according to the optimized data, adopt the electrode rounding and local insulation thickening scheme, adjust the electrode fillet at the winding end from 5mm to 12mm, and increase the insulation thickness at the key position of the lead from 8mm to 12mm. After optimization,复测 the local field strength under the highest voltage condition to be 272kV / m and the electric field amplitude is stable at ±17kV / m, and all indicators meet the design requirements. Finally, determine the electrode fillet size, insulation thickness, insulation material selection, etc. as the design parameters for the adaptation of the electric stress dimension of this transformer.

[0053] Step S202, construct a new temperature rise-life evaluation model by using the aging empirical formula and the high-frequency correction coefficient, conduct an optimization analysis of the temperature rise aging characterization parameters in terms of the thermal stress dimension, and obtain the design parameters adapted to the thermal stress dimension.

[0054] In the embodiment of the present application, construct a new temperature rise-life evaluation model by using the aging empirical formula and the high-frequency correction coefficient, conduct an optimization analysis of the temperature rise aging characterization parameters in terms of the thermal stress dimension, and obtain the design parameters adapted to the thermal stress dimension, including: Step B1, fit the temperature rise aging characterization parameters by using the aging empirical formula to obtain the basic temperature rise aging calculation model.

[0055] Specifically, based on empirical aging formulas, data fitting was performed on the temperature rise aging characterization parameters of converter transformers to build a basic temperature rise aging calculation model. First, basic characterization data such as temperature rise, operating time, and insulation aging degree of the transformer under normal power frequency conditions were collected to clarify the correspondence between temperature rise changes and insulation aging. The measured data were substituted into the classic empirical aging formulas, and the basic coefficients of the formulas were corrected through data fitting and parameter calibration to ensure that the calculation results match the actual temperature rise aging patterns of the transformers. This model is applicable to normal operating environments and can accurately calculate the temperature rise state of equipment and the aging rate of insulation materials under power frequency conditions, clearly reflecting the intrinsic relationship between temperature rise and aging. Finally, the basic temperature rise aging calculation model was completed, providing an initial framework for subsequent model upgrades and optimizations.

[0056] Step B2 involves iterating the model parameters of the basic temperature rise aging calculation model using high-frequency correction coefficients to obtain a temperature rise-life evaluation model adapted to high-frequency disturbances.

[0057] Specifically, high-frequency correction coefficients adapted to on-site operating conditions are introduced to iteratively update the parameters of the established basic temperature rise aging calculation model, creating a temperature rise-life evaluation model adaptable to high-frequency disturbance environments. Since high-frequency harmonics additionally increase equipment losses and exacerbate temperature rise, conventional models cannot accurately reflect this characteristic. Therefore, multiple sets of specialized correction coefficients are set, taking into account the characteristics of loss increments and temperature shifts caused by high-frequency disturbances. These coefficients are embedded into the basic model, and the temperature rise calculation parameters and aging rate parameters within the model are repeatedly iteratively adjusted to continuously correct calculation deviations, enabling the model to quantify the impact of high-frequency harmonics on temperature rise. The adjusted model can accurately simulate the temperature rise trend of transformers under high-frequency disturbances, estimate the remaining service life of insulation, and ultimately obtain a professional temperature rise-life evaluation model to support subsequent thermal stress analysis.

[0058] Step B3: Based on the temperature rise-life evaluation model, perform a full-domain thermal stress quantification analysis on the temperature rise aging characterization parameters to obtain thermal stress optimization benchmark data.

[0059] Specifically, using the established temperature rise-life evaluation model, a comprehensive quantitative analysis of thermal stress was conducted on all temperature rise aging characterization parameters to extract baseline data for thermal stress optimization. Characterization parameters such as temperature, harmonic content, and operating load of each transformer component were input into the model. The actual thermal stress magnitude of windings, core, and insulating oil was calculated by region and operating condition. The temperature rise increment under high-frequency disturbances, the thermal stress distribution range, and the aging risk level under long-term operation were statistically analyzed. High-temperature areas and areas exceeding thermal stress limits were comprehensively investigated, quantifying the impact of thermal stress on the insulation life of the equipment and distinguishing between normal temperature rise and abnormal temperature rise induced by high-frequency harmonics. Through systematic quantitative analysis, the characteristics of thermal stress distribution, key control indicators, and existing design shortcomings were identified, and baseline data for thermal stress optimization was compiled to clarify the optimization direction of the thermal control system.

