Analysis Method and System for Pole-to-Ground Fault of Ice-Melting Device Considering Transient Characteristics

Abstract

The present invention discloses a method and system for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics, which relates to the technical field of power system fault analysis. The method creates a simulation environment according to the topological structure of the symmetric single-pole ice melting device to be measured and the historical operation data of sub-modules; performs fault simulation on the symmetric single-pole ice melting device to be measured with pole-to-ground fault parameters to obtain the voltage transient waveforms of sub-modules under different switching states; conducts voltage stress analysis on the voltage transient waveforms to obtain the voltage stress distribution data and waveform abnormal points of the sub-modules; inputs the voltage stress distribution data and the waveform abnormal points into a pre-trained fault prediction model for processing to obtain the fault prediction results corresponding to the sub-modules; determines the fault risk level of the symmetric single-pole ice melting device to be measured according to the fault prediction results, so as to improve the reliable operation of the symmetric single-pole ice melting device.

Description

Technical Field

[0001] The present invention relates to the technical field of power system fault analysis, and particularly to a method and system for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics. Background Art

[0002] Research in the field of power systems is of crucial significance for ensuring the safe and stable operation of the power grid. Among them, the DC ice melting technology, as a key means to cope with ice and snow disasters, is directly related to the reliability of transmission lines and the safety of social economy. With the intensification of climate change, the threat of ice disasters to the power system is becoming increasingly severe. The symmetric monopole ice melting device has become a research hotspot due to its high efficiency and flexibility. It realizes efficient ice melting through a modular multilevel converter (MMC). However, this structure also increases the probability of faults to a certain extent. For example, in the initial stage of the fault occurrence of the symmetric monopole ice melting device, some arm sub-modules may be damaged due to overvoltage stress, which will further lead to the instability of the power system.

[0003] Traditional fault analysis methods only perform simple steady-state analysis and cannot comprehensively capture the dynamic response characteristics during the fault process, resulting in poor accuracy in fault risk analysis and prediction. It is impossible to formulate reasonable and reliable control strategies or maintenance measures, thereby affecting the ability of the ice melting device to cope with faults.

[0004] Therefore, how to effectively analyze the pole-to-ground fault of the symmetric monopole ice melting device and improve the fault response ability of the ice melting device has become a technical problem that needs to be urgently solved by those skilled in the art. Summary of the Invention

[0005] The present invention provides a method and system for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics, aiming to solve the problem of how to effectively warn and control risks by deeply studying the transient distribution characteristics of the voltage stress of the arm sub-modules during the pole-to-ground fault of the symmetric monopole ice melting device, and maintain the reliability and safety of the power system.

[0006] To solve the above technical problems, an embodiment of the present invention provides a method for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics, including:

[0007] Create a simulation environment according to the topological structure of the symmetric monopole ice melting device to be measured and the historical operation data of the sub-modules;

[0008] Perform fault simulation on the symmetric monopole ice melting device to be measured with preset pole-to-ground fault parameters to obtain the voltage transient waveforms of the sub-modules of the symmetric monopole ice melting device to be measured under different switching states;

[0009] Performing voltage stress analysis on the voltage transient waveform to obtain voltage stress distribution data and waveform abnormal points of the submodule;

[0010] Inputting the voltage stress distribution data and the waveform abnormal points into a pre-trained fault prediction model for processing to obtain a fault prediction result corresponding to the submodule;

[0011] The fault risk level of the symmetrical monopolar ice melting device to be tested is determined according to the fault prediction result.

[0012] Furthermore, before the fault simulation of the symmetrical monopole ice melting device to be tested is performed with the preset pole-to-ground fault parameters, the method further includes:

[0013] Extracting features from the historical switching data in the historical submodule operation data to construct a switching feature data set;

[0014] Input the switching feature data set into a pre-built statistical distribution model, and output the feature distribution during the switching process of the submodule;

[0015] The submodule parameters of the symmetrical monopolar ice melting device to be tested are adjusted according to the characteristic distribution, and the simulation environment is updated with the adjusted submodule parameters and the topological structure.

[0016] Furthermore, the voltage stress analysis of the voltage transient waveform is performed to obtain the voltage stress distribution data and waveform abnormal points of the submodule, including:

[0017] Extracting voltage signal data from the voltage transient waveform, and dividing the on-off state and off-off state of the submodule according to the voltage signal data;

[0018] According to the division results, the voltage stress index values under each switching state are calculated respectively;

[0019] The voltage stress index value is statistically analyzed to obtain the voltage stress distribution data, and the waveform abnormal point in the voltage transient waveform is marked according to the screening factor calculated from the voltage stress index value.

