High-voltage cable circulation monitoring method and system

Abstract

The invention relates to the technical field of cable circulation monitoring, in particular to a high-voltage cable circulation monitoring method and system. The method comprises the following steps: determining a load step triggering moment and a corresponding low-load current fundamental wave vector group and a corresponding high-load current fundamental wave vector group; constructing an induced voltage deviation objective function based on the difference of the two vector groups, and iteratively determining an optimal mutual inductance coefficient vector; performing induced voltage reconstruction on the high-load current fundamental wave vector group by using the optimal mutual inductance coefficient vector, and determining a sheath loop impedance parameter based on a vector relationship between the reconstructed voltage and three-phase sheath loop current data; determining a voltage model calculation deviation degree based on the difference between the reconstruction voltage and the inversion impedance voltage drop; and the operation state of the high-voltage cable is determined. According to the method, the deviation degree and the sheath loop impedance parameter representing the conductivity of electrical connection are calculated by combining the voltage model representing the integrity of the circuit topology, and an inherent structure fault and a real resistive fault are effectively distinguished.

Description

A method and system for monitoring circulating current in high-voltage cables Technical Field

[0001] This invention relates to the field of cable circulating current monitoring technology, and specifically to a method and system for monitoring circulating current in high-voltage cables. Background Technology

[0002] In long-distance high-voltage cable transmission projects, cross-interconnection grounding involves transposing the three-phase metallic sheaths at the insulation joints. This utilizes the principle of mutual cancellation of the vector sum of the three-phase induced voltages to suppress the induced voltage on the metallic sheath and reduce circulating current losses. However, in actual engineering projects, due to limitations imposed by urban underground utility tunnels or other laying conditions, the lengths of the three cross-interconnected cable sections are rarely strictly equal, and the spatial arrangement of the three-phase cables cannot be perfectly symmetrical. This inherent geometric asymmetry results in the vector sum of the three-phase induced voltages not being completely canceled out, thus generating an objective induced circulating current in the metallic sheath circuit, known as the background circulating current.

[0003] According to the principle of electromagnetic induction, the background circulating current changes linearly with the core load current, and its amplitude is often greater than the weak fault current component caused by poor joint contact or early insulation defects.

[0004] The prior art patent document CN120761686A discloses an intelligent detection and analysis system and method for grounding circulating current in tunnel cables. Specifically, it collects the current and induced voltage of the grounding circulating current in the cable's metallic sheath, analyzes and processes the collected data to obtain comprehensive detection parameters, sets thresholds, and compares and analyzes the detection data to determine whether any abnormalities have occurred. Since the monitored sheath current is a coupling result of the cable's inherent mutual inductance parameters (determined by its geometry) and the total loop resistance parameters (determined by the connection status), it is impossible to distinguish between the background circulating current caused by structural asymmetry and the abnormal leakage circulating current caused by a fault, based solely on current and voltage amplitude information. This leads to inaccurate detection of minor faults. Summary of the Invention

[0005] To address the technical problem of difficulty in distinguishing between inherent structural influences and actual resistive faults caused by background circulating currents resulting from asymmetrical cable laying structures, this invention aims to provide a method and system for monitoring circulating currents in high-voltage cables. The specific technical solution is as follows: Firstly, one embodiment of this invention provides a method for monitoring circulating currents in high-voltage cables. This method includes: real-time acquisition of three-phase conductor current data and three-phase sheath circulating current data at each moment during the working period at the cross-interconnection grounding box of the high-voltage cable; determining the load step triggering time based on the fluctuation of the three-phase conductor current data; and generating a low-load current fundamental vector group and a high-load current fundamental vector group for each load step triggering time. The system employs a multi-stage method to analyze the voltage model. Based on the difference between the low-load current fundamental vector group and the high-load current fundamental vector group, an objective function for induced voltage deviation is constructed. The optimal mutual inductance coefficient vector of the high-voltage cable at each load step trigger moment is iteratively analyzed. The optimal mutual inductance coefficient vector is used to reconstruct the induced voltage of the high-load current fundamental vector group. Based on the vector relationship between the reconstructed voltage and the three-phase sheath circulating current data, the sheath loop impedance parameters at each load step trigger moment are determined. The voltage model calculation deviation at each load step trigger moment is determined based on the difference between the reconstructed voltage and the inverted impedance voltage drop. Based on the sheath loop impedance parameters and the voltage model calculation deviation, the operating state of the high-voltage cable is determined.

[0006] Further, determining the load step trigger time includes: calculating the effective value of the current of each phase conductor current data within a preset analysis window before each time, and selecting the maximum value of the effective current of the three-phase conductor current data at the same time as the effective value of the conductor current at each time; the length of the preset analysis window is one power frequency cycle; calculating the relative change rate of the effective value of the conductor current at each time relative to the effective value of the conductor current at the beginning of its previous determination time window, as the current mutation rate at each time; when the effective value of the conductor current at each time is greater than a preset trigger threshold, and the current mutation rate is greater than a preset step threshold, the time is recorded as the load step trigger time.

[0007] Further, the generation of the low-load current fundamental vector set and the high-load current fundamental vector set for each load step trigger moment includes: recording the three-phase conductor current data and the three-phase sheath circulating current data as analytical current data; setting a first steady-state sampling window before each load step trigger moment and a second steady-state sampling window afterward, and recording the two windows as sampling windows; for each sampling window and each type of analytical current data, performing a fast Fourier transform on the time series of analytical current data within the sampling window for each load step trigger moment, and selecting the frequency component with the rated power frequency of the power grid as the power frequency fundamental component; selecting each load step trigger moment... The first positive zero-crossing moment of the A-phase conductor current data within the first steady-state sampling window is taken as the phase reference zero point moment. Using the phase reference zero point moment, the power frequency fundamental component is phase-corrected to obtain the corrected fundamental phasor. The corrected fundamental phasors corresponding to the three-phase conductor current data and the three-phase sheath circulating current data within each sampling window are used to construct the conductor fundamental vector and the sheath fundamental vector, respectively. The two vectors form a fundamental vector group. The fundamental vector groups corresponding to the first steady-state sampling window and the second steady-state sampling window at each load step trigger moment are respectively denoted as the low load current fundamental vector group and the high load current fundamental vector group.

[0008] Further, the iterative analysis of the optimal mutual inductance coefficient vector of the high-voltage cable at each load step triggering moment includes: calculating the difference vector between the same fundamental vector in the high load current fundamental vector group and the low load current fundamental vector group at each load step triggering moment; denoting the difference vectors corresponding to the core fundamental vector and the sheath fundamental vector as the load increment vector and the circulating current increment vector, respectively; constructing a mutual inductance matrix and a self-inductance matrix with the equivalent mutual inductance coefficient vector as independent variables based on the physical topology of the cross-interconnection of the high-voltage cables; left-multiplying the mutual inductance matrix by the load increment vector to obtain the theoretical induced voltage increment vector; left-multiplying the self-inductance matrix by the circulating current increment vector to obtain the actual self-inductance voltage increment vector; constructing an induced voltage deviation objective function based on the Euclidean distance between the theoretical induced voltage increment vector and the actual self-inductance voltage increment vector; and using a nonlinear optimization algorithm to iteratively analyze the equivalent mutual inductance coefficient vector within a preset spacing physical constraint interval to minimize the induced voltage deviation objective function and obtain the optimal mutual inductance coefficient vector.

