Current transformer saturation identification methods, systems, equipment, and media

Abstract

This invention discloses a current transformer saturation identification method, system, device, and medium. Specifically, it includes continuously acquiring phase voltage and current data of each phase on the secondary side of the protected line; determining whether protection should be activated based on the differential current; performing first-order differential processing on the secondary current to obtain a differential secondary current; normalizing the differential secondary current to obtain a normalized secondary current; extracting the phase of the normalized secondary current and constructing an ideal sinusoidal reference waveform with the same phase; calculating the fractal dimension of the phase trajectory of the normalized secondary current and the reference waveform respectively; and determining the saturation state of the current transformer based on the fractal dimension deviation. If the deviation is satisfied, the transformer is determined to be saturated; otherwise, it is determined to be unsaturated. The system includes an acquisition module, a signal module, a processing module, a calculation module, and a determination module. This invention solves the technical problems of relay protection maloperation or failure to operate caused by the high computational complexity, weak anti-interference ability, and insufficient adaptability of existing saturation identification methods.

Description

Technical Field

[0001] This invention belongs to the field of relay protection technology, specifically relating to current transformer saturation identification methods, systems, equipment, and media. Background Technology

[0002] Current transformers (CTs) are critical measurement and protection devices in power systems, and their performance directly affects the safe and stable operation of the power system. When a short-circuit fault occurs in the power system, the large short-circuit current flowing through the primary side may cause the core of the current transformer to saturate. Saturation prevents the secondary current of the current transformer from accurately reflecting the actual value of the primary current, resulting in waveform distortion, or even defects or deviations in the secondary current waveform. This waveform distortion directly affects the operating behavior of relay protection devices, potentially leading to maloperation or failure to operate, and consequently, the escalation of the power system fault or equipment damage.

[0003] To address the impact of current transformer saturation on relay protection, various saturation identification methods have been developed. These mainly include synchronous identification, multi-derivative coordination, and wavelet analysis. Synchronous identification relies on the synchronicity of fault initiation and differential current exceeding limits, but it is highly dependent on the fault occurrence time and may fail to accurately identify saturation under certain complex operating conditions. Multi-derivative coordination determines saturation by analyzing the derivative characteristics of the current waveform, but its computational complexity is high, and it may lead to misjudgments due to noise interference in some cases. Wavelet analysis identifies saturation by extracting high-frequency components of the signal; while it has a certain degree of accuracy, its computational complexity is high, and it requires strict signal preprocessing. Based on the above analysis, existing CT saturation identification methods still have limitations in terms of computational complexity, accuracy, and adaptability. Summary of the Invention

[0004] The purpose of this invention is to provide a current transformer saturation identification method, which solves the technical problems of relay protection maloperation or failure to operate caused by the high computational complexity, weak anti-interference ability and insufficient adaptability of existing saturation identification methods.

[0005] A second objective of this invention is to provide a current transformer saturation identification system.

[0006] A third objective of this invention is to provide a terminal device.

[0007] A fourth objective of this invention is to provide a computer-readable storage medium.

[0008] The first technical solution adopted in this invention is a current transformer saturation identification method, which specifically includes the following steps:

[0009] Step 1: Continuously collect the voltage and current data of each phase on the secondary side of both sides of the protected line, and determine whether the protection should be activated based on the differential current.

[0010] Step 2: Perform first-order differential processing on the secondary current to obtain the differential secondary current, and then normalize the differential secondary current to obtain the normalized secondary current.

[0011] Step 3: Extract the phase of the normalized secondary current and construct an ideal sinusoidal reference waveform with the same phase.

[0012] Step 4: Calculate the fractal dimension of the phase trajectory of the normalized secondary current and the reference waveform, respectively.

[0013] Step 5: Determine the saturation state of the current transformer based on the fractal dimension deviation. If the condition is met, it is determined to be saturated; otherwise, it is determined to be unsaturated.

[0014] The first technical solution of the present invention is further characterized in that:

[0015] In step 1, the protection is activated based on the differential current. The activation criterion is as follows:

[0016] ;

[0017] In the formula, and It refers to the secondary current vector at both ends of the line. It is the action threshold.

