Relay protection setting parameter optimization adjustment method and device, equipment and medium

Abstract

The application discloses a kind of optimization adjustment methods, devices and media of relay protection setting parameter, comprising: according to the current health data of target mutual inductor, parameter value is corrected, according to the parameter value after correction, the parameter value of virtual mutual inductor in power simulation model is initialized, by the power simulation model after initialization, actual operating scene corresponding to historical fault data is simulated, and the secondary side waveform output by virtual mutual inductor under actual operating scene corresponding to historical fault data is obtained, according to secondary side waveform, the risk of transient saturation of target mutual inductor is evaluated, according to risk assessment result, the adjustment of relay protection setting parameter is carried out, and the setting parameter after adjustment is obtained.It makes that the setting parameter after adjustment can effectively deal with the secondary current distortion caused by mutual inductor deterioration and transient saturation, improves the accuracy of determination of relay protection under the condition that equipment health state changes and there is transient saturation risk.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a method and device for optimizing and adjusting relay protection setting parameters, equipment and medium. BACKGROUND

[0002] A relay protection device is an automatic device that can timely send a warning signal to an operator or directly send a trip command to a controlled circuit breaker to terminate the development of an event when a power element (such as a generator, a line, etc.) in a power system or the power system itself has a fault that endangers the safe operation of the power system. The performance of the relay protection device depends on the internal preset setting parameters, which are the threshold values of electrical quantities that trigger the protection action, and usually include parameters such as action current, action time, and action voltage. In the prior art, these parameters are usually calculated and determined based on the electrical characteristics of the equipment in a healthy state, the system operation mode, and the expected fault type during the system design phase, and have static and preset characteristics. However, the power system is a complex dynamic system, and such static and preset setting parameters may cause misoperation or refusal of the relay protection when the system operation mode dynamically changes, the equipment health condition gradually deteriorates, and non-typical fault conditions occur, thereby causing serious system accidents.

[0003] Therefore, how to improve the accuracy of relay protection determination has become a problem to be solved. SUMMARY

[0004] The embodiments of the present application provide a method and device for optimizing and adjusting relay protection setting parameters to solve the problem of how to improve the accuracy of relay protection determination.

[0005] A method for optimizing and adjusting relay protection setting parameters, comprising:

[0006] determining a target device to be protected, obtaining current health data of a target mutual inductor for monitoring the state of the target device and a parameter value related to the characteristics of the target mutual inductor;

[0007] correcting the parameter value according to the current health data to obtain a corrected parameter value, initializing the parameter value of a virtual mutual inductor in a power simulation model composed of a virtual device corresponding to the target device and a virtual mutual inductor corresponding to the target mutual inductor according to the corrected parameter value, and obtaining an initialized power simulation model;

[0008] N pieces of historical fault data of the target device and the target transformer under actual operation scenarios are acquired, and the initialization-based power simulation model is used to simulate each historical fault data corresponding to an actual operation scenario to obtain a secondary side waveform output by the virtual transformer under each historical fault data corresponding to an actual operation scenario, N being an integer greater than zero.

[0009] According to all the secondary side waveforms, a risk of transient saturation of the target transformer is evaluated to obtain a risk evaluation result, and a relay protection setting parameter is adjusted according to the risk evaluation result to obtain an adjusted setting parameter.

[0010] An optimization adjustment device of a relay protection setting parameter comprises:

[0011] A data acquisition module is configured to determine a target device to be protected, acquire current health data of a target transformer for state monitoring of the target device and a parameter value related to characteristics of the target transformer;

[0012] An initial correction module is configured to correct the parameter value according to the current health data to obtain a corrected parameter value, initialize a parameter value of a virtual transformer in a power simulation model composed of a virtual device corresponding to the target device and the virtual transformer corresponding to the target transformer according to the corrected parameter value to obtain an initialization-based power simulation model;

[0013] A simulation and simulation module is configured to acquire N pieces of historical fault data of the target device and the target transformer under actual operation scenarios, and simulate each historical fault data corresponding to an actual operation scenario through the initialization-based power simulation model to obtain a secondary side waveform output by the virtual transformer under each historical fault data corresponding to an actual operation scenario, N being an integer greater than zero.

[0014] A parameter adjustment module is configured to evaluate a risk of transient saturation of the target transformer according to all the secondary side waveforms to obtain a risk evaluation result, and adjust a relay protection setting parameter according to the risk evaluation result to obtain an adjusted setting parameter.

[0015] A computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the above-mentioned optimization adjustment method of a relay protection setting parameter when executing the computer program.

[0016] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the above-mentioned optimization adjustment method of a relay protection setting parameter.

[0017] The aforementioned method, device, equipment, and medium for optimizing and adjusting relay protection setting parameters involve correcting the characteristic-related parameter values ​​of the target instrument transformer based on its current health data. Based on the corrected parameter values, the parameter values ​​of the virtual instrument transformer in the power simulation model, which consists of the virtual device corresponding to the target equipment and the virtual instrument transformer corresponding to the target instrument transformer, are initialized to obtain an initialized power simulation model. Using this initialized power simulation model, historical fault data of the target equipment and target instrument transformer under actual operating scenarios are used to simulate the actual operating scenarios corresponding to the historical fault data, obtaining the secondary-side waveform output by the virtual instrument transformer under the corresponding actual operating scenarios. Based on the secondary-side waveform, the risk of transient saturation of the target instrument transformer is assessed. Based on the risk assessment results, the relay protection setting parameters are adjusted to obtain the adjusted setting parameters.

