A power supply system impedance and short circuit current detection method and system

Abstract

The application discloses a kind of power supply system impedance and short-circuit current detection method and system, it is related to the field of measurement electric variable, in the method, by calculating the node voltage and current characteristic quantity based on the data collected, line impedance is calculated by establishing voltage drop equation and considering temperature influence impedance correction is carried out.The impedance of transformer equipment is determined by obtaining the parameters of the transformer equipment, and the equivalent impedance of the load is calculated.The short-circuit fault is identified by real-time monitoring of the current change rate, voltage amplitude and high-frequency characteristics, and the threshold set by historical data is combined to identify the short-circuit fault.After determining that a short-circuit fault occurs, the fundamental short-circuit current is calculated using the modified impedances by the symmetrical component method, and the impact coefficient is calculated by combining the real-time reactance and resistance ratio of the system, and the peak short-circuit current is finally obtained.The application is used to improve the accuracy of short-circuit current calculation results in a temperature environment with large fluctuations, thereby improving the reliability of relay protection setting.

Description

Technical Field

[0001] This application belongs to the field of measuring electrical variables, and in particular relates to a method and system for detecting the impedance and short-circuit current of a power supply system. Background Technology

[0002] The stable operation of the power supply system is crucial for ensuring the continuity of industrial production and residents' lives. Among these, accurately grasping the short-circuit current level of the system is the foundation for relay protection settings, equipment selection, and power grid structure optimization.

[0003] Related technologies typically employ an online short-circuit current monitoring method based on a wide-area measurement system (WAMS). This method involves installing synchronous phasor measurement devices (PMUs) at key nodes such as substations to collect synchronous phasor data of voltage and current in real time. Using Thevenin's equivalent theorem, the entire external power grid is equivalently represented as a series model of a voltage source and internal impedance. Then, the equivalent impedance of the system is inferred from the real-time measured boundary node data, and the short-circuit current is estimated accordingly.

[0004] However, power supply lines are often exposed to drastically changing temperature environments for extended periods, or experience significant self-heating due to high-current loads. Consequently, the actual resistivity of the conductors drifts significantly with temperature. The aforementioned related technologies typically assume that system parameters are linear and stable over short periods, focusing primarily on changes in electrical quantities at the ports, but failing to consider the nonlinear effects of the physical environment on impedance parameters. When a short-circuit fault occurs, if the impedance model, which does not consider environmental thermal effects, is still used for calculations, the fit between the calculated peak short-circuit current and the actual physical value will decrease, thus affecting the accuracy of relay protection device operation and posing a potential risk to the safe operation of the power supply system. Summary of the Invention

[0005] This application provides a method and system for detecting the impedance and short-circuit current of a power supply system, which improves the accuracy of short-circuit current calculation results under drastic temperature changes, thereby enhancing the reliability of relay protection settings.

[0006] Firstly, this application provides a method for detecting impedance and short-circuit current in a power supply system. This method involves using distributed monitoring units deployed at the beginning of the power supply line, the transformer side, and the load side to collect electrical and environmental parameters of each node in the power supply system. Based on the electrical operating parameters, the method calculates the voltage and current characteristics corresponding to each node. A voltage drop equation is established based on the voltage and current characteristics, and the line impedance of adjacent nodes is calculated based on the voltage drop equation. The line impedance is corrected according to environmental parameters and a preset resistance temperature coefficient to obtain the corrected line impedance. Parameters of the transformer equipment within the power supply system are obtained, and the transformer equipment impedance is determined based on these parameters. Finally, the method calculates the impedance based on the voltage and current characteristics of the load side. The system calculates the equivalent impedance of the load by measuring parameters; extracts the current rate of change, voltage phasor amplitude, and high-frequency component characteristics of electrical operating parameters in real time; calculates the short-circuit judgment threshold based on the historical maximum current rate of change within a preset time window; determines that a short-circuit fault has occurred in the power supply system when the current rate of change is greater than the short-circuit judgment threshold, the voltage phasor amplitude is less than the preset rated voltage ratio, and there are high-frequency components within a preset range in the high-frequency component characteristics; calculates the fundamental short-circuit current using the symmetrical component method based on the corrected line impedance, transformer equipment impedance, and load equivalent impedance; calculates the impulse coefficient based on the ratio of the real-time reactance to the real-time resistance of the power supply system; and uses the product of the impulse coefficient and the fundamental short-circuit current as the peak value of the short-circuit current.

[0007] By adopting the above technical solution, distributed monitoring units are deployed to collect electrical and environmental parameters, calculate the voltage and current characteristics of each node, and perform temperature correction on the line impedance based on environmental parameters. Simultaneously, considering the impedance of transformer equipment and the equivalent impedance of the load, the actual impedance characteristics of the power supply system can be more accurately reflected. Based on this, short-circuit faults are identified through a comprehensive judgment of current change rate, voltage phasor amplitude, and high-frequency component characteristics, reducing potential misjudgments that might arise from relying on a single characteristic. The fundamental short-circuit current is calculated using the symmetrical component method, and an impact coefficient considering the ratio of real-time system reactance to resistance is introduced, making the calculated peak short-circuit current more closely resemble actual operating conditions, improving the accuracy of short-circuit current detection, and contributing to the precise setting of power supply system protection devices.

[0008] In conjunction with some implementations of the first aspect, in some implementations, a voltage drop equation is established based on voltage and current characteristic quantities, and the line impedance of adjacent nodes is calculated based on the voltage drop equation. Specifically, this includes: denoting the voltage characteristic quantities as the line start-up voltage and line end voltage, and the current characteristic quantities as the line start-up current and line end current; establishing a voltage drop equation based on the line start-up voltage, line end voltage, line start-up current, and line end current, the voltage drop equation being: ;

[0009] In the above function, This is the voltage at the beginning of the line. This is the voltage at the end of the line. This is the current at the beginning of the line. For line impedance, This is the current at the end of the line. This is the equivalent branch load impedance between the two ends of the line;

[0010] The voltage drop equation is solved using the least squares method to obtain the line impedance.

[0011] By adopting the above technical solution, and establishing a voltage drop equation that includes the voltage and current at the beginning and end of the line as well as the load branch impedance, and solving this equation using the least squares method, the influence of measurement errors and system noise on the calculation results can be effectively eliminated. This method considers the influence of load branch impedance on voltage drop, making the calculated line impedance value closer to the actual value and improving the accuracy of line impedance measurement. Since the voltage drop equation contains complete circuit topology information, the calculation results can reflect the dynamic changes in line impedance, enhancing the reliability of impedance measurement results.

[0012] In conjunction with some implementation methods of the first aspect, in some implementation methods, a short-circuit determination threshold is calculated based on the historical maximum current change rate within a preset time window, specifically including:

[0013] The historical maximum current change rate is input into the preset threshold calculation function to obtain the short-circuit determination threshold. The preset threshold calculation function is as follows: ;

[0014] In the above function, For preset coefficients, This represents the maximum rate of change of current within a preset time window. This is the threshold for determining a short circuit.

[0015] By adopting the above technical solution and employing an adaptive threshold calculation method based on the historical maximum current change rate, the short-circuit judgment threshold can be dynamically adjusted according to changes in the system's operating state by introducing a preset coefficient to adjust the historical maximum current change rate. This threshold calculation method reduces the false judgment rate that a fixed threshold may cause under different operating conditions, and improves the adaptability of short-circuit fault judgment. Because the threshold calculation takes into account the system's historical operating data, short-circuit fault judgment is more consistent with the actual operating characteristics of the power supply system, enhancing the accuracy of fault judgment.