[0018] In step 2, the differential secondary current is normalized, as shown in the following formula:

[0019] ;

[0020] In the formula, For differential secondary current, for The minimum value, for The maximum value.

[0021] Step 3: Construct an ideal sine wave that is in phase with the normalized secondary current as a reference waveform. The amplitude of the ideal sine wave is 100.

[0022] Step 4, calculating the fractal dimension of the normalized secondary current, includes the following steps:

[0023] Based on Takens' theorem, the delay time τ is calculated by the autocorrelation method, the phase space is reconstructed, the one-dimensional current signal is mapped to the two-dimensional phase space, and the current-derivative phase trajectory diagram is generated.

[0024] The fractal dimension of the phase trajectory is obtained by box counting, as shown in the following formula:

[0025] ;

[0026] In the formula, N ( ε ) is a side length of ε The minimum number of boxes required to cover the fractal.

[0027] The reconstructed phase space is specifically as follows:

[0028] The delay time is determined by the autocorrelation function method, the embedding dimension is determined by the pseudo nearest neighbor algorithm, and finally the reconstructed phase trajectory points are obtained to establish the current-derivative phase trajectory diagram.

[0029] Autocorrelation function The expression is shown in the following formula:

[0030] ;

[0031] In the formula, and These are time series at different times. t and time ( tk ) observations, The mean of the time series. This is the expected value in mathematics.

[0032] In step 5, the saturation state of the current transformer is determined based on the fractal dimension deviation, according to the following formula:

[0033] ;

[0034] In the formula, The fractal dimension is calculated for the normalized secondary current. The upper limit of the fractal dimension calculated from the reference waveform. The lower limit of the fractal dimension calculated based on the reference waveform.

[0035] The second technical solution adopted in this invention is a current transformer saturation identification system, including...

[0036] The data acquisition module continuously collects the voltage and current data of each phase on the secondary side of both sides of the protected line, and determines whether the protection should be activated based on the differential current.

[0037] The signal module performs first-order differential processing on the secondary current to obtain the differential secondary current, and then normalizes the differential secondary current to obtain the normalized secondary current.

[0038] The processing module extracts the phase of the normalized secondary current and constructs an ideal sinusoidal reference waveform with the same phase.

[0039] The calculation module calculates the normalized secondary current and the fractal dimension of the phase trajectory of the reference waveform, respectively.

[0040] The determination module judges the saturation state of the current transformer based on the fractal dimension deviation. If the condition is met, it is determined to be saturated; otherwise, it is determined to be unsaturated.

[0041] The third technical solution adopted in this invention is a terminal device, including a memory and a processor. The memory stores a computer program that can run on the processor, and the processor executes the program to implement the above-mentioned current transformer saturation identification method.

[0042] The fourth technical solution adopted in this invention is a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-mentioned current transformer saturation identification method.

[0043] The beneficial effects of this invention are:

[0044] (1) The saturation identification method for current transformers in this invention constructs a complete saturation identification framework. The core innovation lies in the fractal dimension deviation criterion. Differential processing eliminates interference from aperiodic components, normalization solves the problem of fault current amplitude fluctuations, and an ideal sine wave is constructed as a reference. Finally, the nonlinear characteristics of the phase trajectory fractal dimension are used to identify saturation. Compared with traditional wavelet analysis and derivative methods, this invention reduces computational complexity and captures the essential characteristics of waveform distortion through phase space reconstruction, significantly improving anti-interference capability. Simulations show that the accuracy of saturation identification for faults outside the fault zone reaches 100%, avoiding relay protection maloperation.

[0045] (2) This invention limits the differential current activation threshold, forming a dual protection mechanism. First, the fault is preliminarily screened by the difference in current vector amplitude to avoid invalid calculations. Fractal dimension analysis is only triggered when the differential current exceeds the limit, significantly reducing the system load. Traditional synchronous identification methods rely on fault timing and are prone to missed detections, while this criterion is independent of the time axis. Combined with subsequent fractal dimension analysis, it is more adaptable to complex operating conditions. Even with slight saturation, the method of this invention can still accurately activate protection and block faults outside the protection zone. Attached Figure Description

[0046] Figure 1 This is a flowchart of the current transformer saturation identification scheme based on the phase trajectory nonlinear dynamic criterion of the present invention;

[0047] Figure 2 This is a schematic diagram of the simulation model of the present invention;

[0048] Figure 3 This is a schematic diagram of the original signal caused by an external fault leading to CT saturation.