[0060] Step B4: Based on the thermal stress optimization benchmark data, the thermal control parameters of the converter transformer are adapted and iteratively optimized to obtain the design parameters adapted to the thermal stress dimension.

[0061] Specifically, referring to the obtained thermal stress optimization benchmark data, various thermal control parameters of the converter transformer were iteratively optimized for adaptability to determine the design parameters adapted to the thermal stress dimension. For the identified high-temperature areas and excessive thermal stress issues, thermal control parameters such as heat dissipation pipe layout, cooling medium flow rate, heat dissipation area, and operating temperature rise threshold were adjusted one by one to optimize the overall heat dissipation system of the equipment. After each round of parameter adjustment, the temperature rise and aging status under high-frequency operating conditions were re-verified using a temperature rise-life evaluation model to determine whether the thermal stress had returned to a safe range. This process was iterated multiple times until all indicators met the standards. The optimization process considered heat dissipation efficiency, equipment energy consumption, and structural space constraints to ensure the practicality and stability of the thermal control scheme. Ultimately, the design parameters for the thermal stress dimension were obtained, which can effectively control high-frequency temperature rise, delay insulation aging, and fully adapt to high-frequency disturbance conditions.

[0062] As an example, a complete process demonstration is carried out using a 35kV converter transformer for offshore wind power as the application object, and related model concepts are explained simultaneously: the insulation six-degree aging rule commonly used in power equipment is adopted, and the formula relationship is that the insulation life decay ratio is equal to 2 raised to the power of (measured temperature minus reference temperature divided by 6). Transformer data under normal power frequency operating conditions are collected, the insulation reference temperature is set to 90℃ and the design life is 20 years. The formula coefficient is fitted by combining measured temperature rise aging data of different temperatures and operating times, and a basic temperature rise aging calculation model suitable for power frequency environment is built. Because high-frequency harmonics increase equipment losses and exacerbate heat generation, a high-frequency correction coefficient K=1.3 is introduced to iteratively update the original model parameters, resulting in a temperature rise-life evaluation model. This model is a specialized evaluation model constructed by superimposing additional losses and temperature rise offsets caused by high-frequency harmonics on the traditional power frequency temperature rise aging calculation model. It can quantify the relationship between temperature rise changes, insulation aging rates, and remaining service life of various parts of the transformer under high-frequency disturbances, accurately reflecting the thermal aging law of equipment under harmonic conditions. Then, the measured temperature rise aging characterization parameters, such as winding hot spot 99℃, core 88℃, and insulating oil 82℃, are substituted into the evaluation model for calculation to obtain the winding area life. The life decay ratio was approximately 3.676, indicating a severely excessive aging rate. However, the thermal stress in the core and insulating oil area was within a safe range. Based on this, the optimization target was clearly defined: the winding hot spot temperature should be controlled below 93℃, and the life decay ratio should not exceed 2.0. Benchmark data for thermal stress optimization was compiled. Finally, the thermal control parameters were iteratively optimized based on the benchmark data. The cooling oil circulation flow rate was adjusted from 8 m³ / h to 11 m³ / h, and the heat dissipation pipe layout was optimized. After optimization, the winding hot spot temperature under high-frequency operating conditions dropped to 92℃, and the life decay ratio was approximately 1.46, meeting the control requirements. Finally, parameters such as cooling medium flow rate, pipe structure, and temperature control threshold were determined, forming design parameters adapted to the thermal stress dimension.

[0063] Step S203: Utilizing the vibration characteristics induced by the winding electrodynamics and magnetostrictive force, and the mechanical vibration reduction and control strategy, the mechanical stress dimension of the structural vibration excitation parameters is optimized and analyzed to obtain design parameters adapted to the mechanical stress dimension.

[0064] In this embodiment, the vibration characteristics induced by winding electrodynamics and magnetostrictive force, along with mechanical vibration reduction and control strategies, are used to optimize the mechanical stress dimension of the structural vibration excitation parameters, resulting in design parameters adapted to the mechanical stress dimension, including: Step C1: Using the interaction mechanism of winding electrodynamics and magnetostrictive force, the vibration characteristics of the structural vibration excitation parameters are decomposed and analyzed to obtain vibration characteristic data under high-frequency disturbance.