[0016] In conjunction with some implementations of the first aspect, in some implementations, the fundamental short-circuit current is calculated using the symmetrical component method based on corrected line impedance, transformer equipment impedance, and load equivalent impedance. Specifically, this includes:

[0017] When the short-circuit fault is determined to be a three-phase short-circuit fault, the corrected line impedance, transformer equipment impedance, and load equivalent impedance are input into the three-phase short-circuit current calculation function to obtain the fundamental short-circuit current. The three-phase short-circuit current calculation function is as follows: ;

[0018] If the short circuit fault is determined to be a single-phase-to-ground short circuit fault, the corrected line impedance, transformer equipment impedance, and load equivalent impedance are input into the single-phase-to-ground short circuit current calculation function to obtain the fundamental short circuit current. The single-phase-to-ground short circuit current calculation function is as follows:

[0019] ;

[0020] In the above function, For fundamental short-circuit current, Rated voltage, This is the minimum value of the equivalent load impedance. Zero-sequence impedance, It is a positive sequence impedance. To correct the line impedance, This refers to the impedance of the transformer equipment.

[0021] By adopting the above technical solution, and by distinguishing between three-phase short-circuit faults and single-phase ground faults, different calculation functions are used for each. The corrected line impedance, transformer equipment impedance, and load equivalent impedance are substituted into the calculation, making the calculation of the fundamental short-circuit current more consistent with the characteristics of actual fault types. The minimum value of the load equivalent impedance is considered in the three-phase short-circuit current calculation, while zero-sequence impedance and positive-sequence impedance are introduced in the single-phase ground fault current calculation, improving the accuracy of current calculations under different types of short-circuit faults. Because the calculation method matches the fault type, the reliability of the short-circuit current calculation results is enhanced.

[0022] In conjunction with some implementations of the first aspect, in some implementations, the impact coefficient is calculated based on the ratio of the real-time reactance to the real-time resistance of the power supply system. Specifically, this includes: extracting the resistance and reactance components from the corrected line impedance, transformer equipment impedance, and load equivalent impedance; calculating the real-time reactance and real-time resistance of the power supply system based on the resistance and reactance components; calculating the ratio of the real-time reactance to the real-time resistance; and calculating the impact coefficient based on the attenuation characteristics of the short-circuit transient aperiodic component corresponding to the ratio.

[0023] By employing the above technical solution, the resistive and reactive components of the modified line impedance, transformer equipment impedance, and load equivalent impedance are extracted to calculate the real-time reactance to real-time resistance ratio of the power supply system. Based on the attenuation characteristics of the short-circuit transient aperiodic component corresponding to this ratio, the impact coefficient is calculated. This allows for the consideration of the dynamic changes in the power supply system impedance characteristics when calculating the peak short-circuit current. Since the attenuation characteristics of the short-circuit transient aperiodic component are directly related to the reactance to resistance ratio of the system impedance, real-time calculation can more accurately reflect the transient characteristics under the current system state. This method of calculating the impact coefficient based on real-time impedance characteristics improves the accuracy of short-circuit current peak calculation, making the calculation results closer to the physical characteristics of the actual system, and contributing to more reasonable setting of system protection device parameters.

[0024] In some implementations of the first aspect, after taking the product of the impulse coefficient and the fundamental short-circuit current as the peak value of the short-circuit current, the method further includes: determining the current measured equivalent temperature of the line based on the corrected line impedance; calculating the theoretical temperature rise of the line under the current load based on the current characteristic quantity and the preset line thermal balance model; calculating the temperature rise deviation between the measured equivalent temperature and the theoretical temperature rise; and determining that the line has abnormal contact impedance and issuing a warning signal for line aging or poor contact when the temperature rise deviation exceeds the preset contact hazard threshold.

[0025] By employing the above technical solution, the temperature rise deviation can be obtained by comparing the current measured equivalent temperature of the line with the theoretical temperature rise calculated based on the thermal balance model. When the temperature rise deviation exceeds the preset contact hazard threshold, it indicates that the actual heating degree of the line is significantly higher than the theoretical heating degree under normal conditions. Since poor line contact or aging can lead to increased local contact resistance, resulting in abnormal heating, this type of anomaly can be detected by monitoring the temperature rise deviation. This monitoring method based on temperature rise deviation improves the detection sensitivity of line contact condition deterioration, which is beneficial for timely detection of abnormal heating phenomena caused by poor line contact or aging, and reduces the probability of faults caused by line contact problems.

[0026] In conjunction with some implementation methods of the first aspect, in some implementation methods, the preset line thermal balance model is as follows: ;

[0027] In the above function, For the specific heat capacity of the circuit, For line quality, For theoretical temperature rise, It is a characteristic quantity of current. As a reference resistor, For reference temperature, To consider the overall heat dissipation coefficient, For heat dissipation area, For ambient temperature, It is the sensitivity coefficient for the change of resistivity of a conductor material with temperature.

[0028] This represents the rate at which the circuit itself absorbs heat as its temperature rises.

[0029] This represents the Joule heat power generated when an electric current passes through a conductor.

[0030] This represents the heat output power that the line dissipates into the environment.

[0031] By adopting the above technical solution and employing a thermal balance model that considers multiple influencing factors such as the temperature coefficient of resistance of conductor materials, ambient temperature, and heat dissipation conditions, the model can more accurately describe the temperature change process of the line under actual operating conditions by balancing the power generated by Joule heating, the power absorbed by the line, and the power dissipated. This model not only considers the influence of current magnitude on heating but also the effects of line material properties and environmental conditions on temperature rise, as well as the heat exchange process between the line and the environment. This modeling method based on detailed physical processes improves the accuracy of theoretical temperature rise calculations for the line, making the calculated temperature rise deviation values ​​more reflective of the actual contact state of the line and enhancing the reliability of contact fault diagnosis.

[0032] In a second aspect, embodiments of this application provide a power supply system impedance and short-circuit current detection system, which includes: one or more processors and a memory; the memory is coupled to one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to cause the system to perform the method described in the first aspect and any possible implementation thereof.

[0033] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a system, cause the system to perform the method described in the first aspect and any possible implementation thereof.

[0034] Fourthly, embodiments of this application provide a computer program product that, when run on a system, causes the system to execute the method described in any possible implementation of the first aspect.

[0035] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0036] 1. This application provides a method for detecting impedance and short-circuit current in a power supply system. By deploying distributed monitoring units to collect electrical operating parameters and environmental parameters, the voltage and current characteristics of each node are calculated. Temperature correction is applied to the line impedance based on environmental parameters. Simultaneously, considering the impedance of transformer equipment and the equivalent impedance of the load, the actual impedance characteristics of the power supply system can be more accurately reflected. Based on this, short-circuit faults are identified through a comprehensive judgment of current change rate, voltage phasor amplitude, and high-frequency component characteristics, reducing potential misjudgments that may arise from relying on a single characteristic. The fundamental short-circuit current is calculated using the symmetrical component method, and an impact coefficient considering the ratio of real-time system reactance to resistance is introduced, making the calculated peak short-circuit current more closely resemble actual operating conditions, improving the accuracy of short-circuit current detection, and contributing to the precise setting of power supply system protection devices.

