A fusion identification method for distribution network faults based on 5G communication and DS evidence theory

Abstract

Based on the differences in fault phase voltage amplitude, phase current transient change, and zero-sequence current on fault lines and healthy lines in the distribution network, the present invention proposes a distribution network fault fusion identification method based on 5G communication and D-S evidence theory, which can be applied to the field of distribution network fault identification. This method uses the D-S evidence theory to fuse the three sub-criteria of phase voltage amplitude, phase current transient quantity, and zero-sequence current to perform fault line selection and fault identification, further improving the reliability of distribution network protection. The proposed method can effectively locate the fault location of the distribution network under various line operation modes, has high reliability and adaptability, and is not affected by the fault time and the grounding method of the distribution network. At the same time, the proposed method uses 5G communication without the need for additional communication channels, and has high economic efficiency and promotion value.

Description

Technical Field

[0001] The present invention relates to the field of distribution network fault identification, and specifically to a distribution network fault fusion identification method based on 5G communication and DS evidence theory. Background Art

[0002] Most medium and low voltage distribution networks in my country are either ungrounded neutral point systems or low-current grounded systems. In distribution networks, the majority of faults are single-phase grounding faults, accounting for over 70%. After a single-phase grounding fault occurs, the grounding current is low due to the lack of an obvious grounding path, allowing the system to continue operating for several hours. During this time, the voltage of the remaining two healthy phases will rise to 1.732 times its original value, posing a threat to the insulation of the lines and power equipment. During this period, to minimize the harm caused by overvoltage in the remaining lines and prevent the impact of the fault from expanding, the fault should be located as quickly as possible. However, fault identification in today's distribution networks still mostly relies on manual line inspections. With the increasing number of distribution network branches and the length of lines, manual line inspections are not only resource-intensive but also time-consuming, significantly impacting power supply reliability.

[0003] Numerous experts and scholars have conducted research on fault identification methods in distribution networks and proposed a range of solutions. One approach proposes measuring the phase angle change of the fault current at both ends of the line for fault identification, eliminating the need for directional elements and transformers. Another proposes calculating the measured impedance based on the fault voltage and current. However, these methods are significantly affected by the system's operating mode and are no longer suitable given the increasingly complex topologies of distribution networks.

[0004] To address the above issues, some experts have implemented distribution network fault identification by constructing a transfer function without transposing the three-phase lines. However, the transfer function in this solution is affected by the lines and is not practical. Some experts have implemented fault identification by injecting traveling wave signals into the distribution network. However, this method is not effective for detecting high-resistance grounding faults. Some experts have proposed using the high-frequency band characteristics of phase currents to identify faults in the distribution network. However, this method is not reliable enough. In summary, the following two problems exist in current distribution network fault identification methods: 1) The accuracy of fault identification is severely affected by the fault type and system operation mode, making it impractical. 2) The reliability of using a single criterion for distribution network fault identification is low, and there is a risk of false operation or refusal to operate when a fault occurs. Summary of the Invention

[0005] The technical problem to be solved by this application is to overcome the defects of the above-mentioned existing technologies. Based on the differences in phase voltage amplitude, phase current transient change and zero-sequence current on fault lines and sound lines in the distribution network, a fusion criterion based on 5G communication is proposed, which can be applied to the field of distribution network fault identification.

[0006] To achieve the above objectives, the technical methods adopted in this application are as follows:

[0007] On the one hand, this application proposes a distribution network fault fusion identification method based on 5G communication and DS evidence theory, which includes the following steps:

[0008] The feeder terminal collects the line phase voltage and transmits it to the regional distribution network control center via 5G communication;

[0009] After the feeder terminal identifies the fault and operates, it records the line phase current, zero-sequence current, and zero-sequence voltage within the preset time window before and after the fault, and transmits them to the regional distribution network control center via 5G communication;

[0010] The regional distribution network control center constructs a phase voltage amplitude criterion based on the line phase voltage and determines the action result;

[0011] The regional distribution network control center constructs a phase current transient quantity criterion based on the line phase current and determines the action result;

[0012] The regional distribution network control center constructs a zero-sequence current mutation criterion based on the line zero-sequence current and zero-sequence voltage, and determines the action result;

[0013] The three sub-criteria of phase voltage amplitude criterion, phase current transient quantity criterion and zero-sequence current mutation quantity criterion and their action results are fused through DS evidence theory to obtain the final fusion judgment result.

[0014] In a preferred solution, the phase voltage amplitude criterion constructed according to the line phase voltage is:

[0015]

[0016] In the formula is the phase voltage at the feeder terminal installation location, U set is the voltage setting value;

[0017] When formula (1) is satisfied, it is judged as action, otherwise it is judged as no action.

[0018] In a preferred solution, the phase current transient quantity criterion constructed according to the line phase current includes:

[0019] The three-layer time and frequency domain analysis of phase current is performed using wavelet packet transform;

[0020] The second lowest frequency wavelet packet band after decomposition is selected as the characteristic frequency band, and the wavelet packet coefficients of the characteristic frequency band are used to reconstruct the phase current and calculate the modulus maximum value.

[0021] Fault identification is performed according to the polarity of the modulus maximum value.