[0009] Furthermore, the iterative analysis of the equivalent mutual inductance coefficient vector using a nonlinear optimization algorithm includes: using a preset standard theoretical mutual inductance vector as the initial equivalent mutual inductance coefficient vector; in each iteration, substituting the current equivalent mutual inductance coefficient vector into the induced voltage deviation objective function, and using a trust-region reflection algorithm to determine the parameter step size vector; calculating the sum vector of the current equivalent mutual inductance coefficient vector and the parameter step size vector, as a candidate mutual inductance coefficient vector; if any element in the candidate mutual inductance coefficient vector exceeds the spacing physical constraint interval, then using a reflection transformation to project the candidate mutual inductance coefficient vector into the feasible region defined by the spacing physical constraint interval, and determining the projected vector as the updated equivalent mutual inductance coefficient vector; otherwise, determining the candidate mutual inductance coefficient vector as the updated equivalent mutual inductance coefficient vector; determining whether the Euclidean distance between the updated equivalent mutual inductance coefficient vector and the current equivalent mutual inductance coefficient vector is less than a preset convergence threshold; if yes, then determining the updated equivalent mutual inductance coefficient vector as the optimal mutual inductance coefficient vector; if no, then using the updated equivalent mutual inductance coefficient vector as the current equivalent mutual inductance coefficient vector, and continuing the next iteration update.

[0010] Further, determining the sheath circuit impedance parameters at each load step trigger moment includes: updating the equivalent mutual inductance coefficient vectors in the mutual inductance matrix and self-inductance matrix to the optimal mutual inductance coefficient vector, thereby obtaining the optimal mutual inductance matrix and optimal self-inductance matrix at each load step trigger moment; multiplying the optimal mutual inductance matrix and optimal self-inductance matrix at each load step trigger moment by the core fundamental wave vector and sheath fundamental wave vector in the high load current fundamental wave vector group, and calculating the difference vector between the two vectors obtained by the left multiplication operation, which is used as the voltage drop vector at that moment; if the magnitude of the sheath fundamental wave vector in the high load current fundamental wave vector group at each load step trigger moment is greater than or equal to a preset circulating current effective threshold, then using the principle of orthogonal projection in the complex domain, calculating the projection component of the voltage drop vector in the direction of the sheath fundamental wave vector, and using the real part of the projection component as the sheath circuit impedance parameter at the corresponding load step trigger moment.

[0011] Further, determining the voltage model calculation deviation at each load step triggering moment includes: multiplying the sheath circuit impedance parameter at each load step triggering moment by the sheath fundamental vector in the high load current fundamental vector group to obtain the impedance voltage drop vector; left-multiplying the optimal mutual inductance matrix by the core fundamental vector in the high load current fundamental vector group to obtain the theoretical induced voltage vector; and using the magnitude of the difference vector between the voltage drop vector and the impedance voltage drop vector at each load step triggering moment as the numerator and the magnitude of the theoretical induced voltage vector as the denominator to obtain the ratio as the voltage model calculation deviation.

[0012] Further, determining the operating status of the high-voltage cable includes: when the sheath circuit impedance parameter at each load step trigger moment is less than a preset theoretical upper limit and the voltage model calculation deviation is within a preset reasonable range, this moment is recorded as an effective moment; a set is formed by the sheath circuit impedance parameter and voltage model calculation deviation of the N effective moments starting within the working period, respectively, and is used as the impedance sample set and deviation sample set, respectively, and is recorded as the target sample set; where N is a preset number; the next moment adjacent to the end of the second steady-state sampling window of the Nth effective moment within the working period is taken as the start time of the monitoring period, and the end time of the monitoring period is the same as the end time of the working period; for each load step trigger moment within the monitoring period, calculate each The voltage model calculation deviation at each load step trigger moment is calculated relative to the first deviation index of the deviation sample set. When the first deviation index is greater than a preset structural fault threshold, a structural fault is determined to have occurred. When the first deviation index is less than or equal to the preset structural fault threshold, the sheath circuit impedance parameter at each load step trigger moment is calculated relative to the impedance sample set. If the second deviation index is greater than a preset resistive degradation threshold, a resistive potential is determined to have occurred. If the second deviation index is less than or equal to the preset resistive degradation threshold, it is determined to be in a healthy state. The sheath circuit impedance parameter and voltage model calculation deviation at that moment are sequentially added to the impedance sample set and the deviation sample set to achieve the updating of the resistance sample set and the deviation sample set.

[0013] Further, the method for obtaining the first deviation index and the second deviation index includes: recording the sheathing circuit impedance parameter and the voltage model calculation deviation as target data; calculating the mean and standard deviation of all elements in the target sample set corresponding to each type of target data at each load step triggering time; using the mean of each type of target data at each load step triggering time as the numerator and the sum of the standard deviation and a preset positive number as the denominator to obtain the ratio as the target deviation index; each type of target data has the same type of elements in its corresponding target sample set; and recording the target deviation index corresponding to the voltage model calculation deviation and the sheathing circuit impedance parameter as the first deviation index and the second deviation index, respectively.

[0014] Secondly, another embodiment of the present invention provides a high-voltage cable circulating current monitoring system, which includes: a data acquisition module for real-time acquisition of three-phase conductor current data and three-phase sheath circulating current data at each moment during the working period at the high-voltage cable cross-interconnection grounding box; a dual-state vector extraction module for determining the load step triggering time based on the fluctuation of the three-phase conductor current data, and generating a low-load current fundamental vector group and a high-load current fundamental vector group for each load step triggering time; and a geometric parameter decoupling module for constructing an induced current based on the difference between the low-load current fundamental vector group and the high-load current fundamental vector group. The system employs a voltage deviation objective function to iteratively analyze the optimal mutual inductance coefficient vector of the high-voltage cable at each load step trigger moment. A state parameter inversion module is used to reconstruct the induced voltage of the high-load current fundamental vector group using the optimal mutual inductance coefficient vector. Based on the vector relationship between the reconstructed voltage and the three-phase sheath circulating current data, the sheath circuit impedance parameters at each load step trigger moment are determined. Furthermore, the voltage model calculation deviation at each load step trigger moment is determined based on the difference between the reconstructed voltage and the inverted impedance voltage drop. A voltage status monitoring module is used to determine the operating status of the high-voltage cable based on the sheath circuit impedance parameters and the voltage model calculation deviation.

[0015] The present invention has the following beneficial effects: Firstly, this solution utilizes the thermophysical properties of the conductor and sheath of high-voltage cables, which prevent temperature abrupt changes during high current fluctuations, to capture dual-state data before and after load step, namely the load step trigger moment, as well as the fundamental vector groups of low-load current and high-load current. Based on the difference between the two, an objective function for induced voltage deviation is constructed. This allows for independent iterative analysis of the optimal mutual inductance coefficient vector characterizing the inherent geometric structure of the cable using load fluctuation data, even when the precise cable laying path is unknown. This separates the inherent background circulating current component determined by the laying location from the total circulating current, effectively solving the technical problem of background circulating current interference fault identification caused by asymmetrical laying structure, which leads to frequent false alarms in existing methods.

[0016] Secondly, by combining the optimal mutual inductance coefficient vector with the fundamental vector set of high-load current, the theoretical induced voltage can be accurately reconstructed, and the sheath loop impedance parameters can be inverted to characterize the electrical conductivity of the grounding loop, unaffected by changes in the amplitude of the grid load current. Therefore, even under the masking effect of high background circulating current caused by structural asymmetry, this scheme can still keenly detect minute resistance increments caused by joint oxidation and loosening, achieving accurate quantitative monitoring of early resistive hazards.