[0037] 2. This application provides a method for detecting the impedance and short-circuit current of a power supply system. By comparing the current measured equivalent temperature of the line with the theoretical temperature rise calculated based on a thermal balance model, a temperature rise deviation value can be obtained. When the temperature rise deviation value exceeds a preset contact hazard threshold, it indicates that the actual heating degree of the line is significantly higher than the theoretical heating degree under normal conditions. Poor line contact or aging can lead to increased local contact resistance, resulting in abnormal heating. This type of abnormality can be detected by monitoring the temperature rise deviation value. This monitoring method based on temperature rise deviation improves the detection sensitivity of line contact condition deterioration, which is beneficial for timely detection of abnormal heating phenomena caused by poor line contact or aging, and reduces the probability of faults caused by line contact problems. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating a method for detecting the impedance and short-circuit current of a power supply system in an embodiment of this application.

[0039] Figure 2 This is another flowchart illustrating a method for detecting the impedance and short-circuit current of a power supply system in an embodiment of this application.

[0040] Figure 3 This is a schematic diagram of the physical device structure of a power supply system impedance and short-circuit current detection system provided in an embodiment of this application. Detailed Implementation

[0041] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0042] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0043] The following example is used in conjunction with Figure 1 The present application describes a method for detecting the impedance and short-circuit current of a power supply system in an embodiment of the present application:

[0044] Please see Figure 1 This is a flowchart illustrating a method for detecting the impedance and short-circuit current of a power supply system in an embodiment of this application.

[0045] S101. By deploying distributed monitoring units at the beginning of the power supply line, the transformer side, and the load side, electrical operating parameters and environmental parameters of each node of the power supply system are collected.

[0046] Distributed monitoring units (DMUs) refer to intelligent electronic devices deployed at key nodes of the power network, including but not limited to synchronous phasor measurement units (PMUs), smart meters, protection and control devices with communication functions, and IoT sensor nodes. The power supply system line head end typically refers to the substation outgoing line or power access point; the transformer side refers to the high-voltage or low-voltage bushing of the distribution transformer; and the load side refers to the user terminal or branch box. Electrical operating parameters include instantaneous values ​​of three-phase voltage, instantaneous values ​​of three-phase current, active power, reactive power, power factor, and frequency—physical quantities that reflect the power quality and operating status of the power grid. Environmental parameters mainly refer to external conditions affecting the physical characteristics of conductors, including ambient temperature, relative humidity, wind speed, and solar radiation intensity, among which ambient temperature is a key factor affecting conductor resistivity. The system uses high-frequency sampling technology to digitize the analog signals at the above locations, forming a time-synchronized discrete data sequence. During the acquisition process, the system must ensure the time synchronization of each distributed node to guarantee the accuracy of subsequent phase calculations. The term "unrestricted" means that the communication method of the distributed monitoring unit can be wired or wireless, and environmental parameters can be collected through integrated sensors or through data access from external weather stations.

[0047] The system implements this step using two main methods and technologies. The first method is data acquisition based on fiber optic differential protection channels or industrial Ethernet. The system utilizes the existing fiber optic communication network within the substation, employing the IEC61850 communication protocol or Modbus TCP protocol to transmit high-precision voltage and current waveform data collected by each monitoring unit in real-time to the central processing unit in the form of Sampled Values ​​(SV) messages. This method has strong anti-interference capabilities and low data transmission latency, making it suitable for backbone network monitoring with extremely high real-time requirements. The second method is a wireless acquisition scheme based on LPWAN technology. For geographically dispersed load-side nodes where cabling is difficult, the system utilizes LoRa, NB-IoT, or 5G communication modules to construct a wireless sensor network. The monitoring unit performs preliminary compression encoding on the collected electrical and environmental quantities locally, and then transmits them wirelessly to an edge computing gateway or cloud platform. This method offers flexible deployment, lower cost, and is suitable for large-scale low-voltage distribution network end-point monitoring.

[0048] S102. Calculate the voltage and current characteristics of each node based on the electrical operating parameters;

[0049] Voltage characteristics refer to key indicators extracted from the acquired instantaneous voltage value sequence that characterize the voltage state. These mainly include the effective voltage value (RMS), voltage phasor (including amplitude and phase angle), fundamental voltage component, and harmonic components. Similarly, current characteristics refer to the effective current value, current phasor, fundamental current component, and harmonic content. "Node-specific" means the system processes data independently from the line start-up, transformer side, and load side. The calculation process involves digital signal processing techniques, aiming to convert time-domain waveform data into frequency-domain or complex-domain characteristic data to facilitate subsequent impedance calculations and fault analysis. In this step, the system needs to denoise the raw data to filter out high-frequency noise interference. The accuracy of voltage and current characteristic calculations directly determines the accuracy of subsequent impedance calculations; therefore, the system typically employs high-precision algorithms to handle aperiodic components and spectral leakage.

[0050] The system implements this step using two main methods and technologies. The first method employs a full-cycle Fourier transform (DFT) algorithm. The system uses the power frequency cycle as a reference and performs a discrete Fourier transform on sampled data from one or more cycles. Through the calculation of orthogonal components, the system can accurately separate the real and imaginary parts of the fundamental wave, thereby calculating the amplitude and phase of the voltage and current. To overcome spectral leakage caused by asynchronous sampling, the system can combine windowing interpolation algorithms (such as the Hanning window or Blackman window) to correct frequency deviations and improve the accuracy of phasor calculations. The second method uses a phase-locked loop (PLL) technique based on a second-order generalized integrator (SOGI). The system constructs an orthogonal signal generator to track the frequency changes of the grid voltage in real time and generate a virtual signal orthogonal to the input signal. Through coordinate transformation (such as the Park transform), the system converts the AC quantity in the stationary coordinate system into a DC quantity in a synchronously rotating coordinate system, thereby calculating the amplitude and phase information of the voltage and current in real time. This method has a fast dynamic response speed and is particularly suitable for weak grid environments with large frequency fluctuations.

[0051] S103. Establish voltage drop equations based on voltage and current characteristics, and calculate line impedances of adjacent nodes based on voltage drop equations.

[0052] The system establishes a voltage drop equation based on voltage and current characteristic quantities, and calculates the line impedance of adjacent nodes based on this equation. Specifically, the voltage characteristic quantities are denoted as the line start-up voltage and line end voltage, and the current characteristic quantities are denoted as the line start-up current and line end current. A voltage drop equation is established based on these three values: ;

[0053] In the above function, This is the voltage at the beginning of the line. This is the voltage at the end of the line. This is the current at the beginning of the line. For line impedance, This is the current at the end of the line. The equivalent branch load impedance between the two ends of the line is given; the line impedance is obtained by solving the voltage drop equation using the least squares method.

[0054] The voltage drop equation is a mathematical model describing the relationship between the voltage difference across a power line, the current flowing through the line, and the line impedance. In this step, the voltage characteristics are specified as the voltage at the beginning and end of the line, and the current characteristics are specified as the current at the beginning and end of the line. Line impedance refers to the equivalent complex impedance of the conductor between the beginning and end of the line, including resistive and inductive components. The equivalent branch load impedance between the two ends of the line represents the combined effect of distributed loads or parallel branches that may exist in the middle of the line. The least squares method is a mathematical optimization technique that finds the best function match for the data by minimizing the sum of squares of the errors. Here, due to the noise in the measurement data, the impedance value calculated in a single step may be inaccurate. The system uses multiple sets of measurement data to construct an overdetermined system of equations and solves for the sum of the equation residuals and the optimal estimate.