[0065] Specifically, this step combines the interaction mechanism of winding electrodynamics and the magnetostrictive force of silicon steel sheets to comprehensively decompose and analyze the vibration characteristics of the acquired structural vibration excitation parameters, extracting vibration characteristic data under high-frequency disturbances. It delves into the excitation effect of current-generated electrodynamics on the axial and radial directions of the windings under high-frequency harmonic effects, as well as the vibration law of the iron core laminations induced by magnetostriction, clarifying the generation mechanism and action mode of the two types of vibration sources. Combining the vibration excitation parameters, it distinguishes the vibration amplitude, vibration frequency, vibration transmission path, and other information under different high-frequency frequencies and load conditions, decomposing the overall vibration signal and separating different components such as winding vibration, iron core vibration, and auxiliary structure vibration. It fully records the variation law, peak characteristics, and propagation characteristics of vibration under high-frequency disturbances, integrating all analysis results to form detailed vibration characteristic data.

[0066] Step C2 involves identifying the structural resonance risk and stress concentration points of the converter transformer based on vibration characteristic data, thereby obtaining mechanical defect identification data.

[0067] Specifically, vibration characteristic data is used to examine the overall structure of the converter transformer, accurately identify structural resonance risks and stress concentration points under high-frequency operating conditions, and compile mechanical defect identification data. The excitation frequency in the vibration characteristics is compared with the natural frequencies of components such as the transformer core, windings, clamping devices, and lead structures to determine if they are close or coincident, thereby locating structural locations prone to high-frequency resonance. Simultaneously, the vibration amplitude and transmission path are combined to analyze the structural stress distribution under vibration, identify weak points with mechanical stress concentration and uneven structural stress, and assess potential problems such as component loosening, deformation, and fatigue damage caused by resonance and stress concentration. All risk points are classified, labeled, and quantitatively rated, with complete records of defect location, risk type, and severity, ultimately forming mechanical defect identification data.

[0068] Step C3 involves using mechanical vibration reduction and control strategies to perform targeted optimization analysis on the mechanical defect identification data, thereby obtaining benchmark data for mechanical stress control.

[0069] Specifically, for the identified high-frequency resonance defects in the iron core, a tuning and vibration isolation control approach was adopted. By reducing the working magnetic flux density of the iron core, the stiffness and equivalent mass distribution of the iron core were changed, thereby shifting the natural frequency of the structure and completely escaping the 300Hz high-frequency harmonic excitation resonance range. Combined with simulation iteration, the optimized standard of reducing the iron core magnetic flux density from 1.6T to 1.4T and adjusting the iron core natural frequency to the safe range of 250Hz–260Hz was determined. For the stress concentration defects in the winding clamping structure, a structural reinforcement and stress distribution control approach was adopted. By thickening the clamping steel plate and optimizing the fastening arrangement, the problem of uneven local stress was eliminated, and the peak value of the structural mechanical stress was limited to not exceeding the allowable threshold of 140MPa for materials.

[0070] To address the defects of excessive high-frequency vibration amplitude and severe vibration transmission, a damping and limiting control strategy was adopted. This included optimizing the pre-tightening torque of the winding clamping device, upgrading the lead wire support structure, and adding a vibration damping buffer layer. This weakened the transmission and superposition effects of high-frequency vibration in the overall structure, and determined that the vibration amplitude of key parts of the machine should be controlled within 0.12 mm. By matching corresponding vibration reduction, frequency modulation, reinforcement, and damping optimization schemes for each resonance defect, stress defect, and excessive vibration defect, the rectification direction, structural adjustment parameters, and performance control thresholds for each defect were quantified. This resulted in a multi-dimensional targeted optimization analysis, and the final summary formed a mechanical stress control benchmark data that included core magnetic flux density limits, structural natural frequency ranges, mechanical stress thresholds, upper limits of vibration amplitude, and structural reinforcement standards.

[0071] Step C4: Based on the mechanical stress control benchmark data, iteratively optimize and adapt the transformer structural parameters to obtain the design parameters adapted to the mechanical stress dimension.