[0017] Thirdly, the difference between the reconstructed voltage and the inverted impedance voltage drop characterizes the degree to which the actual circuit topology of the cable conforms to the standard cross-connection structure. The deviation in voltage model calculation characterizes the integrity of the circuit topology, while the sheath loop impedance parameters characterize the conductivity of the electrical connection. Combining both can effectively distinguish between inherent structural faults and true resistive faults, improving the accuracy of high-voltage cable condition monitoring. Attached Figure Description

[0018] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art 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.

[0019] Figure 1 is a flowchart of a high-voltage cable circulating current monitoring method according to an embodiment of the present invention; Figure 2 is a system structure diagram of a high-voltage cable circulating current monitoring system according to an embodiment of the present invention; Figure 3 is a schematic diagram of a computer device for a high-voltage cable circulating current monitoring equipment according to an embodiment of the present invention. Detailed Implementation

[0020] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a high-voltage cable circulating current monitoring method and system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0022] The following description, in conjunction with the accompanying drawings, details the specific scheme of the high-voltage cable circulating current monitoring method and system provided by the present invention.

[0023] Example 1:

[0024] This invention proposes a method for monitoring circulating current in high-voltage cables. Please refer to Figure 1, which shows a flowchart of the steps of a method for monitoring circulating current in high-voltage cables according to an embodiment of this invention. The method includes: Step S1: Real-time acquisition of three-phase conductor current data and three-phase sheath circulating current data at each moment during the working period at the cross-interconnection grounding box of the high-voltage cable.

[0025] This step relies on a data acquisition system deployed within the cross-connection grounding box of the high-voltage cable line. Specifically, it utilizes switchable current transformers installed on the A, B, and C phase cables and high-frequency current transformers installed on the corresponding three-phase metallic sheath grounding wires to sense the three-phase conductor current signals and three-phase sheath circulating current signals on the primary side in real time. The supporting data acquisition terminal is connected to the aforementioned transformers via shielded cables. Using a built-in multi-channel high-precision analog-to-digital converter, it synchronously digitizes the analog signals at a sampling frequency of 5 kHz, thereby acquiring a discrete digital sequence with precise timestamps—that is, the three-phase conductor current data and three-phase sheath circulating current data at each moment within the working period. The working period refers to the continuous time interval during which the monitoring system is in an active state, beginning when the device is powered on and completes its initial self-test, and ending when the device is powered off or receives a stop monitoring command.

[0026] Step S2: Determine the load step trigger time based on the fluctuation of the three-phase conductor current data, and generate the low load current fundamental vector group and the high load current fundamental vector group for each load step trigger time.

[0027] To provide a sufficient signal-to-noise ratio for the differential model, it is necessary to capture the moment when the cable core load current changes significantly, i.e., the moment of load step triggering. Small load fluctuations are insufficient to produce observable induced voltage increments, while slow load changes cause temperature drift with current, violating the thermal inertia assumption.

[0028] Due to the large heat capacity of high-voltage cables, the temperature field distribution of the cable conductor and metal sheath does not change significantly in the short period after a current step, and the real part of the total impedance of the sheath circuit can be considered constant at this time. Utilizing this thermal inertia characteristic, the fundamental vector sets of the low-load current and the fundamental vector sets of the high-load current at the moment of load step triggering can be extracted to characterize the electromagnetic fingerprint of the high-voltage cable in both cold and hot states, providing an accurate vector basis for subsequent differential calculations.

[0029] Step S3: Based on the difference between the fundamental vector set of low load current and the fundamental vector set of high load current, construct the objective function of induced voltage deviation, and iteratively analyze the optimal mutual inductance coefficient vector of the high-voltage cable at each load step triggering moment.

[0030] Because the geometric parameters determining mutual inductance and the loop connection state determining resistance are strongly coupled in the steady-state voltage balance equation, single-state data cannot distinguish between the two. This step utilizes the differences between the aforementioned dual-state samples—namely, the low-load current fundamental vector set and the high-load current fundamental vector set—to construct an objective function for induced voltage deviation, quantifying the error between the theoretical inductance increment and the actual measured increment, and iteratively searching for the optimal mutual inductance coefficient vector. This step independently identifies the geometric parameters characterizing the inherent cable laying structure, i.e., the optimal mutual inductance coefficient vector, without needing to know the resistance value, achieving the first level of decoupling of physical parameters.

[0031] Step S4: Reconstruct the induced voltage of the high load current fundamental vector group using the optimal mutual inductance coefficient vector. Based on the vector relationship between the reconstructed voltage and the three-phase sheath circulating current data, determine the sheath circuit impedance parameters at each load step triggering moment. And determine the voltage model calculation deviation at each load step triggering moment based on the difference between the reconstructed voltage and the inverted impedance voltage drop.

[0032] This step, based on the known geometric structure, further inverts the electrical connection state. Using the optimal mutual inductance coefficient vector, the theoretically induced voltage vector that should be generated under high load conditions can be accurately reconstructed based on the law of electromagnetic induction. The difference between the actual measured sheath circulating current and the reconstructed induced voltage is mainly caused by the resistance of the sheath loop. By analyzing this vector relationship, the impedance parameters of the sheath loop that represent the conductivity of the grounding system are determined, ensuring the accuracy of weak resistance signal extraction.

[0033] Based on the difference between the reconstructed voltage and the inverted impedance voltage drop, it reflects the difference between the voltage reconstructed based on the standard physical model and the voltage interpreted from actual observation data. It is used to characterize the degree of conformity of the actual circuit topology of the cable with respect to the standard cross-connection structure, describe faults that change the circuit structure such as open circuits and breakdowns, and make the calculated deviation of the determined voltage model a key criterion for distinguishing between structural faults and parametric hazards.

[0034] Step S5: Calculate the deviation based on the sheath circuit impedance parameters and voltage model to determine the operating status of the high-voltage cable.

[0035] Voltage model calculation deviation characterizes the integrity of circuit topology, while sheath loop impedance parameters characterize the conductivity of electrical connections. Combining the two can effectively distinguish between inherent structural faults and true resistive faults.

[0036] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the load step trigger moment includes: calculating the effective value of the current of each phase conductor current data within a preset analysis window before each moment, selecting the maximum value of the effective current of the three-phase conductor current data at the same moment as the effective value of the conductor current at each moment; the length of the preset analysis window is one power frequency cycle; calculating the relative change rate of the effective value of the conductor current at each moment relative to the effective value of the conductor current at the beginning of its previous determination time window, as the current mutation rate at each moment; when the effective value of the conductor current at each moment is greater than a preset trigger threshold and the current mutation rate is greater than a preset step threshold, the moment is recorded as the load step trigger moment. The method for obtaining the effective current value is a known technique and will not be described further here.

[0037] It should be noted that the power frequency period T refers to the time required for a complete cycle of change in industrial AC voltage or current. The standard frequency for industrial electricity, i.e., the rated power frequency f, is 50 Hz. In this embodiment, the power frequency period is 20 milliseconds. To ensure that load fluctuations in any phase can be detected, the maximum value of the effective current among the three-phase conductor current data is selected as the effective conductor current value. The absolute difference between the effective conductor current value at each moment and the effective conductor current value at the beginning of the judgment time window is calculated. The ratio of the absolute difference as the numerator and the sum of the effective conductor current value at the beginning moment and a minimum positive number as the denominator is used as the current mutation rate at each moment, which can measure the severity of conductor current changes; the minimum positive number is used to prevent the denominator from being zero and is set to 0.1 amperes. When the effective value of the conductor current is greater than the preset trigger threshold, it can ensure that the cable is in an effective load-bearing operation state, eliminating invalid data under no-load, shutdown, or extremely low load conditions; when the current mutation rate is greater than the preset step threshold, it can capture the transient process of significant adjustment of the power grid load, ensuring that the induced voltage increment generated by this process is sufficient to be identified by the sensor and meets the accuracy requirements of differential calculation; when both conditions are met simultaneously, it indicates that an effective event with both sufficient signal strength and rich dynamic information has been detected, which is recorded as the load step trigger moment.