[0020] Further, the performing of statistical analysis on the voltage stress index value to obtain the voltage stress distribution data, and marking the waveform abnormal point in the voltage transient waveform according to the screening factor calculated from the voltage stress index value, includes:

[0021] Performing a multi-index joint analysis on the voltage stress index value to fit the voltage stress distribution curve of the submodule; and,

[0022] Calculate the overvoltage multiple and the voltage change rate according to the voltage stress index value, and use the overvoltage multiple and the voltage change rate as double screening factors;

[0023] When any indicator of the dual screening factors exceeds a preset abnormal threshold, the waveform abnormal point is marked in the voltage transient waveform.

[0024] Furthermore, the dividing of the input and removal states of the submodules according to the voltage signal data includes:

[0025] Calculating the difference between the voltage signal data and a preset submodule rated voltage value, and setting a division threshold based on the difference;

[0026] Based on the division threshold, a sliding window algorithm is used to traverse the voltage transient waveform to determine the switching state of the submodule.

[0027] Furthermore, the process of performing voltage stress analysis on the voltage transient waveform further includes:

[0028] Adjusting the topological connection mode of the submodules in the symmetrical monopolar ice melting device to be tested, and updating the simulation environment with the adjusted first topological structure;

[0029] In the updated simulation environment, the input / disconnection logic of the control submodule is re-simulated for faults;

[0030] According to the simulation results, the contrast voltage transient waveforms corresponding to the submodules under different topological structures are obtained;

[0031] Determine comparative voltage stress distribution data according to the comparative voltage transient waveform;

[0032] The comparative voltage stress distribution data and the voltage stress distribution data are compared and analyzed to determine a high-level indicator that affects the voltage stress of the submodule.

[0033] Furthermore, the comparing and analyzing the comparison voltage stress distribution data and the voltage stress distribution data to determine the high-level index affecting the voltage stress of the submodule includes:

[0034] Preprocessing the first topology structure, the switching state of the submodule, the voltage stress distribution data and the comparative voltage stress distribution data to obtain a data set to be input;

[0035] Inputting the data set to be input into a trained random forest model, and outputting an importance score affecting the voltage stress index;

[0036] The importance scores are sorted, and the high-level indicator is determined according to the sorting result.

[0037] Furthermore, the process of performing voltage stress analysis on the voltage transient waveform further includes:

[0038] Comparing the first voltage stress differences of the sub-modules in different switching states according to the voltage stress distribution data;

[0039] Comparing the second voltage stress differences of the sub-modules in different topological connection modes according to the comparative voltage stress distribution data;

[0040] Inputting the preprocessed first voltage stress difference and the second voltage stress difference into a pre-trained difference classification model to obtain the stress difference levels of each sub-module;

[0041] Modifying the topological structure and switching state parameters of the sub-module according to the stress difference levels, and re-iterating the simulation analysis process.

[0042] Furthermore, determining the fault risk level of the to-be-tested symmetrical single-pole ice melting device according to the fault prediction result includes:

[0043] Performing feature extraction on the fault prediction result to obtain a fault feature data set;

[0044] Inputting the fault feature data set into a pre-trained risk prediction model to obtain the fault risk level, and formulating a corresponding maintenance strategy for the to-be-tested symmetrical single-pole ice melting device according to the fault risk level.

[0045] Another embodiment of the present invention provides an ice melting device pole-to-ground fault analysis system considering transient characteristics, including:

[0046] A simulation initialization module, configured to create a simulation environment according to the topological structure of the to-be-tested symmetrical single-pole ice melting device and historical sub-module operation data;

[0047] A fault simulation module, configured to perform fault simulation on the to-be-tested symmetrical single-pole ice melting device with preset pole-to-ground fault parameters to obtain voltage transient waveforms of the sub-modules of the to-be-tested symmetrical single-pole ice melting device in different switching states;

[0048] A transient analysis module, configured to perform voltage stress analysis on the voltage transient waveforms to obtain voltage stress distribution data and waveform abnormal points of the sub-modules;

[0049] A fault prediction module, configured to input the voltage stress distribution data and the waveform abnormal points into a pre-trained fault prediction model for processing to obtain a fault prediction result corresponding to the sub-module;

[0050] A risk analysis module, configured to determine the fault risk level of the to-be-tested symmetric monopole ice melting device according to the fault prediction result.