[0049] Figure 4Schematic diagram of the denoised signal caused by CT saturation due to an external fault.

[0050] Figure 5 A schematic diagram of the fractal dimension of the phase trajectory caused by CT saturation due to an external fault.

[0051] Figure 6 A schematic diagram of the original signal of the faulty CT in the area without saturation;

[0052] Figure 7 Schematic diagram of the denoised signal of the faulty CT without saturation within the area.

[0053] Figure 8 A schematic diagram of the fractal dimension of the phase trajectory of the faulty CT in the region;

[0054] Figure 9 A schematic diagram of the primary and secondary currents of the CT causing mild saturation due to an external fault.

[0055] Figure 10 A schematic diagram of the fractal dimension of the original secondary current and the reference signal when an external fault causes mild saturation of the CT.

[0056] Figure 11 A schematic diagram of the primary and secondary currents of the CT scanner caused by an external fault.

[0057] Figure 12 A schematic diagram of the fractal dimension of the original secondary current and the reference signal when an external fault causes severe saturation of the CT.

[0058] Figure 13 A schematic diagram of the primary and secondary currents of a faulty CT in the area, indicating unsaturated primary and secondary currents.

[0059] Figure 14 A schematic diagram of the fractal dimension of the original secondary current and the reference signal for the faulty CT in the region.

[0060] Figure 15 This is a schematic block diagram of the structure of the terminal device of the present invention, which is a computer device;

[0061] Figure 16 This is a schematic block diagram of the structure of the terminal device of the present invention, which is an electronic device.

[0062] In the diagram, 60. Computer equipment, 61. Processor, 62. Memory, 63. Computer program, 600. Electronic device, 610. Processing unit, 620. Storage unit, 6201. Random access memory unit, 6202. Cache memory unit, 6203. Read-only memory unit, 6204. Program / utility, 6205. Program module, 630. Bus, 640. Display unit, 650. Input / output interface, 660. Network adapter, 700. External device. Detailed Implementation

[0063] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0064] Example 1

[0065] The present invention provides a current transformer saturation identification method, such as... Figure 1 As shown, the specific steps include:

[0066] Step 1: Continuously collect the voltage and current data of each phase on the secondary side of both sides of the protected line, and determine whether the protection should be started based on the differential current; the specific start criterion is as follows (1):

[0067] (1);

[0068] In the formula, and It refers to the secondary current vector at both ends of the line. It is the action threshold.

[0069] Step 2: To eliminate the influence of aperiodic components, a first-order difference is performed on the secondary current to obtain the differential secondary current. I diff To eliminate the order-of-magnitude differences between different fault types, differential secondary currents are analyzed. I diff Normalization is performed to obtain the normalized secondary current. I norm And its amplitude is proportionally increased to 100, making the fractal dimension easier to tune.

[0070] Step 3: Extract the phase of the normalized secondary current and construct an ideal sinusoidal waveform with the same phase as the normalized secondary current, with an amplitude of 100, as a reference waveform.

[0071] Step 4: Calculate the fractal dimension of the phase trajectory of the normalized secondary current and the reference waveform, respectively.

[0072] Step 5: Determine the saturation state of the current transformer based on the fractal dimension deviation. If the condition is met, it is determined to be saturated; otherwise, it is determined to be unsaturated.

[0073] Example 2

[0074] Based on Embodiment 1 above, in step 2 of the current transformer saturation identification method of the present invention, the differential secondary current is normalized, as shown in the following formula (2):

[0075] (2);

[0076] In the formula, For differential secondary current, for The minimum value, for The maximum value.