[0038] In one implementation of this invention, the preset minimum trigger threshold is set to 20% of the rated current of the high-voltage cable, and the preset step threshold is usually set to 10%. The implementer can set it according to the specific circumstances.

[0039] To ensure that the two effective current values ​​used for comparison do not overlap in time, and to filter out high-frequency transient noise to focus on the true load adjustment trend, the length of the decision time window should be greater than the length of the preset analysis window. In one implementation of this invention, 0.1 seconds before each moment is used as the decision time window; the implementer can set this according to specific requirements.

[0040] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the fundamental vector set of low load current and the fundamental vector set of high load current includes: recording the three-phase conductor current data and the three-phase sheath circulating current data as analytical current data; setting a first steady-state sampling window before each load step triggering moment and a second steady-state sampling window afterward, and recording the two windows as sampling windows; for each sampling window and each type of analytical current data, performing a fast Fourier transform on the time series of analytical current data within the sampling window at each load step triggering moment, and selecting the frequency component with the rated power frequency of the power grid as the power frequency fundamental component; selecting each The first positive zero-crossing moment of the A-phase conductor current signal within the first steady-state sampling window at the load step trigger moment is taken as the phase reference zero point moment. Using the phase reference zero point moment, the power frequency fundamental component is phase-corrected to obtain the corrected fundamental phasor. The corrected fundamental phasors corresponding to the three-phase conductor current data and the three-phase sheath circulating current data within each sampling window are sequentially used to construct the conductor fundamental vector and the sheath fundamental vector, forming a fundamental vector group. The fundamental vector groups corresponding to the first and second steady-state sampling windows at each load step trigger moment are respectively denoted as the low-load current fundamental vector group and the high-load current fundamental vector group. The corrected fundamental phasors with the same subscript in the conductor fundamental vector and the sheath fundamental vector correspond to the same phase.

[0041] It should be noted that, if At the moment of load step triggering, the first steady-state sampling window before the triggering is retrieved retrospectively. and the second steady-state sampling window after triggering ,in, The length of the first steady-state sampling window is set to 5 seconds. To stabilize the waiting time, the electromagnetic transient oscillation process during the instant of load step change can be avoided, and a setting of 0.5 seconds can be used; The length of the second steady-state sampling window is set to 1 second. To ensure that the current data of the two sampling windows are within the same thermal inertia period and to ensure the physical validity of the subsequent differential, the end time of the second steady-state sampling window should be much shorter than the thermal time constant of the high-voltage cable (usually 30 minutes).

[0042] Because data distributed across different phases or monitoring terminals may have slight deviations in sampling clocks, directly using the original waveform for differential calculation will lead to significant phase errors. Therefore, it is essential to extract the fundamental frequency and strictly align the current data within the two sampling windows. The specific steps are as follows: In actual high-voltage cable lines, current signals are often mixed with high-order harmonics and non-periodic random noise. Directly using the original time-domain waveform for differential calculation will amplify these noise errors, thus severely affecting the accuracy of mutual inductance coefficient and resistance inversion. By converting the time-domain signal to the frequency domain using Fast Fourier Transform and extracting the fundamental frequency component (50 Hz) of the power grid, harmonic interference and high-frequency noise can be effectively filtered out. The power frequency fundamental frequency component is the main component that best characterizes the energy transmission characteristics of the power grid.

[0043] The reasons for determining the phase reference zero-crossing time based on the A-phase conductor current data within the first steady-state sampling window are as follows: First, the conductor current directly originates from the main grid load, and its waveform distortion rate is low and the signal-to-noise ratio is high. Compared with the sheath circulating current, which is easily affected by stray current interference, it can provide a clearer and more accurate zero-crossing signal. Second, the power grid is in a relatively stable state within the first steady-state sampling window, with minimal phase jitter. Finally, specifying phase A is to establish a unique reference phasor; phase B or phase C conductor current analysis can also be performed to determine the phase reference zero-crossing time. In this embodiment of the invention, the method for obtaining the positive zero-crossing time includes: forming a time pair from every two adjacent times within the first steady-state sampling window of each load step triggering time; selecting a target pair from the time pairs, wherein the A-phase conductor current data at the first time of the target pair is less than or equal to zero, and the A-phase conductor current data at the second time is greater than zero; performing linear interpolation on the A-phase conductor current data at the two times of each target pair to calculate the time when the A-phase conductor current data is zero, which is recorded as the positive zero-crossing time.

[0044] Corrected fundamental phasor The expression formula is ,in, This represents the amplitude of the fundamental frequency component. The original initial phase angle of the fundamental frequency component is obtained through fast Fourier transform. This represents the start time of the sampling window in which the fundamental frequency component of the power frequency is located; This is the time when the phase reference is at zero. The power frequency is set to the rated power frequency of the grid. This ensures that all data are aligned under the same phase reference. It is important to note that the power frequency fundamental components of the three-phase conductor current data and the three-phase sheath circulating current data within the first and second steady-state sampling windows at the load step trigger moment are all corrected using the above formula to obtain the corresponding fundamental phasors. The low-load current fundamental vector set and the high-load current fundamental vector set respectively characterize the electromagnetic fingerprint of the high-voltage cable under cold and hot conditions, providing an accurate vector basis for subsequent differential calculations.

[0045] The load step trigger moment refers to a positive step in the conductor load current (i.e., a jump from low load to high load). The first steady-state sampling window is in the steady state before the step, with a lower conductor current level. The corresponding cable conductor temperature and sheath circuit resistance are in a relatively low cold-state equilibrium. Therefore, the fundamental frequency vector group corresponding to this window constitutes the low-load current fundamental frequency vector group. In the second steady-state sampling window, the conductor current has jumped to a high level, but due to the cable's huge heat capacity, the conductor and sheath temperatures have not yet increased significantly, and their resistance parameters remain at the level before the step. The fundamental frequency vector group corresponding to this window constitutes the high-load current fundamental frequency vector group. Through this timing definition, it is ensured that the two vector groups have significant electrical current differences but consistent physical resistance parameters, thereby achieving independent decoupling of the equivalent mutual inductance coefficient vector based solely on current changes.

[0046] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the optimal mutual inductance coefficient vector includes: calculating the difference vector between the same fundamental vector in the high load current fundamental vector group and the low load current fundamental vector group at each load step triggering moment; denoting the difference vectors corresponding to the core fundamental vector and the sheath fundamental vector as the load increment vector and the circulating current increment vector, respectively; constructing a mutual inductance matrix and a self-inductance matrix with the equivalent mutual inductance coefficient vector as independent variables based on the physical topology of the cross-interconnection of high-voltage cables; multiplying the mutual inductance matrix by the load increment vector to obtain the theoretical induced voltage increment vector; multiplying the self-inductance matrix by the circulating current increment vector to obtain the actual self-inductance voltage increment vector; constructing an induced voltage deviation objective function based on the Euclidean distance between the theoretical induced voltage increment vector and the actual self-inductance voltage increment vector; and using a nonlinear optimization algorithm to iteratively analyze the equivalent mutual inductance coefficient vector within a preset spacing physical constraint interval to minimize the induced voltage deviation objective function and obtain the optimal mutual inductance coefficient vector.