[0051] Compared with the prior art, the beneficial effects of the embodiments of the present invention are at least one of the following:

[0052] By building an electromagnetic transient simulation environment including a sub-module model of a bridge arm, the embodiments of the present invention can accurately capture the voltage transient data in the initial stage of a fault through simulation, and at the same time quantify the key parameters of the sub-module voltage stress, so as to improve the accuracy of the analysis of the dynamic response; by analyzing the influence of different switching states on the voltage stress distribution, the influence law of the voltage stress distribution in the fault scenario is comprehensively revealed, and a classification prediction model of voltage stress index parameters is established to effectively identify the fault type, location and sub-module switching state; thus, the risk of sub-module damage can be accurately evaluated to formulate a reasonable and reliable device prevention strategy or maintenance measure, ensuring the stable operation of the symmetric monopole ice melting device under extreme working conditions. Description of the Drawings

[0053] Figure 1 is a schematic flow chart of a method for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics in one embodiment of the present invention;

[0054] Figure 2 is a schematic structural diagram of a system for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics in one embodiment of the present invention;

[0055] Description of the Drawings: M1, simulation initialization module; M2, fault simulation module; M3, transient analysis module; M4, fault prediction module; M5, risk analysis module. Detailed Embodiments

[0056] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0057] In the description of the present application, the terms "first", "second", "third", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", "third", etc. may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0058] In the description of the present application, it should be noted that unless otherwise clearly specified or limited, the terms "installed", "connected", and "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two components. The terms "vertical", "horizontal", "left", "right", "upper", "lower" and similar expressions used herein are only for the purpose of illustration, rather than indicating or implying that the device or component referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be construed as a limitation on the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0059] In the description of the present application, it should be noted that unless otherwise defined, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0060] When the symmetric monopole ice melting device has a pole-to-ground fault, the overvoltage stress borne by the arm sub-module during the electromagnetic transient process may cause equipment damage. Based on this, an embodiment of the present invention provides a method for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics. Specifically, please refer to Figure 1 , Figure 1 which is shown as a schematic flow chart of the method for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics in one of the embodiments of the present invention, and includes the following steps:

[0061] S1. Create a simulation environment according to the topological structure of the symmetric monopole ice melting device to be measured and the historical operation data of the sub-module.

[0062] Obtain the topological structure of the symmetric monopole ice melting device to be tested. The topological structure of the symmetric monopole ice melting device is usually designed based on a modular multilevel converter. The core lies in realizing the DC ice melting function through the series and parallel combination of sub-modules. Exemplarily, in this embodiment, a high-precision electromagnetic transient simulation tool (such as PSCAD / EMTDC or MATLAB / Simulink) can be selected to establish a simulation model including a sub-module cascade structure. Correspondingly, various parameters for the reasonable operation of the device should be configured in the simulation software, and the parameter configuration can be carried out through the obtained historical sub-module operation data, including configuring the capacitance value, rated voltage value, IGBT withstand voltage level, switching strategy (such as switching timing) of the arm sub-module, etc.

[0063] Exemplarily, the topology of the symmetric monopole ice melting device to be tested in this embodiment can be that multiple arms are connected in parallel, and each arm is composed of several sub-modules connected in series. The sub-module can adopt a half-bridge or full-bridge form. For example, one arm in the device contains 10 sub-modules. If the rated voltage of each sub-module is 1 kV, the total voltage of the arm can reach 10 kV, thus meeting the DC output required for ice melting.

[0064] Furthermore, before the fault simulation, to ensure the simulation efficiency and accuracy, this embodiment will calibrate the constructed simulation model. Specifically, in this embodiment, the simulation parameters are optimized by analyzing the characteristic distribution of the sub-modules during the historical switching process.

[0065] First, construct a feature dataset, extract features from the historical switching data in the historical sub-module operation data, construct a switching feature dataset, and input it into a pre-constructed statistical distribution model to output the characteristic distribution during the sub-module switching process. In this embodiment, the extracted switching features include switching frequency, the number of sub-modules involved in a single switching, date, and capacitance voltage value.

[0066] Subsequently, adjust the sub-module parameters of the symmetric monopole ice melting device to be tested according to the characteristic distribution, and update the simulation environment with the adjusted sub-module parameters and topological structure.

[0067] Exemplarily, the switching operation records of the sub-modules in the past year can be extracted from the historical data. Suppose the record shows that the switching frequency is concentrated between 50 Hz and 100 Hz, and each switching involves 2 to 5 sub-modules. Using statistical analysis methods, the characteristic distribution is obtained, such as maximum likelihood estimation, regression analysis, Poisson distribution, or normal distribution, etc. For example, the number of switching times follows a normal distribution, with a mean of 3 sub-modules and a standard deviation of 1. This indicates high-frequency switching, and the capacitor needs to be charged and discharged frequently. Based on this, the capacitance value is optimized from 1000 μF to 1200 μF to improve the response speed of the topology during the simulation process.