[0022] In a preferred solution, the three-layer time-domain and frequency-domain analysis of the phase current using wavelet packet transform is specifically as follows:

[0023]

[0024] Where: j is the decomposition layer, j = 1, 2, 3; n is the current frequency band number under the current decomposition layer (0≤n≤2 j -1), k is the result point set of the decomposition coefficient, t is the time series t of the data point set, h(k-2t) is the value of the Meyer wavelet basis low-pass filter at the (k-2t)th point in the wavelet decomposition coefficient point set, g(k-2t+1) is the value of the Meyer wavelet basis high-pass filter at the (k-2t)th point in the wavelet decomposition coefficient point set, is the kth point in the wavelet packet decomposition coefficient point set under frequency band n at the jth decomposition level, is the k+1th point in the wavelet packet decomposition coefficient point set under frequency band n at the jth decomposition level, and for the reason and The derived next level wavelet packet decomposition coefficients;

[0025] The phase current is reconstructed using the wavelet packet coefficients of the characteristic frequency band. The reconstruction formula is as follows:

[0026]

[0027] Where, M matrix is ​​the determined Meyer wavelet basis matrix, is the wavelet coefficient of the wavelet packet in the sub-low frequency band;

[0028] Fault identification according to the polarity of the modulus maximum value includes:

[0029] If the polarity of the modulus maximum value at the installation location of the feeder terminal of a main line in the distribution network is opposite to that of the lower-level line, it can be preliminarily considered that the line has a fault; further, based on the polarity of the reconstructed phase current modulus maximum value at the main line feeder terminal of the line, it is compared with the reconstructed current modulus maximum value of the lower-level line in sequence until a line with opposite modulus maximum value polarity appears for the first time. The line at the end of the comparison is considered to be the faulty line; if the polarity of the reconstructed current modulus maximum value of all main lines is the same, the result is judged to be a bus fault; if a line fault or bus fault is identified, it is considered that the phase current transient quantity criterion is activated, otherwise it is determined that the phase current transient quantity criterion is not activated.

[0030] In a preferred solution, the regional distribution network control center constructs a zero-sequence current mutation criterion based on the line zero-sequence current and zero-sequence voltage, including:

[0031] Convert zero-sequence current to uniform voltage;

[0032] Calculate the zero-sequence current mutation amount based on the converted zero-sequence current;

[0033] Fault identification is performed based on the comparison between the zero-sequence current mutation amount and the mutation amount setting threshold.

[0034] In a preferred solution, the zero-sequence current sudden change calculation formula is:

[0035] |ΔI n |=|I n2 (U 01 +U 02 ) / U 02 -I n1 |,n=1,2,...,N (4)

[0036] Where n is the number of the branch line in the distribution network, N is the total number of all branches in the distribution network, |ΔI n | is the zero-sequence current mutation of line n, I n1 、U 01 is the effective value of zero-sequence current and zero-sequence voltage of R cycles before the fault of line n, R is a positive integer, I n2 、U 02 is the effective value of zero-sequence current and zero-sequence voltage after the fault of line n;

[0037] I n2 (U 01 +U 02 ) / U 02 For I n2 Converted value;

[0038] The constructed zero-sequence current mutation criterion is as follows:

[0039] |ΔIn |>ΔI set (5-1)

[0040] |U 01 / U 02 |>K set (5-2)

[0041] Where, ΔI set K is the zero-sequence current sudden change setting threshold, set is the threshold value for calculating the relative rate of change;

[0042] When formula (5-1) is satisfied, it is considered that the line has a fault; when formula (5-1) is not satisfied but formula (5-2) is satisfied, it is considered that a busbar fault has occurred; when both formulas (5-1) and (5-2) are not satisfied, the line is considered to be a sound line; if a line fault or a busbar fault is identified, it is considered that the zero-sequence current mutation criterion is activated; otherwise, it is determined that the zero-sequence current mutation criterion is not activated.

[0043] In a preferred solution, the three sub-criteria of the phase voltage amplitude criterion, the phase current transient quantity criterion and the zero-sequence current mutation quantity criterion and their action results are fused by the DS evidence theory to obtain the final fusion judgment result, including:

[0044] First, based on the three sub-criteria, the evidence set of the fusion model is obtained as Q = {C1, C2, C3}, where C1, C2 and C3 are the original confidence subsets of the three sub-criteria, namely, the phase voltage amplitude criterion, the phase current transient quantity criterion and the zero-sequence current mutation quantity criterion; according to the possible judgment results, the identification framework is defined as B = {action, no action}; the confidence results of each sub-criteria in the set Q under the identification framework are defined as q h,l , where h represents the criterion number, and its values ​​are 1, 2, and 3, respectively, representing three sub-criteria; l represents the criterion result, and l = 1 and 2 correspond to action and no action, respectively. When the sub-criteria result is action, the corresponding q h,1 =1,q h,2 =0, when the result of the sub-criteria is no action, the corresponding q h,1 =0,q h,2 =1;

[0045] Then, the fusion criterion conflict coefficient P is obtained, which represents the difference between the judgments of the same event among the sub-criteria. The expression is as follows:

[0046]

[0047] Where q h (C h ) is the sub-criterion C h The basic trust allocation function is expressed as follows:

[0048]

[0049] Correct the original reliability of the criterion to obtain the corrected fusion criterion conflict coefficient for

[0050]

[0051] Where, Sub-criterion C h The modified basic trust allocation function is expressed as follows:

[0052]

[0053] Corrected reliability The expression is as follows:

[0054]

[0055] Where, ω h The neutron criterion C for the set Q h The real-time weighted value of the fault is 1 / 3, and the real-time weight ω is adjusted according to the historical fault analysis results. h Make adjustments:

[0056]

[0057] Where s is the current decision position, a s 、b s,h are the correct judgment times and sub-criteria C of all criteria in the judgment results of the previous s-1 and s-2 times respectively. h The number of correct judgments;

[0058] Finally, the fusion criterion can be constructed as follows:

[0059]

[0060] Where P set is the setting threshold of the conflict coefficient;

[0061] When the modified fusion criterion conflict coefficient is satisfied When the criterion (12) is met, it is determined that a fault has occurred and the protection is activated; otherwise, it is determined that there is no fault and the protection is not activated.