[0018] Specifically, by correcting the parameter values ​​of the target instrument transformer based on its current health data, the corrected parameter values ​​accurately reflect the true physical characteristics of the target instrument transformer under its current operating state. This allows the output secondary waveform to accurately reflect the actual response characteristics and potential saturation distortion features of the target instrument transformer when facing a fault, when simulating historical fault data using a power simulation model initialized based on the corrected parameter values. Furthermore, based on the secondary waveform, the risk of transient saturation of the target instrument transformer is quantitatively assessed. Based on the risk assessment results, the relay protection setting parameters are adjusted so that the adjusted setting parameters can effectively address secondary current distortion caused by instrument transformer deterioration or transient saturation, preventing maloperation or failure to operate. This improves the accuracy of relay protection in determining changes in equipment health status and the presence of transient saturation risk. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of an application environment for an optimization adjustment method for relay protection setting parameters provided in Embodiment 1 of the present invention;

[0021] Figure 2 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment 2 of the present invention.

[0022] Figure 3This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment 3 of the present invention.

[0023] Figure 4 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment 4 of the present invention.

[0024] Figure 5 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment 5 of the present invention.

[0025] Figure 6 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment Six of the present invention.

[0026] Figure 7 This is a schematic diagram of the structure of an optimization and adjustment device for relay protection setting parameters provided in Embodiment 7 of the present invention;

[0027] Figure 8 This is a schematic diagram of the structure of a computer device provided in Embodiment 8 of the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] The method for optimizing and adjusting relay protection setting parameters provided in Embodiment 1 of this invention can be applied to applications such as... Figure 1 In this application environment, the client and server communicate over a network. The server provides optimization and adjustment services, and the client triggers optimization and adjustment tasks to the server. The client, also known as the user terminal, refers to the program that provides local services to the client, corresponding to the server. The client can be installed on, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0030] See Figure 2 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment 2 of the present invention. This method for optimizing and adjusting relay protection setting parameters is applied to... Figure 1 The server shown includes the following steps:

[0031] Step S201: Determine the target device to be protected, and obtain the current health data of the target current transformer and the parameter values ​​related to the characteristics of the target current transformer for status monitoring of the target device.

[0032] In this embodiment, the target device can refer to relay protection equipment, such as transformers, cables, and generators in a power system. The target instrument transformer can refer to an instrument transformer that monitors the status of the target device and provides a basis for action judgment for relay protection. The target instrument transformer can be a current transformer. The current transformer monitors the current on the target device side, proportionally converts the large current on the primary side of the target device into a small current on the secondary side, and outputs it to the subsequent relay protection device to provide a basis for action judgment for relay protection. The current health data can refer to data reflecting the current operating status and deterioration degree of the target instrument transformer. The parameter values ​​related to the characteristics of the target instrument transformer can refer to parameter values ​​reflecting the electromagnetic characteristics and steady-state performance of the target instrument transformer. The parameter values ​​can include the saturation knee voltage, excitation inductance, and core loss resistance of the target instrument transformer.

[0033] Specifically, the current operating status and deterioration level of the target transformer can be monitored through online and offline monitoring methods to obtain current health data, as well as the saturation knee voltage, magnetizing inductance, and core loss resistance of the target transformer.

[0034] Step S202: Based on the current health data, correct the parameter values ​​to obtain corrected parameter values. Based on the corrected parameter values, initialize the parameter values ​​of the virtual transformers in the power simulation model consisting of the virtual device corresponding to the target device and the virtual transformer corresponding to the target transformer to obtain the initialized power simulation model.

[0035] Step S203: Obtain N historical fault data of the target device and the target transformer in the actual operating scenario. Through the initialized power simulation model, simulate the actual operating scenario corresponding to each historical fault data to obtain the secondary side waveform output by the virtual transformer in the actual operating scenario corresponding to each historical fault data.

[0036] In this embodiment, the corrected parameter value can refer to the parameter value after correction based on the current health data. The virtual device can refer to a software-based digital entity in the power simulation model that is established based on the physical parameters and characteristics of the target device to simulate the target device. The virtual transformer can refer to a software-based digital component in the power simulation model that is established based on the physical parameters and electromagnetic characteristics of the target transformer to simulate the target transformer. The power simulation model can refer to a digital computing system composed of virtual devices, virtual transformers and other components, used to reproduce the dynamic operation process of the real power system under various operating conditions. The initialized power simulation model can refer to the power simulation model after the parameters of the virtual transformer have been configured according to the corrected parameter value.

[0037] Historical fault data can refer to the set of fault data recorded by the target equipment and the target transformer in past actual operation. It can include the fault type, fault location, and resistance range at the fault point in the circuit formed by the target equipment, the target transformer, and the fault points that occurred in past actual operation. N is an integer greater than zero. The actual operation scenario can refer to the fault condition scenario corresponding to the historical fault data. The secondary waveform can refer to the secondary waveform output by the virtual transformer in response to the actual operation scenario corresponding to the historical fault data. If the health of the target transformer deteriorates, the secondary waveform will reflect the characteristic that the deteriorated target transformer is more prone to transient saturation under the action of fault current, such as increased waveform distortion and increased second harmonic content.

[0038] Specifically, based on the current health data, the parameter values ​​related to the characteristics of the target transformer are corrected to obtain the corrected parameter values. Based on the corrected parameter values, the parameter values ​​of the virtual transformer in the power simulation model are configured to obtain the initialized power simulation model. Through the initialized power simulation model, the actual operating scenario corresponding to each historical fault data is simulated to obtain the secondary side waveform output by the virtual transformer under the actual operating scenario corresponding to each historical fault data.

[0039] Step S204: Based on all secondary side waveforms, assess the risk of transient saturation of the target transformer and obtain the risk assessment result. Based on the risk assessment result, adjust the relay protection setting parameters to obtain the adjusted setting parameters.