[0068] In another embodiment of the present invention, the voltage waveform of a 10 kV arm under switching at 50 Hz is simulated in a simulation environment. In the initial configuration, the waveform may have an overshoot of 5%. After adjustment by the feature distribution, the overshoot is reduced to 2%, indicating that the parameter optimization is effective. If the calculation resource occupancy exceeds the standard, for example, the CPU usage rate reaches 90% which exceeds the threshold of 80%, then through the load balancing algorithm, the simulation tasks are distributed to a multi-core processor, and the usage rate is reduced to 70% after optimization, improving the simulation efficiency.

[0069] S2. Perform fault simulation on the to-be-tested symmetric single-pole ice melting device with preset pole-to-earth fault parameters to obtain the voltage transient waveforms of the sub-modules of the to-be-tested symmetric single-pole ice melting device under different switching states.

[0070] After the simulation environment is set up, the pole-to-earth fault parameters will be defined to simulate the pole-to-earth faults that may occur during the actual operation of the symmetric single-pole ice melting device. Specifically, the pole-to-earth faults include fault types such as single-phase grounding, two-phase grounding, three-phase grounding, and pole-to-earth short circuit, and the fault locations involve the upper arm, lower arm, or specific sub-modules of the arm.

[0071] The fault parameters to be set include the transition resistance value, phase current / voltage value, short-circuit resistance value, and duration, etc. Taking the pole-to-earth short-circuit fault as an example: Suppose the short-circuit fault occurs in the 3rd sub-module of the upper arm, and the fault parameters can be set such as the short-circuit resistance is 0.1 ohm and the fault trigger time is 0.5 seconds. For the above short-circuit fault, the simulation result will show that the voltage of the 3rd sub-module instantly rises to 1500 V (the normal value is 1000 V).

[0072] It should be understood that during the simulation process, the pre-configured sub-module switching strategy, that is, the switching frequency of sub-module input, cut-off, and switching, will also be incorporated into the simulation. Specifically, in different pole-to-earth fault scenarios, by injecting different input / cut-off states and running the fault scenarios in the electromagnetic transient simulation environment, the port voltage transient waveform data of each sub-module can be collected. Preferably, the sampling rate is set ≥10 kHz.

[0073] S3. Perform voltage stress analysis on the voltage transient waveforms to obtain the voltage stress distribution data and waveform abnormal points of the sub-modules.

[0074] It can be understood that the voltage transient waveforms in the initial stage of the fault contain core information such as the fault type (short circuit / grounding) and location (upper / middle section of the arm), which are the data basis for subsequent device diagnosis and control. That is, the voltage transient waveforms record the information of the voltage change over time during the fault process, including the peak voltage, rising rate, and duration, and these indicators reflect the voltage stress distribution of the sub-modules in the initial stage of the fault.

[0075] Among them, the peak voltage refers to the maximum value of the instantaneous voltage, reflecting the overvoltage risk; the rising rate refers to the speed at which the voltage rises from the steady state to the peak, reflecting the rapid release of electromagnetic energy; the duration refers to the time when the voltage exceeds the safety threshold, which is related to the tolerance ability of the associated equipment.

[0076] Specifically, in the embodiments of the present invention, voltage signal data in the voltage transient waveform is extracted, and the input and cut-off states of the sub-module are divided according to the voltage signal data. Exemplarily, the voltage signal data in the voltage transient waveform can be extracted by a high-speed data collector, or the waveform can be subjected to spectrum analysis by using Fourier transform, and the noise can be filtered through filter processing to obtain the required voltage signal data (i.e., voltage amplitude, time, rising / falling rate, oscillation frequency, etc.).

[0077] Regarding the process of dividing the input and cut-off states of the sub-module in the waveform, in this embodiment, traversal is performed in the waveform through a set division threshold. Specifically, the difference between the voltage signal data and the preset rated voltage value of the sub-module is calculated, and the division threshold is set with the difference. Based on the division threshold, the sliding window algorithm is used to traverse in the voltage transient waveform to determine the input and cut-off states of the sub-module. Exemplarily, if the determination threshold for the input state is set to 1.1 times the rated value and lasts for more than 1 ms, and the determination threshold for the cut-off state is set to 0.9 times the rated value.

[0078] It can be understood that the switching of the input and cut-off states directly affects the voltage distribution. When the sub-module is input or cut off, the charging and discharging process of the capacitor will change its voltage. If the input and cut-off are unbalanced, some sub-modules may charge and discharge frequently, resulting in large fluctuations in the capacitor voltage, while the voltage of other sub-modules remains stable. This will affect the voltage distribution of the entire converter, may cause voltage imbalance, increase harmonics, and even damage the equipment.