[0055] The system implements this refined technical solution using two main methods. The first method employs Recursive Least Squares (RLS). This method eliminates the need to store large amounts of historical data; instead, it updates the impedance estimate in real-time as new voltage and current sampling data arrives. The system initializes a covariance matrix and parameter vector. Upon receiving a new set of data, it corrects the current impedance estimate based on the prediction error and updates the covariance matrix. This method has low computational complexity, making it suitable for online operation in embedded terminals and enabling rapid tracking of slow changes in line impedance over time. The second method employs Total Least Squares (TLS). Considering that not only voltage measurements but also current measurements have errors (i.e., the variables on both sides of the equation contain noise), traditional least squares methods may introduce bias. The system constructs an augmented matrix and uses Singular Value Decomposition (SVD) to solve the linear equations while considering errors in all variables.

[0056] S104. Based on environmental parameters and the preset resistance temperature coefficient, the line impedance is corrected to obtain the corrected line impedance.

[0057] Environmental parameters mainly refer to the ambient temperature along the line collected in step S101. The preset temperature coefficient of resistance is the proportionality constant of the resistivity of the conductor material (such as copper or aluminum) as a function of temperature, usually defined at 20 degrees Celsius. Line impedance correction aims to eliminate the significant impact of temperature changes on the resistance value of the conductor, because the resistance of metallic conductors increases with temperature. Correcting the line impedance means reducing the original impedance value calculated based on real-time electrical quantities to the impedance at a certain reference temperature, or adjusting the theoretical impedance model according to the current actual temperature to make it more consistent with the current physical state. This step is crucial for improving the accuracy of short-circuit current calculation, because the magnitude of the short-circuit current is very sensitive to the loop impedance. The system needs to store the material information of the line conductors (copper, aluminum, steel-cored aluminum stranded wire, etc.) and their corresponding physical constants. The correction process is usually based on the linear resistance-temperature formula in physics.

[0058] The system implements this step using two main methods and technologies. The first method is dynamic correction based on real-time temperature monitoring. The system directly reads the values ​​from temperature sensors deployed in line towers or cable trenches. Using the temperature dependence formula for conductor resistance, the system calculates the current temperature correction factor, using 20℃ or 75℃ as a reference. The system multiplies the line resistance component calculated in step S103 by this correction factor, while the inductance component is generally considered to be less affected by temperature, remaining unchanged or undergoing minor adjustments, thus obtaining the corrected line impedance. The second method is indirect correction based on a thermal balance model. In the absence of direct temperature sensors, the system uses collected load current data, environmental meteorological data (such as air temperature, sunshine duration, and wind speed), and conductor geometric parameters to establish a thermal balance differential equation for the conductor (IEEE 738 standard model). The system solves for the real-time operating temperature of the conductor through numerical integration, and then uses this calculated temperature to correct the line impedance.

[0059] S105. Calculate the equivalent impedance of the load based on the voltage and current characteristics on the load side;

[0060] The voltage and current characteristics on the load side refer to the voltage and current data collected and calculated at the user's connection point or the low-voltage side of the distribution transformer. The equivalent load impedance simplifies the complex downstream power network (including various motors, lighting, electronic equipment, etc.) into an equivalent complex impedance model. This impedance is not a fixed value but changes in real time with user electricity consumption and equipment operating status. The purpose of calculating the equivalent load impedance is to accurately assess the load's shunting or amplifying effect on the short-circuit current (such as motor feedback current) in subsequent short-circuit current calculations. The system typically uses the complex form of Ohm's law, dividing the voltage phasor by the current phasor to obtain the real-time equivalent impedance magnitude and impedance angle. The system needs to distinguish between the characteristics of static and dynamic loads because they behave differently at the moment of a short circuit.

[0061] The system implements this step using two main methods and technologies. The first method is a direct calculation based on steady-state power frequency quantities. The system utilizes the fundamental voltage phasor and fundamental current phasor extracted in step S102. Through complex division, the apparent impedance of the load is directly obtained and decomposed into equivalent resistance and equivalent reactance. This method assumes that the load characteristics are linear and time-invariant within the sampling window, making it suitable for equivalent modeling of most residential and commercial lighting loads. It is simple to calculate and has high real-time performance. The second method is a dynamic modeling method based on load identification. The system not only utilizes current voltage and current data but also combines it with a historical load feature database. Through cluster analysis or pattern recognition algorithms, it determines the main components of the current load (such as the proportion of induction motors). For loads containing a large number of motors, the system uses an equivalent circuit model of induction motors and inversely calculates the slip and equivalent rotor impedance based on the measured P and Q (active and reactive power).

[0062] S106. Real-time extraction of current change rate, voltage phasor amplitude and high-frequency component characteristics of electrical operating parameters;

[0063] The rate of change of current (di / dt) refers to how quickly the instantaneous value of current changes over time, and is an important indicator of whether there are sudden changes (such as short-circuit faults) in a circuit. Voltage phasor amplitude refers to the amplitude or effective value of the voltage waveform, used to determine whether a voltage drop has occurred in the system. High-frequency component characteristics refer to the high-frequency signal components superimposed on the power frequency (50Hz or 60Hz) waveform, usually generated by arcs, traveling waves, or equipment switching actions at the moment of a fault. Real-time extraction means that the system needs to complete data processing and feature calculation within an extremely short time window (usually on the order of milliseconds). Preset interval high-frequency components refer to the signal energy within a specific frequency range (e.g., from several hundred hertz to several thousand hertz) that the system focuses on; this range is usually the frequency band where short-circuit fault characteristics are most obvious. This step is the pre-processing stage of the fault detection algorithm, aiming to extract key feature vectors that can characterize the fault from massive amounts of raw waveform data.

[0064] The system implements this step using two main methods and techniques. The first method is feature extraction based on differential operations and digital filtering. For the rate of change of current, the system approximates the derivative by dividing the current difference between adjacent sampling points by the sampling interval. For the voltage amplitude, the system uses half-cycle integration or peak detection algorithms for rapid acquisition. For high-frequency components, the system designs a set of digital bandpass filters (such as IIR or FIR filters), with the center frequency set within the dominant frequency range of the fault traveling wave. After filtering out the power frequency components, the energy or amplitude of the remaining signal is calculated. The second method is multi-scale analysis based on wavelet transform. The system selects a wavelet basis suitable for power system transient analysis (such as the Daubechies wavelet) to perform multi-level decomposition of the voltage and current signals. Utilizing the detail components of the wavelet coefficients at different scales, the system can simultaneously obtain the signal's abrupt change points (corresponding to di / dt extrema), low-frequency profile (corresponding to voltage amplitude), and high-frequency details (corresponding to high-frequency component characteristics).

[0065] S107. Calculate the short-circuit judgment threshold based on the historical maximum current change rate within a preset time window.