[0077] In step 4, the fractal dimension remains within a finite range for the reference waveform. However, when the secondary current saturates, the fractal dimension of the secondary current differs significantly from that of the reference waveform. Fractal dimension is a mathematical tool used to quantify the nonlinear characteristics of complex systems, irregular geometric structures, or time series. Unlike traditional Euclidean dimensions (e.g., 1 for a line and 2 for a plane), fractal dimension can be non-integer (e.g., 1.5, 2.3, etc.), enabling a more precise description of the self-similarity, complexity, and irregularities widely present in nature and man-made systems.

[0078] When a current transformer is saturated, the secondary current waveform undergoes significant distortion and defects; these changes are nonlinear. Fractal dimension can effectively capture these nonlinear characteristics, thus more accurately identifying the saturation state.

[0079] In step 5, the saturation state of the current transformer is determined based on the fractal dimension deviation, and the determination is based on the following formula (3):

[0080] (3);

[0081] In the formula, The fractal dimension is calculated for the normalized secondary current. The upper limit of the fractal dimension calculated based on the reference waveform is taken as 1.15 here. The lower limit of the fractal dimension calculated for the reference waveform is 0.95.

[0082] The relationship between the saturation status of current transformers on the load side of the line and the corresponding faults is as follows:

[0083] Due to historical reasons and economic conditions, a considerable number of line transformers still use the P-class (which has weak transient transmission performance). When a fault occurs, due to the non-periodic component of the fault current, it is highly likely to saturate when a fault occurs.

[0084] For faults within the zone, there are two scenarios:

[0085] 1) Neither of them is saturated.

[0086] 2) The power supply side is saturated, while the load side is not saturated.

[0087] Since the current on the power supply side is always large and the current on the load side is very small, the differential protection can operate normally in both situations.

[0088] For faults outside the protection zone, if neither current transformer is saturated, the differential protection will not activate. If both current transformers are saturated, differential current can easily occur when their parameters differ. This includes two scenarios:

[0089] 1) Both are saturated.

[0090] 2) One is saturated and the other is unsaturated.

[0091] Instrument transformers with poor performance parameters and prone to saturation can be manually placed on the load side. In this way, when saturation is detected in the instrument transformer on the load side, it indicates an external fault.

[0092] Therefore, by determining whether the current transformer on the load side is saturated, it is possible to determine whether a fault has occurred. If it is saturated, it is an external fault; if it is not saturated, it is an internal fault.

[0093] Example 3

[0094] Based on Example 2 above, step 4 of this invention, calculating the fractal dimension of the normalized secondary current, includes the following steps:

[0095] Based on Takens' theorem, the delay time τ is calculated using the autocorrelation method, and the phase space is reconstructed, mapping the one-dimensional current signal to a two-dimensional phase space to generate a current-derivative phase trajectory diagram; the horizontal axis represents the current value. i 2( t The vertical axis represents its first derivative d. i 2( t ) / d t .

[0096] The reconstructed phase space is specifically as follows:

[0097] First, the delay time needs to be determined when reconstructing the phase space. This invention uses the autocorrelation function method to determine the delay time. The autocorrelation function measures the linear correlation between a time series and its own lag value as shown in equation (4):

[0098] (4);

[0099] in, It is the mean of the time series. N It is the length of the time series, which is usually chosen. First drop to 1 / of the original value e Or the first crossing of zero can be used as the delay time.

[0100] From a statistical perspective, the autocorrelation function is the autocovariance function of a stochastic process. The standardized result is shown in equation (5) below:

[0101] (5);

[0102] in, It is a lag k The autocovariance function, It is the zero-lag autocovariance, that is, the autocovariance at the same time point is equal to the variance of the sequence. This is shown in formulas (6) and (7):

[0103] (6);

[0104] (7);

[0105] in, μ It is the mean of the process. E This represents the expected value.

[0106] Therefore, the autocorrelation function of the present invention is shown in equation (8):

[0107] (8);

[0108] Secondly, the embedding dimension is determined, which can be optimized using the pseudo-nearest neighbor algorithm. Here, a fixed dimension of 3 is chosen.

[0109] Finally, the reconstructed phase trajectory points are obtained, and a current-derivative phase trajectory diagram is established.