[0062] On the other hand, the present application provides an electronic device, comprising:

[0063] A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, any one of the aforementioned distribution network fault fusion identification methods based on 5G communication and DS evidence theory is implemented.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] (1) The present invention integrates the three sub-criteria of phase voltage amplitude criterion, phase current transient quantity criterion and zero-sequence current criterion through DS evidence theory, thereby improving the reliability of distribution network fault identification criterion.

[0066] (2) The present invention solves the problem that the current fault identification criteria are affected by the system operation mode. The proposed criteria can be applied to fault identification of distribution networks under different topologies and various operation modes.

[0067] (3) The present invention solves the defects of current distribution network fault identification methods, such as insufficient selectivity, difficulty in setting, low ability to resist transition resistance, and high maintenance cost of laying optical fiber communications.

[0068] (4) The present invention uses 5G technology to carry out information communication, and does not require the installation of additional communication optical fibers, thus having high economic efficiency and practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is a flow chart of the distribution network fault fusion identification criteria based on 5G communication and DS evidence theory in an embodiment of the present application.

[0070] Figure 2 This is a distribution network simulation model diagram of an embodiment of the present application. The model is a 10kV distribution network grounded through an arc suppression coil.

[0071] Figure 3 This is the voltage waveform of phase A when a metallic fault occurs on line L5 in the distribution network.

[0072] Figure 4 This is the reconstructed current waveform of phase A when a metallic fault occurs on line L5 in the distribution network.

[0073] Figure 5 This is the waveform of the zero-sequence current mutation ΔI5 when a metallic fault occurs on phase A of line L5 in the distribution network.

[0074] Figure 6 A block diagram of an electronic device according to an exemplary embodiment is shown. DETAILED DESCRIPTION

[0075] The present invention will be further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0076] Evidence theory is an imprecise reasoning theory first proposed by Dempster in 1967 and further developed by his student Shafer in 1976. It is also called Dempster / Shafer evidence theory (DS evidence theory). It belongs to the category of artificial intelligence and was first applied in expert systems. It has the ability to process uncertain information. As an uncertain reasoning method, the main characteristics of evidence theory are: it meets conditions that are weaker than Bayesian probability theory; it has the ability to directly express "uncertainty" and "not knowing". Due to the rapid development of 5G technology, the application of 5G technology has appeared in various fields. Due to its advantages of large bandwidth, wide connection, ultra-high reliability and low latency, it brings new opportunities for the development of rapid fault location in distribution networks. In particular, today's distribution networks are gradually developing towards multi-branch and complex topology. This application combines 5G communication for rapid transmission of measurement data and combines DS evidence theory to achieve fault identification.

[0077] like Figure 1 The figure shows a flow chart of a distribution network fault fusion identification method based on 5G communication and DS evidence theory proposed in an embodiment of the present application, which includes the following steps:

[0078] S101. The feeder terminal collects the line phase voltage and transmits it to the regional distribution network control center via 5G communication. After the feeder terminal identifies the fault and operates, it records the line phase current, zero-sequence current, and zero-sequence voltage within the preset time window before and after the fault, and transmits them to the regional distribution network control center via 5G communication.

[0079] Feeder terminals installed on the distribution network include FTUs, DTUs, and fault indicators. These feeder terminals collect voltage information at their installation locations and transmit this information to the regional distribution network control center using 5G communications. The feeder terminal units can also automatically detect various short-circuit faults in the distribution network, record the fault data, and report it to the distribution network control center according to specific communication protocols. When the corresponding feeder terminal in the distribution network identifies a fault and operates, it records the line phase current, zero-sequence current, and zero-sequence voltage for several power frequency cycles before and after the fault at the corresponding feeder terminal installation location. Each feeder terminal then transmits this line phase current, zero-sequence current, and zero-sequence voltage to the regional distribution network control center using 5G communications.

[0080] S102: The regional distribution network control center constructs a phase voltage amplitude criterion based on the line phase voltages, compares the phase voltage amplitude with the voltage threshold, and determines the action result. When a single-phase ground fault occurs in the system, the voltage of the faulted phase will decrease. Based on the characteristics of the single-phase ground fault and the voltage amplitude criterion, the faulted phase can be accurately identified.

[0081] S103. The regional distribution network control center constructs a phase current transient quantity criterion based on the line phase current and determines the action result. First, a three-layer time-domain and frequency-domain analysis of the phase current is performed using wavelet packet transform. The sub-lowest frequency wavelet packet band is then selected as the characteristic frequency band, and the phase current modulus maximum is calculated using the wavelet packet coefficients of the characteristic frequency band. Finally, fault identification is performed based on the polarity of the modulus maximum. After three-layer wavelet packet decomposition, there are eight frequency bands, and the sub-lowest frequency wavelet packet band refers to the band with the second lowest frequency.

[0082] S104. The regional distribution network control center constructs a zero-sequence current mutation criterion based on the line zero-sequence current and zero-sequence voltage, and determines the action result. First, the zero-sequence current is converted to a uniform voltage; then, the zero-sequence current mutation is calculated based on the converted zero-sequence current; finally, the fault is identified based on the comparison between the zero-sequence current mutation and the mutation setting threshold. According to the fault characteristics, the zero-sequence voltage sampling modulus of each feeder terminal is basically equal before and after the arc suppression coil is changed. When a fault occurs, the switching of the distribution network arc suppression coil will cause its parameters to change significantly. Therefore, converting the zero-sequence current to a uniform voltage can reflect the changes in the arc suppression coil caused by the fault.