[0066] The system calculates a short-circuit determination threshold based on the historical maximum current change rate within a preset time window. Specifically, this involves inputting the historical maximum current change rate into a preset threshold calculation function to obtain the short-circuit determination threshold. The preset threshold calculation function is as follows: ;

[0067] In the above function, For preset coefficients, This represents the maximum rate of change of current within a preset time window. This is the threshold for determining a short circuit.

[0068] The preset time window refers to a specific duration for which the system reviews historical data, such as the past 24 hours or the past week. The historical maximum current change rate refers to the maximum current change rate monitored by the system under all normal operating conditions (including non-fault disturbances such as load switching and transformer no-load closing) within this time window. The short-circuit judgment threshold is a critical value used to distinguish between normal operation and short-circuit faults. The preset coefficient k is a safety margin coefficient greater than 1, used to ensure that the threshold is higher than all known normal disturbances, avoiding false tripping.

[0069] The system implements this refined technical solution using two main methods and technologies. The first method is a real-time update algorithm based on a sliding time window. The system maintains a fixed-length circular queue in memory, storing the peak values ​​of di / dt over a recent period. Whenever a new sampling period ends, the system calculates the current maximum value of di / dt and pushes it into the queue, while simultaneously removing the oldest data. The system scans the maximum value in the queue in real time as the short-circuit judgment threshold and multiplies it by a coefficient k to obtain the current threshold. This method ensures that the threshold always reflects the recent power grid operating status. The second method is an update algorithm based on long-period statistics and event triggering. The system stores historical long-period operating data in a database. Periodically (e.g., daily or weekly) or when a change in the power grid topology is detected, the system initiates a background analysis program to scan the historical database and identify the maximum inrush current change rate caused by normal operation. The system uses this statistical value as a benchmark to update the threshold and sends it to the monitoring unit.

[0070] S108. If the current change rate is greater than the short circuit judgment threshold, the voltage phasor amplitude is less than the preset rated voltage ratio, and there are high-frequency components in the preset range in the high-frequency component characteristics, a short circuit fault is determined to have occurred in the power supply system.

[0071] This step describes the comprehensive judgment logic for short-circuit faults, employing AND logic to improve the reliability of the judgment. A current change rate greater than the short-circuit judgment threshold is the initiation criterion for fault occurrence, indicating an abnormal sudden change in current. A voltage phasor amplitude less than a preset rated voltage ratio (e.g., below 80% or 70% of the rated voltage) is an auxiliary fault criterion, as short circuits are usually accompanied by a significant drop in bus voltage. The presence of high-frequency components within a preset range in the high-frequency component characteristics is the confirming criterion for the nature of the fault, utilizing the broadband electromagnetic transient characteristics generated at the moment of the short circuit to distinguish between a short circuit and a heavy load start-up (heavy load start-ups typically have lower frequency components). Determining a short-circuit fault in the power supply system means that the system ultimately outputs a fault alarm signal, which may trigger protection actions. This multi-dimensional fusion judgment logic effectively solves the problem of misjudgment due to interference from single characteristics.

[0072] The system implements this step using two main methods and technologies. The first method is a hard-decision technique based on logic gates or Boolean logic programming. The system converts the comparison results of the three conditions into Boolean values ​​(True / False). Only when all three Boolean values ​​are True simultaneously is the system's final output a fault state. This method is logically simple, executes extremely quickly, and is suitable for implementation in low-level FPGA or DSP chips, meeting microsecond-level protection response requirements. The second method is a soft-decision technique based on fuzzy logic reasoning. The system does not set an absolute hard threshold but instead designs a membership function for each feature. The system establishes a fuzzy rule base. Through fuzzy reasoning and defuzzification, the system outputs a fault confidence probability. When the probability exceeds a set value, a fault is determined.

[0073] S109. Obtain the parameters of the transformer equipment in the power supply system, and determine the impedance of the transformer equipment based on the parameters;

[0074] The parameters of transformer equipment in a power supply system mainly refer to the transformer's nameplate data and factory test data, including rated capacity, rated voltage, short-circuit impedance percentage, short-circuit loss, and connection group. Transformer impedance refers to the complex sum of the transformer's resistance and leakage reactance in the equivalent circuit. Determining transformer impedance involves converting the aforementioned per-unit or percentage parameters into ohmic values. Transformer impedance is a crucial component of the short-circuit current loop, especially in short circuits near the transformer outlet, where it plays a dominant current-limiting role. The system needs to establish a transformer parameter database and be able to call up the correct parameters for calculations in real time based on the number of currently operating transformers and tap positions.

[0075] The system implements this step using two main methods and technologies. The first method is a lookup-based calculation method using a static database. The system pre-enters detailed nameplate parameters of all transformers into the background management system. During operation, the system indexes the database based on the transformer's number or ID to read data such as short-circuit impedance percentage, short-circuit loss, and rated capacity. Using the standard transformer impedance calculation formula, the system calculates the transformer's resistance and reactance. The second method is a parameter identification method based on online condition estimation. For older transformers or equipment with missing parameters, the system utilizes real-time voltage and current data collected by monitoring units installed simultaneously on the high and low voltage sides of the transformer. By constructing a two-port network model of the transformer, the system uses the least squares method or Kalman filtering algorithm to estimate the transformer's equivalent leakage impedance online. This method can reflect impedance changes caused by transformer aging or winding deformation.

[0076] S110. Based on the corrected line impedance, transformer equipment impedance and load equivalent impedance, the fundamental short-circuit current is calculated using the symmetrical component method.

[0077] The system calculates the fundamental short-circuit current using the symmetrical component method based on corrected line impedance, transformer equipment impedance, and load equivalent impedance. Specifically, when the short-circuit fault is determined to be a three-phase short-circuit fault, the corrected line impedance, transformer equipment impedance, and load equivalent impedance are input into the three-phase short-circuit current calculation function to obtain the fundamental short-circuit current. The three-phase short-circuit current calculation function is as follows: ;

[0078] If the short circuit fault is determined to be a single-phase-to-ground short circuit fault, the corrected line impedance, transformer equipment impedance, and load equivalent impedance are input into the single-phase-to-ground short circuit current calculation function to obtain the fundamental short circuit current. The single-phase-to-ground short circuit current calculation function is as follows:

[0079] ;

[0080] In the above function, For fundamental short-circuit current, Rated voltage, This is the minimum value of the equivalent load impedance. Zero-sequence impedance, It is a positive sequence impedance. To correct the line impedance, This refers to the impedance of the transformer equipment.

[0081] The corrected line impedance, transformer equipment impedance, and load equivalent impedance constitute the total impedance parameters of the short-circuit loop. The symmetrical component method is a mathematical approach for handling three-phase unbalanced systems. It decomposes any set of unbalanced three-phase phasors into three sets of symmetrical components: positive-sequence, negative-sequence, and zero-sequence. The fundamental short-circuit current refers to the power frequency component of the short-circuit current, excluding DC components and higher harmonics. In a three-phase short-circuit fault, only the positive-sequence network needs to be considered; however, in a single-phase ground fault, the system needs to connect positive-sequence, negative-sequence, and zero-sequence networks in series.

[0082] The system can utilize a numerical calculation method based on sequence network matrix operations. The system constructs the node admittance matrix for the entire power supply network and modifies matrix elements according to the fault type (e.g., modifying the self-impedance of the corresponding node in the case of a single-phase ground fault). The system solves the linear equations using Gaussian elimination or LU decomposition to directly obtain the voltage and current components of each sequence network, and finally synthesizes the three-phase short-circuit current. This method is highly versatile and applicable to arbitrarily complex network topologies.