[0040] In this embodiment, the risk assessment result can refer to the result of assessing the risk of transient saturation of the target current transformer. This result quantifies the degree to which the target current transformer saturates and its potential adverse effects on relay protection. The setting parameter can refer to the electrical quantity threshold that triggers the protection action, which may include parameters such as operating current, operating time, and operating distance. The adjusted setting parameter can refer to the setting parameter adjusted according to the risk assessment result.

[0041] Specifically, based on all secondary side waveforms, the risk of transient saturation of the target transformer is assessed to obtain the risk assessment results. Based on the risk assessment results, the relay protection setting parameters are adjusted to obtain the adjusted setting parameters.

[0042] In this embodiment, the parameter values ​​of the target transformer are corrected based on its current health data, so that the corrected parameter values ​​can accurately reflect the true physical characteristics of the target transformer under the current operating state. Therefore, when the power simulation model initialized based on the corrected parameter values ​​simulates historical fault data, the output secondary waveform can accurately reflect the actual response characteristics and potential saturation distortion features of the target transformer when facing a fault under the current operating state. Based on this, the risk of transient saturation of the target transformer is quantitatively assessed according to the secondary waveform. Based on the risk assessment results, the relay protection setting parameters are adjusted so that the adjusted setting parameters can effectively cope with secondary current distortion caused by transformer deterioration and transient saturation, preventing protection maloperation or failure to operate. This improves the accuracy of relay protection in determining changes in equipment health status and the presence of transient saturation risk.

[0043] See Figure 3 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment 3 of the present invention. In step S202 above, the parameter values ​​are corrected based on the current health data to obtain the corrected parameter values, including the following steps:

[0044] Step S301: Based on the current health data, determine the health indicator data that characterizes the health status of the target transformer.

[0045] Step S302: For any parameter value, based on health indicator data and in conjunction with preset mapping rules, determine the correction amount to be applied to the parameter value.

[0046] Step S303: Obtain the weight value of the parameter value. Based on the parameter value, the correction amount, and the weight value, obtain the corrected parameter value corresponding to the parameter value.

[0047] In this embodiment, health indicator data can refer to indicators obtained based on current health data that can numerically represent the health status of the target transformer. Preset mapping rules can refer to the association rules or functional relationships between health indicator data and the correction amounts of corresponding parameter values. These can include linear mapping, nonlinear mapping, and expert experience rules. Linear mapping refers to a mapping method that quantifies the linear proportional relationship between health indicator data and correction amounts, which can be implemented using a linear function model. Nonlinear mapping refers to a mapping method that quantifies the nonlinear relationship between health indicator data and correction amounts, which can be implemented using a polynomial function, exponential function, or neural network model. Expert experience rules refer to rules established based on the knowledge and experience of domain experts. The qualitative or quantitative correlation rules between quantitative health indicator data and correction quantities can be implemented using conditional statements or fuzzy logic. The correction quantity can refer to the change between the corrected parameter value and the parameter value that has not been corrected based on the current health data. For example, the correction quantity can be the change of the parameter value relative to the standard value under the health state of the target transformer. It can be expressed as an absolute change or a relative change. The weight value of the parameter value can refer to the numerical value that characterizes the degree of influence of the parameter value on the transient saturation of the target transformer. For example, the saturation knee voltage of the target transformer has the most direct influence on transient saturation, and its weight value can be set to 0.6. The weight value of the excitation inductance can be set to 0.3, and the weight value of the core loss resistance can be set to 0.1.

[0048] Specifically, the current health data is analyzed to obtain health index data that can represent the health status of the target current transformer in numerical form. For any parameter value, based on the health index data and a preset mapping rule, the correction amount for the parameter value is determined. The correction amount is multiplied by the weight value of the parameter value to obtain the multiplication result. The multiplication result is added to the parameter value to obtain the corrected parameter value.

[0049] For example, based on health indicator data and a preset mapping rule, it is determined that the saturation knee voltage of the target transformer needs to be corrected by -10%, the excitation inductance by +5%, and the core loss resistance by -3%. If the target transformer's parameters are: saturation knee voltage 200V, excitation inductance 100mH, core loss resistance 500 ohms, with a weight of 0.6 for the saturation knee voltage, 0.3 for the excitation inductance, and 0.1 for the core loss resistance, then the process of obtaining the corrected values ​​for the saturation knee voltage, excitation inductance, and core loss resistance can be as follows:

[0050] Saturation knee voltage correction: 200V*(-10%)=-20V; Magnetizing inductance correction: 100mH*(+5%)=+5mH; Core loss resistance correction: 500 ohms*(-3%)=-15 ohms.

[0051] Update parameter values ​​using a weighted average method:

[0052] The corrected saturation knee voltage = 200V + (-20V * 0.6) = 200V - 12V = 188V; the corrected magnetizing inductance = 100mH + (5mH * 0.3) = 100mH + 1.5mH = 101.5mH; the corrected core loss resistance = 500 ohms + (-15 ohms * 0.1) = 500 ohms - 1.5 ohms = 498.5 ohms.

[0053] In this embodiment, by using health index data and preset mapping rules, the abstract trend of the deterioration of the current transformer's health status is transformed into specific numerical corrections of its parameters (such as the saturation knee voltage). Combined with the weighted allocation of different degrees of influence of each parameter on transient saturation, a refined and weighted adaptive update of the target current transformer's parameter values ​​is achieved. This corrected parameter value is then applied to a virtual current transformer, enabling the virtual current transformer's parameters to accurately reflect the true deterioration state of the target current transformer. This allows the secondary waveform output by the simulation to more realistically expose potential saturation distortion risks, improving the reliability of the simulation results. Furthermore, when adjusting the setting parameters based on the simulation results, the accuracy of setting parameter adjustments and relay protection judgments is also improved.