[0110] The fractal dimension of the phase trajectory is then obtained by using the box counting method. By analyzing the change in the fractal dimension of the phase trajectory of the saturated waveform, it is possible to determine whether the waveform is saturated.

[0111] Fractal dimension is a commonly used nonlinear dynamic index. The calculation method uses box counting, as shown in equation (9) below:

[0112] (9);

[0113] In the formula, N ( ε ) is a side length of ε The minimum number of boxes required to cover the fractal.

[0114] To verify the effectiveness of the current transformer saturation identification method based on the phase trajectory nonlinear dynamic criterion, a 110kV distribution line was used as an example. The method was then implemented using the electromagnetic transient simulation software PSCAD. Figure 2The simulation model shown is primarily based on a 110kV / 10kV transformer with saturation characteristics and its adjacent primary side lines. Transformer and line parameters are shown in Tables 1 and 2. The active load per phase is 1MW (approximately no-load to ensure normal model operation), and the system frequency is 50Hz. The overhead line length is 4km. The main transformer is a 330kV / 110kV transformer.

[0115] Table 1 Parameters of 110kV Overhead Line

[0116]

[0117] Table 2 Parameters of SF10-50000 / 110 Transformer

[0118]

[0119] Figures 3 to 5 and Figures 6 to 8 The fractal dimensions of one period for external and internal faults are shown respectively. Figure 9 and Figure 10 This refers to a situation where the current transformer is slightly saturated under conditions of an external fault. Figure 11 and Figure 12 This refers to a situation where the current transformer is severely saturated under conditions of an external fault. Figure 13 and Figure 14 This refers to the fault situation within the zone. It can be seen that when the current transformer is not saturated, the fractal dimension is always in the range of 0.95~1.15. When the current transformer becomes saturated, the fractal dimension will change significantly and jump out of this range. Therefore, it can be determined whether the current transformer is saturated.

[0120] In the simulation, single-phase grounding faults were set at different locations on the line. The specific simulation results are shown in Table 3. For faults outside the zone, the transformers were adjusted to be in unsaturated, slightly saturated, and heavily saturated states respectively by adjusting the load on the secondary side of the transformers and the transition resistance. For faults inside the zone, the Q-side transformers were unsaturated by changing the different fault locations and the transition resistance.

[0121] Table 3 Simulation Results

[0122]

[0123] Table 3 shows that this method can effectively identify the protection status of current transformers and promptly lock them out, preventing maloperation of line differential protection caused by faults outside the protection zone. Simulation results fully demonstrate the effectiveness of this invention.

[0124] Example 4

[0125] The present invention relates to a current transformer saturation identification system, which can be used to implement the above-mentioned current transformer saturation identification method. Specifically, the current transformer saturation identification system includes an acquisition module, a signal module, a processing module, a calculation module, and a judgment module.

[0126] The acquisition module continuously collects the voltage and current data of each phase on the secondary side of both sides of the protected line, and determines whether the protection should be activated based on the differential current.

[0127] The signal module performs first-order differential processing on the secondary current to obtain the differential secondary current, and then normalizes the differential secondary current to obtain the normalized secondary current.

[0128] The processing module extracts the phase of the normalized secondary current and constructs an ideal sinusoidal reference waveform with the same phase.

[0129] The calculation module calculates the normalized secondary current and the fractal dimension of the phase trajectory of the reference waveform, respectively.

[0130] The determination module judges the saturation state of the current transformer based on the fractal dimension deviation. If the condition is met, it is determined to be saturated; otherwise, it is determined to be unsaturated.

[0131] In summary, this invention provides a method and system for identifying saturation in current transformers. Fractal dimension effectively captures these nonlinear characteristics by quantifying the geometric complexity of the curve trajectory, thereby effectively distinguishing between normal and saturation states. In practical applications, the computational complexity of fractal dimension is not higher than existing wavelet analysis or derivative criterion methods, meeting real-time requirements. When a current transformer is saturated, the secondary current waveform exhibits distortion, such as missing peaks or waveform asymmetry. Fractal dimension can quantify the degree of these distortions, providing an objective basis for judgment. Compared to traditional methods, fractal dimension can more comprehensively reflect waveform changes. Current transformers may be affected by various factors in actual operation, such as residual magnetism and load changes. The fractal dimension method can adapt to these complex operating conditions, providing more reliable saturation identification results.