[0083] S111. Calculate the impact coefficient based on the ratio of real-time reactance to real-time resistance of the power supply system;

[0084] The system calculates the impact factor based on the ratio of the real-time reactance to the real-time resistance of the power supply system. Specifically, it extracts the resistive and reactive components from the corrected line impedance, transformer equipment impedance, and load equivalent impedance; calculates the real-time reactance and real-time resistance of the power supply system based on the resistive and reactive components; calculates the ratio of the real-time reactance to the real-time resistance; and calculates the impact factor based on the attenuation characteristics of the short-circuit transient aperiodic component corresponding to the ratio. The ratio of the real-time reactance (X) to the real-time resistance (R) of the power supply system (i.e., the X / R ratio) is a key parameter determining the attenuation time constant of the aperiodic component (DC component) in the short-circuit current. "Real-time" means that this parameter is dynamically calculated based on the network topology and equipment status at the time of the fault, rather than being a fixed value. The impact factor is a coefficient greater than 1, used to describe the multiple of the maximum instantaneous value of the short-circuit current (impact current) relative to the amplitude of the fundamental short-circuit current. Physically, at the instant of a short circuit, the current in the inductor cannot change abruptly, resulting in a DC component that decays exponentially. The larger the X / R ratio, the larger the time constant of the circuit, the slower the DC component decays, and the larger the resulting impact factor. The system extracts the resistance and reactance components from the corrected line impedance, transformer equipment impedance, and load equivalent impedance, performs summation or series-parallel calculations to obtain the total equivalent resistance and total equivalent reactance at the fault point, and then calculates the ratio.

[0085] The system implements this refined technical solution using two main methods. The first method is an analytical calculation method based on the standard curve formula. The system directly substitutes the calculated real-time X / R ratio into this empirical formula to quickly obtain the impact coefficient. This method has a high degree of standardization and is easy to apply in engineering. The second method is a numerical mapping method based on transient simulation lookup tables. The system pre-simulates the short-circuit process under different X / R ratios using electromagnetic transient simulation software (such as EMTP or PSCAD), records the ratio of the peak impact current to the steady-state current amplitude, and generates a high-precision lookup table. During real-time operation, after calculating the X / R ratio, the system obtains the corresponding impact coefficient through table lookup and linear interpolation. This method can consider more complex nonlinear factors, and its accuracy may be higher than that of the general formula.

[0086] S112. The product of the impulse coefficient and the fundamental short-circuit current is taken as the peak value of the short-circuit current.

[0087] The impact coefficient (obtained from step S111) characterizes the amplifying effect of the non-periodic component on the current peak value. The fundamental short-circuit current (obtained from step S110) characterizes the amplitude of the AC component in the short-circuit steady state. The short-circuit current peak value ($i_p$) refers to the instantaneous maximum current value that appears approximately half a cycle after the short circuit occurs. It is a key indicator for verifying the dynamic stability of electrical equipment (i.e., its ability to withstand electrodynamic effects).

[0088] The system implements this step using two main methods and technologies. The first method involves direct multiplication and extreme value output. The system directly performs floating-point multiplication in the microprocessor, multiplying the impulse coefficient obtained in S111 by the fundamental current obtained in S110 (if it's an RMS value, it's first converted to amplitude). The system displays the calculation results through a human-machine interface and uploads them to the dispatch center via the SCADA system. The second method is range output based on worst-case analysis. Considering potential errors in the calculation parameters, the system not only calculates a nominal peak value but also, considering the parameter error range (e.g., impedance error ±5%), calculates the upper and lower limits of the short-circuit current peak value. The system outputs a peak value range containing a confidence interval, providing engineers with a more comprehensive decision-making reference.

[0089] In the above embodiments, by deploying distributed monitoring units to collect electrical operating parameters and environmental parameters, calculating the voltage and current characteristics of each node, and combining environmental parameters to perform temperature correction on the line impedance, while also considering the impedance of transformer equipment and the equivalent impedance of the load, the actual impedance characteristics of the power supply system can be more accurately reflected. Based on this, short-circuit faults are identified through a comprehensive judgment of current change rate, voltage phasor amplitude, and high-frequency component characteristics, reducing the possibility of misjudgment that may arise from relying on a single characteristic. The fundamental short-circuit current is calculated using the symmetrical component method, and an impact coefficient considering the ratio of real-time system reactance to resistance is introduced, making the calculated peak short-circuit current result closer to actual operating conditions, improving the accuracy of short-circuit current detection, and contributing to the precise setting of power supply system protection devices.

[0090] Based on accurately obtaining the peak value of the short-circuit current, this application also proposes another method for detecting the impedance and short-circuit current of the power supply system to further improve the operational reliability of the power supply system. This method utilizes the obtained corrected line impedance and combines it with a thermal balance model to analyze the heating characteristics of the line. The contact state of the line is determined by the temperature rise deviation, thereby achieving early warning of potential line faults. The following section combines... Figure 2 Another method for detecting power supply system impedance and short-circuit current in the embodiments of this application is described below:

[0091] Please see Figure 2 This is another flowchart illustrating a method for detecting the impedance and short-circuit current of a power supply system in an embodiment of this application.

[0092] S201. Determine the current measured equivalent temperature of the line based on the corrected line impedance.

[0093] The measured equivalent temperature refers to the average operating temperature of the circuit conductor derived from the conductor's physical properties, rather than the surface temperature directly measured by an external temperature sensor. The corrected line impedance here specifically refers to the line impedance value, including the real-time resistance component, calculated by the voltage drop equation or state estimation technique during real-time system operation. This is not a limitation; the impedance value can be an AC resistance including the skin effect and proximity effect, or a converted DC resistance. The core logic of this step lies in utilizing the approximately linear relationship between the resistivity and temperature of metallic conductors (such as copper or aluminum). The system knows the reference resistance value of the circuit at a reference temperature (typically 20°C) and the temperature coefficient of resistance of the conductor. By comparing the real-time calculated line resistance with the reference resistance, the system can analyze the temperature increment causing the resistance change, thereby determining the current measured equivalent temperature.

[0094] The system implements this step using two main methods and techniques. The first method is a reverse solution based on the linear resistance-temperature formula. The system first extracts the real part, i.e., the real-time resistance component, from the calculated complex impedance. The system then calls the line parameters stored in the database, including the resistance per unit length at the reference temperature, the total line length, and the temperature coefficient of resistance of the material. The system constructs a linear equation with the real-time resistance as the dependent variable and the temperature as the independent variable. Through algebraic operations, the system subtracts the reference resistance from the real-time resistance, divides by the product of the reference resistance and the temperature coefficient, and finally adds the reference temperature value, thus directly calculating the current conductor temperature. This method has minimal computational complexity and is suitable for high-frequency real-time calculations in embedded terminals. The second method is a mapping method based on table lookup and interpolation. Considering that the resistance-temperature relationship of some alloy conductors may exhibit slight nonlinearity over a wide temperature range, or to reduce real-time floating-point division operations, the system pre-generates a high-precision resistance-temperature mapping table in the background. This table covers the extreme temperature range that the line may operate in (e.g., -40℃ to 150℃). During operation, the system uses the calculated real-time resistance value as an index key to look up the corresponding temperature range in the mapping table. If the real-time resistance value lies between two list values, the system uses linear interpolation or spline interpolation algorithms to calculate the accurate measured equivalent temperature.