[0054] See Figure 4 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment 4 of the present invention. In step S203 above, the initialized power simulation model is used to simulate the actual operating scenario corresponding to each historical fault data, thereby obtaining the secondary side waveform output by the virtual transformer under the actual operating scenario corresponding to each historical fault data. The steps include the following:

[0055] Step S401: For any historical fault data, determine the simulation parameters for simulating the historical fault data based on the historical fault data.

[0056] Step S402: Determine the fault type, fault location, and fault resistance range of the corresponding fault point in the historical fault data;

[0057] Step S403: Using the initialized power simulation model, based on the simulation parameters, fault type, fault location, and fault resistance range, simulate the actual operating scenario corresponding to the historical fault data to obtain the secondary side waveform output by the virtual transformer under the actual operating scenario corresponding to the historical fault data.

[0058] In this embodiment, historical fault data may include the fault type, fault location, and fault resistance range of the fault point. The fault type may include single-phase grounding fault, two-phase short-circuit fault, and three-phase short-circuit fault. The fault location may include the near end, far end, and intermediate position between the busbars where the target transformer is located. The near-end fault location is less than 1 km from the busbar where the target transformer is located, and the far-end fault location is more than 5 km from the busbar where the target transformer is located. The fault resistance range refers to the resistance range at the fault point. The resistance at the fault point can be selected as low-impedance grounding resistance or high-impedance grounding resistance. The low-impedance grounding resistance can have a value range of 0-1 ohms, and the high-impedance grounding resistance can have a value range of 100-1000 ohms. Simulation parameters include simulation step size, simulation duration, and convergence accuracy. The simulation step size can be determined based on the power system frequency and transient process frequency, and is less than 1 / 20 of the highest transient process frequency. The simulation duration can cover the transient and steady-state processes after the fault occurs and is greater than 5 power frequency cycles. The convergence accuracy can be less than 1e-6 to ensure the accuracy of the simulation results.

[0059] Specifically, for any historical fault data, simulation parameters are determined based on the historical fault data. Through the initialized power simulation model, simulation is performed on the actual operating scenario corresponding to the historical fault data according to the simulation parameters, fault type, fault location and fault resistance range, and the secondary side waveform of the virtual transformer affected in the scenario is recorded.

[0060] Optionally, during the simulation of the actual operating scenario corresponding to the historical fault data using the initialized power simulation model based on simulation parameters, fault type, fault location, and fault resistance value range, at least one fault resistance value can be determined from the fault resistance value range. Based on the fault type, fault location, and each fault resistance value, fault injection parameters for simulating the historical fault data are determined. The fault injection parameters include the fault occurrence time, fault duration, and fault injection location. Based on the simulation parameters, fault injection parameters, fault type, fault location, and each fault resistance value, the actual operating scenario corresponding to the historical fault data is simulated to obtain the secondary side waveform output by the virtual transformer under the actual operating scenario corresponding to the historical fault data.

[0061] That is, based on the range of fault resistance values, multiple resistance values ​​are selected as fault resistance values ​​within the ranges of low-impedance grounding resistance and high-impedance grounding resistance. Based on the selected fault resistance values, combined with the fault type and fault location, the corresponding fault current amplitude is calculated. Based on the fault current amplitude, fault type, and fault location, fault injection parameters are determined. The fault injection parameters include the fault occurrence time, fault duration, and fault injection location. The fault occurrence time can be set to 0.1 seconds after the start of the simulation, the fault duration can be set to 0.2 seconds, and the fault injection location can be determined based on the fault location in the fault scenario set. Based on the simulation parameters, fault injection parameters, fault type, fault location, and each fault resistance value, the actual operating scenario corresponding to the historical fault data is simulated to obtain the secondary side waveform output by the virtual transformer under the actual operating scenario corresponding to the historical fault data.

[0062] Optionally, after obtaining the secondary waveform, the secondary waveform can also be filtered and denoised, and the data format can be converted. The filtering and denoising can be done using wavelet transform, and the data format can be converted to a general data format for subsequent analysis.

[0063] Optionally, the range of fault resistance values ​​can be determined based on a preset probability distribution model. The preset probability distribution model can be a mathematical model that describes the probability of occurrence of fault resistance at different values ​​by statistically analyzing the fault resistance values ​​in a large number of historical fault times. This model can be represented in the form of a histogram, probability density function curve, or cumulative distribution function.

[0064] In this embodiment, the range of values ​​for the fault resistance is determined by combining a preset probability distribution model, and a refined, multi-dimensional fault scenario simulation is performed on this basis. This allows the simulated secondary-side waveform to comprehensively and realistically reflect the transient response behavior of the target transformer under various extreme and typical operating conditions in its current healthy state, thereby improving the accuracy of the simulation. This provides an accurate data basis for subsequent transient saturation risk assessment and setting parameter adjustment, thus improving the accuracy of setting parameter adjustment and relay protection judgment.

[0065] See Figure 5 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment 5 of the present invention. In step S204 above, the risk of transient saturation of the target transformer is assessed based on all secondary side waveforms to obtain the risk assessment result, including the following steps:

[0066] Step S501: For any secondary waveform, perform Hilbert transform on the secondary waveform to obtain an analytical signal, and determine the instantaneous frequency and instantaneous amplitude based on the analytical signal.

[0067] Step S502: Based on the instantaneous frequency, use Fast Fourier Transform to identify the harmonic components in the second-order waveform, and calculate the amplitude and phase of any harmonic component.

[0068] Step S503: Determine the saturation range where the amplitude exceeds the preset saturation threshold from the secondary waveform, and determine the duration and saturation depth of the saturation range based on the instantaneous amplitude.