[0132] Example 5

[0133] This invention provides a terminal device, which includes a processor and a memory. The memory stores a computer program that can run on the processor. When the processor executes the program, it implements the aforementioned current transformer saturation identification method, specifically including:

[0134] Continuously collect phase voltage and current data on the secondary side of both sides of the protected line, and determine whether the protection should be activated based on the differential current; perform first-order differential processing on the secondary current to obtain the differential secondary current, and normalize the differential secondary current to obtain the normalized secondary current; extract the phase of the normalized secondary current and construct an ideal sinusoidal reference waveform with the same phase; calculate the fractal dimension of the phase trajectory of the normalized secondary current and the reference waveform respectively; determine the saturation state of the current transformer based on the fractal dimension deviation, and if it meets the requirement, it is determined to be saturated; otherwise, it is determined to be unsaturated.

[0135] like Figure 15 As shown, the terminal device is a computer device. The computer device 60 in this embodiment includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the computer program 63 implements the current transformer saturation identification method in this embodiment; to avoid repetition, it will not be described in detail here. Alternatively, when executed by the processor 61, the computer program 63 implements the functions of each model / unit in the current transformer saturation identification system of this embodiment; to avoid repetition, it will not be described in detail here.

[0136] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 15 This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0137] The processor 61 can be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0138] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the computer device 60.

[0139] Furthermore, the memory 62 may include both internal storage units of the computer device 60 and external storage devices. The memory 62 is used to store computer programs and other programs and data required by the computer device 60. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0140] like Figure 16 As shown, the terminal device is an electronic device 600, which is manifested in the form of a general-purpose computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including storage unit 620 and processing unit 610), a display unit 640, etc.

[0141] The storage unit 620 stores program code, which can be executed by the processing unit 610 to perform the steps described in the method section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 610 can perform actions such as... Figure 1 The steps are shown in the figure.

[0142] Storage unit 620 may include readable media in the form of volatile storage units, such as random access storage unit 6201 and / or cache storage unit 6202, and may further include read-only storage unit 6203.

[0143] Storage unit 620 may also include a program / utility 6204 having a set (at least one) program module 6205, such program module 6205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0144] Bus 630 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0145] Electronic device 600 can also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 600, and / or with any device that enables electronic device 600 to communicate with one or more other computing devices (e.g., router, modem). This communication can be performed via input / output interface 650. Furthermore, electronic device 600 can also communicate with one or more networks (e.g., local area network, wide area network, and / or public network, such as the Internet) via network adapter 660. Network adapter 660 can communicate with other modules of electronic device 600 via bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0146] Example 6

[0147] The present invention also provides a computer-readable storage medium, which is a memory device in a terminal device storing a computer program thereon. When executed by a processor, the computer program implements the aforementioned current transformer saturation identification method. It is understood that the computer-readable storage medium here may include the built-in storage medium in the terminal device, or it may include extended storage media supported by the terminal device. It 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.

[0148] A computer-readable storage medium provides storage space in which the operating system of a terminal is stored. Furthermore, this storage space also contains one or more instructions suitable for loading and execution by a processor; these instructions may be one or more computer programs (including program code). It should be noted that more specific examples of a computer-readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical fiber, portable compact disk read-only memory, optical storage device, magnetic storage device, or any suitable combination of the foregoing.

[0149] Computer-readable storage media also include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium can also be any readable medium other than a readable storage medium that can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, etc., or any suitable combination thereof.

[0150] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0151] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the current transformer saturation identification method in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor to perform the following steps:

[0152] Continuously collect phase voltage and current data on the secondary side of both sides of the protected line, and determine whether the protection should be activated based on the differential current; perform first-order differential processing on the secondary current to obtain the differential secondary current, and normalize the differential secondary current to obtain the normalized secondary current; extract the phase of the normalized secondary current and construct an ideal sinusoidal reference waveform with the same phase; calculate the fractal dimension of the phase trajectory of the normalized secondary current and the reference waveform respectively; determine the saturation state of the current transformer based on the fractal dimension deviation, and if it meets the requirement, it is determined to be saturated; otherwise, it is determined to be unsaturated.