[0083] S105. The three sub-criteria of the phase voltage amplitude criterion, the phase current transient quantity criterion, and the zero-sequence current mutation quantity criterion and their action results are fused through the DS evidence theory to obtain the final fusion judgment result. The evidence set of the fusion model is obtained based on the three sub-criteria and the action results. The evidence set is based on the obtained fusion criterion conflict coefficient representing the difference between the judgments of the sub-criteria on the same event. Since the original value reliability has only two results of 1 and 0, the calculated conflict coefficient is either 0 or 1, which is not easy to use for setting the judgment. Therefore, the original reliability of the criterion is corrected by introducing a real-time weighted value to obtain a corrected fusion criterion conflict coefficient. The corrected fusion criterion conflict coefficient is compared with the setting threshold of the conflict coefficient to obtain the final judgment result.

[0084] In some embodiments, the line phase voltage is constructed using a phase voltage amplitude criterion as follows:

[0085]

[0086] In the formula is the phase voltage at the feeder terminal installation location, U set is the voltage setting value;

[0087] When formula (1) is satisfied, it is judged as action, otherwise it is judged as no action.

[0088] In some embodiments, a three-layer time-domain and frequency-domain analysis is performed on the phase current using wavelet packet transform, specifically:

[0089]

[0090] Where: j is the decomposition layer, j = 1, 2, 3; n is the current frequency band number under the current decomposition layer (0≤n≤2 j -1), k is the result point set of the decomposition coefficient, t is the time series t of the data point set, h(k-2t) is the value of the Meyer wavelet basis low-pass filter at the (k-2t)th point in the wavelet decomposition coefficient point set, g(k-2t+1) is the value of the Meyer wavelet basis high-pass filter at the (k-2t)th point in the wavelet decomposition coefficient point set, is the kth point in the wavelet packet decomposition coefficient point set under frequency band n at the jth decomposition level, is the k+1th point in the wavelet packet decomposition coefficient point set under frequency band n at the jth decomposition level, and for the reason and The derived next level wavelet packet decomposition coefficients;

[0091] The phase current is reconstructed using the wavelet packet coefficients of the characteristic frequency band. The reconstruction formula is as follows:

[0092]

[0093] Where, M matrix is ​​the determined Meyer wavelet basis matrix, is the wavelet coefficient of the wavelet packet in the sub-low frequency band;

[0094] Fault identification according to the polarity of the modulus maximum value includes:

[0095] If the polarity of the modulus maximum value at the installation location of the feeder terminal of a main line in the distribution network is opposite to that of the lower-level line, it can be preliminarily considered that the line has a fault; further, based on the polarity of the reconstructed phase current modulus maximum value at the main line feeder terminal of the line, it is compared with the reconstructed current modulus maximum value of the lower-level line in sequence until a line with opposite modulus maximum value polarity appears for the first time. The line at the end of the comparison is considered to be the faulty line; if the polarity of the reconstructed current modulus maximum value of all main lines is the same, the result is judged to be a bus fault; if a line fault or bus fault is identified, it is considered that the phase current transient quantity criterion is activated, otherwise it is determined that the phase current transient quantity criterion is not activated.

[0096] In some embodiments, the zero-sequence current sudden change amount is calculated as follows:

[0097] |ΔI n |=|I n2 (U 01 +U 02 ) / U 02 -I n1 |,n=1,2,...,N (4)

[0098] Where n is the number of the branch line in the distribution network, N is the total number of all branches in the distribution network, |ΔI n | is the zero-sequence current mutation of line n, I n1 、U 01 is the effective value of zero-sequence current and zero-sequence voltage of R cycles before the fault of line n, R is a positive integer, I n2 、U 02 is the effective value of zero-sequence current and zero-sequence voltage after the fault of line n; I n2 (U 01 +U 02 ) / U 02 For I n2 Converted value;

[0099] Because if |ΔI n | is not zero, the line is considered to be faulty. n | is basically zero, the line is considered to be a sound line; if the The relative rate of change is greater than a certain value, and |ΔI n | is basically zero, it is considered that a busbar fault has occurred. Based on this, the criterion for the zero-sequence current mutation is constructed as follows:

[0100] |ΔI n |>ΔI set (5-1)

[0101] |U 01 / U 02 |>K set (5-2)

[0102] Where, ΔI set K is the zero-sequence current sudden change setting threshold, set is the threshold value for calculating the relative rate of change;

[0103] When formula (5-1) is satisfied, it is considered that the line has a fault; when formula (5-1) is not satisfied but formula (5-2) is satisfied, it is considered that a busbar fault has occurred; when both formulas (5-1) and (5-2) are not satisfied, the line is considered to be a sound line; if a line fault or a busbar fault is identified, it is considered that the zero-sequence current mutation criterion is activated; otherwise, it is determined that the zero-sequence current mutation criterion is not activated.