[0072] Specifically, guided by the benchmark data for mechanical stress control output from the steps, multiple rounds of iterative optimization and adaptation debugging were performed on various structural parameters of the converter transformer to determine the design parameters for adapting the mechanical stress dimension. According to the benchmark data requirements, key parameters such as core magnetic flux density, winding clamping force, lead wire fixing method, outgoing line device shape, and overall support structure were adjusted sequentially to change the structure's natural frequency away from the high-frequency excitation range. Simultaneously, component shapes and connection methods were optimized to disperse mechanical stress. After each parameter adjustment, the vibration and stress state under high-frequency operating conditions were re-simulated and tested to verify the actual effect of vibration reduction and stress control. Parameters were continuously fine-tuned based on the test results. Iterative optimization was repeated until the equipment completely avoided high-frequency resonance problems, and both mechanical stress and vibration amplitude were within safe ranges. Finally, design parameters for the mechanical stress dimension that could resist the influence of high-frequency vibration and exhibit excellent structural stability were obtained.

[0073] It should be noted that the winding electrodynamic force and magnetostrictive force are the mechanisms by which the two core vibration sources of the converter transformer are generated and function: when alternating current flows through the winding, the current-carrying conductor generates alternating electrodynamic force in the magnetic field, which in turn induces axial and radial reciprocating vibration of the winding; the silicon steel sheets in the core undergo periodic expansion and contraction under the action of the alternating magnetic field, driving the core to vibrate as a whole. Under high-frequency harmonic conditions, these two forces continuously output high-frequency vibration excitation. The mechanical vibration reduction and control strategy is a series of comprehensive optimization methods adopted to address problems such as vibration, resonance, and stress concentration. It mainly involves adjusting the magnetic flux density of the core to change the natural frequency of the structure to avoid the resonance range, optimizing the component structure and connection method to disperse mechanical stress, and strengthening the clamping and outgoing wire devices to weaken vibration transmission, thereby reducing the vibration amplitude, controlling structural stress, and ensuring the long-term stable operation of the equipment's mechanical structure.

[0074] Step S204: Integrate the design parameters for adapting the dimensions of electrical stress, thermal stress and mechanical stress to obtain a preliminary design scheme for adapting the performance of each dimension.

[0075] In this embodiment, the optimized electrical stress, thermal stress, and mechanical stress are summarized and integrated. Electrical parameters such as electrode size and insulation thickness, thermal control parameters such as cooling medium flow rate and temperature control threshold, and structural parameters such as core magnetic flux density, component thickness, and fastening standards are uniformly incorporated into the overall design framework. The compatibility and adaptability of various parameters are checked in a coordinated manner to avoid conflicts between single-dimensional optimized parameters. The overall matching is completed in combination with the operating characteristics of offshore wind power without filters and long-term harmonic superposition. Finally, a preliminary design scheme for converter transformer that takes into account insulation tolerance, temperature rise control, vibration resistance stability, and the matching of various physical field performances is formed.

[0076] As a complete example, such as Figure 3 As shown, this paper takes a 35kV converter transformer used in an uncontrolled rectifier system for offshore wind power diodes as an example and implements the complete design process: In the electrical stress control stage, potential distribution and multi-condition electric field response data of key insulation areas under high-frequency conditions are obtained through potential gradient measurement and stepped pressure test. The electric field concentration problem in areas such as the winding ends is analyzed. The electric field distribution is optimized by electrode rounding and local insulation thickening to suppress the electric field amplitude to a safe range and obtain electrical stress adaptation parameters. In the thermal stress control stage, a basic temperature rise aging model is constructed based on the aging empirical formula. A high-frequency correction coefficient is introduced to obtain a temperature rise-life evaluation model adapted to high-frequency disturbances. The thermal stress quantitative analysis of the domain identifies the problem of excessive hot spots in the winding, optimizes the cooling oil flow and heat dissipation structure, and obtains thermal stress adaptation parameters. In the mechanical stress control stage, the vibration characteristics caused by the winding electrodynamics and magnetostriction are analyzed to identify core resonance and stress concentration defects in the clamping structure. By reducing the core magnetic flux density, thickening the clamping steel plate, and optimizing the structural design to avoid high-frequency resonance, mechanical stress adaptation parameters are obtained. Finally, based on the adaptation parameters of the above three dimensions, an electro-thermal-mechanical multi-physics coupling mechanism is constructed. Through the internal stress collaborative control method, cross-physics performance balance is achieved, ultimately forming a converter transformer design scheme that can withstand long-term high-order harmonic disturbances.