[0047] In this embodiment of the invention, the objective function for the induced voltage deviation at each load step trigger moment is expressed by the following formula:

[0048] in, The objective function for the induced voltage deviation at each load step trigger moment is constructed based on an engineering approximation model that ignores the voltage drop due to small resistance increments. The vector represents the equivalent mutual inductance coefficients; j is the imaginary unit. It is angular frequency. , The rated power frequency of the power grid is set to 50 Hz. It is the load increment vector at each load step trigger moment; It is the circulating current increment vector at each load step trigger moment; It is a mutual inductance matrix; The self-inductance matrix; It is a 2-norm function.

[0049] It should be noted that the electromagnetic coupling relationship between the three-phase conductors and the three-phase sheaths is constructed based on the standard physical topology model of a high-voltage cable cross-interconnection grounding system. Since it includes three-phase conductors (A, B, and C) and their corresponding three-phase metallic sheaths, both the mutual inductance matrix and the self-inductance matrix are 3×3 square matrices, their dimensions determined by the number of phases in the three-phase power system. The equivalent mutual inductance coefficient vector is also described. The geometric position parameters of the three-phase cable (the straight-line geometric distance between the center of phase A cable and the center of phase B cable) The straight-line geometric distance between the center of phase B cable and the center of phase C cable The straight-line geometric distance between the center of phase C cable and the center of phase A cable Using the principle of electromagnetic induction in a long straight conductor, calculate each element in the matrix. Mutual inductance matrix. off-diagonal elements The mutual inductance of the v-th phase conductor current to the u-th phase sheath is typically calculated using the following formula: ,in, Let be the linear geometric distance between the center of phase u and the center of phase v. The equivalent recirculation depth of the earth. Let be the vacuum permeability, used to describe the ability of a magnetic field to conduct in a vacuum, and set to . Henry per meter. Diagonal element The mutual inductance between the phase conductor and the phase sheath typically depends on the conductor radius and the sheath radius. The values ​​of u and v range from 1 to integers between the number of phase conductors. Self-inductance matrix. This matrix characterizes the inductive properties of the three-phase sheath circuit itself. In cross-connected systems, this matrix is ​​diagonally dominant, and its elements are determined by the sheath radius, geometric arrangement, and transposition of the cross-connections. By using the aforementioned geometric parameters... By substituting the parameterized matrix into the above formula as the independent variable, a parameterized matrix that changes with the geometric structure can be dynamically generated. This represents the increase in theoretical induced electromotive force caused by changes in the load on the conductor core. This represents the actual increase in self-induced back electromotive force caused by changes in the sheath circulation.

[0050] It is important to note that, based on the thermal inertia of high-voltage cables, it is assumed that the temperature of the cable conductor and sheath remains constant within a short time window after a load step, meaning the loop resistance does not change. Furthermore, in the power frequency increment model, the voltage increment caused by resistance is much smaller than the induced voltage increment caused by mutual inductance. Therefore, in the iterative process of solving the equivalent mutual inductance coefficient vector, the influence of the resistance increment can be neglected in an engineering manner.

[0051] In this embodiment of the invention, a preset standard theoretical mutual inductance vector is used as the initial equivalent mutual inductance coefficient vector. During each iteration, the current equivalent mutual inductance coefficient vector is substituted into the induced voltage deviation objective function, and the parameter step size vector is determined using a trust-region reflection algorithm. The sum vector of the current equivalent mutual inductance coefficient vector and the parameter step size vector is calculated as a candidate mutual inductance coefficient vector. If any element in the candidate mutual inductance coefficient vector exceeds the spacing physical constraint interval, the candidate mutual inductance coefficient vector is projected into the feasible region defined by the spacing physical constraint interval using a reflection transformation, and the projected vector is determined as the updated equivalent mutual inductance coefficient vector. Otherwise, the candidate mutual inductance coefficient vector is determined as the updated equivalent mutual inductance coefficient vector. It is determined whether the Euclidean distance between the updated equivalent mutual inductance coefficient vector and the current equivalent mutual inductance coefficient vector is less than a preset convergence threshold. If so, the updated equivalent mutual inductance coefficient vector is determined as the optimal mutual inductance coefficient vector. If not, the updated equivalent mutual inductance coefficient vector is used as the current equivalent mutual inductance coefficient vector, and the next iteration is performed.

[0052] It should be noted that in the first iteration, the current equivalent mutual inductance coefficient vector is the initial equivalent mutual inductance coefficient vector. The system defines the physical constraint interval for spacing (e.g., [150mm, 500mm]) according to high-voltage cable laying standards (e.g., GB 50217), and initializes the equivalent mutual inductance coefficient vector to the theoretical values ​​under a standard equilateral triangle arrangement. When an element in the candidate mutual inductance coefficient vector exceeds the physical constraint interval for spacing, a reflection transformation is applied, that is, using the boundary as a mirror, reflecting the excess step size back into the feasible region, thereby ensuring that the solution always has physical meaning and maintaining the validity of the search direction. The nth element in the projected vector... ,in, This is the nth element in the candidate mutual inductance coefficient vector; for The encountered constraint boundary (e.g., the constraint interval is [L, U], where L and U are the lower and upper boundaries of the constraint interval, respectively). ,but ;like ,but ).

[0053] When the Euclidean distance between the updated equivalent mutual inductance coefficient vector and the current equivalent mutual inductance coefficient vector is less than the preset convergence threshold, it indicates that the optimization algorithm has entered the stable convergence region. Minor adjustments to the parameter values ​​can no longer significantly reduce the induced voltage deviation. Using this condition as the basis for stopping the iteration ensures that the algorithm terminates efficiently while meeting engineering accuracy requirements, outputting a stable and reliable optimal mutual inductance coefficient vector, representing the optimal solution for the current actual cable laying structure. The preset convergence threshold is set to... .

[0054] In one implementation of this invention, the method for obtaining the preset standard theoretical mutual inductance vector is as follows: based on the design and construction drawings of the monitored high-voltage cable line or relevant laying standards (such as GB 50217), determine the standard laying method of the cable (such as direct burial equilateral triangle laying) and the corresponding standard design spacing (e.g., phase spacing 300mm); based on these standard geometric parameters, calculate the theoretical mutual inductance value under ideal symmetry using the electromagnetic field mutual inductance calculation formula; use this theoretical mutual inductance value as the value of all components of the preset standard theoretical mutual inductance vector; the preset standard theoretical mutual inductance vector is... .

[0055] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the sheath circuit impedance parameter includes: updating the equivalent mutual inductance coefficient vectors in the mutual inductance matrix and the self-inductance matrix to the optimal mutual inductance coefficient vector, thereby obtaining the optimal mutual inductance matrix and the optimal self-inductance matrix at each load step triggering moment; multiplying the optimal mutual inductance matrix and the optimal self-inductance matrix at each load step triggering moment by the core fundamental wave vector and the sheath fundamental wave vector in the high load current fundamental wave vector group, and calculating the difference vector of the two vectors obtained by the left multiplication operation as the voltage drop vector at that moment; if the magnitude of the sheath fundamental wave vector in the high load current fundamental wave vector group at each load step triggering moment is greater than or equal to a preset circulating current effective threshold, then using the principle of orthogonal projection in the complex domain, calculating the projection component of the voltage drop vector in the direction of the sheath fundamental wave vector, and using the real part of the projection component as the sheath circuit impedance parameter at the corresponding load step triggering moment.