[0104] In some embodiments, the three sub-criteria of the phase voltage amplitude criterion, the phase current transient quantity criterion, and the zero-sequence current mutation quantity criterion and their action results are fused through the DS evidence theory to obtain a final fusion judgment result, including:

[0105] First, based on the three sub-criteria, the evidence set of the fusion model is obtained as Q = {C1, C2, C3}, where C1, C2 and C3 are the original confidence subsets of the three sub-criteria, namely, the phase voltage amplitude criterion, the phase current transient quantity criterion and the zero-sequence current mutation quantity criterion; according to the possible judgment results, the identification framework is defined as B = {action, no action}; the confidence results of each sub-criteria in the set Q under the identification framework are defined as q h,l , where h represents the criterion number, and its values ​​are 1, 2, and 3, respectively, representing three sub-criteria; l represents the criterion result, and l = 1 and 2 correspond to action and no action, respectively. When the sub-criteria result is action, the corresponding q h,1 =1,q h,2 =0, when the result of the sub-criteria is no action, the corresponding q h,1 =0,q h,2 = 1. For example, if the result of the C1 sub-criteria is action, then the original confidence of C1 is q 1,1 =1,q 1,2 =0.

[0106] Then, the fusion criterion conflict coefficient P is obtained, which represents the difference between the judgments of the same event among the sub-criteria. The expression is as follows:

[0107]

[0108] Where q h (C h ) is the sub-criterion C h The basic trust allocation function is expressed as follows:

[0109]

[0110] From the above analysis, we can see that the original reliability has only two results: 1 and 0. Therefore, the calculated conflict coefficient is either 0 or 1, which is not easy to use for setting judgment. Therefore, the original reliability of the criterion is corrected to obtain the corrected fusion criterion conflict coefficient for

[0111]

[0112] Where, Sub-criterion C h The modified basic trust allocation function is expressed as follows:

[0113]

[0114] Corrected reliability The expression is as follows:

[0115]

[0116] Where, ωh The neutron criterion C for the set Q h The real-time weighted value of the fault is 1 / 3, and the real-time weight ω is adjusted according to the historical fault analysis results. h Make adjustments:

[0117]

[0118] Where s is the current decision position, a s 、b s,h are the correct judgment times and sub-criteria C of all criteria in the judgment results of the previous s-1 and s-2 times respectively. h The number of correct judgments;

[0119] Finally, the fusion criterion can be constructed as follows:

[0120]

[0121] Where P set is the setting threshold of the conflict coefficient;

[0122] When the modified fusion criterion conflict coefficient is satisfied When the criterion (12) is met, it is determined that a fault has occurred and the protection is activated; otherwise, it is determined that there is no fault and the protection is not activated.

[0123] The following combination Figure 2 The fault identification method proposed is specifically introduced with reference to the distribution network shown in FIG. Figure 2 The distribution network of distributed power generation is built based on PSCAD / EMTDC. The voltage level of the entire distribution network is 10kV. The data sampling frequency of each feeder terminal in the distribution network is 10kHz, the fault occurrence time is set to 1.0s, and the length of each branch line in the distribution network is Figure 2 As indicated in the figure, the line parameters are as follows: resistance per unit length is 0.137Ω / km, and inductance per unit length is 0.0032H / km. For this embodiment, after a metallic ground fault occurs on the L5 line, the specific fault identification method steps are as follows:

[0124] Step (201) is as follows Figure 1 As shown, the feeder terminals in the distribution network of this embodiment include L1 to L11. The feeder terminals collect line phase voltages and transmit them to the regional distribution network control center via 5G communication. When a fault occurs in the distribution network, the feeder terminals identify the fault and operate to record the line phase current, zero-sequence current, and zero-sequence voltage within a preset time window before and after the fault, and transmit them to the regional distribution network control center via 5G communication.

[0125] Step (202) The regional distribution network control center constructs the phase voltage amplitude criterion according to the line phase voltage as follows:

[0126]

[0127] In the formula is the phase voltage at the feeder terminal installation location, U set is the setting value, which is generally set at 0.7 times the phase voltage under normal working conditions. set Set to 4.039kV.

[0128] After a metallic ground fault occurs on the L5 line, the voltage waveform of the fault phase of the line is as follows: Figure 3 As shown. Figure 3 It can be seen that when the fault occurs, the voltage of phase A drops rapidly to 0kV, which is lower than the setting threshold value. This indicates that the fault occurs in phase A.

[0129] Step (203) The regional distribution network control center constructs a phase current transient quantity criterion based on the line phase current and determines the action result. First, the control center uses the Meyer wavelet basis to decompose the collected phase current data into wavelet packet decomposition coefficients in each frequency band:

[0130]

[0131] Where: j is the decomposition layer number, n is the current frequency band number under the current decomposition layer number (0≤n≤2 j -1), k is the result point set of the decomposition coefficient, t is the time series t of the data point set, h(k-2t) is the value of the Meyer wavelet basis low-pass filter at the (k-2t)th point in the wavelet decomposition coefficient point set, g(k-2t+1) is the value of the Meyer wavelet basis high-pass filter at the (k-2t)th point in the wavelet decomposition coefficient point set, is the kth point in the wavelet packet decomposition coefficient point set under frequency band n at the jth decomposition level, is the k+1th point in the wavelet packet decomposition coefficient point set under frequency band n at the jth decomposition level, and for the reason and The next level wavelet packet decomposition coefficients are derived.

[0132] In this embodiment, a three-layer wavelet packet decomposition is performed at 10kHz, decomposing it into eight frequency bands: 0-1.25kHz, 1.25kHz-2.5kHz, 2.5kHz-3.75kHz, 3.75-5kHz, 5kHz-6.25kHz, 6.25kHz-7.5kHz, 7.5kHz-8.75kHz, and 8.75kHz-10kHz. The sub-low frequency wavelet packet corresponds to the energy in the 1.25kHz-2.5kHz frequency band. The frequency band corresponding to the sub-low frequency wavelet packet, i.e., 1.25kHz to 2.5kHz, is selected as the characteristic frequency band for fault discrimination. The wavelet packet coefficients of the sub-low frequency band are used to reconstruct the phase current. The reconstruction formula is as follows:

[0133]

[0134] Where, M matrix is ​​the determined Meyer wavelet basis matrix, is the wavelet coefficient of the wavelet packet in the sub-low frequency band.