[0077] This embodiment also provides a converter transformer high-harmonic resistance optimization device based on multi-physics coupling. This device is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0078] This embodiment provides a converter transformer high-harmonic resistance optimization device based on multi-physics coupling, such as... Figure 4 As shown, it includes: The acquisition module 401 is used to acquire multi-physics stress response data of the converter transformer under high-frequency disturbances; The optimization module 402 is used to perform dimensional optimization of electric stress, thermal stress and mechanical stress on the multi-physics stress response data respectively, so as to obtain a preliminary design scheme with performance adaptation in each dimension. Module 403 is used to construct a multi-physics coupling mechanism under high-frequency disturbances based on the preliminary design scheme. Processing module 404 is used to optimize the operating characteristics of transformers based on the multi-physics coupling mechanism and adopt a multi-dimensional stress synergistic control strategy to obtain a target design scheme that can withstand long-term high-order harmonics.

[0079] In this embodiment, the multiphysics stress response data includes: high-frequency potential distribution parameters, temperature rise aging characterization parameters, and structural vibration excitation parameters; In this embodiment, the optimization module 402 is used to conduct electrical stress analysis on high-frequency potential distribution parameters through potential gradient measurement and stepped pressure test to obtain initial optimization data for electrical stress control, and to optimize the electric field distribution of the initial optimization data to suppress electric field amplitude, thereby obtaining design parameters adapted to the electrical stress dimension; to construct a new temperature rise-life evaluation model using aging empirical formulas and high-frequency correction coefficients, and to conduct thermal stress dimension optimization analysis on the temperature rise aging characterization parameters, thereby obtaining design parameters adapted to the thermal stress dimension; to conduct mechanical stress dimension optimization analysis on the structural vibration excitation parameters using the vibration characteristics induced by winding electrodynamics and magnetostrictive force and mechanical vibration reduction control strategies, thereby obtaining design parameters adapted to the mechanical stress dimension; and to integrate the design parameters adapted to the electrical stress, thermal stress, and mechanical stress dimensions to obtain a preliminary design scheme for performance adaptation in each dimension.

[0080] In this embodiment, the optimization module 402 is used to measure the potential gradient of the key insulation area of ​​the converter transformer using high-frequency potential distribution parameters to obtain measured potential distribution data of each area; to conduct stepped voltage tests on the converter transformer at different voltage levels using the measured potential distribution data to obtain electric field response data under multiple operating conditions; to analyze the electric stress distribution characteristics of the converter transformer based on the electric field response data under multiple operating conditions to obtain initial optimization data for electric stress control; and to perform targeted optimization of the electric field distribution of the converter transformer based on the initial optimization data for electric stress control to suppress electric field amplitude, thereby obtaining design parameters adapted to the electric stress dimension.

[0081] In this embodiment, the optimization module 402 is used to fit the temperature rise aging characterization parameters using empirical aging formulas to obtain a basic temperature rise aging calculation model; to iterate the model parameters of the basic temperature rise aging calculation model using high-frequency correction coefficients to obtain a temperature rise-life evaluation model adapted to high-frequency disturbances; to perform a global thermal stress quantification analysis on the temperature rise aging characterization parameters based on the temperature rise-life evaluation model to obtain thermal stress optimization benchmark data; and to perform adaptive iterative optimization of the thermal control parameters of the converter transformer based on the thermal stress optimization benchmark data to obtain design parameters adapted to the thermal stress dimension.

[0082] In this embodiment, the optimization module 402 is used to decompose and analyze the vibration characteristics of the structural vibration excitation parameters using the mechanism of winding electrodynamics and magnetostrictive force to obtain vibration characteristic data under high-frequency disturbance; to identify the resonance risk and stress concentration points of the converter transformer structure based on the vibration characteristic data to obtain mechanical defect identification data; to perform targeted optimization analysis on the mechanical defect identification data using a mechanical vibration reduction and control strategy to obtain mechanical stress control benchmark data; and to iteratively optimize and adapt the transformer structural parameters based on the mechanical stress control benchmark data to obtain design parameters adapted to the mechanical stress dimension.