[0079] Based on this, in this embodiment, according to the division result, that is, the input and cut-off states divided, the voltage stress index values corresponding to the sub-modules in each input and cut-off state are calculated. That is, the quantization results of the peak voltage, rising rate, and duration. Exemplarily, if the simulation process shows that the voltage of the sub-module in the bypass state is 0V, and after input, the detected voltage peak is 1800V, exceeding the safety threshold of 1500V. By comparing the data at different times, it can be found that the voltage stress increases significantly at the moment of input, while it tends to be stable during bypass, revealing the law of state switching and voltage stress change.

[0080] Further, statistical analysis is performed on the voltage stress index values to obtain voltage stress distribution data. In this embodiment, multi-index joint analysis can be performed on the voltage stress index values to fit the voltage stress distribution curve of the sub-module, and the voltage stress distribution can be intuitively obtained from the curve. Exemplarily, three indexes, namely peak voltage, rising rate, and duration, can be combined to draw a two-dimensional histogram or contour map to obtain the distribution curve.

[0081] Further, abnormal waveform segments can be marked according to these index values, and waveform abnormal points in the voltage transient waveform can be marked according to the screening factor calculated from the voltage stress index values. In this embodiment, it should be understood that the abnormal segment refers to a specific time interval marked in the voltage transient waveform due to overvoltage or voltage change rate exceeding the preset threshold, which can be used for accurate positioning of the root cause of equipment failure in the follow-up and can also quantify the tolerance of the equipment.

[0082] Among them, the screening factor is used to screen out abnormal wave bands exceeding / falling below the set threshold. Specifically, the overvoltage multiple and voltage change rate are calculated according to the voltage stress index values, and the overvoltage multiple and voltage change rate are used as double screening factors. When any index in the double screening factors exceeds the preset abnormal threshold, waveform abnormal points will be marked in the voltage transient waveform. Exemplarily, the overvoltage multiple is determined by the ratio between the peak voltage and the rated voltage. If the peak voltage is 2 kV and the rated voltage is 1 kV, the overvoltage multiple is 2 / 1 = 2 p.u. If the set overvoltage multiple threshold is 1.5 kV, it indicates that the voltage stress exceeds the safe range and needs to be marked as an abnormal segment.

[0083] The calculation of the voltage change rate (dv / dt) requires the voltage difference and time difference. In this embodiment, the voltage-time sequence is extracted from the waveform, and the differential method is used to calculate the instantaneous change rate. Exemplarily, the ratio of the voltage value difference corresponding to the 1.1 ms moment and the 1.0 ms moment to the time change amount is calculated to obtain the corresponding voltage change rate. When this change amount exceeds the threshold (such as 7 kV / ms), it indicates that the voltage stress exceeds the safe range and needs to be marked as an abnormal segment.

[0084] The above process takes the switching state of the sub-module as an index to evaluate the voltage stress distribution of the sub-module in different switching states. In some embodiments of the present invention, the topology structure of the sub-module is also introduced as an evaluation index to further analyze the voltage stress distribution of the sub-module under different topological connection modes (such as half-bridge, full-bridge, or hybrid structure). It should be understood that the number and connection mode of the switching devices in different topological structures are different, which will affect the voltage distribution path and the voltage bearing capacity of the devices. Moreover, in the case of a fault, the fault current blocking capabilities of different topological structures are different, which will also affect the voltage stress distribution during the fault.

[0085] Based on this, the adjustment sub-module in this embodiment adjusts the topological connection mode in the symmetric monopolar ice melting device to be measured. For example, it is adjusted from a full-bridge structure to a half-bridge structure, and the number of branches is adjusted accordingly, and the simulation environment is updated with the adjusted first topological structure.

[0086] In the updated simulation environment, the input / removal logic of the control sub-module re-performs fault simulation, and according to the simulation results, the corresponding comparative voltage transient waveforms of the sub-module under different topological structures are obtained. It should be noted that the switching logic is usually determined by the pulse width modulation signal. For example, adjusting the modulation ratio from 0.8 to 0.9 may cause the switching frequency of the sub-module to increase, and the voltage stress to rise from 1600V to 1900V. From this, it can also be judged that the switching control strategy needs to balance the switching frequency and the stress level to avoid frequent switching and amplifying the stress.

[0087] Similar to the above analysis method, statistical analysis is performed on the comparative voltage transient waveforms, the voltage stress index value is calculated, and the comparative voltage stress distribution data is obtained.

[0088] Exemplarily, it is set that the sub-module adopts a half-bridge topology. When in the input state, the capacitor bears all the voltage, and there is no stress when bypassed. In an arm containing 10 sub-modules, a certain sub-module has a higher voltage stress near the midpoint of the arm due to its topological position, reaching 2000V. And this distribution difference actually also indicates that the topological design of this device needs to be optimized.