[0135] Finally, after reconstructing the phase current modulus maximum value through the above method, if the polarity of the modulus maximum value at the installation position of the feeder terminal of a main line in the distribution network is opposite to that of the lower line, it can be preliminarily considered that the line has a fault; further, the polarity of the reconstructed phase current modulus maximum value on the main line feeder terminal of the line is used as a reference basis, and the reconstructed current modulus maximum value of the lower line is compared in sequence until the line with the opposite polarity of the modulus maximum value appears for the first time. The line at the end of the comparison is considered to be the faulty line. If the polarity of the reconstructed current modulus maximum value of all main lines is the same, the judgment result is a bus fault. If a line fault or bus fault is identified, it is considered that the phase current transient quantity judgment criterion is activated, otherwise it is determined that the phase current transient quantity judgment criterion is not activated.

[0136] After a fault occurs, the phase current of each line in the distribution network is decomposed by wavelet packets and the reconstructed phase current is as follows: Figure 4 As shown. Figure 4 The waveform results show that only the reconstructed current modulus maxima on lines L2 and L5 are negative, while the polarity of the reconstructed current modulus maxima on the remaining lines is positive. Therefore, the current transient criterion identifies that the fault occurred on line L5.

[0137] Step (204) The regional distribution network control center constructs a zero-sequence current mutation criterion based on the line zero-sequence current and zero-sequence voltage, and determines the action result. The zero-sequence current mutation is as follows:

[0138] |ΔI n |=|I n2 (U 01 +U 02 ) / U 02 -I n1|,n=1,2,...,N (4) Where n is the number of the branch line in the distribution network, N is the total number of all branches in the distribution network, |ΔI n | is the zero-sequence current mutation of line n, I n1 、U 01 is the effective value of zero-sequence current and zero-sequence voltage of R cycles before the fault of line n. In this embodiment, R is 2, I n2 、U 02 is the effective value of zero-sequence current and zero-sequence voltage after the fault of line n; I n2 (U 01 +U 02 ) / U 02 For I n2 Converted value.

[0139] The constructed zero-sequence current mutation criterion is as follows:

[0140] |ΔI n |>ΔI set (5-1)

[0141] |U 01 / U 02 |>K set (5-2)

[0142] Where, ΔI set The threshold value for zero-sequence current mutation is generally set between 0.01kA and 0.05kA in a 10kV low-voltage distribution network. In this embodiment, it is set to 0.01kA. set The threshold value for converting the relative change rate is 10% in this embodiment.

[0143] The zero-sequence current mutation calculated based on the zero-sequence current and zero-sequence voltage of L5 line is as follows: Figure 5 As shown in Figure 5. The fault occurred 1.0s after the zero-sequence current surge increased sharply to 0.13kA and continued to increase after the fault. Equation (5-1) shows that the current surge exceeded the set threshold after the fault. Therefore, the zero-sequence current surge criterion determined that the fault occurred on line L5.

[0144] Step (205) further fuses the three sub-criteria of voltage amplitude criterion, phase current transient quantity criterion and zero-sequence current mutation quantity criterion by combining the DS evidence theory to obtain the fusion judgment result proposed in this scheme, thereby realizing distribution network fault identification. The constructed fusion criterion is as follows:

[0145]

[0146] Where P setis the adjustment threshold of the conflict coefficient.

[0147] DS evidence theory is an effective uncertainty reasoning method that can be used in the field of fault diagnosis and result evaluation. The process of constructing fusion criteria based on DS evidence theory is as follows:

[0148] First, based on the three sub-criteria constructed above, the evidence set of the fusion model can be obtained as Q = {C1, C2, C3}, where C1, C2, and C3 are the original confidence subsets of the three sub-criteria. The results of each criterion are only two types: action and no action. Based on the possible judgment results, the recognition framework is defined as B = {action, no action}. Therefore, the confidence results of each sub-criteria in the set Q under the recognition framework are defined as q h,l , where h represents the criterion number, and its values ​​are 1, 2, and 3, respectively, representing three sub-criteria; l represents the criterion result, and l = 1 and 2 correspond to action and no action, respectively. When the sub-criteria result is action, the corresponding q h,1 =1,q h,2 =0, when the result of the sub-criteria is no action, the corresponding q h,1 =0,q h,2 = 1. For example, if the result of the C1 sub-criteria is action, then the original confidence of C1 is q 1,1 =1,q 1,2 =0.

[0149] Then, the fusion criterion conflict coefficient P is obtained, which represents the difference between the judgments of the same event among the sub-criteria. The expression is as follows:

[0150]

[0151] Where q h (C h ) is the sub-criterion C h The basic trust allocation function is expressed as follows:

[0152]

[0153] From the above analysis, we can see that the original reliability has only two results: 1 and 0. Therefore, the calculated conflict coefficient is either 0 or 1, which is not easy to use for setting judgment. Therefore, the original reliability of the criterion is corrected to obtain the corrected fusion criterion conflict coefficient for

[0154]

[0155] Where, Sub-criterion C h The modified basic trust allocation function is expressed as follows:

[0156]

[0157] Corrected reliability The expression is as follows:

[0158]

[0159] Where, ω h The neutron criterion C for the set Q h The real-time weighted value of the fault is 1 / 3, and the real-time weight ω is adjusted according to the historical fault analysis results. h Make adjustments:

[0160]

[0161] Where s is the current decision position, a s 、b s,h are the correct judgment times and sub-criteria C of all criteria in the judgment results of the previous s-1 and s-2 times respectively. h The number of correct judgments.