[0056] In this embodiment of the invention, the formula for calculating the sheath loop impedance parameter is as follows:

[0057]

[0058] in, The sheath circuit impedance parameters at each load step trigger moment; The sheath fundamental wave vector in the high load current fundamental wave vector set at each load step trigger moment; Let be the voltage drop vector at each load step trigger moment; j is the imaginary unit; It is angular frequency. , The rated power frequency of the power grid is set to 50 Hz. The optimal mutual inductance coefficient vector for each load step trigger moment; The optimal mutual inductance matrix for each load step trigger moment; The optimal self-inductance matrix for each load step trigger moment; It is the transpose symbol; To take the real part of the function; It is a 2-norm function.

[0059] It should be noted that, in order to eliminate the influence of single-phase measurement noise and prevent calculation divergence under low current, the system introduces a preset circulating current effective threshold (e.g., 0.5A) for data filtering. When the current is less than or equal to the preset effective circulating current threshold (0.5 amperes in this embodiment), it indicates that the circuit is in an open circuit or extremely high resistance state, and the circuit is directly... Mark as infinity; otherwise, it is valid data. Only valid data is treated using the complex domain least squares projection method. By calculating the projection of the voltage drop vector onto the direction of the circulating current vector and extracting its real part, the sheath loop impedance parameter, which is robust to random noise, is obtained. The larger this value, the worse the conductivity of the grounding system.

[0060] It is important to note that if the modulus of the fundamental wave vector of any phase conductor current data in the high-load current fundamental wave vector group is less than the preset minimum analysis current threshold, it indicates that the conductor current is too small, resulting in insufficient magnetic field strength. This leads to an extremely weak sheath induced signal, which cannot be used to accurately invert the weak resistive parameters, thus preventing subsequent analysis. The preset minimum analysis current threshold is set to 10% of the rated current carrying capacity of the high-voltage cable.

[0061] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the voltage model calculation deviation includes: multiplying the sheath circuit impedance parameter at each load step triggering moment by the sheath fundamental vector in the high load current fundamental vector group to obtain the impedance voltage drop vector; multiplying the optimal mutual inductance matrix on the left by the core fundamental vector in the high load current fundamental vector group to obtain the theoretical induced voltage vector; and using the magnitude of the difference vector between the voltage drop vector and the impedance voltage drop vector at each load step triggering moment as the numerator and the magnitude of the theoretical induced voltage vector as the denominator to obtain the ratio as the voltage model calculation deviation.

[0062] In this embodiment of the invention, the formula for calculating the voltage model deviation is as follows:

[0063] In the formula, The deviation of the voltage model is calculated for each load step trigger moment; This is the voltage drop vector at each load step trigger moment; The sheath circuit impedance parameters at each load step trigger moment; The sheath fundamental wave vector in the high load current fundamental wave vector set at each load step trigger moment; j is the imaginary unit; It is angular frequency. , The rated power frequency of the power grid is set to 50 Hz. The optimal mutual inductance coefficient vector for each load step trigger moment; The optimal mutual inductance matrix for each load step trigger moment; The fundamental wave vector of the core in the high load current fundamental wave vector set at each load step trigger moment; It is a 2-norm function.

[0064] It should be noted that the voltage model calculation bias is used to evaluate the ability of the physical model obtained from the inversion to interpret actual observation data. This represents the residual between the voltage drop across the resistor calculated based on the physical model and the voltage drop generated by the actual inverted resistor. The magnitude of the theoretical induced voltage vector is used to standardize the residuals. A smaller voltage model calculation deviation indicates that the current observation data can be perfectly explained by the physical model of "standard cross-connection topology + optimal geometric parameters + inversion resistance," and the circuit structure is normal. Conversely, a larger deviation means that the actual circuit may have experienced topological changes outside the model (such as open circuits, breakdowns, or commutation errors), leading to physical model failure. Therefore, the voltage model calculation deviation can serve as an effective criterion for identifying structural faults.

[0065] Preferably, in some possible implementations of the embodiments of the present invention, the method for monitoring the cable operating status includes: when the sheath loop impedance parameter at each load step trigger moment is less than a preset theoretical upper limit and the voltage model calculation deviation is within a preset reasonable range, the moment is recorded as an effective moment; a set is formed by the sheath loop impedance parameter and voltage model calculation deviation of the N effective moments starting within the working period, respectively, and is used as the impedance sample set and the deviation sample set, respectively, and is recorded as the target sample set; where N is a preset number; the next moment adjacent to the end of the second steady-state sampling window of the Nth effective moment within the working period is taken as the start time of the monitoring period, and the end time of the monitoring period is the same as the end time of the working period; for each load within the monitoring period At the step trigger moment, the voltage model calculation deviation at each load step trigger moment is calculated relative to the first deviation index of the deviation sample set. When the first deviation index is greater than the preset structural fault threshold, a structural fault is determined to have occurred. When the first deviation index is less than or equal to the preset structural fault threshold, the sheath circuit impedance parameter at each load step trigger moment is calculated relative to the impedance sample set. If the second deviation index is greater than the preset resistive degradation threshold, a resistive potential is determined to have occurred. If the second deviation index is less than or equal to the preset resistive degradation threshold, it is determined to be in a healthy state. The sheath circuit impedance parameter and voltage model calculation deviation at that moment are then added to the impedance sample set and the deviation sample set in sequence to update the resistance sample set and the deviation sample set.

[0066] It should be noted that during system initialization or cold start phases, strict physical verification thresholds are set. Specifically: the theoretical upper limit is determined based on the cable line design specifications; in this embodiment, it is set to twice the design total circuit resistance value to exclude obvious open-circuit or high-resistance fault data. The reasonable range is determined based on the accuracy of the empirical model; in this embodiment, it is set to 0% to 10% (i.e., the voltage interpretation error of the inversion model is required to not exceed 10%) to ensure that the circuit topology conforms to the standard cross-connection structure. When establishing the discrimination benchmark, i.e., the target sample set, it is necessary to ensure the absolute health and physical authenticity of the data. At the moment when both of the above conditions are met, the electrical connection path of the sheath circuit is complete, and the induced voltage response characteristics of the actual circuit are highly consistent with the standard cross-connection physical model. The data at this moment can represent the true health level of the cable, thereby establishing the initial normal operation benchmark, i.e., the target sample set.

[0067] In this embodiment of the invention, the sheathing circuit impedance parameter and the voltage model calculation deviation are recorded as target data; the mean and standard deviation of all elements in the target sample set corresponding to each type of target data at each load step triggering time are calculated respectively; the ratio of the mean of each type of target data at each load step triggering time as the numerator and the sum of the standard deviation and the preset positive number as the denominator is used as the target deviation index; each type of target data has the same type of elements in its corresponding target sample set; the target deviation index corresponding to the voltage model calculation deviation and the sheathing circuit impedance parameter are recorded as the first deviation index and the second deviation index respectively.