[0069] Step S504: Based on the amplitude, phase, duration of the saturation interval and saturation depth of each harmonic component, assess the risk of transient saturation of the target transformer, obtain the assessment results corresponding to the secondary side waveform, and take the assessment results corresponding to all secondary side waveforms as the risk assessment results.

[0070] In this embodiment, the analytic signal can refer to the complex signal obtained by performing a Hilbert transform on the secondary waveform. Its real part is the original real signal corresponding to the secondary waveform, and its imaginary part is the Hilbert transform of the original real signal. This imaginary part can be obtained by combining the original real signal with the Hilbert transform. The instantaneous frequency can refer to the frequency of the analytic signal at a certain moment, which can be calculated by differentiating the phase of the analytic signal with respect to time. The instantaneous amplitude can refer to the amplitude of the analytic signal at a certain moment, which can be calculated based on the magnitude of the analytic signal. Harmonic components can refer to components in the secondary waveform whose frequencies are integer multiples of the fundamental frequency. These components can be identified by performing a fast Fourier transform on the secondary waveform and analyzing them at specific frequency points. They can include the second, third, and fifth harmonics. The preset saturation threshold can refer to the amplitude limit set in advance to define whether the secondary waveform has entered a saturated state. It can be set by multiplying the rated current amplitude of the target transformer by a coefficient. The saturation interval can refer to the time period during which the amplitude of the secondary current waveform exceeds the preset saturation threshold. It can be identified by comparing the secondary waveform with the threshold. The duration can refer to the length of time that an event or state lasts. It can be calculated by measuring the time span of the saturation interval, reflecting the length of time the saturation state is maintained. The saturation depth can refer to the cumulative amount of the degree to which the waveform corresponding to the saturation interval exceeds the preset saturation threshold. It can be calculated by integrating the difference between the instantaneous amplitude in the saturation interval and the preset saturation threshold, quantifying the degree to which the waveform has penetrated into the saturation region.

[0071] Specifically, for any secondary-side waveform, a Hilbert transform is performed to obtain an analytical signal. Based on the analytical signal, the instantaneous frequency and instantaneous amplitude are calculated. Based on the instantaneous frequency, a Fast Fourier Transform is used to identify the 2nd, 3rd, and 5th harmonic components in the secondary-side waveform, and the amplitude and phase of each harmonic component are calculated. By setting a preset saturation threshold of 1.2 times the rated current amplitude, saturation intervals in the secondary-side waveform where the amplitude exceeds the preset saturation threshold are identified. Based on the instantaneous amplitude, the duration and saturation depth of the saturation interval are calculated. The saturation depth is defined as the integral of the difference between the instantaneous amplitude and the preset saturation threshold within the saturation interval. The amplitude, phase, duration, and saturation depth of each harmonic component are used as transient saturation characteristic quantities reflecting the transient saturation degree of the target transformer, and normalized to obtain a set of normalized transient saturation characteristic quantities. Based on the set of normalized transient saturation characteristic quantities, the risk of transient saturation of the target transformer is assessed, and the assessment results corresponding to the secondary-side waveforms are obtained. The assessment results corresponding to all secondary-side waveforms are the risk assessment results.

[0072] Optionally, during the process of performing a Hilbert transform on the secondary waveform to obtain an analytical signal, the model of the target current transformer can be determined. Based on the model of the target current transformer and a preset mapping table, the saturation voltage threshold corresponding to the target current transformer can be determined. The preset mapping table includes the mapping relationship between the model of the target current transformer and the saturation voltage threshold. Based on the saturation voltage threshold, the parameters of the Hilbert transform are adjusted. Based on the adjusted parameters of the Hilbert transform, the secondary waveform is subjected to a Hilbert transform to obtain an analytical signal.

[0073] That is, before determining the saturation voltage threshold corresponding to the target current transformer based on its model and a preset mapping table, a parameter database containing core material, winding parameters, and geometric dimensions can be established for different models of current transformers. Based on the parameter database, simulation models of different models of current transformers are established using the finite element analysis method, and simulation calculations are performed to obtain the volt-ampere characteristic curves of different models of current transformers at different saturation levels. Based on the volt-ampere characteristic curves, the saturation voltage threshold (i.e., the key voltage value on the volt-ampere characteristic curve indicating that the current transformer has entered the saturation state) of different models of current transformers is extracted, and a mapping relationship between the saturation voltage threshold and the current transformer model is established. When determining the saturation voltage threshold of the target current transformer, the mapping relationship between the saturation voltage threshold and the current transformer model in the preset mapping table is consulted according to the model of the target current transformer to obtain the saturation voltage threshold corresponding to the target current transformer. Based on the saturation voltage threshold, the Hilbert transform parameters are adaptively adjusted. The transform parameters include the time window length and the frequency resolution. The time window length is set to twice the saturation time corresponding to the saturation voltage threshold, and the frequency resolution is set to 1 / 10 of the frequency of the power system. Using the adjusted Hilbert transform parameters, the secondary waveform is subjected to Hilbert transform to obtain the analytical signal.

[0074] In this embodiment, the second-order waveform is processed by Hilbert transform to obtain its analytic signal, and the instantaneous frequency and instantaneous amplitude are calculated accordingly, thereby accurately capturing the dynamic characteristics of the waveform during transient saturation. Simultaneously, by identifying and analyzing the harmonic components in the waveform, the degree and type of saturation are effectively determined. Based on a preset saturation threshold, the duration and depth of saturation can be calculated within the identified saturation range based on the instantaneous amplitude, intuitively quantifying the persistence and severity of the saturation state from a time-domain perspective. Finally, the frequency domain features (harmonic amplitude, phase) and time domain features (saturation duration, depth) are combined to form a multi-dimensional, comprehensive set of transient saturation features. This feature set comprehensively describes the complex phenomenon of transient saturation from different perspectives, thereby improving the reliability and accuracy of the risk assessment.