[0162] Finally, the fusion criterion can be constructed as follows:

[0163]

[0164] Where P set is the setting threshold of the conflict coefficient, ranging from 0.01 to 0.08. In this embodiment, it is set to 0.04. When equation (12) is satisfied, the fusion criterion determines that the current line has a fault; otherwise, the line is considered to be not faulty.

[0165] Combine Figure 2 , the three sub-criteria of voltage amplitude criterion, phase current transient quantity criterion and zero-sequence current mutation quantity criterion are all activated. At this time, the initial weight values ​​of the three criteria are all 1 / 3. Using formula (11) and combining formula (9), the conflict coefficient of the fusion criterion calculated using the modified reliability can be obtained as follows:

[0166]

[0167] Therefore, based on the calculation result of the fusion criterion conflict coefficient and formula (13), the distribution network fault fusion identification criterion proposed by the present invention determines that line L5 has a fault. This shows that the criterion proposed in this embodiment, after fusing the three sub-criteria using DS evidence theory, is conducive to reducing the impact of different distribution network operating modes on fault identification and improving the reliability of the criterion operation.

[0168] In summary, the above embodiments verify the correctness and feasibility of the invention of a distribution network fault fusion identification method based on 5G communication and DS evidence theory.

[0169] Figure 6A block diagram of an electronic device according to an exemplary embodiment is shown.

[0170] Refer to the following Figure 6 hereinafter, an electronic device 200 according to this embodiment of the present application is described. Figure 6 The electronic device 200 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0171] like Figure 6 As shown, electronic device 200 is implemented as a general-purpose computing device. Components of electronic device 200 may include, but are not limited to, at least one processing unit 210, at least one storage unit 220, a bus 230 connecting various system components (including storage unit 220 and processing unit 210), a display unit 240, and the like.

[0172] The storage unit stores program codes, and the program codes can be executed by the processing unit 210, so that the processing unit 210 executes the methods described in this specification according to various exemplary embodiments of the present application.

[0173] The storage unit 220 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 2201 and / or a cache memory unit 2202 , and may further include a read-only memory unit (ROM) 2203 .

[0174] The storage unit 220 may also include a program / utility 2204 having a set (at least one) of program modules 2205, such program modules 2205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0175] Bus 230 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0176] The electronic device 200 can also communicate with one or more external devices 300 (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 200, and / or any device that enables the electronic device 200 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication can occur via an input / output (I / O) interface 250. Furthermore, the electronic device 200 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 260. The network adapter 260 can communicate with other modules of the electronic device 200 via the bus 230. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with the electronic device 200, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0177] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software or by combining software with necessary hardware. The technical solution according to the embodiment of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, or a network device, etc.) to execute the above method according to the embodiment of the present application.

[0178] The software product can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0179] Computer-readable storage media may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0180] The program code for performing the operations of the present application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0181] The computer-readable medium carries one or more programs. When the one or more programs are executed by the device, the computer-readable medium implements the aforementioned functions.

[0182] The above is a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A distribution network fault fusion identification method based on 5G communication and DS evidence theory, characterized by: include: The feeder terminal collects the line phase voltage and transmits it to the regional distribution network control center via 5G communication; After the feeder terminal identifies the fault and operates, it records the line phase current, zero-sequence current, and zero-sequence voltage within the preset time window before and after the fault, and transmits them to the regional distribution network control center via 5G communication; The regional distribution network control center constructs a phase voltage amplitude criterion according to the line phase voltage and determines the action result; The regional distribution network control center constructs a phase current transient quantity criterion based on the line phase current and determines the action result; The regional distribution network control center constructs a zero-sequence current mutation criterion based on the line zero-sequence current and zero-sequence voltage, and determines the action result; The three sub-criteria of phase voltage amplitude criterion, phase current transient quantity criterion and zero-sequence current mutation quantity criterion and their action results are fused through DS evidence theory to obtain the final fusion judgment result; including: First, based on the three sub-criteria, the evidence set of the fusion model is obtained as Q = {C1, C2, C3}, where C1, C2 and C3 are the original confidence subsets of the three sub-criteria, namely, the phase voltage amplitude criterion, the phase current transient quantity criterion and the zero-sequence current mutation quantity criterion; according to the possible judgment results, the identification framework is defined as B = {action, no action}; the confidence results of each sub-criteria in the set Q under the identification framework are defined as q h,l , where h represents the criterion number, and its values ​​are 1, 2, and 3, respectively, representing three sub-criteria; l represents the criterion result, and l = 1 and 2 correspond to action and no action, respectively. When the sub-criteria result is action, the corresponding q h,1 =1,q h,2 =0, when the result of the sub-criteria is no action, the corresponding q h,1 =0,q h,2 =1; Then, the fusion criterion conflict coefficient P is obtained, which represents the difference between the judgments of the same event among the sub-criteria. The expression is as follows: Where q h (C h ) is the sub-criterion C h The basic trust allocation function is expressed as follows: Correct the original reliability of the criterion to obtain the corrected fusion criterion conflict coefficient for Where, Sub-criterion C h The modified basic trust allocation function is expressed as follows: Corrected reliability The expression is as follows: Where, ω h The neutron criterion C for the set Q h The real-time weighted value of the fault is 1 / 3, and the real-time weight ω is adjusted according to the historical fault analysis results. h Make adjustments: Where s is the current decision position, a s 、b s,h are the correct judgment times and sub-criteria C of all criteria in the judgment results of the previous s-1 and s-2 times respectively. h The number of correct judgments; Finally, the fusion criterion is constructed as follows: Where P set is the setting threshold of the conflict coefficient; When the modified fusion criterion conflict coefficient is satisfied When the criterion (12) is met, it is determined that a fault has occurred and the protection is activated; otherwise, it is determined that there is no fault and the protection is not activated.