[0068] The voltage model calculation deviation directly reflects the inconsistency between the actual induced voltage and the theoretical voltage calculated based on the standard cross-connection topology. When faults such as open circuits, commutation errors, or insulation breakdown occur, altering the circuit connection structure, the physical laws are disrupted, causing the model to be unable to interpret the observed data, thus increasing the voltage model calculation deviation, i.e., significantly deviating from the normal reference. The incremental model eliminates the interference of cable geometric asymmetry on parameter calculations, ensuring that the sheath loop impedance parameter is only related to the resistance of the conductive path in the loop. When potential hazards such as contact surface oxidation or loose bolts cause increased resistance, the sheath loop impedance parameter will increase, i.e., significantly deviating from the normal reference. Therefore, when the first deviation index is greater than the preset structural fault threshold, the voltage model calculation deviation significantly deviates from the normal reference, indicating a structural fault; conversely, it indicates that the cable circuit connection structure is normal. A second deviation index can be further judged. If the second deviation index is greater than the preset resistive degradation threshold, it indicates that the sheath loop impedance parameter significantly deviates from the normal reference, indicating a resistive hazard; conversely, the cable circuit connection structure is normal and the contact is good, indicating a healthy state. These two factors respectively pinpoint anomalies in two dimensions: model failure and parameter drift. Finally, in order to eliminate the impact of seasonal drift in ambient temperature on monitoring accuracy, the sheath circuit impedance parameters and voltage model calculation deviations at the time when the system is in a healthy state are added to the corresponding target sample set to maintain the timeliness of the reference.

[0069] In one implementation of this invention, the preset quantity N is set to 30, which can be set by the implementer according to specific circumstances.

[0070] In one implementation of this invention, the specific setting of the judgment threshold adopts the 3σ criterion based on statistical principles. Specifically, the preset structural fault threshold is set to 3, meaning that when the monitored voltage model deviation deviates from the historical mean by more than 3 standard deviations, the probability of its occurrence is extremely low, and there is sufficient reason to determine that the circuit structure has undergone an abnormal change. Similarly, the preset resistive degradation threshold is also set to 3 to determine whether the impedance parameter significantly deviates from the normal statistical fluctuation range.

[0071] This invention is now complete.

[0072] Example 2:

[0073] This invention proposes a high-voltage cable circulating current monitoring system. Referring to Figure 2, which shows a system structure diagram of a high-voltage cable circulating current monitoring system according to an embodiment of this invention, the system includes: a data acquisition module 610, used for real-time acquisition of three-phase conductor current data and three-phase sheath circulating current data at each moment during the working period at the high-voltage cable cross-interconnection grounding box; a dual-state vector extraction module 620, used to determine the load step triggering time based on the fluctuation of the three-phase conductor current data, and generate low-load current fundamental vector groups and high-load current fundamental vector groups for each load step triggering time; and a geometric parameter decoupling module 630, used to determine the load step triggering time based on the low-load current fundamental vector group... The difference between the mutual inductance coefficient set and the fundamental vector set of the high-load current is used to construct an objective function for induced voltage deviation, and iteratively analyze the optimal mutual inductance coefficient vector of the high-voltage cable at each load step triggering moment. The state parameter inversion module 640 is used to reconstruct the induced voltage of the fundamental vector set of the high-load current using the optimal mutual inductance coefficient vector. Based on the vector relationship between the reconstructed voltage and the three-phase sheath circulating current data, the sheath circuit impedance parameters at each load step triggering moment are determined. The voltage model calculation deviation at each load step triggering moment is determined based on the difference between the reconstructed voltage and the inverted impedance voltage drop. The cable condition monitoring module 650 is used to determine the operating status of the high-voltage cable based on the sheath circuit impedance parameters and the voltage model calculation deviation.

[0074] It should be noted that the devices provided in the above embodiments are only illustrative examples of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. In addition, the high-voltage cable circulating current monitoring system and the high-voltage cable circulating current monitoring method provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0075] Example 3:

[0076] Figure 3 is a schematic diagram of a computer device for a high-voltage cable circulating current monitoring device according to an embodiment of the present invention. Exemplarily, as shown in Figure 3, the computer device includes: a memory 701, a processor 702, and a computer program 703 stored in the memory 701 and running on the processor 702. When the processor 702 executes the computer program 703, the computer device can perform any of the high-voltage cable circulating current monitoring methods described above.

[0077] Furthermore, embodiments of this application also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform a high-voltage cable circulating current monitoring method provided in embodiments of this application.

[0078] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0079] It should be understood that the device provided in this embodiment is used to perform the above-described high-voltage cable circulating current monitoring method, and therefore can achieve the same effect as the above-described implementation method.

[0080] When using integrated units, the device may include a processing module and a storage module. When applied to a workpiece, the processing module can be used to control and manage the workpiece's operations. The storage module can be used to support the execution of program code by the workpiece.

[0081] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits contained in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0082] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0084] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for monitoring circulating current in high-voltage cables, characterized in that, The method includes: acquiring three-phase conductor current data and three-phase sheath circulating current data at each moment during the working period at the cross-interconnection grounding box of the high-voltage cable; determining the load step triggering time based on the fluctuation of the three-phase conductor current data, and generating low-load current fundamental vector groups and high-load current fundamental vector groups for each load step triggering time; constructing an induced voltage deviation objective function based on the difference between the low-load current fundamental vector group and the high-load current fundamental vector group, and iteratively analyzing the optimal mutual inductance coefficient vector of the high-voltage cable at each load step triggering time; reconstructing the induced voltage of the high-load current fundamental vector group using the optimal mutual inductance coefficient vector, and determining the sheath loop impedance parameters at each load step triggering time based on the vector relationship between the reconstructed voltage and the three-phase sheath circulating current data; determining the voltage model calculation deviation at each load step triggering time based on the difference between the reconstructed voltage and the inverted impedance voltage drop; and determining the operating status of the high-voltage cable based on the sheath loop impedance parameters and the voltage model calculation deviation.

2. The method for monitoring circulating current in high-voltage cables according to claim 1, characterized in that, The determination of the load step trigger time includes: calculating the effective value of the current of each phase conductor current data within a preset analysis window before each time, and selecting the maximum value of the effective current of the three-phase conductor current data at the same time as the effective value of the conductor current at each time; the length of the preset analysis window is one power frequency cycle; calculating the relative change rate of the effective value of the conductor current at each time relative to the effective value of the conductor current at the beginning of its previous determination time window, as the current mutation rate at each time; when the effective value of the conductor current at each time is greater than a preset trigger threshold and the current mutation rate is greater than a preset step threshold, the time is recorded as the load step trigger time.

3. The method for monitoring circulating current in high-voltage cables according to claim 1, characterized in that, The generation of the low-load current fundamental vector set and high-load current fundamental vector set for each load step trigger moment includes: recording the three-phase conductor current data and the three-phase sheath circulating current data as the analysis current data; setting a first steady-state sampling window before each load step trigger moment and a second steady-state sampling window after each load step trigger moment, and recording the two windows as sampling windows; for each sampling window and each type of analysis current data, performing a fast Fourier transform on the time series of the analysis current data within the sampling window of each load step trigger moment, and selecting the frequency component with the rated power frequency of the power grid as the power frequency fundamental component; selecting each load step trigger moment... The first positive zero-crossing moment of the A-phase conductor current data within the first steady-state sampling window is taken as the phase reference zero point moment. Using the phase reference zero point moment, the power frequency fundamental component is phase-corrected to obtain the corrected fundamental phasor. The corrected fundamental phasors corresponding to the three-phase conductor current data and the three-phase sheath circulating current data within each sampling window are used to construct the conductor fundamental vector and the sheath fundamental vector, respectively. The two vectors form a fundamental vector group. The fundamental vector groups corresponding to the first steady-state sampling window and the second steady-state sampling window at each load step trigger moment are respectively denoted as the low load current fundamental vector group and the high load current fundamental vector group.