[0095] S202. Based on current characteristics and a preset line thermal balance model, calculate the theoretical temperature rise of the line under the current load.

[0096] The system calculates the theoretical temperature rise of the line under the current load based on current characteristics and a preset line thermal balance model. The preset line thermal balance model is as follows: ;

[0097] In the above function, For the specific heat capacity of the circuit, For line quality, For theoretical temperature rise, It is a characteristic quantity of current. As a reference resistor, For reference temperature, To consider the overall heat dissipation coefficient, For heat dissipation area, For ambient temperature, It is the sensitivity coefficient for the change of resistivity of a conductor material with temperature.

[0098] This represents the rate at which the circuit itself absorbs heat as its temperature rises.

[0099] This represents the Joule heat power generated when an electric current passes through a conductor.

[0100] This represents the heat output power that the line dissipates into the environment.

[0101] The current characteristic quantity here mainly refers to the effective value sequence of the current flowing through the line, which is the direct source of Joule heat. The preset line thermal balance model is a differential equation describing the thermodynamic dynamic process of the conductor, which follows the law of conservation of energy. The theoretical temperature rise refers to the temperature rise when the Joule heat generated by the load current and the heat dissipation from the environment reach dynamic equilibrium, assuming the line is in an ideal connection state (i.e., no poor contact, no aging corrosion). The specific heat capacity of the line and the line mass are physical constants describing the thermal inertia of the conductor; the reference resistance, reference temperature, and resistance temperature sensitivity coefficient are parameters describing the characteristics of the heat source; the comprehensive heat dissipation coefficient, heat dissipation area, and ambient temperature are parameters describing the heat dissipation conditions. This model not only considers the heat generated by the current (input power), but also the change in heat dissipation power caused by the increase in resistance after the conductor heats up (positive feedback), and the convection and radiation heat dissipation caused by the temperature difference (negative feedback). By solving this differential equation, the system can predict the temperature of a healthy line under the current and environmental conditions.

[0102] The system implements this refined technical solution using two main methods. The first method is a dynamic solution based on numerical integration. Since the thermal balance model is a first-order ordinary differential equation about time, the system uses a finite difference method (such as the forward Euler method or the fourth-order Runge-Kutta method) for discretization. The system sets a small time step (e.g., 1 second or less), uses the theoretical temperature rise from the previous moment and the current characteristic quantity at the current moment to calculate the rate of temperature change. The rate of change is multiplied by the time step and accumulated to the temperature rise from the previous moment, thus iteratively updating the current theoretical temperature rise. This method can accurately simulate the transient temperature rise process during current fluctuations, reflecting the thermal inertia of the conductor. The second method is a fast calculation method based on steady-state approximation. When the system detects that the load current fluctuates small over a period of time (operating in steady state), the system assumes that the rate of temperature change is zero (dT / dt=0). At this time, the differential equation degenerates into an algebraic equation: the heat generation power equals the heat dissipation power. The system utilizes the Newton-Raphson iteration method or binary search method to directly solve for the roots of the nonlinear algebraic equation, thereby obtaining the theoretical temperature rise under steady-state conditions. This method offers fast computation speed and is suitable for rapid verification during periods of stable load.

[0103] S203. Calculate the temperature rise deviation between the measured equivalent temperature and the theoretical temperature rise.

[0104] The temperature rise deviation is a scalar indicator used to quantify the difference between the actual and ideal thermal states of a power line. The measured equivalent temperature, from step S201, represents the current state; the theoretical temperature rise, from step S202, represents the standard. Before calculating the deviation, the system typically needs to add the ambient temperature to the theoretical temperature rise to convert it into a theoretical absolute temperature, or subtract the ambient temperature from the measured equivalent temperature to convert it into a measured temperature rise, to ensure that the two are compared under the same benchmark. This seemingly simple subtraction operation actually involves data alignment and synchronization. The system must ensure that the measured temperature and theoretical temperature rise used in the calculation are based on current and environmental data from the same time segment. The physical meaning of the temperature rise deviation is that it eliminates the influence of load current magnitude and ambient temperature changes on the absolute temperature of the power line, reflecting only the thermal effect caused by changes in the line's own impedance characteristics (such as contact resistance). If the line is intact, this deviation should theoretically be close to zero or fluctuate within a very small error range.

[0105] The system implements this step using two main methods and techniques. The first method is an instantaneous difference calculation method based on time synchronization. The system uses a global clock or synchronization sampling marker to strictly match the calculation time of the measured impedance data with the output time of the thermal balance model. In each calculation cycle (e.g., once per second), the system directly performs a subtraction operation: Deviation = Measured equivalent temperature - (Theoretical temperature rise + Ambient temperature). To eliminate random fluctuations caused by measurement noise, the system can perform moving average filtering or median filtering on the calculated instantaneous deviation value sequence to output a smoothed deviation value. The second method is an interval deviation calculation method based on statistical analysis. The system sets a relatively long time window, calculates the average value of the measured equivalent temperature and the average value of the theoretical temperature rise within that window, and then calculates the difference between the two. Alternatively, the system calculates the root mean square value of the difference within the window.

[0106] S204. If the temperature rise deviation value exceeds the preset contact hazard threshold, it is determined that there is an abnormal contact impedance in the line, and a warning signal of line aging or poor contact is issued.

[0107] The preset contact hazard threshold is a critical indicator for the system to determine whether a line has a physical defect. This threshold is usually set based on the line's design specifications, the allowable increase rate of contact resistance, and the heat resistance rating of the insulation material. Contact hazard thresholds can be divided into multiple levels, such as warning thresholds and alarm thresholds, each corresponding to different response levels. Determining that a line has abnormal contact impedance means that the system confirms the temperature rise deviation is not due to measurement or model errors, but rather to increased local resistance caused by factors such as joint oxidation, loose bolts, or broken wire strands. Issuing a warning signal means the system sends a status message to the monitoring center via the communication interface, illuminates a local indicator light, or triggers an audible and visual alarm. This step is the decision-making output of the entire monitoring process, and its accuracy directly affects whether maintenance personnel can intervene in a timely manner to prevent overheating from causing line breaks or fires. The system typically incorporates anti-jitter logic during the judgment process to prevent false alarms triggered by momentary interference.

[0108] The system implements this step using two main methods and technologies. The first method is a hierarchical early warning technology based on multi-level setpoint comparison. The system sets two thresholds: a low threshold and a high threshold. When the temperature rise deviation value consistently exceeds the low threshold for a set time, the system determines it as potentially aging and issues a yellow warning signal, prompting maintenance personnel to pay attention during the next inspection. When the temperature rise deviation value exceeds the high threshold, the system determines it as a serious contact failure, issues a red alarm signal, and may push an emergency notification via SMS or APP, recommending immediate power outage and repair. The second method is a predictive alarm technology based on deviation change trends. The system not only monitors whether the current deviation value exceeds the limit but also calculates the rate of change of the deviation value over time. If the system detects that the temperature rise deviation value, although not yet reaching the absolute threshold, shows a rapid upward trend, the system uses linear regression or exponential extrapolation algorithms to predict the deviation value over a future period. Once the predicted value exceeds the safety limit, the system issues an early warning of trend deterioration.