2. The distribution network fault fusion identification method based on 5G communication and DS evidence theory according to claim 1 is characterized in that: The phase voltage amplitude criterion constructed according to the line phase voltage is: In the formula is the phase voltage at the feeder terminal installation location, U set is the voltage setting value; When formula (1) is satisfied, it is judged as action, otherwise it is judged as no action.

3. The distribution network fault fusion identification method based on 5G communication and DS evidence theory according to claim 1 is characterized in that: The phase current transient quantity criterion constructed according to the line phase current includes: The three-layer time and frequency domain analysis of phase current is performed using wavelet packet transform; The sub-low frequency wavelet packet band is selected as the characteristic frequency band, and the wavelet packet coefficients of the characteristic frequency band are used to reconstruct the phase current and calculate the modulus maximum value. Fault identification is performed according to the polarity of the modulus maximum value.

4. The distribution network fault fusion identification method based on 5G communication and DS evidence theory according to claim 3 is characterized in that: The three-layer time-domain and frequency-domain analysis of the phase current using wavelet packet transform is specifically as follows: Where: j is the decomposition layer number, j = 1, 2, 3; n is the current frequency band number under the current decomposition layer number, 0≤n≤2 j -1, k is the result point set of the decomposition coefficient, t is the data point set at time series t, h(k-2t) is the value of the Meyer wavelet basis low-pass filter at the (k-2t)th point in the wavelet decomposition coefficient point set, g(k-2t+1) is the value of the Meyer wavelet basis high-pass filter at the (k-2t)th point in the wavelet decomposition coefficient point set, is the kth point in the wavelet packet decomposition coefficient point set under frequency band n at the jth decomposition level, is the k+1th point in the wavelet packet decomposition coefficient point set under frequency band n at the jth decomposition level, and for the reason and The derived next level wavelet packet decomposition coefficients; The phase current is reconstructed using the wavelet packet coefficients of the characteristic frequency band, and the reconstruction formula is as follows: Where, M matrix is ​​the determined Meyer wavelet basis matrix, is the wavelet coefficient of the wavelet packet in the sub-low frequency band; Fault identification according to the polarity of the modulus maximum value includes: If the polarity of the modulus maximum value at the installation location of the feeder terminal of a main line and the lower-level line in the distribution network is opposite, it is preliminarily considered that the line has a fault; Furthermore, the polarity of the reconstructed phase current modulus maximum value at the main line feeder terminal of the line is used as a reference basis, and is compared with the reconstructed current modulus maximum values ​​of the lower-level lines in sequence until a line with opposite modulus maximum polarity appears for the first time. The line at the end of the comparison is considered to be the faulty line; if the polarity of the reconstructed current modulus maximum values ​​of all main lines is the same, the judgment result is a busbar fault; if a line fault or a busbar fault is identified, it is considered that the phase current transient quantity criterion is activated, otherwise it is determined that the phase current transient quantity criterion is inactivated.

5. The distribution network fault fusion identification method based on 5G communication and DS evidence theory according to claim 1 is characterized in that: The regional distribution network control center constructs a zero-sequence current mutation criterion based on the line zero-sequence current and zero-sequence voltage, including: Convert zero-sequence current to uniform voltage; Calculate the zero-sequence current mutation amount based on the converted zero-sequence current; Fault identification is performed based on the comparison between the zero-sequence current mutation amount and the mutation amount setting threshold.

6. The distribution network fault fusion identification method based on 5G communication and DS evidence theory according to claim 5 is characterized in that: The calculation formula for the zero-sequence current mutation is: |ΔI n |=|I n2 (U 01 +U 02 ) / U 02 -I n1 |,n=1,2,...,N (4) Where n is the number of the branch line in the distribution network, N is the total number of all branches in the distribution network, |ΔI n | is the zero-sequence current mutation of line n, I n1 、U 01 is the effective value of zero-sequence current and zero-sequence voltage of R cycles before the fault of line n, R is a positive integer, I n2 、U 02 is the effective value of zero-sequence current and zero-sequence voltage after the fault of line n; I n2 (U 01 +U 02 ) / U 02 is I n2 the converted value; The constructed zero-sequence current mutation criterion is as follows: |ΔI n |>ΔI set (5-1) |In 01 / IN 02 |>K set (5-2) Where, ΔI set K is the zero-sequence current sudden change setting threshold, set is the threshold value for converting the relative rate of change; When formula (5-1) is satisfied, it is considered that the line has a fault; when formula (5-1) is not satisfied but formula (5-2) is satisfied, it is considered that a busbar fault has occurred; when both formulas (5-1) and (5-2) are not satisfied, the line is considered to be a sound line; if a line fault or a busbar fault is identified, it is considered that the zero-sequence current mutation criterion is activated; otherwise, it is determined that the zero-sequence current mutation criterion is not activated.

7. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the computer program.

Images