4. The method for monitoring circulating current in high-voltage cables according to claim 3, characterized in that, The iterative analysis of the optimal mutual inductance coefficient vector of the high-voltage cable at each load step trigger moment includes: calculating the difference vector between the same fundamental vector in the high load current fundamental vector group and the low load current fundamental vector group at each load step trigger moment; denoting the difference vectors corresponding to the core fundamental vector and the sheath fundamental vector as the load increment vector and the circulating current increment vector, respectively; constructing a mutual inductance matrix and a self-inductance matrix with the equivalent mutual inductance coefficient vector as independent variables based on the physical topology of the cross-interconnection of the high-voltage cables; left-multiplying the mutual inductance matrix by the load increment vector to obtain the theoretical induced voltage increment vector; left-multiplying the self-inductance matrix by the circulating current increment vector to obtain the actual self-inductance voltage increment vector; constructing an induced voltage deviation objective function based on the Euclidean distance between the theoretical induced voltage increment vector and the actual self-inductance voltage increment vector; and using a nonlinear optimization algorithm to iteratively analyze the equivalent mutual inductance coefficient vector within a preset spacing physical constraint interval to minimize the induced voltage deviation objective function and obtain the optimal mutual inductance coefficient vector.

5. The method for monitoring circulating current in high-voltage cables according to claim 4, characterized in that, The iterative analysis of the equivalent mutual inductance coefficient vector using a nonlinear optimization algorithm includes: using a preset standard theoretical mutual inductance vector as the initial equivalent mutual inductance coefficient vector; in each iteration, substituting the current equivalent mutual inductance coefficient vector into the induced voltage deviation objective function, and using a trust-region reflection algorithm to determine the parameter step size vector; calculating the sum vector of the current equivalent mutual inductance coefficient vector and the parameter step size vector, as a candidate mutual inductance coefficient vector; if any element in the candidate mutual inductance coefficient vector exceeds the spacing physical constraint interval, then using a reflection transformation to project the candidate mutual inductance coefficient vector into the feasible region defined by the spacing physical constraint interval, and determining the projected vector as the updated equivalent mutual inductance coefficient vector; otherwise, determining the candidate mutual inductance coefficient vector as the updated equivalent mutual inductance coefficient vector; determining whether the Euclidean distance between the updated equivalent mutual inductance coefficient vector and the current equivalent mutual inductance coefficient vector is less than a preset convergence threshold; if yes, determining the updated equivalent mutual inductance coefficient vector as the optimal mutual inductance coefficient vector; if no, using the updated equivalent mutual inductance coefficient vector as the current equivalent mutual inductance coefficient vector, and continuing the next iteration update.

6. The method for monitoring circulating current in high-voltage cables according to claim 4, characterized in that, The determination of the sheath circuit impedance parameters at each load step trigger moment includes: updating the equivalent mutual inductance coefficient vectors in the mutual inductance matrix and self-inductance matrix to the optimal mutual inductance coefficient vectors, thereby obtaining the optimal mutual inductance matrix and optimal self-inductance matrix at each load step trigger moment; multiplying the optimal mutual inductance matrix and optimal self-inductance matrix at each load step trigger moment by the core fundamental wave vector and the sheath fundamental wave vector in the high load current fundamental wave vector group, and calculating the difference vector between the two vectors obtained by the left multiplication operation, which is used as the voltage drop vector at that moment; if the magnitude of the sheath fundamental wave vector in the high load current fundamental wave vector group at each load step trigger moment is greater than or equal to a preset circulating current effective threshold, then using the principle of orthogonal projection in the complex domain, calculating the projection component of the voltage drop vector in the direction of the sheath fundamental wave vector, and using the real part of the projection component as the sheath circuit impedance parameter at the corresponding load step trigger moment.

7. The method for monitoring circulating current in high-voltage cables according to claim 6, characterized in that, The step of determining the voltage model calculation deviation at each load step triggering moment includes: multiplying the sheath circuit impedance parameter at each load step triggering moment by the sheath fundamental vector in the high load current fundamental vector group to obtain the impedance voltage drop vector; multiplying the optimal mutual inductance matrix on the left by the core fundamental vector in the high load current fundamental vector group to obtain the theoretical induced voltage vector; and using the magnitude of the difference vector between the voltage drop vector and the impedance voltage drop vector at each load step triggering moment as the numerator and the magnitude of the theoretical induced voltage vector as the denominator to obtain the ratio as the voltage model calculation deviation.

8. The method for monitoring circulating current in high-voltage cables according to claim 3, characterized in that, The determination of the operating status of the high-voltage cable includes: when the sheath circuit impedance parameter at each load step trigger moment is less than a preset theoretical upper limit and the voltage model calculation deviation is within a preset reasonable range, the moment is recorded as an effective moment; the sheath circuit impedance parameters and voltage model calculation deviations at N effective moments starting within the working period are respectively used as impedance sample set and deviation sample set, denoted as target sample set; where N is a preset number; the next moment adjacent to the end of the second steady-state sampling window at the Nth effective moment within the working period is taken as the start time of the monitoring period, and the end time of the monitoring period is the same as the end time of the working period; for each load step trigger moment within the monitoring period, the calculation of each load... The voltage model calculation deviation at the step trigger moment is compared with the first deviation index of the deviation sample set. When the first deviation index is greater than the preset structural fault threshold, a structural fault is determined to have occurred. When the first deviation index is less than or equal to the preset structural fault threshold, the sheath circuit impedance parameter at each load step trigger moment is calculated with respect to the impedance sample set. If the second deviation index is greater than the preset resistive degradation threshold, a resistive potential is determined to have occurred. If the second deviation index is less than or equal to the preset resistive degradation threshold, it is determined to be in a healthy state. The sheath circuit impedance parameter and voltage model calculation deviation at that moment are added to the impedance sample set and the deviation sample set in sequence to update the resistance sample set and the deviation sample set.

9. A method for monitoring circulating current in high-voltage cables according to claim 8, characterized in that, The method for obtaining the first deviation index and the second deviation index includes: recording the sheathing circuit impedance parameter and the voltage model calculation deviation as target data; calculating the mean and standard deviation of all elements in the target sample set corresponding to each type of target data at each load step triggering time; using the mean of each type of target data at each load step triggering time as the numerator and the sum of the standard deviation and a preset positive number as the denominator to obtain the ratio as the target deviation index; each type of target data has the same type of elements in its corresponding target sample set; and recording the target deviation index corresponding to the voltage model calculation deviation and the sheathing circuit impedance parameter as the first deviation index and the second deviation index, respectively.

10. A high-voltage cable circulating current monitoring system, characterized in that, The system includes: a data acquisition module for real-time acquisition of three-phase conductor current data and three-phase sheath circulating current data at each moment during the working period at the high-voltage cable cross-interconnection grounding box; a dual-state vector extraction module for determining the load step triggering time based on the fluctuation of the three-phase conductor current data, and generating low-load current fundamental vector sets and high-load current fundamental vector sets for each load step triggering time; and a geometric parameter decoupling module for constructing an induced voltage deviation objective function based on the difference between the low-load current fundamental vector set and the high-load current fundamental vector set, and iteratively analyzing the high-voltage cable... The system includes: an optimal mutual inductance coefficient vector for the cable at each load step trigger moment; a state parameter inversion module, used to reconstruct the induced voltage of the high load current fundamental vector group using the optimal mutual inductance coefficient vector; determining the sheath loop impedance parameters at each load step trigger moment based on the vector relationship between the reconstructed voltage and the three-phase sheath circulating current data; and determining the voltage model calculation deviation at each load step trigger moment based on the difference between the reconstructed voltage and the inverted impedance voltage drop; and a cable condition monitoring module, used to determine the operating status of the high-voltage cable based on the sheath loop impedance parameters and the voltage model calculation deviation.

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