[0089] Regarding the influence of the above switching state and topological structure on the voltage stress distribution, this embodiment further analyzes the importance of the two influences. Specifically, in this embodiment, the comparative analysis of the voltage stress distribution data and the comparative voltage stress distribution data is performed to determine the high-order index affecting the sub-module voltage stress.

[0090] Specifically, first, preprocessing is performed on the first topological structure, the sub-module switching state, the voltage stress distribution data, and the comparative voltage stress distribution data to obtain the dataset to be input. Exemplarily, for the changed topological structure, its various structure types can be mapped into the form of one-hot encoding respectively, and the number of branches is standardized. And for the switching state, it can be discretized.

[0091] The dataset to be input is input into the trained random forest model, the importance scores affecting the voltage stress index are output, the importance scores are sorted, and the high-order indexes with greater influence on the voltage stress distribution are determined according to the sorting results. For example, if the random forest model output shows that the importance of the topological type is 28% and the switching state is 32%, then the switching state is the high-order influence index. Exemplarily, in the subsequent device optimization process, more attention will be paid to formulating a more reasonable switching control strategy.

[0092] Furthermore, this embodiment optimizes the simulation process according to the difference in voltage stress distribution under different indicator variables to improve the accuracy of the simulation results.

[0093] Specifically, first, according to the voltage stress distribution data, the first voltage stress differences of the submodules under different switching states are compared. For example, the previously fitted voltage stress distribution curves under different switching states can be compared and analyzed. Or the mean difference between the voltage stress index value data of two groups under different switching states can be compared.

[0094] Similarly, based on the comparison of voltage stress distribution data, the difference in second voltage stress of submodules in different topological connection modes is compared by using methods such as mean value calculation method and principal component analysis method.

[0095] The preprocessed first voltage stress difference and the second voltage stress difference are input into the pre-trained difference classification model to obtain the stress difference level of each submodule, such as the output label 0 / 1 / 2, corresponding to the results of low / medium / high risk respectively. For example, these difference data can be cleaned and standardized. Preferably, the present embodiment adopts the support vector machine pre-trained difference classification model.

[0096] According to the stress difference level, the submodule topology and switching state parameters are modified, and the simulation and stress analysis process are iterated again. For example, if the output is a high risk difference, the switching strategy can be optimized to reduce the switching frequency. If the output is a medium risk, the topology can be adjusted to replace the half bridge with a hybrid bridge. If the output is a low risk, the current parameters are maintained and the current simulation test continues.

[0097] S4~S5, input the voltage stress distribution data and waveform abnormal points into the pre-trained fault prediction model for processing, and obtain the fault prediction results corresponding to the submodules. According to the fault prediction results, determine the fault risk level of the symmetrical monopolar ice melting device to be tested.

[0098] This step is the process of fault prediction. Preferably, the fault prediction model is obtained by training the support vector machine model. The model will output the fault type classification probability, the fault location confidence interval, and the abnormal submodule number list, so that the fault location can be accurately located and the fault type can be identified. In some embodiments of the present invention, when the fault prediction model is established using the support vector machine algorithm, training can be performed based on key input variables. If the input data set contains two types of samples, normal and faulty, the voltage peak of the normal sample is mostly below 580V, and the faulty sample is above 620V. The model determines the fault type such as "overvoltage fault" and the location such as "bridge arm third submodule" by finding the optimal classification boundary.

[0099] After obtaining the above fault prediction results, this embodiment will further perform risk assessment on the fault prediction results.

[0100] Extract features from the fault prediction results to obtain a fault feature dataset. These features include, but are not limited to, features such as voltage peak, ripple coefficient, current amplitude, and fault type.

[0101] Input the fault feature dataset into a pre-trained risk prediction model to obtain the fault risk level, and formulate corresponding maintenance strategies for the symmetric single-pole ice melting device to be tested based on the fault risk level. Exemplarily, a risk prediction model can be trained using, for example, a random forest model, a LightGBM gradient boosting decision tree model, etc.

[0102] Exemplarily, if the level is high risk: predicted as a three-phase ground fault, and the abnormal point density > 5 points / ms, or the peak mean exceeds the threshold by 30%, it is recommended to immediately cut off the faulty bridge arm and enable the maintenance strategy of the redundant sub-module.

[0103] If the level is low risk: predicted as a single-phase ground fault, the abnormal point density < 2 points / ms, and the peak mean does not exceed the standard, it is recommended to conduct regular inspections and record the trend of abnormal points.