[0109] In the above embodiments, the temperature rise deviation value can be obtained by comparing the current measured equivalent temperature of the line with the theoretical temperature rise calculated based on the thermal balance model. When the temperature rise deviation value exceeds a preset contact hazard threshold, it indicates that the actual heat generation of the line is significantly higher than the theoretical heat generation under normal conditions. Since poor line contact or aging can lead to increased local contact resistance, resulting in abnormal heating, this type of anomaly can be detected by monitoring the temperature rise deviation value. This monitoring method based on temperature rise deviation improves the detection sensitivity of line contact condition deterioration, which is beneficial for timely detection of abnormal heating phenomena caused by poor line contact or aging, and reduces the probability of faults caused by line contact problems.

[0110] The system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of a power supply system impedance and short-circuit current detection system provided in an embodiment of this application.

[0111] It should be noted that, Figure 3 The structure of the system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0112] like Figure 3As shown, the system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on a program stored in Read-Only Memory (ROM) 302 or a program loaded from storage portion 308 into Random Access Memory (RAM) 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0113] The following components are connected to I / O interface 305: input section 306 including a camera, infrared sensor, etc.; output section 307 including a liquid crystal display (LCD) and speakers, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card and a modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0114] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0115] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. The transmitted data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0116] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0117] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the system described in the above embodiments; or it may exist independently and not assembled into the system. The storage medium carries one or more computer programs that, when executed by a processor of a system, cause the system to implement the methods provided in the above embodiments.

[0118] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application 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 scope of the technical solutions of the embodiments of this application.

[0119] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0120] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0121] 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 program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for detecting impedance and short-circuit current of a power supply system, characterized by, include: By deploying distributed monitoring units at the beginning of the power supply line, the transformer side, and the load side, electrical operating parameters and environmental parameters of each node of the power supply system are collected. Calculate the voltage and current characteristics of each node based on the electrical operating parameters; A voltage drop equation is established based on the voltage and current characteristics, and the line impedance of adjacent nodes is calculated based on the voltage drop equation. The line impedance is corrected based on the environmental parameters and the preset temperature coefficient of resistance to obtain the corrected line impedance. Obtain the parameters of the transformer equipment in the power supply system, and determine the impedance of the transformer equipment based on the parameters; Calculate the equivalent impedance of the load based on the voltage and current characteristics of the load side; Real-time extraction of the current change rate, voltage phasor amplitude, and high-frequency component characteristics of the electrical operating parameters; The short-circuit judgment threshold is calculated based on the historical maximum current change rate within a preset time window. If the current change rate is greater than the short-circuit determination threshold, the voltage phasor amplitude is less than the preset rated voltage ratio, and the high-frequency component features contain high-frequency components within a preset range, then the power supply system is determined to have experienced a short-circuit fault. Based on the corrected line impedance, the transformer equipment impedance, and the equivalent load impedance, the fundamental short-circuit current is calculated using the symmetrical component method, specifically including: If the short-circuit fault is determined to be a three-phase short-circuit fault, the corrected line impedance, the transformer equipment impedance, and the load equivalent impedance are input into a three-phase short-circuit current calculation function to obtain the fundamental short-circuit current. The three-phase short-circuit current calculation function is as follows: ； If the short-circuit fault is determined to be a single-phase-to-ground short-circuit fault, the corrected line impedance, the transformer equipment impedance, and the load equivalent impedance are input into the single-phase-to-ground short-circuit current calculation function to obtain the fundamental short-circuit current. The single-phase-to-ground short-circuit current calculation function is as follows: ； In the above function, the The fundamental short-circuit current, the For the rated voltage, the The minimum value of the equivalent impedance of the load, For zero-sequence impedance, the As the positive sequence impedance, the For the corrected line impedance, the The impedance of the transformer equipment; The impact factor is calculated based on the ratio of the real-time reactance to the real-time resistance of the power supply system. The product of the impact coefficient and the fundamental short-circuit current is taken as the peak value of the short-circuit current.

2. The method according to claim 1, characterized in that, The process of establishing a voltage drop equation based on the voltage and current characteristics, and calculating the line impedance of adjacent nodes based on the voltage drop equation, specifically includes: The voltage characteristic quantities are denoted as the line start voltage and the line end voltage, and the current characteristic quantities are denoted as the line start current and the line end current. A voltage drop equation is established based on the voltage at the beginning of the line, the voltage at the end of the line, the current at the beginning of the line, and the current at the end of the line. The voltage drop equation is as follows: ； In the above function, the The voltage at the beginning of the line is the voltage at the beginning of the line. The voltage at the end of the line, the The current at the beginning of the line is the current at the beginning of the line. The line impedance is the line impedance. The current at the end of the line, the This is the equivalent branch load impedance between the two ends of the line; The voltage drop equation is solved using the least squares method to obtain the line impedance.

3. The method according to claim 1, characterized in that, The calculation of the short-circuit determination threshold based on the historical maximum current change rate within a preset time window specifically includes: The historical maximum current change rate is input into a preset threshold calculation function to obtain the short-circuit determination threshold. The preset threshold calculation function is as follows: ； In the above function, the As a preset coefficient, the The maximum rate of change of current within the preset time window, the The short-circuit determination threshold is defined as follows.

4. The method according to claim 1, characterized in that, The calculation of the impact coefficient based on the ratio of the real-time reactance to the real-time resistance of the power supply system specifically includes: Extract the resistive and reactive components from the corrected line impedance, the transformer equipment impedance, and the load equivalent impedance; Calculate the real-time reactance and real-time resistance of the power supply system based on the resistive component and the reactant component; Calculate the ratio of the real-time reactance to the real-time resistance; The impact coefficient is calculated based on the short-circuit transient aperiodic component attenuation characteristics corresponding to the ratio.

5. The method according to claim 1, characterized in that, After multiplying the impulse coefficient by the fundamental short-circuit current as the peak short-circuit current, the method further includes: The current measured equivalent temperature of the line is determined based on the corrected line impedance. Based on the current characteristic quantity and the preset line thermal balance model, the theoretical temperature rise of the line under the current load is calculated; Calculate the temperature rise deviation between the measured equivalent temperature and the theoretical temperature rise; If the temperature rise deviation value exceeds the preset contact hazard threshold, it is determined that the line has abnormal contact impedance and a warning signal of line aging or poor contact is issued.

6. The method according to claim 5, characterized in that, The preset line thermal balance model is as follows: ； In the above function, the For the specific heat capacity of the circuit, the For line quality, the For the theoretical temperature rise, the For the current characteristic quantity, the As a reference resistor, the For reference temperature, the To optimize the overall heat dissipation coefficient, the aforementioned For heat dissipation area, the For ambient temperature, the It is the sensitivity coefficient for the change of resistivity of a conductor material with temperature. The This represents the rate at which the circuit itself absorbs heat as its temperature rises. The This represents the Joule heat power generated when an electric current passes through a conductor. The This represents the heat power emitted by the line into the environment.

7. A power supply system impedance and short-circuit current detection system, characterized in that, The system includes: One or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the system to perform the method as described in any one of claims 1-6.

8. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the system, the system performs the method as described in any one of claims 1-6.

9. A computer program product, characterized in that, When the computer program product is run on the system, the system performs the method as described in any one of claims 1-6.

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