[0075] See Figure 6 This is a flowchart illustrating a method for optimizing and adjusting relay protection setting parameters according to Embodiment Six of the present invention. In step S204 above, the relay protection setting parameters are adjusted based on the risk assessment results to obtain the adjusted setting parameters, including the following steps:

[0076] Step S601: Determine the protection type of the relay protection, and based on the protection type, determine the sensitivity of the relay protection to the transient saturation of the target transformer.

[0077] Step S602: Based on the risk assessment results and sensitivity, determine the adjustment amount for adjusting the setting parameters. Adjust the setting parameters according to the protection type and the adjustment amount to obtain the adjusted setting parameters.

[0078] In this embodiment, the relay protection types may include differential protection, overcurrent protection, and distance protection. The adjustment amount refers to the change in the setting parameters, which aims to compensate for measurement errors caused by changes in the health status of the target transformer and saturation, thereby improving the reliability of the protection.

[0079] Specifically, the protection type of the relay protection is determined. Based on the protection type, a preset saturation sensitivity level table is consulted to determine the sensitivity of the relay protection to the transient saturation of the target current transformer. The preset saturation sensitivity level table can be a pre-established data structure used to store the correspondence between different types of relay protection and the transient saturation sensitivity of current transformers, including high sensitivity level for differential protection, medium sensitivity level for overcurrent protection, and low sensitivity level for distance protection. Based on the risk assessment results, the transient saturation risk level or risk probability of the target current transformer is determined. Based on the transient saturation risk level and sensitivity of the target current transformer, a preset setting parameter adjustment lookup table is consulted to determine the adjustment amount for adjusting the setting parameters. The parameter adjustment lookup table can refer to a pre-established two-dimensional data structure used to store the adjustment amounts that the relay protection setting parameters should be adjusted under different transient saturation risk levels or probabilities and different combinations of transient saturation sensitivity. Based on the adjustment amounts of the setting parameters, the setting parameters are adjusted to obtain the adjusted setting parameters. For example, the adjustment methods can be as follows: if the relay protection is differential protection, then reduce the instantaneous overcurrent setting value of the differential instantaneous overcurrent protection and extend the operating time of the differential protection to enhance its anti-saturation false trip capability; if the relay protection is overcurrent protection, then increase the current setting value of the overcurrent protection to compensate for the low measured value caused by saturation; if the relay protection is distance protection, then increase the operating impedance of the distance protection to avoid the impedance measurement value being too small due to saturation.

[0080] In this embodiment, by combining the risk assessment results with the relay protection type, the setting parameters are adjusted. This comprehensively considers changes in the health status of the target transformer, transient saturation risk, and relay protection sensitivity, thereby improving the accuracy of setting parameter adjustment and thus improving the accuracy of relay protection in determining changes in equipment health status and the presence of transient saturation risk.

[0081] See Figure 7 This is a schematic diagram of a relay protection setting parameter optimization and adjustment device provided in Embodiment 7 of the present invention. This device corresponds one-to-one with the relay protection setting parameter optimization and adjustment method described in the above embodiments. Figure 7As shown, the relay protection setting parameter optimization and adjustment device includes a data acquisition module 71, an initial correction module 72, a simulation module 73, and a parameter adjustment module 74. Detailed descriptions of each functional module are as follows:

[0082] Data acquisition module 71 is used to determine the protected target device and acquire the current health data of the target current transformer for monitoring the status of the target device and parameter values ​​related to the characteristics of the target current transformer;

[0083] The initial correction module 72 is used to correct the parameter value according to the current health data to obtain the corrected parameter value, and to initialize the parameter value of the virtual transformer in the power simulation model composed of the virtual device corresponding to the target device and the virtual transformer corresponding to the target transformer according to the corrected parameter value to obtain the initialized power simulation model.

[0084] The simulation module 73 is used to acquire N historical fault data of the target device and the target transformer in the actual operation scenario. Through the initialized power simulation model, it simulates the actual operation scenario corresponding to each historical fault data to obtain the secondary side waveform output by the virtual transformer in the actual operation scenario corresponding to each historical fault data. N is an integer greater than zero.

[0085] The parameter adjustment module 74 is used to assess the risk of transient saturation of the target transformer based on all secondary side waveforms, obtain the risk assessment result, and adjust the relay protection setting parameters according to the risk assessment result to obtain the adjusted setting parameters.

[0086] Optionally, the aforementioned initial correction module 72 includes:

[0087] The first determining unit is used to determine health indicator data characterizing the health status of the target transformer based on the current health data.

[0088] The second determining unit is used to determine, for any parameter value, the amount of correction to be made to the parameter value based on the health indicator data and in combination with a preset mapping rule.

[0089] The parameter correction unit is used to obtain the weight value of the parameter value, and to obtain the corrected parameter value corresponding to the parameter value based on the parameter value, the correction amount and the weight value.

[0090] Optionally, the simulation module 73 mentioned above includes:

[0091] The third determining unit is used to determine, based on any historical fault data, simulation parameters for simulating the historical fault data, including simulation step size, simulation duration, and convergence accuracy.

[0092] The fourth determining unit is used to determine the fault type, fault location, and fault resistance range of the corresponding fault point in the historical fault data;

[0093] The first simulation unit is used to simulate the actual operating scenario corresponding to the historical fault data using the initialized power simulation model, based on the simulation parameters, the fault type, the fault location, and the fault resistance value range, to obtain the secondary side waveform output by the virtual transformer under the actual operating scenario corresponding to the historical fault data.