[0104] In summary, in the embodiment of the present invention, by constructing an electromagnetic transient simulation environment, analyzing the voltage transient characteristics under pole-to-ground faults, combining the switching states of sub-modules, analyzing the voltage peak, rising rate, and duration used to evaluate the voltage stress distribution, and locating abnormal points. Further, a support vector machine is used to establish a machine learning model, with the voltage stress distribution and abnormal points as inputs to predict the fault type and location of the ice melting device. It can quickly distinguish fault features, effectively locate the source of the problem, and finally evaluate the damage risk level of the sub-module based on the prediction results, so as to formulate effective maintenance and warning strategies. The present invention effectively integrates dynamic simulation and machine learning technologies, makes up for the deficiencies of traditional steady-state analysis, and provides an accurate risk assessment basis for improving equipment reliability and power grid safe operation.

[0105] An embodiment of the present invention provides a system. Specifically, please refer to Figure 2 , Figure 2 which is shown as the structural schematic diagram of the pole-to-ground fault analysis system of the ice melting device considering transient characteristics in one embodiment of the present invention, including the following:

[0106] A simulation initialization module M1, configured to create a simulation environment according to the topological structure of the symmetric single-pole ice melting device to be tested and the historical operation data of the sub-module.

[0107] A fault simulation module M2, configured to perform fault simulation on the symmetric single-pole ice melting device to be tested with preset pole-to-ground fault parameters, and obtain the voltage transient waveforms of the sub-modules of the symmetric single-pole ice melting device to be tested in different switching states.

[0108] A transient analysis module M3 is used to perform voltage stress analysis on the voltage transient waveform to obtain voltage stress distribution data and waveform abnormal points of the sub-module;

[0109] A fault prediction module M4 is used to input the voltage stress distribution data and the waveform abnormal points into a pre-trained fault prediction model for processing to obtain a fault prediction result corresponding to the sub-module;

[0110] A risk analysis module M5 is used to determine the fault risk level of the to-be-tested symmetric monopolar ice melting device according to the fault prediction result.

[0111] The technical features and technical effects of the system proposed in the embodiments of the present invention are the same as those of the method proposed in the embodiments of the present invention, and will not be elaborated here.

[0112] The above embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several deformations and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the appended claims.

Claims

1. A method for analyzing the pole-to-ground fault of an ice melting device considering transient characteristics, characterized in that, Including: Create a simulation environment according to the topological structure of the symmetric monopole ice melting device to be tested and the historical sub-module operation data; Perform fault simulation on the symmetric monopole ice melting device to be tested with preset pole-to-earth fault parameters, and obtain the voltage transient waveforms of the sub-modules of the symmetric monopole ice melting device to be tested under different switching states; Conduct voltage stress analysis on the voltage transient waveforms to obtain the voltage stress distribution data and waveform abnormal points of the sub-modules; specifically: extract the voltage signal data in the voltage transient waveforms, and divide the input and cut-off states of the sub-modules according to the voltage signal data; according to the division results, calculate the voltage stress index values under each switching state respectively; Conduct statistical analysis on the voltage stress index values to obtain the voltage stress distribution data, and mark the waveform abnormal points in the voltage transient waveforms according to the screening factors calculated from the voltage stress index values; The process of the voltage stress analysis further includes: adjusting the topological connection mode of the sub-modules in the symmetric monopole ice melting device to be tested, and updating the simulation environment with the adjusted first topological structure; in the updated simulation environment, control the input / cut-off logic of the sub-modules to re-perform fault simulation; obtain the corresponding comparison voltage transient waveforms of the sub-modules under different topological structures according to the simulation results; determine the comparison voltage stress distribution data according to the comparison voltage transient waveforms; compare and analyze the comparison voltage stress distribution data and the voltage stress distribution data to determine the high-order indexes affecting the voltage stress of the sub-modules; Moreover, according to the voltage stress distribution data, compare the first voltage stress differences of the sub-modules under different switching states; according to the comparison voltage stress distribution data, compare the second voltage stress differences of the sub-modules under different topological connection modes; input the pre-processed first voltage stress differences and the second voltage stress differences into a pre-trained difference classification model to obtain the stress difference levels of each sub-module; correct the topological structure and switching state parameters of the sub-modules according to the stress difference levels, and re-iterate the simulation analysis process; Input the voltage stress distribution data and the waveform abnormal points into a pre-trained fault prediction model for processing to obtain the fault prediction results corresponding to the sub-modules; Determine the fault risk level of the symmetric monopole ice melting device to be tested according to the fault prediction results.

2. The method for analyzing the pole-to-ground fault of the ice melting device considering transient characteristics according to claim 1, characterized in that, Before performing the fault simulation on the symmetric monopole ice melting device to be tested with preset pole-to-earth fault parameters, it further includes: Extract features from the historical switching data in the historical sub-module operation data to construct a switching feature data set; Input the switching feature data set into a pre-constructed statistical distribution model, and output the feature distribution during the sub-module switching process; Adjust the sub-module parameters of the symmetric monopole ice melting device to be tested according to the feature distribution, and update the simulation environment with the adjusted sub-module parameters and the topological structure.