[0083] In this embodiment, the construction module 403 is used to construct analysis models for each single physics field using design parameters adapted to each dimension in the preliminary design scheme, thereby obtaining a set of single physics field models; based on the set of single physics field models, analyze the mutual influence relationships between electro-thermal, thermo-mechanical, and electro-mechanical fields to obtain multi-physics field coupling correlation data; based on the multi-physics field coupling correlation data, establish coupling boundary conditions and parameter transfer rules between each physics field to obtain an initial model of the coupling mechanism; and perform simulation verification and correction of the initial model of the coupling mechanism under multiple operating conditions to obtain the multi-physics field coupling mechanism under high-frequency disturbances.

[0084] In this embodiment, the processing module 404 is used to perform a full-domain simulation analysis of the electro-thermal-mechanical coupled stress response of the converter transformer using the multi-physics coupling mechanism to obtain coupled stress distribution data; based on the coupled stress distribution data, it identifies weak links and stress amplification risk points under the synergistic effect of multi-physics fields to obtain key target data for stress regulation; it adopts a multi-dimensional stress synergistic regulation strategy to perform cross-physics synergistic optimization of the key target data for stress regulation to obtain optimized design parameters after synergistic regulation; and iteratively corrects and verifies the overall design of the transformer based on the optimized design parameters after synergistic regulation to obtain a target design scheme that can withstand long-term high-order harmonics.

[0085] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system).

[0086] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0087] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0088] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device as shown by a landing page for an app. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, which can be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0089] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0090] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0091] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0092] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for optimizing the high-harmonic resistance of converter transformers based on multi-physics coupling, characterized in that, The method includes: Acquire multi-physics stress response data of converter transformers under high-frequency disturbances; The multi-physics stress response data were optimized in terms of electrical stress, thermal stress and mechanical stress dimensions to obtain a preliminary design scheme for performance adaptation in each dimension. Based on the preliminary design scheme, a multi-physics coupling mechanism under high-frequency disturbance is constructed. Based on the aforementioned multi-physics coupling mechanism, a multi-dimensional stress synergistic control strategy is adopted to optimize the transformer's operating characteristics, resulting in a target design scheme that can withstand long-term high-order harmonics.

2. The method according to claim 1, characterized in that, The multiphysics stress response data includes: high-frequency potential distribution parameters, temperature rise aging characterization parameters, and structural vibration excitation parameters. The multi-physics stress response data is optimized for electrical stress, thermal stress, and mechanical stress dimensions to obtain preliminary design schemes for performance adaptation in each dimension, including: For the high-frequency potential distribution parameters, electrical stress analysis was carried out through potential gradient measurement and stepped pressure test to obtain initial optimization data for electrical stress control. The electric field distribution of the initial optimization data was then optimized to suppress the electric field amplitude, and design parameters for electrical stress dimension adaptation were obtained. A novel temperature rise-life evaluation model is constructed using empirical aging formulas and high-frequency correction coefficients. The temperature rise aging characterization parameters are then optimized in the thermal stress dimension to obtain design parameters adapted to the thermal stress dimension. By utilizing the vibration characteristics induced by the winding electrodynamics and magnetostrictive forces, and mechanical vibration reduction and control strategies, the vibration excitation parameters of the structure are optimized in the mechanical stress dimension to obtain design parameters adapted to the mechanical stress dimension. By integrating the design parameters for the electrical stress, thermal stress, and mechanical stress dimensions, a preliminary design scheme for performance adaptation in each dimension is obtained.

3. The method according to claim 2, characterized in that, For the aforementioned high-frequency potential distribution parameters, electrical stress analysis is conducted through potential gradient measurement and stepped pressure testing to obtain initial optimized data for electrical stress control. Furthermore, the electric field distribution of this initial optimized data is optimized to suppress electric field amplitude, resulting in design parameters adapted to the electrical stress dimension, including: The high-frequency potential distribution parameters were used to measure the potential gradient in the key insulation area of ​​the converter transformer, and the measured potential distribution data of each area were obtained. Using the measured potential distribution data, a stepped voltage test was conducted on the converter transformer at different voltage levels to obtain electric field response data under multiple operating conditions. Based on the electric field response data under multiple operating conditions, the electric stress distribution characteristics of the converter transformer are analyzed to obtain the initial optimization data for electric stress regulation. Based on the initial optimization data of electric stress regulation, the electric field distribution of the converter transformer is optimized in a targeted manner to suppress the electric field amplitude, and design parameters adapted to the electric stress dimension are obtained.