[0094] Optionally, the above-mentioned fault simulation unit includes:

[0095] The fifth determining subunit is used to determine at least one fault resistance value from the range of fault resistance values, and to determine fault injection parameters for simulating the historical fault data based on the fault type, the fault location and each fault resistance value. The fault injection parameters include the fault occurrence time, the fault duration and the fault injection location.

[0096] The second simulation subunit is used to simulate the actual operating scenario corresponding to the historical fault data based on the simulation parameters, the fault injection parameters, the fault type, the fault location, and each fault resistance value, so as to obtain the secondary side waveform output by the virtual transformer under the actual operating scenario corresponding to the historical fault data.

[0097] Optionally, the above parameter adjustment module 74 includes:

[0098] A waveform processing unit is used to perform a Hilbert transform on any secondary waveform to obtain an analytical signal, and to determine the instantaneous frequency and instantaneous amplitude based on the analytical signal.

[0099] The sixth determining unit is used to identify the harmonic components in the second-order waveform based on the instantaneous frequency using a fast Fourier transform, and to calculate the amplitude and phase of any harmonic component.

[0100] The seventh determining unit is used to determine the saturation interval from the secondary side waveform where the amplitude exceeds a preset saturation threshold, and to determine the duration and saturation depth of the saturation interval based on the instantaneous amplitude.

[0101] The evaluation unit is used to assess the risk of transient saturation of the target transformer based on the amplitude, phase, duration and saturation depth of each harmonic component, and to obtain the evaluation result corresponding to the secondary side waveform. The evaluation results corresponding to all secondary side waveforms are the risk assessment results.

[0102] Optionally, the waveform processing unit includes:

[0103] The eighth determining subunit is used to determine the model of the target current transformer. Based on the model of the target current transformer and in conjunction with a preset mapping table, the saturation voltage threshold corresponding to the target current transformer is determined. The preset mapping table includes the mapping relationship between the model of the target current transformer and the saturation voltage threshold.

[0104] The transformation adjustment subunit is used to adjust the parameters of the Hilbert transform according to the saturation voltage threshold to obtain the adjusted parameters of the Hilbert transform.

[0105] The transformation subunit is used to perform a Hilbert transform on the secondary side waveform according to the adjusted Hilbert transform parameters to obtain the analytical signal.

[0106] Optionally, the above parameter adjustment module 74 includes:

[0107] The ninth determining unit is used to determine the protection type of the relay protection and, based on the protection type, determine the sensitivity of the relay protection to the transient saturation of the target transformer.

[0108] The tenth determining unit is used to determine the adjustment amount for adjusting the setting parameters based on the risk assessment results and the sensitivity, and to adjust the setting parameters according to the protection type and the adjustment amount to obtain the adjusted setting parameters.

[0109] Specific limitations regarding the device for optimizing and adjusting relay protection setting parameters can be found in the limitations of the optimization and adjustment method for relay protection setting parameters described above, and will not be repeated here. Each module in the aforementioned device for optimizing and adjusting relay protection setting parameters can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0110] See Figure 8 This is a schematic diagram of the structure of a computer device provided in Embodiment 8 of the present invention. The computer device can be a server, and its internal structure diagram can be as follows. Figure 8As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores the current health data of the target current transformer and parameter values ​​related to the characteristics of the target current transformer. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a method for optimizing the adjustment of relay protection setting parameters.

[0111] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for optimizing and adjusting relay protection setting parameters described in the above embodiments, for example... Figure 2 As shown in S201-S204, or Figures 3 to 6 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the relay protection setting parameter optimization and adjustment device, for example... Figure 7 The functions of the data acquisition module 71, initial correction module 72, simulation module 73, and parameter adjustment module 74 shown are not described again here to avoid repetition.

[0112] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the method for optimizing and adjusting relay protection setting parameters as described in the above embodiment, for example... Figure 2 As shown in S201-S204, or Figures 3 to 6 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the relay protection setting parameter optimization and adjustment device, for example... Figure 7 The functions of the data acquisition module 71, initial correction module 72, simulation module 73, and parameter adjustment module 74 shown are not described again here to avoid repetition.

[0113] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0114] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0115] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for optimizing and adjusting relay protection setting parameters, characterized in that, include: Identify the target device to be protected, and obtain the current health data of the target current transformer used for status monitoring of the target device and parameter values ​​related to the characteristics of the target current transformer; Based on the current health data, the parameter values ​​are corrected to obtain corrected parameter values. Based on the corrected parameter values, the parameter values ​​of the virtual transformer in the power simulation model composed of the virtual device corresponding to the target device and the virtual transformer corresponding to the target transformer are initialized to obtain the initialized power simulation model. N historical fault data of the target device and the target transformer under actual operating scenarios are obtained. Through the initialized power simulation model, the actual operating scenarios corresponding to each historical fault data are simulated to obtain the secondary side waveform output by the virtual transformer under the actual operating scenarios corresponding to each historical fault data. N is an integer greater than zero. Based on all secondary side waveforms, the risk of transient saturation of the target transformer is assessed, and the risk assessment result is obtained. Based on the risk assessment result, the relay protection setting parameters are adjusted to obtain the adjusted setting parameters. The risk of transient saturation of the target transformer is assessed based on all secondary side waveforms, and the risk assessment results are obtained, including: For any secondary waveform, perform a Hilbert transform on the secondary waveform to obtain an analytical signal, and determine the instantaneous frequency and instantaneous amplitude based on the analytical signal; Based on the instantaneous frequency, the harmonic components in the second-order waveform are identified using a fast Fourier transform. For any harmonic component, the amplitude and phase of the harmonic component are calculated. The saturation interval where the amplitude exceeds a preset saturation threshold is determined from the secondary waveform, and the duration and saturation depth of the saturation interval are determined based on the instantaneous amplitude. The risk of transient saturation of the target transformer is assessed based on the amplitude, phase, duration and saturation depth of each harmonic component, and the assessment results corresponding to the secondary side waveform are obtained. The assessment results corresponding to all secondary side waveforms are the risk assessment results.