3. The method for analyzing the pole-to-earth fault of the ice melting device considering transient characteristics according to claim 1, characterized in that, Performing statistical analysis on the voltage stress index values to obtain the voltage stress distribution data, and marking the waveform anomaly points in the voltage transient waveform according to the screening factors calculated from the voltage stress index values, including: Performing multi-index joint analysis on the voltage stress index values to fit the voltage stress distribution curve of the sub-module; and, Calculating the overvoltage multiple and the voltage change rate according to the voltage stress index values, and using the overvoltage multiple and the voltage change rate as double screening factors; When any index in the double screening factors exceeds the preset anomaly threshold, marking the waveform anomaly points in the voltage transient waveform.

4. The method for analyzing the pole-to-earth fault of the ice melting device considering transient characteristics according to claim 1, characterized in that The dividing the on and off states of the sub-module according to the voltage signal data includes: Calculating the difference between the voltage signal data and the preset rated voltage value of the sub-module, and setting the dividing threshold with the difference; Taking the dividing threshold as a reference, traversing in the voltage transient waveform using the sliding window algorithm to determine the switching state of the sub-module.

5. The method for analyzing the pole-to-earth fault of the ice melting device considering transient characteristics according to claim 1, characterized in that, The comparing the comparative voltage stress distribution data and the voltage stress distribution data to determine the high-order indexes affecting the voltage stress of the sub-module includes: Preprocessing the first topological structure, the sub-module switching state, the voltage stress distribution data and the comparative voltage stress distribution data to obtain the input data set to be input; Inputting the input data set to be input into the trained random forest model, and outputting the importance scores affecting the voltage stress index; Sorting the importance scores, and determining the high-order indexes according to the sorting results.

6. The method for analyzing the pole-to-earth fault of the ice melting device considering transient characteristics according to claim 1, characterized in that The determining the fault risk level of the to-be-tested symmetric monopole ice melting device according to the fault prediction result includes: Performing feature extraction on the fault prediction result to obtain a fault feature data set; Inputting the fault feature data set into the pre-trained risk prediction model to obtain the fault risk level, and formulating a corresponding maintenance strategy for the to-be-tested symmetric monopole ice melting device with the fault risk level.

7. An ice melting device pole-to-earth fault analysis system considering transient characteristics, characterized in that, Including: A simulation initialization module, configured to create a simulation environment according to the topological structure of the to-be-tested symmetric monopole ice melting device and the historical sub-module operation data; A fault simulation module, configured to perform fault simulation on the to-be-tested symmetric monopole ice melting device with preset pole-to-ground fault parameters to obtain the voltage transient waveforms of the sub-modules of the to-be-tested symmetric monopole ice melting device under different switching states; A transient analysis module, configured to perform voltage stress analysis on the voltage transient waveforms to obtain the voltage stress distribution data and waveform anomaly points of the sub-modules; specifically: extracting the voltage signal data in the voltage transient waveforms, dividing the on and off states of the sub-modules according to the voltage signal data; according to the division results, respectively calculating the voltage stress index values in each switching state; Performing statistical analysis on the voltage stress index values to obtain the voltage stress distribution data, and marking the waveform anomaly points in the voltage transient waveform according to the screening factors calculated from the voltage stress index values; The process of the voltage stress analysis further includes: adjusting the topological connection mode of the sub-module in the to-be-tested symmetric monopole ice melting device, and updating the simulation environment with the adjusted first topological structure; in the updated simulation environment, controlling the input / removal logic of the sub-module to re-perform fault simulation; obtaining the comparative voltage transient waveforms corresponding to the sub-module under different topological structures according to the simulation results; determining the comparative voltage stress distribution data according to the comparative voltage transient waveforms; comparing and analyzing the comparative voltage stress distribution data and the voltage stress distribution data to determine the high-order indexes affecting the voltage stress of the sub-module; moreover, comparing the first voltage stress differences of the sub-module under different switching states according to the voltage stress distribution data; comparing the second voltage stress differences of the sub-module under different topological connection modes according to the comparative voltage stress distribution data; inputting the pre-processed first voltage stress difference and the second voltage stress difference into a pre-trained difference classification model to obtain the stress difference levels of each sub-module; correcting the topological structure and switching state parameters of the sub-module according to the stress difference levels, and re-iterating the simulation analysis process; a fault prediction module, configured to process the voltage stress distribution data and the waveform anomaly points by inputting them into a pre-trained fault prediction model to obtain the fault prediction results corresponding to the sub-module; a risk analysis module, configured to determine the fault risk level of the to-be-tested symmetric monopole ice melting device according to the fault prediction results.

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