4. The method according to claim 2, characterized in that, The novel temperature rise-life evaluation model is constructed using empirical aging formulas and high-frequency correction coefficients. The model optimizes the temperature rise aging characterization parameters in the thermal stress dimension, yielding design parameters adapted to the thermal stress dimension, including: The temperature rise aging characterization parameters are fitted using empirical aging formulas to obtain a basic temperature rise aging calculation model. By iterating the model parameters of the basic temperature rise aging calculation model using the high-frequency correction coefficient, a temperature rise-life evaluation model adapted to high-frequency disturbances is obtained. Based on the temperature rise-life evaluation model, a global thermal stress quantification analysis is performed on the temperature rise aging characterization parameters to obtain thermal stress optimization benchmark data. Based on the aforementioned thermal stress optimization benchmark data, the thermal control parameters of the converter transformer are adapted and iteratively optimized to obtain design parameters adapted to the thermal stress dimension.

5. The method according to claim 2, characterized in that, The vibration characteristics induced by the winding electrodynamics and magnetostrictive force, along with mechanical vibration reduction and control strategies, are used to optimize the mechanical stress dimension of the structural vibration excitation parameters, resulting in design parameters adapted to the mechanical stress dimension, including: By utilizing the interaction mechanism of winding electrodynamics and magnetostrictive force, the vibration excitation parameters of the structure are analyzed to decompose the vibration characteristics and obtain vibration characteristic data under high-frequency disturbance. Based on vibration characteristic data, the structural resonance risk and stress concentration points of the converter transformer are identified to obtain mechanical defect identification data. By utilizing mechanical vibration reduction and control strategies, targeted optimization analysis is performed on mechanical defect identification data to obtain benchmark data for mechanical stress control. Based on the benchmark data for mechanical stress regulation, the structural parameters of the transformer are iteratively optimized and adapted to obtain the design parameters adapted to the mechanical stress dimension.

6. The method according to claim 1, characterized in that, Based on the preliminary design scheme, the multi-physics coupling mechanism under high-frequency disturbances is constructed, including: Using the design parameters adapted to each dimension in the preliminary design scheme, an analysis model for each single physics field is constructed, resulting in a set of single physics field models. Based on the set of single-physics models, the mutual influence relationships between electro-thermal, thermo-mechanical, and electro-mechanical fields are analyzed to obtain multi-physics coupling correlation data; Based on multi-physics coupling correlation data, we establish coupling boundary conditions and parameter transfer rules between various physics fields to obtain an initial model of the coupling mechanism. The initial model of the coupling mechanism was verified and corrected under multiple operating conditions through simulation, and the multi-physics coupling mechanism under high-frequency disturbance was obtained.

7. The method according to claim 1, characterized in that, Based on the multi-physics coupling mechanism, a multi-dimensional stress synergistic control strategy is adopted to optimize the transformer's operating characteristics, resulting in a target design scheme that can withstand long-term high-order harmonics, including: By utilizing the coupling mechanism of multiple physical fields, a global simulation analysis of the electro-thermal-mechanical coupling stress response of the converter transformer is performed to obtain the coupling stress distribution data. Based on the coupled stress distribution data, weak links and stress amplification risk points under the synergistic effect of multiple physical fields are identified, and key target data for stress regulation are obtained. A multi-dimensional stress synergistic regulation strategy is adopted to perform cross-physics field synergistic optimization on key target data of stress regulation, and obtain the optimized design parameters after synergistic regulation. Based on the optimized design parameters after coordinated control, the overall design of the transformer is iteratively corrected and verified to obtain the target design scheme that can withstand long-term high-order harmonics.

8. A converter transformer high-harmonic resistance optimization device based on multi-physics coupling, characterized in that, The device includes: The acquisition module is used to acquire multi-physics stress response data of converter transformers under high-frequency disturbances; The optimization module is used to perform dimensional optimization of the multi-physics stress response data for electrical stress, thermal stress and mechanical stress respectively, so as to obtain a preliminary design scheme for performance adaptation in each dimension. A construction module is used to construct a multi-physics coupling mechanism under high-frequency disturbances based on the preliminary design scheme. The processing module is used to optimize the transformer's operating characteristics based on the multi-physics coupling mechanism and a multi-dimensional stress synergistic control strategy to obtain a target design scheme that can withstand long-term high-order harmonics.

9. A computer device, characterized in that, include: A memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method of any one of claims 1 to 7.

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