2. The method for optimizing and adjusting relay protection setting parameters according to claim 1, characterized in that, The step of correcting the parameter value based on the current health data to obtain the corrected parameter value includes: Based on the current health data, determine the health index data that characterizes the health level of the target transformer; For any parameter value, based on the health indicator data and a preset mapping rule, determine the correction amount for the parameter value. Obtain the weight value of the parameter value, and based on the parameter value, the correction amount, and the weight value, obtain the corrected parameter value corresponding to the parameter value.

3. The method for optimizing and adjusting relay protection setting parameters according to claim 1, characterized in that, The process involves using the initialized power simulation model to simulate the actual operating scenario corresponding to each historical fault data point, thereby obtaining the secondary waveform output by the virtual transformer under each historical fault data point's corresponding actual operating scenario. This includes: For any historical fault data, simulation parameters for simulating the historical fault data are determined based on the historical fault data. The simulation parameters include simulation step size, simulation duration, and convergence accuracy. Determine the fault type, fault location, and fault resistance range for the corresponding fault point in the historical fault data; Using the initialized power simulation model, based on the simulation parameters, the fault type, the fault location, and the fault resistance range, the actual operating scenario corresponding to the historical fault data is simulated to obtain the secondary waveform output by the virtual transformer under the actual operating scenario corresponding to the historical fault data.

4. The method for optimizing and adjusting relay protection setting parameters according to claim 3, characterized in that, The process involves using the initialized power simulation model to simulate the actual operating scenario corresponding to the historical fault data, based on the simulation parameters, fault type, fault location, and fault resistance range. This simulation yields the secondary waveform output by the virtual transformer under the corresponding actual operating scenario, including: At least one fault resistance value is determined from the range of fault resistance values. Based on the fault type, the fault location, and each fault resistance value, fault injection parameters are determined to simulate the historical fault data. The fault injection parameters include the fault occurrence time, the fault duration, and the fault injection location. Based on the simulation parameters, the fault injection parameters, the fault type, the fault location, and the resistance value of each fault, the actual operating scenario corresponding to the historical fault data is simulated to obtain the secondary side waveform output by the virtual transformer under the actual operating scenario corresponding to the historical fault data.

5. The method for optimizing and adjusting relay protection setting parameters according to claim 1, characterized in that, The step of performing a Hilbert transform on any second-order waveform to obtain an analytic signal includes: The model of the target current transformer is determined. Based on the model of the target current transformer and a preset mapping table, the saturation voltage threshold corresponding to the target current transformer is determined. The preset mapping table includes the mapping relationship between the model of the target current transformer and the saturation voltage threshold. Based on the saturation voltage threshold, the parameters of the Hilbert transform are adjusted to obtain the adjusted parameters of the Hilbert transform. Based on the adjusted Hilbert transform parameters, the secondary waveform is subjected to a Hilbert transform to obtain the analytic signal.

6. The method for optimizing and adjusting relay protection setting parameters according to claim 1, characterized in that, The step of adjusting the relay protection setting parameters based on the risk assessment results to obtain the adjusted setting parameters includes: Determine the protection type of the relay protection, and based on the protection type, determine the sensitivity of the relay protection to the transient saturation of the target current transformer; Based on the risk assessment results and the sensitivity, the adjustment amount for adjusting the setting parameters is determined. Based on the protection type and the adjustment amount, the setting parameters are adjusted to obtain the adjusted setting parameters.

7. A device for optimizing and adjusting relay protection setting parameters, characterized in that, include: The data acquisition module is used to determine the target device to be protected, and to acquire the current health data of the target current transformer for monitoring the status of the target device and the parameter values ​​related to the characteristics of the target current transformer. The initial correction module is used to correct the parameter values ​​according to the current health data to obtain corrected parameter values, and to initialize the parameter values ​​of the virtual transformers in the power simulation model composed of the virtual device corresponding to the target device and the virtual transformer corresponding to the target transformer according to the corrected parameter values ​​to obtain an initialized power simulation model. The simulation module is used to acquire N historical fault data of the target device and the target transformer in the actual operating scenario. Through the initialized power simulation model, the actual operating scenario corresponding to each historical fault data is simulated to obtain the secondary side waveform output by the virtual transformer in the actual operating scenario corresponding to each historical fault data. N is an integer greater than zero. The parameter adjustment module is used to assess the risk of transient saturation of the target transformer based on all secondary side waveforms, obtain the risk assessment result, and adjust the relay protection setting parameters according to the risk assessment result to obtain the adjusted setting parameters. The parameter adjustment module includes: A waveform processing unit is used to perform a Hilbert transform on any secondary waveform to obtain an analytical signal, and to determine the instantaneous frequency and instantaneous amplitude based on the analytical signal. The sixth determining unit is used to identify the harmonic components in the second-order waveform based on the instantaneous frequency using a fast Fourier transform, and to calculate the amplitude and phase of any harmonic component. The seventh determining unit is used to determine the saturation interval from the secondary side waveform where the amplitude exceeds a preset saturation threshold, and to determine the duration and saturation depth of the saturation interval based on the instantaneous amplitude. The evaluation unit is used to assess the risk of transient saturation of the target transformer based on the amplitude, phase, duration and saturation depth of each harmonic component, and to obtain the evaluation result corresponding to the secondary side waveform. The evaluation results corresponding to all secondary side waveforms are the risk assessment results.

8. A computer device, characterized in that, The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for optimizing and adjusting relay protection setting parameters as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for optimizing and adjusting relay protection setting parameters as described in any one of claims 1 to 6.

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