[0153] The databases involved in the embodiments provided in this application include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0154] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0155] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for identifying saturation in a current transformer, characterized in that, Specifically, the following steps are included: Step 1: Continuously collect the voltage and current data of each phase on the secondary side of both sides of the protected line, and determine whether the protection should be activated based on the differential current. If so, proceed to Step 2. Step 2: Perform first-order differential processing on the secondary current to obtain the differential secondary current, and then normalize the differential secondary current to obtain the normalized secondary current. Step 3: Extract the phase of the normalized secondary current and construct an ideal sinusoidal reference waveform with the same phase. Step 4: Calculate the fractal dimension of the phase trajectory of the normalized secondary current and the reference waveform, respectively. Step 5: Determine the saturation state of the current transformer based on the fractal dimension deviation. If the condition is met, it is determined to be saturated; otherwise, it is determined to be unsaturated. In step 5, the saturation state of the current transformer is determined based on the fractal dimension deviation, and the determination is based on the following formula: ； In the formula, The fractal dimension is calculated for the normalized secondary current. The upper limit of the fractal dimension calculated from the reference waveform. The lower limit of the fractal dimension calculated for the reference waveform.

2. The current transformer saturation identification method according to claim 1, characterized in that, In step 1, the protection is activated based on the differential current. The activation criterion is as follows: ； In the formula, and It refers to the secondary current vector at both ends of the line. It is the action threshold.

3. The current transformer saturation identification method according to claim 1, characterized in that, In step 2, the differential secondary current is normalized, as shown in the following formula: ； In the formula, For differential secondary current, for The minimum value, for The maximum value.

4. The current transformer saturation identification method according to claim 1, characterized in that, In step 3, an ideal sine wave in phase with the normalized secondary current is constructed as a reference waveform, and the amplitude of the ideal sine wave is 100.

5. The current transformer saturation identification method according to claim 1, characterized in that, Step 4, calculating the fractal dimension of the normalized secondary current, includes the following steps: Based on Takens' theorem, the delay time τ is calculated by the autocorrelation method, the phase space is reconstructed, the one-dimensional current signal is mapped to the two-dimensional phase space, and the current-derivative phase trajectory diagram is generated. The fractal dimension of the phase trajectory is obtained by box counting, as shown in the following formula: ； In the formula, N ( ε ) is a side length of ε The minimum number of boxes required to cover the fractal.

6. The current transformer saturation identification method according to claim 5, characterized in that, The reconstructed phase space is specifically: The delay time is determined by the autocorrelation function method, the embedding dimension is determined by the pseudo nearest neighbor algorithm, and finally the reconstructed phase trajectory points are obtained to establish the current-derivative phase trajectory diagram. Autocorrelation function The expression is shown in the following formula: ； In the formula, and These are time series at different times. t and time ( t- The observed value of τ). The mean of the time series. This is the expected value in mathematics.

7. A current transformer saturation identification system, characterized in that, include The data acquisition module continuously collects the voltage and current data of each phase on the secondary side of both sides of the protected line, and determines whether the protection should be activated based on the differential current. The signal module performs first-order differential processing on the secondary current to obtain the differential secondary current, and then normalizes the differential secondary current to obtain the normalized secondary current. The processing module extracts the phase of the normalized secondary current and constructs an ideal sinusoidal reference waveform with the same phase. The calculation module calculates the normalized secondary current and the fractal dimension of the phase trajectory of the reference waveform, respectively. The determination module judges the saturation state of the current transformer based on the fractal dimension deviation. If the condition is met, it is determined to be saturated; otherwise, it is determined to be unsaturated. The judgment criteria are as follows: ； In the formula, The fractal dimension is calculated for the normalized secondary current. The upper limit of the fractal dimension calculated from the reference waveform. The lower limit of the fractal dimension calculated for the reference waveform.

8. A computer device, comprising a memory and a processor, said memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the current transformer saturation identification method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the current transformer saturation identification method as described in any one of claims 1 to 6.

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